Searching for massive pre--stellar cores through observations of N2H+ and N2D+

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Hope for Earth

Hope for Earth

Hope for Earth: Planet Survives Star's Death Throesby Ker Than, Staff Writer | September 12, 2007 01:00pm ETThis illustration shows the system V 391 Pegasi as it was about 100 million years ago, when the star was at its maximum red giant expansion. Copyright HELAS. Artist Mark Garlick.Astronomers have spotted a planet that has survived the massive ballooning of its parent star, providing the first optimistic evidence for the long-term survival of Earth.The discovery, detailed in the Sept. 13 issue of the journal N ature, could motivate other scientists to look for similar red giant survivors. That in turn could eventually lead to ananswer to one of astronomers' favorite questions: Will Earth survive the sun's swelling when it goes through its own red giant phase in a few billion years?"The fact that we have found this planet proves that a planet with a small orbital distance can survive" a star's red giant phase, said study team member Roberto Silvotti of the National Institute of Astrophysics in Naples, Italy.Not your typical red giantThe parent star, V 391 Pegasi, belongs to a rare class of red giant stars known as B-type subdwarfs that have prematurely expelled their outer shells of hydrogen.At one point, V 391 Pegasi was a star much like our own sun. As it evolved and grew old, its core ran out of hydrogen fuel. The star's core contracted and began burning helium instead, while its outer shell expanded by a factor of about 100. Scientists think our sun will undergo the same expansion when it runs out of hydrogen fuel in about 5 billion years.After a while, most red giants expel their outer envelopes to create planetary nebulas, revealing dense, stellar corpses known as white dwarfs where the core used to be.But for reasons that are still unclear, V 391 Pegasi expelled its outer envelope early, before the core even began fusing helium, exposing a compact, dense star that has not yet fully died. Only about 2 percent of stars that reach the red-giant phase are thought to undergo the same catastrophic mass loss that V 391 Pegasi did."This is a rather particular kind of star because 98 percent of these stars do not lose so much mass during the red giant phase, so they do not become subdwarfs," Silvottitold . "This is a very particular evolutionary channel."Even more unusual, V 391 Pegasi pulsates, dimming and brightening for several minutes at a time. By making precise observations of the timing of the pulses for seven years, Silvotti's team detected a giant gas planet in the system that was gravitationally tugging the star to and fro as seen from Earth."This is the first planet found after the red giant phase [of its star]," Silvotti said.Surviving by a hairThe planet is about three times the mass of Jupiter and currently orbits its star from a distance of about 1.7 astronomical units (AU), or about 158 million miles (a bit further out than Mars currently orbits the sun). One AU is equal to the distance between the Earth and the sun. Scientists think that during V 391 Pegasi's red giant phase, only about 1 AU separated the star and planet.It's possible that the planet's presence has something to do with V 391 Pegasi's premature shell ejection, but more cases will be needed to confirm this. "If we happen tofind other stars like it that have planets, then you might ascertain that the planet has something to do with the star losing its mass," said Jonathan Fortney, an astronomer at NASA Ames Research Center in California who was not involved in the study. "But there's no agreed upon way for why this happens."Because very few red giants are expected to go through what V 391 Pegasi did, the new discovery will likely not have direct implications for whether Earth will or will not be engulfed by our sun, Silvotti said. It's almost certain that the two planets closest to our sun, Mercury and Venus, eventually will be vaporized, and that Mars will not, Silvotti said."But Earth is in the middle, so we don't know," he said.Silvotti thinks the new finding will spur scientists to look for other planets that have survived their star's red giant phase. Maybe then, Earth's fate can be determined."For sure this discovery will move other people to look for other similar systems, so in a few years we will have much stronger constraints for the models," Silvotti said. "At that point, it will be possible to do relatively good models for what happens to the planets in general in the red giant phase. So in the end we might know what will happen to Earth."。

The Mass Assembly History for Galaxies with MaNGA

The Mass Assembly History for Galaxies with MaNGA

The Mass Assembly History for Galaxies with MaNGA Xue Ge;Hong-Tao Wang;Cheng-Long Lei;Yun-Jun Guo;Yi-Long Jiang;Xiao-Xiao Cao【期刊名称】《Research in Astronomy and Astrophysics》【年(卷),期】2024(24)3【摘要】How galaxies assemble masses through their own star formation or interaction with the external environment is still an important topic in the field of galaxy formation and evolution.We use Value Added Catalogs with galaxy features that are spatially and temporally resolved from Sloan Digital Sky Survey Data Release 17 to investigate the mass growth histories of early-type galaxies(ETGs)and late-type galaxies(LTGs).We find that the mass growth of ETGs is earlier than that of LTGs for massivegalaxies(M_(*)>10^(10)M_⊙),while low-mass(M_(*)≤10^(10)M_⊙)ETGs have statistically similar mass assembly histories as low-mass LTGs.The stellar metallicity of all massive galaxies shows a negative gradient and basically does not change with time.However,in low-mass galaxies,the stellar metallicity gradient of elliptical galaxies is negative,and the stellar metallicity gradient of lenticular and spiral galaxies evolves from positive to negative.ETGs are not all in a high-density environment,but exhibit mass dependence.As the tidal strength increases,the star formation rate of low-mass ETGs rapidly decreases.These results support a picture where massive galaxies exhibit inside-out quenching mode,while low-mass galaxies showoutside-in quenching mode.Environmental effects play an important role in regulating the mass assembly histories of low-mass ETGs.【总页数】12页(P58-69)【作者】Xue Ge;Hong-Tao Wang;Cheng-Long Lei;Yun-Jun Guo;Yi-Long Jiang;Xiao-Xiao Cao【作者单位】School of Physics and Information Engineering Second Normal University;Jiangsu Province Engineering Research Center of Basic Education Big Data Application Second Normal University;Key Laboratory of Modern Astronomy and Astrophysics University of Education;School of Science Normal University【正文语种】中文【中图分类】P15【相关文献】1.A thick-disk galaxy model and simulations of equal-mass galaxy pair collisions2.Radial stellar populations of AGN-host dwarf galaxies in SDSS-Ⅳ MaNGA survey3.Spatially resolved properties of supernova host galaxies in SDSS-IV MaNGA4.Velocity Dispersionσ_(aper)Aperture Corrections as a Function of Galaxy Properties from Integral-field Stellar Kinematics of 10,000 MaNGA Galaxies5.Measuring stellar populations,dust attenuation and ionized gas at kpc scales in 10010 nearby galaxies using the integral field spectroscopy from MaNGA因版权原因,仅展示原文概要,查看原文内容请购买。

低频活动漂浮潜水船声探测系统(LFATS)说明书

低频活动漂浮潜水船声探测系统(LFATS)说明书

LOW-FREQUENCY ACTIVE TOWED SONAR (LFATS)LFATS is a full-feature, long-range,low-frequency variable depth sonarDeveloped for active sonar operation against modern dieselelectric submarines, LFATS has demonstrated consistent detection performance in shallow and deep water. LFATS also provides a passive mode and includes a full set of passive tools and features.COMPACT SIZELFATS is a small, lightweight, air-transportable, ruggedized system designed specifically for easy installation on small vessels. CONFIGURABLELFATS can operate in a stand-alone configuration or be easily integrated into the ship’s combat system.TACTICAL BISTATIC AND MULTISTATIC CAPABILITYA robust infrastructure permits interoperability with the HELRAS helicopter dipping sonar and all key sonobuoys.HIGHLY MANEUVERABLEOwn-ship noise reduction processing algorithms, coupled with compact twin line receivers, enable short-scope towing for efficient maneuvering, fast deployment and unencumbered operation in shallow water.COMPACT WINCH AND HANDLING SYSTEMAn ultrastable structure assures safe, reliable operation in heavy seas and permits manual or console-controlled deployment, retrieval and depth-keeping. FULL 360° COVERAGEA dual parallel array configuration and advanced signal processing achieve instantaneous, unambiguous left/right target discrimination.SPACE-SAVING TRANSMITTERTOW-BODY CONFIGURATIONInnovative technology achievesomnidirectional, large aperture acousticperformance in a compact, sleek tow-body assembly.REVERBERATION SUPRESSIONThe unique transmitter design enablesforward, aft, port and starboarddirectional transmission. This capabilitydiverts energy concentration away fromshorelines and landmasses, minimizingreverb and optimizing target detection.SONAR PERFORMANCE PREDICTIONA key ingredient to mission planning,LFATS computes and displays systemdetection capability based on modeled ormeasured environmental data.Key Features>Wide-area search>Target detection, localization andclassification>T racking and attack>Embedded trainingSonar Processing>Active processing: State-of-the-art signal processing offers acomprehensive range of single- andmulti-pulse, FM and CW processingfor detection and tracking. Targetdetection, localization andclassification>P assive processing: LFATS featuresfull 100-to-2,000 Hz continuouswideband coverage. Broadband,DEMON and narrowband analyzers,torpedo alert and extendedtracking functions constitute asuite of passive tools to track andanalyze targets.>Playback mode: Playback isseamlessly integrated intopassive and active operation,enabling postanalysis of pre-recorded mission data and is a keycomponent to operator training.>Built-in test: Power-up, continuousbackground and operator-initiatedtest modes combine to boostsystem availability and accelerateoperational readiness.UNIQUE EXTENSION/RETRACTIONMECHANISM TRANSFORMS COMPACTTOW-BODY CONFIGURATION TO ALARGE-APERTURE MULTIDIRECTIONALTRANSMITTERDISPLAYS AND OPERATOR INTERFACES>State-of-the-art workstation-based operator machineinterface: Trackball, point-and-click control, pull-down menu function and parameter selection allows easy access to key information. >Displays: A strategic balance of multifunction displays,built on a modern OpenGL framework, offer flexible search, classification and geographic formats. Ground-stabilized, high-resolution color monitors capture details in the real-time processed sonar data. > B uilt-in operator aids: To simplify operation, LFATS provides recommended mode/parameter settings, automated range-of-day estimation and data history recall. >COTS hardware: LFATS incorporates a modular, expandable open architecture to accommodate future technology.L3Harrissellsht_LFATS© 2022 L3Harris Technologies, Inc. | 09/2022NON-EXPORT CONTROLLED - These item(s)/data have been reviewed in accordance with the InternationalTraffic in Arms Regulations (ITAR), 22 CFR part 120.33, and the Export Administration Regulations (EAR), 15 CFR 734(3)(b)(3), and may be released without export restrictions.L3Harris Technologies is an agile global aerospace and defense technology innovator, delivering end-to-endsolutions that meet customers’ mission-critical needs. The company provides advanced defense and commercial technologies across air, land, sea, space and cyber domains.t 818 367 0111 | f 818 364 2491 *******************WINCH AND HANDLINGSYSTEMSHIP ELECTRONICSTOWED SUBSYSTEMSONAR OPERATORCONSOLETRANSMIT POWERAMPLIFIER 1025 W. NASA Boulevard Melbourne, FL 32919SPECIFICATIONSOperating Modes Active, passive, test, playback, multi-staticSource Level 219 dB Omnidirectional, 222 dB Sector Steered Projector Elements 16 in 4 stavesTransmission Omnidirectional or by sector Operating Depth 15-to-300 m Survival Speed 30 knotsSize Winch & Handling Subsystem:180 in. x 138 in. x 84 in.(4.5 m x 3.5 m x 2.2 m)Sonar Operator Console:60 in. x 26 in. x 68 in.(1.52 m x 0.66 m x 1.73 m)Transmit Power Amplifier:42 in. x 28 in. x 68 in.(1.07 m x 0.71 m x 1.73 m)Weight Winch & Handling: 3,954 kg (8,717 lb.)Towed Subsystem: 678 kg (1,495 lb.)Ship Electronics: 928 kg (2,045 lb.)Platforms Frigates, corvettes, small patrol boats Receive ArrayConfiguration: Twin-lineNumber of channels: 48 per lineLength: 26.5 m (86.9 ft.)Array directivity: >18 dB @ 1,380 HzLFATS PROCESSINGActiveActive Band 1,200-to-1,00 HzProcessing CW, FM, wavetrain, multi-pulse matched filtering Pulse Lengths Range-dependent, .039 to 10 sec. max.FM Bandwidth 50, 100 and 300 HzTracking 20 auto and operator-initiated Displays PPI, bearing range, Doppler range, FM A-scan, geographic overlayRange Scale5, 10, 20, 40, and 80 kyd PassivePassive Band Continuous 100-to-2,000 HzProcessing Broadband, narrowband, ALI, DEMON and tracking Displays BTR, BFI, NALI, DEMON and LOFAR Tracking 20 auto and operator-initiatedCommonOwn-ship noise reduction, doppler nullification, directional audio。

星体的消亡【英文】

星体的消亡【英文】

Planetary Nebula IC 418 (Spirograph Nebula)
The Eskimo Nebula
White Dwarfs
Degenerate stellar remnant (C,O core) Extremely dense: 1 teaspoon of WD material: mass ≈ 16 tons!!! Chunk of WD material the size of a beach ball would outweigh an ocean liner!
Black Holes
Just like white dwarfs (Chandrasekhar limit: 1.4 Msun), there is a mass limit for neutron stars:
Subrahmanyan Chandrasekhar,
(1910-1995, Indian-born American):
In 1983 won Nobel Prize in Physics for his theoretical studies of the physical processes of importance to the structure and evolution of the stars. The Chandra X-Ray Space Telescope is named in his honor.
The Famous Supernova of 1987: SN 1987A
Before At maximum
Unusual type II Supernova in the Large Magellanic Cloud in Feb. 1987

大家论坛

大家论坛

2010年职称英语考试已结束,为了更好的帮助大家学习和备考2011年职称英语考试,大家论坛特整理了2010年职称英语考试理工类(A级)考试真题及答案解析。

希望对大家考试学习和备考有用,祝大家顺利通过2011年职称英语考试!2010年职称英语考试理工类(A级)考试真题及答案解析第1部分:词汇选项(第1~15题,每题1分,共15分)下面每个句子中均有1个词或短语划有底横线,请为每处划线部分确定1个意义最为接近的选项。

1.I can't put up with my neighbor's noise any longer,it'S driving me mad.A.tolerateB.generateC.reduceD.mensure2.Regular visits from a social worker can be of immense value to old people living alone.A.equalB.immediateC.moderateD.great3.He was rather vague about the reasons why he never finished school.A.brightB.unclearC.generalD.bad4.I want to provide my boys with a decent education.A.specialB.privateC.generalD.good5.Sleep stairs can present a particular hazard to older people.A.pictureB.dangerC.evidenceD.case6.Our arrangements were thrown into complete turmoil.A.doubtB.reliefC.failureD.confusion7.Patricia stared at the other girls with resentment.A.loveB.surpriseC.angerD.doubt8.Y our dog needs at least 20 minutes of vigorous exercise every day.A.energeticB.freeC.physicalD.regular9.I enjoyed the play-it had a clever plot and very funny dialogues.A.boringB.originalC.humorousD.long10.Lower taxes would spur investment and help economic growth.A.attractB.spendC.encourageD.require11.He demolished my argument in minutes.A.supportedB.disprovedC.disputedD.accepted12.The two banks have announced plans to merge next year.A.closeB.sellC.breakD.combine13.Her father was a quiet man with graceful manners.A.politeB.usualC.badD.similar14.The project required ten years of diligent research.A.hardworkingB.socialC.basicD.scientific15.He was kept in appalling conditions in prison.A.necessaryB.terribleC.criticalD.normal第2部分:阅读判断(第16~22题,每题1分,共7分)下面的短文后列出了7个句子,请根据短文的内容对每个句子做出判断:如果该句提供的是正确信息,请选择A;如果该句提供的是错误信息,请选择B;如果该句的信息文中没有提及,请选择C。

2021年托福听力模拟试题及答案(卷十四)

2021年托福听力模拟试题及答案(卷十四)

2021年托福听力模拟试题及答案(卷十四)Post-it NotesPost-it Notes were invented in the 1970s at the 3M company in Minnesota quite by accident, Researchers at 3M were working on developing different types of adhesives, and one particularly weak adhesive, a compound of acrylate copolymer microspheres, was developed. Employees at 3M were asked if they could think of a use for a weak adhesive which, provided it did not get dirty, could be reused. One suggestion was that it could be applied to a piece of paper to use as a bookmark that would stay in place in a book. Another use was found when the product was attached to a report that was to be sent to a colleague with a request for comments on the report; the colleague made his comments on the paper attached to the report and returned the report. The idea for Post-it Notes was born.It was decided within the company that there would be a test launch of product in 1977 in four American cities. Sales of this innovative product in test cities were less than stellar, most likely because the product, while innovative, was also quite unfamiliar. A final attempt was then made in the city of Boise to introduce the product. In that attempt, 3M salesmen gave demonstrations of the product in offices throughout Boise and gave away free samples of the produce. When the salesmen returned a week later to the office workers, having noted how useful thesimple little product could be, were interested in purchasing it. Over time, 3M came to understand the huge potential of this new product, and over the next few decades more than 400 varieties of Post-it products - in different colors, shapes, and sizes –have been developed.3. Which of the sentences below expresses the essential information in the first highlighted sentence in the passage 1?Incorrect choices change the meaning in important ways or leave out essential information.Of the many adhesives that were being developed at 3M, one was not a particularly strong adhesive.Researchers at 3M spent many years trying to develop a really weak adhesive.Numerous weak adhesives resulted from a program to develop the strongest adhesive of all.Researchers were assigned to develop different types of uses for acrylate copolymer microspheres.答案:A4. Which of the sentences below expresses the essential information in the second highlighted sentence in the passage 1?Incorrect choices change the meaning in important ways or leave out essential information.The 3M company suggested applying for a patent on the product ina report prepared by a colleague.One unexpectedly-discovered use for the adhesive was in sending and receiving notes attached to documents.A note was attached to a report asking for suggestion for uses of one of 3M’s products.A colleague who developed the new product kept notes with suggestions by other workers.答案:B5. Which of the sentences below expresses the essential information in the first highlighted sentence in the passage 2?Incorrect choices change the meaning in important ways or leave out essential information.The 3M company was unfamiliar with the process of using test cities to introduce innovative products.Sales of the product soared even though the product was quite unfamiliar to most customers.The new product did not sell well because potential customers did not understand it.After selling the product for a while, the company understood that the product was not innovative enough.答案:C6. Which of the sentences below expresses the essentialinformation in the second highlighted sentence in the passage 2?Incorrect choices change the meaning in important ways or leave out essential information.The company immediately understood the potential of the product and began to develop it further.The company worked overtime to develop its new product, initially creating numerous varieties to make it successful.The company initially introduced 400 varieties of the product and then watched for decades as sales improved.It took some time for the company to understand how important its new product was and how many variation were possible.答案:DCamouflageCamouflage is one of the most effective ways for animals to avoid attack in the treeless Arctic. However, the summer and winter landscapes there are so diverse that a single protective coloring scheme would, of course, prove ineffective in one season or the other. Thus, many of the inhabitants of the Arctic tundra change their camouflage twice a year. The arctic fox is a clear-cut example of this phenomenon; it sports a brownish-gray coat in the summer which then turns white as cold weather sets in, and the process reverses itself in the springtime. Its brownish-gray coat blends in with the barren tundra landscape in themonths without snow, and the white coat naturally blends in with the landscape of the frozen wintertime tundra.1. Which of the sentences below expresses the essential information in the first highlighted sentence in the passage?Incorrect choices change the meaning in important ways or leave out essential information.Opposite conditions in summer and in winter necessitate different protective coloration for Arctic animals.The coloration of the summer and winter landscapes in the Arctic fails to protect the Arctic tundra.In a single season, protective coloring scheme are ineffective in the treeless Arctic.For many animals, a single protective coloring scheme effectively protects them during summer and winter months.答案:A2. Which of the sentences below expresses the essential information in the second highlighted sentence in the passage?Incorrect choices change the meaning in important ways or leave out essential information.The arctic fox is unusual in that he color of its coat changes for no reason.The arctic fox lives in an environment that is brownish gray in thesummer and white in the winter.It is a phenomenon that the coat of the arctic fox turns white I the springtime and gray in the fall.The arctic fox demonstrates that protective coloration can change during different seasons.答案:DThe Great Red SpotOne distinctive feature of the planet Jupiter is the Great Red Spot, a massive oval of swirling reddish-brown clouds. Were Earth to be juxtaposed with the Great Red Spot, our planet would be dwarfed in comparison, with a diameter less than half that of the Great Red Spot. The Spot’s clouds, most likely tinted red as a result of the phosphorus that they contain, circulate in a counterclockwise direction. The outer winds require six Earth days to complete the circumference of the Great Red Spot, a length of time indicative of vastness of the Great Red Spot.1. Which of the sentences below best expresses the essential information in the highlighted sentence in the passage? Incorrect choices change the meaning in important ways or leave out essential information.A. The density of the Great Red spot is much higher than that the Earth.B. If the diameter of the Great Red Spot were doubled, it wouldequal that of the Earth.C. By placing the Earth next to the Great Red Spot, one could see the Earth has a much smaller diameter.D. Because the Earth is close to the Great Red Spot, Earth is influenced by its huge size.答案:C2.Which of the sentences below best expresses the essential information in the highlighted sentence in the passage? Incorrect choices change the meaning in important ways or leave out essential information.A. The Earth’s outer winds move a distance equal to the circumference of the Great Red Spot.B. The outer winds of the Great Red Spot move more quickly than do those on Earth.C. The Winds moving across the Great Red Spot finally change direction every six Earth days.D. The fact that the winds take so long to move around the Great Red Spot proves how big it is.答案:DOne of the most interesting and distinctive of all uses of language is commentary. An oral reporting of ongoing activity, commentary is used in such public arenas as political ceremonies, parades, funerals, fashionshows and cooking demonstrations. The most frequently occurring type of commentary may be that connected with sports and games. In sports there are two kinds of commentary, and both are often used for the same sporting event. “play-by-play”commentary narrates the sports event, while “color –adding”or “color”commentary provides the audience with pre-event background, during-event interpretation, and post-event evaluation. Color commentary is usually conversational in style and can be a dialogue with two or more commentators.Play-by-play commentary is of interest to linguists because it is unlike other kinds of narrative, which are typically reported in past tense. Play-by-play commentary is reported in present tense. Some examples are “he takes the lead by four”and “she’s in position.”One linguist characterizes radio play-by-play commentary as “a monologue directed at an unknown, unseen mass audience who voluntarily choose to listen…and provide no feedback to the speaker.”It is these characteristics that make this kind of commentary unlike any other type of speech situation.The chief feature of play-by-play commentary is a highly formulaic style of presentation. There is distinctive grammar not only in the use of the present tense but also in the omission of certain elements of sentence structure. For example “Smith in close”eliminates the verb, as some newspaper headlines do. Another example is inverted wordorder, as in “over at third is Johnson.”Play-by-play commentary is very fluent, keeping up with the pace of the action. The rate is steady and there is little silence. The structure of the commentary is cyclical, reflecting the way most games consist of recurring sequences of short activities---as in tennis and baseball---or a limited number of activity options---as in the various kinds of football. In racing, the structure is even simpler, with the commentator informing the listener of the varying order of the competitors in a “state of play”summary, which is crucial for listeners or viewers who have just tuned in.1.Which of the following statements is true of color commentary?A.It narrates the action of the event in real time, using the present tense.B.It is a monologue given to an audience that does not respond to the speaker.C.It is steady and fluent because it must keep up with the action of the event.D.It gives background on the event, and interprets and evaluates the event.2.Why does the author quote a linguist in paragraph 2?A.To describe the uniqueness of radio play-by-playB.To show how technical sports commentary isC.To give examples of play-by-play commentaryD.To criticize past trends in sports commentary3.It can be inferred from the passage that the author most likely agrees with which of the following statements about sports commentary?A.Color commentary is more important than play-by-play commentaryB.Sports commentators do not need special knowledge of the sport.mentary enhances the excitement and enjoyment of sports.D.Sports commentators should work hard to improve their grammar.答案:1. D2. A3.CPennsylvania's colonial ironmasters forged iron and a revolution that had both industrial and political implications. The colonists in North America wanted the right to the profits gained from their manufacturing. However, England wanted all of the Line colonies' rich ores and raw materials to feed its own factories, and also wanted the (5) colonies to be a market for its finished goods. England passed legislation in 1750 to prohibit colonists from making finished iron products, but by 1771, when entrepreneur Mark Bird established the Hopewell blast furnace in Pennsylvania, iron making had become the backbone of American industry. It also had become one of the major issues that fomented therevolutionary break between England and the British colonies. By the (10) time the War of Independence broke out in 1776, Bird, angered and determined, was manufacturing cannons and shot at Hopewell to be used by the Continental Army.After the war, Hopewell, along with hundreds of other "iron plantations," continued to form the new nation's industrial foundation well into the nineteenth century. The rural landscape became dotted with tall stone pyramids that breathed flames and smoke, (15) charcola-fueled iron furnaces that produced the versatile metal so crucial to the nation's growth. Generations of ironmasters, craftspeople, and workers produced goods during war and peace-—ranging from cannons and shot to domestic items such as cast-iron stoves, pots, and sash weights for windows.The region around Hopewell had everything needed for iron production: a wealth of(20) iron ore near the surface, limestone for removing impurities from the iron, hardwood forests to supply the charcoal used for fuel, rushing water to power the bellows that pumped blasts of air into the furnace fires, and workers to supply the labor. By the 1830's, Hopewell had developed a reputation for producing high quality cast-iron stoves, for which there was a steady market. As Pennsylvania added more links to its (25) transportation system of roads, canals, and railroads, it became easier to ship parts made by Hopewell workers tosites all over the east coast. There they ware assembled into stoves and sold from Rhode Island to Maryland as the "Hopewell stove". By the time the last fires burned out at Hopewell ironworks in 1883, the community had produced some 80,000 cast-iron stoves.5. Pennsylvania was an ideal location for the Hopewell ironworks for all of the following reasons EXCEPT(A) Many workers were available in the area(B) The center of operations of the army was nearby(C) The metal ore was easy to acquire(D) There was an abundance of wood答案:BUnder the Earth's topsoil, at various levels, sometimes under a layer of rock, there are deposits of clay. Look at cuts where highways have been built to see exposed clay beds; or look at a construction site, where pockets of clay may be exposed. Rivers also reveal Line clay along their banks, and erosion on a hillside may make clay easily accessible.(5) What is clay made of? The Earth's surface is basically rock, and it is this rock that gradually decomposes into clay. Rain, streams, alternating freezing and thawing, roots of trees and plants forcing their way into cracks, earthquakes, volcanic action, and glaciers—all of these forces slowly break down the Earth's exposed rocky crust into smaller and smaller pieces that eventually become clay.(10) Rocks are composed of elements and compounds of elements. Feldspar, which is the most abundant mineral on the Earth's surface, is basically made up of the oxides silica and alumina combined with alkalis like potassium and some so-called impurities such as iron. Feldspar is an essential component of granite rocks, and as such it is the basis of clay. When it is wet, clay can be easily shaped to make a variety of useful (15) objects, which can then be fired to varying degrees of hardness and covered with impermeable decorative coatings of glasslike material called glaze. Just as volcanic action, with its intense heat, fuses the elements in certain rocks into a glasslike rock called obsidian, so can we apply heat to earthen materials and change them into a hard, dense material. Different clays need different heat levels to fuse, and some, the low-fire (20) clays, never become nonporous and watertight like highly fired stoneware. Each clay can stand only a certain amount of heat without losing its shape through sagging or melting.Variations of clay composition and the temperatures at which they are fired account for the differences in texture and appearance betweena china teacup and an earthenware flowerpot.2. It can be inferred from the passage that clay is LEAST likely to be plentiful in which of the following areas?(A) in desert sand dunes(B) in forests(C) on hillsides(D) near rivers答案:AIn July of 1994, an astounding series of events took place. The world anxiously watched as, every few hours, a hurtling chunk of comet plunged into the atmosphere of Jupiter. All of the twenty-odd fragments, collectively called comet Shoemaker-Levy 9 after its discoverers, were once part of the same object, now dismembered and strung out along the same orbit. This cometary train, glistening like a string of pearls, had been first glimpsed only a few months before its fateful impact with Jupiter, and rather quickly scientists had predicted that the fragments were on a collision course with the giant planet. The impact caused an explosion clearly visible from Earth, a bright flaming fire that quickly expanded as each icy mass incinerated itself. When each fragment slammed at 60 kilometers per second into the dense atmosphere, its immense kinetic energy was transformed into heat, producing a superheated fireball that was ejected back through the tunnel the fragment had made a few seconds earlier. The residues from these explosions left huge black marks on the face of Jupiter, some of which have stretched out to form dark ribbons.Although this impact event was of considerable scientific import, it especially piqued public curiosity and interest. Photographs of eachcollision made the evening television newscast and were posted on the Internet. This was possibly the most open scientific endeavor in history. The face of the largest planet in the solar system was changed before our very eyes. And for the very first time, most of humanity came to fully appreciate the fact that we ourselves live on a similar target, a world subject to catastrophe by random assaults from celestial bodies. That realization was a surprise to many, but it should not have been. One of the great truths revealed by the last few decades of planetary exploration is that collisions between bodies of all sizes are relatively commonplace, at least in geologic terms, and were even more frequent in the early solar system.1. The passage mentions which of the following with respect to the fragments of comet Shoemaker-Levy 9?(A) They were once combine in a larger body.(B) Some of them burned up before entering the atmosphere of Jupiter.(C) Some of them are still orbiting Jupiter.(D) They have an unusual orbit.2. The word "collectively" in line 3 is closest in meaning to(A) respectively(B) popularly(C) also(D) together3. The author compares the fragments of comet Shoemaker-Levy 9 to all of the following EXCEPT(A) a dismembered body(B) a train(C) a pearl necklace(D) a giant planet4. Before comet Shoemaker-Levy 9 hit Jupiter in July 1994, scientists(A) had been unaware of its existence(B) had been tracking it for only a few months(C) had observed its breakup into twenty-odd fragments(D) had decided it would not collide with the planet5. Before the comet fragments entered the atmosphere of Jupiter, they were most likely(A) invisible(B) black(C) frozen(D) exploding6. Superheated fireballs were produced as soon as the fragments of comet Shoemaker- Levy 9(A) hit the surface of Jupiter(B) were pulled into Jupiter’s orbit(C) were ejected back through the tunnel(D) entered the atmosphere of Jupiter7. The phrase "incinerated itself" in line 9 is closest in meaning to(A) burned up(B) broke into smaller pieces(C) increased its speed(D) grew in size8. Which of the following is mentioned as evidence of the explosions that is still visible on Jupiter?(A) fireballs(B) ice masses(C) black marks(D) tunnels9. Paragraph 2 discusses the impact of the comet Shoemaker-Levy 9 primarily in terms of(A) its importance as an event of great scientific significance(B) its effect on public awareness of the possibility of damage to Earth(C) the changes it made to the surface of Jupiter(D) the effect it had on television broadcasting10. The "target" in line 20 most probably referred to(A) Earth(B) Jupiter(C) the solar system(D) a cometADDBC DACBA1. Most doctors of the Colonial period believed _______ was caused by an imbalance of humors in the body.A. in diseaseB. that diseaseC. of diseaseD. about disease答案:B分析:动词believe 的用法:直接加that引导的宾语从句。

Searching

Searching

Abstract We propose a strategy for searching for isolated stellar mass black holes in the solar neighborhood with the Sloan Digital Sky Survey. Due to spherical accretion of the inter-stellar medium and the ambient magnetic field, an isolated black hole is expected to emit a blended, thermal synchrotron spectrum with a roughly flat peak from the optical down to the far infra-red. We find that the Sloan Survey will be able to detect isolated black holes, in the considered mass range of 1–100M , out to a few hundred parsecs, depending on the local conditions of the ISM. We also find that the black holes are photmetrically distinguishable from field stars and they have a photometry similar to QSOs. They can be further singled out from QSO searches because they have a featureless spectrum with no emission lines. The Sloan Survey will likely find hundreds of objects that meet these criteria, and to further reduce the number of candidates, we suggest other selection criteria such as infra-red searches and proper motion measurements. Estimates indicate that dozens of black holes may exist out to a few hundred parsecs. If no black hole candidates are found in this survey, important limits can be placed on the local density of black holes and the halo fraction in black holes, especially for masses greater than about 20M .

冰冻的冥王星英文版

冰冻的冥王星英文版


Pluto • Pluto, considered a planet for 76 years, was reclassified as a dwarf planet in 2006. • On August 24, 2006, The International Astronomical Union (IAU), the officially defines a "dwarf planet”
Pluto
Pluto It was predicted by Percival Lowell, based on perturbation theory, but later discovered by Clyde Tombaugh (19061/17/1997) (the first planet found by an American) in 1930 by a fortunate accident.
Pluto
Pluto – Rotation: 6 days/ 9 hrs/ 18 min (RETROGRADE) – Revolves: 248 years – distance: 39.529 AU 3 674 490 973 miles – Gravity: .06 – Tilt 50° – Incline: 17.2 – MASS: 1.27e22 kgperihelion, it is likely that some of the atmosphere escapes to space perhaps even interacting with its moons.
Unit 46
Ice Worlds, Pluto and Beyond
Copyright (c) The McGraw-Hill Companies, Inc. Permission required for reproduction or display.

职称英语理工类C级-49_真题-无答案

职称英语理工类C级-49_真题-无答案

职称英语理工类C级-49(总分100,考试时间90分钟)第1部分:词汇选项下面每个句子中均由1个词或短语划有底横线,请为每处划线部分确定1个意思最接近的选项。

1. I can't put up with my neighbor's noise any longer, it's driving me mad.A. tolerate B. generate C. reduce D. measure2. Regular visits from a social worker can be of immense value to old people living alone.A. equal B. immediate C. moderate D. great3. He was rather vague about the reasons why he never finished school.A. bright B. unclear C. general D. bad4. I want to provide my boys with a decent education.A. special B. private C. general D. good5. Sleep stairs can present a particular hazard to older people.A. picture B. danger C. evidence D. case6. Our arrangements were thrown **plete turmoil.A. doubt B. relief C. failure D. confusion7. He was weary of the constant battle between them.A. fond B. proud C. tired D. afraid8. Your dog needs at least 20 minutes of vigorous exercise every day.A. energetic B. free C. physical D. regular9. I enjoyed the play—it had a clever plot and very funny dialogues.A. boring B. original C. humorous D. long10. Lower taxes would spur investment and help economic growth.A. attract B. spend C. encourage D. require11. He demolished my argument in minutes.A. supported B. disproved C.disputed D. accepted12. Many cities have restricted smoking in public places.A. limited B. allowed C. stopped D. kept13. The two banks have announced plans to merge nest year.A. combine B. sell C. close D. break14. The project required ten years of diligent research.A. hardworking B. social C. basic D. scientific15. He was kept in appalling conditions in prison.A. necessary B. terrible C. critical D. normal第2部分:阅读判断Europa's Watery under WorldEuropa, one of Jupiter's 63 known moons, looks bright and icy on the surface. But appearances can be deceiving: Miles within its cracked, frigid shell, Europa probably hides giant pools of liquid water. Where scientists find liquid water, they hope to find life as well.Since we can't go diving into Europa's depths just yet, scientists instead have to investigate the moon's surface for clues to what lies beneath. In a new study, scientists investigated one group of strange ice patterns on Europa and concluded that the formations mark the top of an underground pool that holds as much water as the U. S. Great Lakes.Pictures of Europa, which is slightly smaller than Earth's moon, clearly show a tangled, icy mishmash of lines and cracks known as "chaos terrains." These chaotic places cover more than half of Europa. For more than 10 years, scientists have wondered what causes the formations. The new study suggests that they arise from the mixing of vast underground stores of liquid water with icy material near the surface.For scientists who suspect that Europa also may be hiding life beneath its icy surface, the news about the new lake is exciting."It would be great if these lakes harbored life, " Britney Schmidt, a planetary scientist who worked on the study, told Science News. "But even if they didn't, they say that Europa is doing something interesting and active right now. "Schmidt, a scientist at the University of Texas at Austin, and her colleagues wanted to know how chaos terrains form. Since they couldn't rocket to Europa to see for themselves, they searched for similar formations here on Earth. They studied collapsed ice shelves in Antarctica and icy caps on volcanoes in Iceland. Those features on Earth formed when liquid water mixed with ice. The scientists now suspect something similar might be happening on Europa: that as water and ice of different temperatures mingle and shift, the surface fractures. This would explain the jumbled ice sculptures."Fracturing catastrophically disrupts the ice in the same way that it causes ice shelves tocollapse on Earth, " Schmidt told Science News. She and her team found that the process could be causing chaos terrains to form quickly on Europa.The new study suggests that on this moon, elements such as oxygen from the surface blend with the deep bodies of water. That mixture may create an environment that supports life.16. The liquid water of an underground pool of Europa is estimated to be equivalent to the water of the U. S. Great lakes.A. Right B. Wrong C. Not mentioned17. The strange ice patterns on Europa are formed as a result of a mixing underground water pool.A. Right B. Wrong C. Not mentioned18. Europa is the most recently discovered one among Jupiter's 63 known moons.A. Right B. Wrong C. Not mentioned19. The size of Europa is a bit larger than that of Earth's moon.A. Right B. Wrong C. Not mentioned20. Schmidt and her colleagues are the first group of scientists studying Europa.A. Right B. Wrong C. Not mentioned21. The formations on Europa's surface are rather unique in the universe.A. Right B. Wrong C. Not mentioned22. The existence of liquid water is a necessity for a life-supportA. Right B. Wrong C. Not mentioned第3部分:概括大意与完成句子Natural Gas1. Natural gas is produced from reservoirs deep beneath the earth's surface. It is a fossil fuel, meaning that it is derived from organic material buried in the earth millions of years ago. The **ponent of natural gas is methane.2. The popularity and use of clean natural gas has increased dramatically over the past 50 years as pipeline infrastructure has been installed to deliver it conveniently and economically to millions of residential, commercial and industrial customers worldwide. Today, natural gas services available in all 50 states in the U.S., and is the leading energy choice for fueling American homes and industries. More than 65 million American homes use natural gas. In fact, natural gas is the most economical source for home energy needs, costing one-third as much as electricity. In addition to heating homes, much of the gas used in the United States is used as a raw material to manufacture a wide variety of products, from paint to fibers for clothing, to plastics for healthcare, computing and furnishings. Natural gas is also used in a significant number of new electricity-generating power plants.3. Natural gas is one of the safest and cleanest fuels available. It emits less pollution than otherfossil fuel sources. When natural gas is burned, it produces mostly carbon dioxide and water vapour—the same substances emitted when humans exhale. Compared with some other fossil fuels, natural gas emits the least amount of carbon dioxide into the air **busted, making natural gas the cleanest burning fossil fuel of all.4. The United States consumes about one-third of the world's natural gas output, making it the largest gas-consuming region in the world. The U.S. Department of Energy Information Administration forecasts that natural gas demand will grow by more than 50 percent by 2025.5. There are huge reserves of natural gas beneath the earth's surface. The largest reserves of natural gas can be found in Russia, West and North Africa and the Middle East. LNG has been produced domestically and imported in the United States for more than four decades. Today, the leading imports of LNG are Japan, Korea, France and Spain.23. Paragraph 2 ______. A. Popularity and use of natural gas B. Natural gas reserves and supply C. Natural gas prices D. Clean fuel of choice E. Disadvantages of natural gas F. Natural gas consumption24. Paragraph 3 ______.25. Paragraph 4 ______.26. Paragraph 5 ______.27. Natural gas is stored deep ______. A. over the past 50 years B. beneath the earth's surface C. by more than 50 percent D. for more than four decadesE. as a raw materialF. for home energy needs28. Natural gas is recognized as the most economical energy source ______.29. When manufacturing many products, **monly use natural gas ______.30. It is estimated that by 2025 that natural gas demand in the United States will increase ______.第4部分:阅读理解下面有3篇短文,每篇短文后有5道题。

Radioactivedecay...

Radioactivedecay...

Radioactive decay lines from asymmetric supernova explosionsA.HungerfordLos Alamos National Laboratory,P.O.Box 1663,Los Alamos,NM 87545,USASteward Observatory,University of Arizona,USAAbstractHigh energy emission from supernovae provide a direct window into the quantity and distribution of radioactive elements produced in these bining supernova explosion calculations with 3D Monte Carlo c -ray transport,I have studied the effect mixing and asymmetries have on the hard X-ray and c -ray spectra.With sufficient spectral resolution,the emission line profiles from nickel decay have enough information to distinguish between spherical and mildly asymmetric supernova explosions.Ó2003Elsevier B.V.All rights reserved.PACS:95.85.Pw;97.60.BwKeywords:c -rays ;Supernovae;Asymmetries1.IntroductionThe past decade has brought great strides in observational and theoretical studies of core-col-lapse supernovae,with interest stimulated by the wealth of data (and surprises)obtained from SN 1987A.For theoretical work in particular,the early emergence of hard X-and c -ray emission from SN 1987A (X-rays:e.g.Dotani et al.,1987;c -rays:e.g.Cook et al.,1988;Mahoney et al.,1988;Matz et al.,1988)signaled a departure from the spherically symmetric geometry that had been as-sumed in models of core-collapse explosions to that point.The appearance of this high energy emission,nearly 6months earlier than theorists had predicted,was most readily explained by theoutward mixing of the nickel synthesized in the inner layers of the explosion (e.g.Pinto and Woosley,1988a;Arnett et al.,1989a,b and refer-ences therein).In addition,line profiles from iron (the daughter product of nickel decay)were broadened to roughly 3500km/s (Spyromilio et al.,1990),further evidence that nickel had been mixed to large radii in the homologous supernova ejecta.This qualitative explanation for the observations motivated several groups to investigate,at a de-tailed level,the multidimensional instabilities which give rise to such mixing within the context of massive star explosions (Arnett et al.,1989a,b;Hachisu et al.,1990;Herant and Benz,1992;Kifonidis et al.,2000).The hydrodynamical sim-ulations carried out by these groups resulted in extended spatial distributions of the nickel,but not sufficiently extended to match the line profiles of the iron emission from SN 1987A.E-mail address:**************(A.Hungerford).1387-6473/$-see front matter Ó2003Elsevier B.V.All rights reserved.doi:10.1016/j.newar.2003.11.001New Astronomy Reviews 48(2004)19–24/locate/newastrevA number of ways to enhance the mixing in theoretical calculations,thus bringing them into agreement with observations,were proposed by Herant and Benz(1992):(1)the decay of56Ni could inject enough energy to force additional mixing,(2)convection in the pre-collapse core could seed more vigorous mixing and(3)global asymmetries in the explosion mechanism itself could enhance mixing along a particular direction in the explosion.This third possibility has been invoked to explain several other observational puzzles regarding core-collapse events.Nagataki et al.(1998)found that not only could slight asymmetries in the supernova explosion produce the required mixing to explain1987A,but they could also explain anomalies in the nucleosyn-thetic yields produced by several supernovae. Furthermore,the most straightforward explana-tion of the large polarization seen in core-collapse supernovae(see Leonard and Filippenko,2001 and references therein)is that the explosion driv-ing these supernovae is inherently asymmetric (H€oflich,1991).In addition,the high observed velocities of pulsars and the formation scenarios of neutron star binaries both suggest that neutron stars are given strong kicks at birth.These kicks are most easily explained by some asymmetry in the supernova explosion where the neutron star is born(see Fryer et al.,1996for a review).In this proceeding,we present theoretical c-ray spectra calculated using asymmetric supernova models as input to a Monte Carlo c-ray transport code.The asymmetry of the input model is moti-vated by the strong asymmetries that stellar rota-tion has been shown to produce in the supernova explosion(M€o nchmeyer and M€u ller,1989;Janka and M€o nchmeyer,1989;Fryer and Heger,2000; Khokhlov et al.,1999).The nature of these asymmetries depends upon the angular momen-tum profile of the collapsing star and,although most calculations predict jet-like explosions along the rotation axis,some calculations imply that an equatorial explosion could occur(M€o nchmeyer and M€u ller,1989).Our spectral calculations were carried out for both a jet-like explosion with axis ratio of2:1(motivated by Fryer and Heger(2000); we refer to this explosion model as Jet2)and a symmetric explosion model(Symmetric).Our analysis of these model spectra concentrates on the differences in total luminosity and line profile shape with the introduction of realistic explosion asymmetries.Since the progenitor star used as in-put to our simulations was a15M red supergiant, we are unable to directly compare our calculated spectra with the observed high energy spectra of SN1987A.However,we discuss how our models compare to various spectral trends observed from SN1987A.2.c-ray line profilesThe high energy spectra were calculated using a Monte Carlo technique,similar to that described in Ambwani and Sutherland(1988),for modeling c-ray transport in three-dimensions.Input models of the supernova ejecta(element abundances, density and velocities)were taken from3D SPH explosion simulations(Hungerford et al.,2003; models Jet2and Symmetric)and mapped onto a 140Â140Â140Cartesian grid.Escaping photons were tallied into250coarse energy bins,withfiner binning at the decay line energies to provide line profile information.The emergent photons were also tallied into11angular bins(D h¼10°)along the polar axis(the models investigated in this work are essentially axisymmetric,alleviating the need to tally in azimuthal angle as well.)A detailed look at the c-ray line profile shapes and strengths,for the1.238and0.847MeV56Co lines,reveals clear trends with viewing angle.Fig.1 shows line profiles of the0.847MeV56Co line for both the Symmetric and Jet2explosion models. We have placed this object at the distance of the Large Magellanic Cloud(60kpc)for easy com-parison withflux data from SN1987A observa-tions.The broadening of the line is caused by Doppler velocity shifts resulting from the spatial distribution of radioactive nickel in the homolo-gously expanding ejecta.The four panels are shown for days200,250,300and365after ex-plosion.The three lines in the Jet2spectra repre-sent different viewing angles through the ejecta (along the pole,the equator and an intermediate angle$45°.)For the Symmetric spectra,we have plotted these same viewing angles.20 A.Hungerford/New Astronomy Reviews48(2004)19–24As we can see from the abovefigure,both ex-plosion scenarios(Symmetric and Jet2)show blue-shifted line profiles,though to varying degree. These differences can be best understood by examining the physical effects which dictate the formation of the line profile edges.The blue edge to the lines is set by the maximum observed line of sight velocity of the56Co in the ejecta.Since the expansion is basically homologous after100days, the line of sight velocity of afluid element in the ejecta is proportional to its distance above the mid-plane of the explosion.Each spectral energy bin in the line profile can be mapped to a unique line of sight velocity in the ejecta,which can in turn be mapped to a specific height above the mid-plane.For example,defining the line of sight to be along the z-axis,the line profile shape should be proportional to the total mass of cobalt summed in x and y as a function of z height in the ejecta. Therefore,the bluest edge of the line will arise from material that was mixed furthest out along the line of sight direction.Fig.2shows a contour plot of density(outer contour)and56Co number density(inner contour) for the Jet2and Symmetric models at t¼150days. Decay of56Co is the major source of c-ray pho-tons,so the inner contour essentially traces the surface of the emission region.The horizontal and vertical lines in Fig.2represent lines of sight from the ejecta surface to the emission source and are labeled with the optical depth along that line-of-sight.The dominant opacity for the hard X-and c-rays is Compton scattering offelectrons and,since the density contours remainroughly A.Hungerford/New Astronomy Reviews48(2004)19–2421spherical in both models,the optical depth from a given point to the ejecta surface is roughly constant.It is clear from Fig.2that the nickel was mixed further out in the polar direction (z -axis of Fig.2)of the asymmetric explosion.Following the arguments above,it is not surprising that the c -ray line profiles viewed along the polar direction are much more blue-shifted for the Jet2model than the Symmetric model.Fig.2does not show a very large difference in the extent of mixing along the equatorial direc-tion between the two models.Correspondingly,the blue edge of the Symmetric lines and the equator view of the Jet2lines are comparable.The red edge of the lines is determined by the escaping emission from 56Co with the smallest line of sight velocity in the ejecta.In a Symmetric model,this should be an indication of how deep into the ejecta we can see along a given viewing angle.However,there is a more pronounced effect at play in the asymmetric explosion models.Much of the c -ray emission for the equatorial view arises from the ‘‘tips’’of the elongated 56Co distribution.This material has a very low line of sight velocity for an equatorial observer,since it is being ejected predominantly in the polar direction.This allows for a significantly lower velocity red edge of the equator view lines,even though the optical depth profiles do not vary much between polar and equator viewing angles.It is interesting to note that the c -ray line pro-files from SN 1987A were in fact red-shifted,a trend that is not obtained with these simulations.Although the c -ray data uncertainties were quite high,this red-shift was also observed in the far infrared forbidden lines of FeII,providing verifi-cation for the c -ray line centroid measurements.As was discussed above,the spectral line shape is directly correlated with the total cobalt mass at a given z -coordinate along the line-of-sight.With this in mind,the observed red-shifted line profiles towards SN 1987A imply,not only a break in spherical symmetry,but also a break in axisym-metry of the ly,there should be more nickel/cobalt mass on the far side of SN 1987A Õs ejecta as seen from our viewing angle.Pulsar ve-locity distributions also support the need for some non-axisymmetry in core-collapse supernova ex-plosions.An interesting study,which will be ad-dressed in a future paper,is to link the magnitude of velocity kick imparted to a neutron star with the compositional asymmetry implied by the red-shif-ted line profiles of SN 1987A.3.Hard X-ray and c -ray spectrumFig.3is a logarithmic plot of the calculated photon flux (c /s/MeV/cm 2)across the entireenergyFig.2.Contour plots in the xz -plane of the Symmetric and Jet2explosion models at t ¼150days.Inner contour is for 56Co number density which traces the surface of the c -ray emitting region.Outer contour is for the mass density which follows electron density and thus traces the dominant opacity source (Compton scattering).The lines represent lines-of-sight through the ejecta for which the optical depth from emission region to ejecta surface has been calculated.Regardless of viewing angle,the optical depth of the 56Co ejected along the poles in the Jet2explosion remains quite low.Hence,it is this material that dominates the observed emission for all viewing angles in the aspherical explosion.22 A.Hungerford /New Astronomy Reviews 48(2004)19–24range investigated with these simulations(0.3keV to4MeV).Thefive panels are spectra from the different time slices;in each panel,we plot the spectrum for the Symmetric model,along with polar and equatorial views of the Jet2model.The effects of mixing are present in both these simula-tions,though at differing levels due to the differ-ences in explosion asymmetry.It can be seen immediately that the hard X-rays emerge earlier from the ejecta with a global explosion asymmetry (Jet2model).This holds regardless of viewing an-gle(pole versus equator)towards the explosion.As discussed in Section1,the observed high energy spectrum of SN1987A differed from the predictions of theoretical onion-skin models in two fundamental ways.Both the broad lines of nickel and the early emergence of the hard X-rays could be explained qualitatively by invoking a mixing argument.From a theoretical standpoint,including a1D prescription for that mixing makes the as-sumption that both data points can befit with one free parameter.However,the simulations in this work suggest that the addition of a global asym-metry will change the direct correlation between the emergence time and the degree of line broadening. That is to say,for a given hard X-rayflux,the Symmetric model will correspond to a single line profile,regardless of viewing angle.The Jet2model, however,produces similar hard X-ray continua for different viewing angles,but the line profile varies significantly with viewing angle.In fact,the data for SN1987A(the c-line profiles and hard X-ray continuum)were notfit well by1D models.In particular,the model10HMM(Pinto and Woos-ley,1988a),which was mixed sufficiently to account for theflux in the hard X-ray continuum observa-tions,resulted in c-line centroids that were shifted too far to the blue(Tueller et al.,1990).Although the uncertainties in these data were relatively large, this trend may be in the right direction to suggest a global asymmetry(i.e.,an asymmetric explosion scenario for SN1987A could produce thesame A.Hungerford/New Astronomy Reviews48(2004)19–2423hard X-rayflux level,but with a redder line profile than the symmetric explosion scenario). ReferencesAmbwani,K.,Sutherland,P.,1988.ApJ325,820.Arnett,D.,Fryxell,B.,M€u ller,E.,1989a.ApJ341,L63. Arnett,W.D.,Bahcall,J.N.,Kirshner,R.P.,Woosley,S.E., 1989b.ARA&A27,629.Cook,W.R.,Palmer, D.M.,Prince,T.A.,Schindler,S.M., Starr,C.H.,Stone,E.C.,1988.ApJ334,L87.Dotani,T.,Hayashida,K.,Inoue,H.,Itoh,M.,Koyama,K., 1987.Nature330,230.Fryer,C.L.,Burrows,A.,Benz,W.,1996.ApJ496,333. Fryer,C.L.,Heger,A.,2000.ApJ541,1033.Hachisu,I.,Matsuda,T.,Nomoto,K.,Shigeyama,T.,1990.ApJ358,L57.Herant,M.,Benz,W.,1992.ApJ387,294.H€oflich,P.,1991.A&A246,481.Hungerford,A.L.,Fryer,C.L.,Warren,M.S.,2003.ApJ594, 390.Janka,H.-T.,M€o nchmeyer,R.,1989.A&A209,L5. Kifonidis,K.,Plewa,T.,Janka,H.-T.,M€u ller,E.,2000.ApJ 531,L123.Khokhlov, A.M.,H€oflich,P.A.,Oran, E.S.,Wheeler,J.C., Wang,L.,Chtchelkanova,A.Yu.,1999.ApJ524,L107. Leonard,D.C.,Filippenko,A.V.,2001.PASP113,920. Mahoney,W.A.,Varnell,L.S.,Jacobson, A.S.,Ling,J.C., Radocinski,R.G.,Wheaton,Wm.A.,1988.ApJ334,L81. Matz,S.M.,Share,G.H.,Leising,M.D.,Chupp, E.L., Vestrand,W.T.,1988.Nature331,416.M€o nchmeyer,R.,M€u ller,E.,1989.In:€Ogelman,H.,van den Heuvel,E.P.J.(Eds.),NATO ASI Series,Timing Neutron Stars.ASI,New York.Nagataki,S.,Shimizu,T.M.,Sato,K.,1998.ApJ495,413. Pinto,P.A.,Woosley,S.E.,1988a.ApJ329,820. Spyromilio,J.,Meikle,W.P.S.,Allen,D.A.,1990.MNRAS 242,669.Tueller,J.,Barthelmy,S.,Gehrels,N.,Teegarden, B.J., Leventhal,M.,MacCallum,C.J.,1990.ApJ351,L41.24 A.Hungerford/New Astronomy Reviews48(2004)19–24。

From Data Mining to Knowledge Discovery in Databases

From Data Mining to Knowledge Discovery in Databases

s Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media atten-tion of late. What is all the excitement about?This article provides an overview of this emerging field, clarifying how data mining and knowledge discovery in databases are related both to each other and to related fields, such as machine learning, statistics, and databases. The article mentions particular real-world applications, specific data-mining techniques, challenges in-volved in real-world applications of knowledge discovery, and current and future research direc-tions in the field.A cross a wide variety of fields, data arebeing collected and accumulated at adramatic pace. There is an urgent need for a new generation of computational theo-ries and tools to assist humans in extracting useful information (knowledge) from the rapidly growing volumes of digital data. These theories and tools are the subject of the emerging field of knowledge discovery in databases (KDD).At an abstract level, the KDD field is con-cerned with the development of methods and techniques for making sense of data. The basic problem addressed by the KDD process is one of mapping low-level data (which are typically too voluminous to understand and digest easi-ly) into other forms that might be more com-pact (for example, a short report), more ab-stract (for example, a descriptive approximation or model of the process that generated the data), or more useful (for exam-ple, a predictive model for estimating the val-ue of future cases). At the core of the process is the application of specific data-mining meth-ods for pattern discovery and extraction.1This article begins by discussing the histori-cal context of KDD and data mining and theirintersection with other related fields. A briefsummary of recent KDD real-world applica-tions is provided. Definitions of KDD and da-ta mining are provided, and the general mul-tistep KDD process is outlined. This multistepprocess has the application of data-mining al-gorithms as one particular step in the process.The data-mining step is discussed in more de-tail in the context of specific data-mining al-gorithms and their application. Real-worldpractical application issues are also outlined.Finally, the article enumerates challenges forfuture research and development and in par-ticular discusses potential opportunities for AItechnology in KDD systems.Why Do We Need KDD?The traditional method of turning data intoknowledge relies on manual analysis and in-terpretation. For example, in the health-careindustry, it is common for specialists to peri-odically analyze current trends and changesin health-care data, say, on a quarterly basis.The specialists then provide a report detailingthe analysis to the sponsoring health-care or-ganization; this report becomes the basis forfuture decision making and planning forhealth-care management. In a totally differ-ent type of application, planetary geologistssift through remotely sensed images of plan-ets and asteroids, carefully locating and cata-loging such geologic objects of interest as im-pact craters. Be it science, marketing, finance,health care, retail, or any other field, the clas-sical approach to data analysis relies funda-mentally on one or more analysts becomingArticlesFALL 1996 37From Data Mining to Knowledge Discovery inDatabasesUsama Fayyad, Gregory Piatetsky-Shapiro, and Padhraic Smyth Copyright © 1996, American Association for Artificial Intelligence. All rights reserved. 0738-4602-1996 / $2.00areas is astronomy. Here, a notable success was achieved by SKICAT ,a system used by as-tronomers to perform image analysis,classification, and cataloging of sky objects from sky-survey images (Fayyad, Djorgovski,and Weir 1996). In its first application, the system was used to process the 3 terabytes (1012bytes) of image data resulting from the Second Palomar Observatory Sky Survey,where it is estimated that on the order of 109sky objects are detectable. SKICAT can outper-form humans and traditional computational techniques in classifying faint sky objects. See Fayyad, Haussler, and Stolorz (1996) for a sur-vey of scientific applications.In business, main KDD application areas includes marketing, finance (especially in-vestment), fraud detection, manufacturing,telecommunications, and Internet agents.Marketing:In marketing, the primary ap-plication is database marketing systems,which analyze customer databases to identify different customer groups and forecast their behavior. Business Week (Berry 1994) estimat-ed that over half of all retailers are using or planning to use database marketing, and those who do use it have good results; for ex-ample, American Express reports a 10- to 15-percent increase in credit-card use. Another notable marketing application is market-bas-ket analysis (Agrawal et al. 1996) systems,which find patterns such as, “If customer bought X, he/she is also likely to buy Y and Z.” Such patterns are valuable to retailers.Investment: Numerous companies use da-ta mining for investment, but most do not describe their systems. One exception is LBS Capital Management. Its system uses expert systems, neural nets, and genetic algorithms to manage portfolios totaling $600 million;since its start in 1993, the system has outper-formed the broad stock market (Hall, Mani,and Barr 1996).Fraud detection: HNC Falcon and Nestor PRISM systems are used for monitoring credit-card fraud, watching over millions of ac-counts. The FAIS system (Senator et al. 1995),from the U.S. Treasury Financial Crimes En-forcement Network, is used to identify finan-cial transactions that might indicate money-laundering activity.Manufacturing: The CASSIOPEE trou-bleshooting system, developed as part of a joint venture between General Electric and SNECMA, was applied by three major Euro-pean airlines to diagnose and predict prob-lems for the Boeing 737. To derive families of faults, clustering methods are used. CASSIOPEE received the European first prize for innova-intimately familiar with the data and serving as an interface between the data and the users and products.For these (and many other) applications,this form of manual probing of a data set is slow, expensive, and highly subjective. In fact, as data volumes grow dramatically, this type of manual data analysis is becoming completely impractical in many domains.Databases are increasing in size in two ways:(1) the number N of records or objects in the database and (2) the number d of fields or at-tributes to an object. Databases containing on the order of N = 109objects are becoming in-creasingly common, for example, in the as-tronomical sciences. Similarly, the number of fields d can easily be on the order of 102or even 103, for example, in medical diagnostic applications. Who could be expected to di-gest millions of records, each having tens or hundreds of fields? We believe that this job is certainly not one for humans; hence, analysis work needs to be automated, at least partially.The need to scale up human analysis capa-bilities to handling the large number of bytes that we can collect is both economic and sci-entific. Businesses use data to gain competi-tive advantage, increase efficiency, and pro-vide more valuable services to customers.Data we capture about our environment are the basic evidence we use to build theories and models of the universe we live in. Be-cause computers have enabled humans to gather more data than we can digest, it is on-ly natural to turn to computational tech-niques to help us unearth meaningful pat-terns and structures from the massive volumes of data. Hence, KDD is an attempt to address a problem that the digital informa-tion era made a fact of life for all of us: data overload.Data Mining and Knowledge Discovery in the Real WorldA large degree of the current interest in KDD is the result of the media interest surrounding successful KDD applications, for example, the focus articles within the last two years in Business Week , Newsweek , Byte , PC Week , and other large-circulation periodicals. Unfortu-nately, it is not always easy to separate fact from media hype. Nonetheless, several well-documented examples of successful systems can rightly be referred to as KDD applications and have been deployed in operational use on large-scale real-world problems in science and in business.In science, one of the primary applicationThere is an urgent need for a new generation of computation-al theories and tools toassist humans in extractinguseful information (knowledge)from the rapidly growing volumes ofdigital data.Articles38AI MAGAZINEtive applications (Manago and Auriol 1996).Telecommunications: The telecommuni-cations alarm-sequence analyzer (TASA) wasbuilt in cooperation with a manufacturer oftelecommunications equipment and threetelephone networks (Mannila, Toivonen, andVerkamo 1995). The system uses a novelframework for locating frequently occurringalarm episodes from the alarm stream andpresenting them as rules. Large sets of discov-ered rules can be explored with flexible infor-mation-retrieval tools supporting interactivityand iteration. In this way, TASA offers pruning,grouping, and ordering tools to refine the re-sults of a basic brute-force search for rules.Data cleaning: The MERGE-PURGE systemwas applied to the identification of duplicatewelfare claims (Hernandez and Stolfo 1995).It was used successfully on data from the Wel-fare Department of the State of Washington.In other areas, a well-publicized system isIBM’s ADVANCED SCOUT,a specialized data-min-ing system that helps National Basketball As-sociation (NBA) coaches organize and inter-pret data from NBA games (U.S. News 1995). ADVANCED SCOUT was used by several of the NBA teams in 1996, including the Seattle Su-personics, which reached the NBA finals.Finally, a novel and increasingly importanttype of discovery is one based on the use of in-telligent agents to navigate through an infor-mation-rich environment. Although the ideaof active triggers has long been analyzed in thedatabase field, really successful applications ofthis idea appeared only with the advent of theInternet. These systems ask the user to specifya profile of interest and search for related in-formation among a wide variety of public-do-main and proprietary sources. For example, FIREFLY is a personal music-recommendation agent: It asks a user his/her opinion of several music pieces and then suggests other music that the user might like (<http:// www.ffl/>). CRAYON(/>) allows users to create their own free newspaper (supported by ads); NEWSHOUND(<http://www. /hound/>) from the San Jose Mercury News and FARCAST(</> automatically search information from a wide variety of sources, including newspapers and wire services, and e-mail rele-vant documents directly to the user.These are just a few of the numerous suchsystems that use KDD techniques to automat-ically produce useful information from largemasses of raw data. See Piatetsky-Shapiro etal. (1996) for an overview of issues in devel-oping industrial KDD applications.Data Mining and KDDHistorically, the notion of finding useful pat-terns in data has been given a variety ofnames, including data mining, knowledge ex-traction, information discovery, informationharvesting, data archaeology, and data patternprocessing. The term data mining has mostlybeen used by statisticians, data analysts, andthe management information systems (MIS)communities. It has also gained popularity inthe database field. The phrase knowledge dis-covery in databases was coined at the first KDDworkshop in 1989 (Piatetsky-Shapiro 1991) toemphasize that knowledge is the end productof a data-driven discovery. It has been popular-ized in the AI and machine-learning fields.In our view, KDD refers to the overall pro-cess of discovering useful knowledge from da-ta, and data mining refers to a particular stepin this process. Data mining is the applicationof specific algorithms for extracting patternsfrom data. The distinction between the KDDprocess and the data-mining step (within theprocess) is a central point of this article. Theadditional steps in the KDD process, such asdata preparation, data selection, data cleaning,incorporation of appropriate prior knowledge,and proper interpretation of the results ofmining, are essential to ensure that usefulknowledge is derived from the data. Blind ap-plication of data-mining methods (rightly crit-icized as data dredging in the statistical litera-ture) can be a dangerous activity, easilyleading to the discovery of meaningless andinvalid patterns.The Interdisciplinary Nature of KDDKDD has evolved, and continues to evolve,from the intersection of research fields such asmachine learning, pattern recognition,databases, statistics, AI, knowledge acquisitionfor expert systems, data visualization, andhigh-performance computing. The unifyinggoal is extracting high-level knowledge fromlow-level data in the context of large data sets.The data-mining component of KDD cur-rently relies heavily on known techniquesfrom machine learning, pattern recognition,and statistics to find patterns from data in thedata-mining step of the KDD process. A natu-ral question is, How is KDD different from pat-tern recognition or machine learning (and re-lated fields)? The answer is that these fieldsprovide some of the data-mining methodsthat are used in the data-mining step of theKDD process. KDD focuses on the overall pro-cess of knowledge discovery from data, includ-ing how the data are stored and accessed, howalgorithms can be scaled to massive data setsThe basicproblemaddressed bythe KDDprocess isone ofmappinglow-leveldata intoother formsthat might bemorecompact,moreabstract,or moreuseful.ArticlesFALL 1996 39A driving force behind KDD is the database field (the second D in KDD). Indeed, the problem of effective data manipulation when data cannot fit in the main memory is of fun-damental importance to KDD. Database tech-niques for gaining efficient data access,grouping and ordering operations when ac-cessing data, and optimizing queries consti-tute the basics for scaling algorithms to larger data sets. Most data-mining algorithms from statistics, pattern recognition, and machine learning assume data are in the main memo-ry and pay no attention to how the algorithm breaks down if only limited views of the data are possible.A related field evolving from databases is data warehousing,which refers to the popular business trend of collecting and cleaning transactional data to make them available for online analysis and decision support. Data warehousing helps set the stage for KDD in two important ways: (1) data cleaning and (2)data access.Data cleaning: As organizations are forced to think about a unified logical view of the wide variety of data and databases they pos-sess, they have to address the issues of map-ping data to a single naming convention,uniformly representing and handling missing data, and handling noise and errors when possible.Data access: Uniform and well-defined methods must be created for accessing the da-ta and providing access paths to data that were historically difficult to get to (for exam-ple, stored offline).Once organizations and individuals have solved the problem of how to store and ac-cess their data, the natural next step is the question, What else do we do with all the da-ta? This is where opportunities for KDD natu-rally arise.A popular approach for analysis of data warehouses is called online analytical processing (OLAP), named for a set of principles pro-posed by Codd (1993). OLAP tools focus on providing multidimensional data analysis,which is superior to SQL in computing sum-maries and breakdowns along many dimen-sions. OLAP tools are targeted toward simpli-fying and supporting interactive data analysis,but the goal of KDD tools is to automate as much of the process as possible. Thus, KDD is a step beyond what is currently supported by most standard database systems.Basic DefinitionsKDD is the nontrivial process of identifying valid, novel, potentially useful, and ultimate-and still run efficiently, how results can be in-terpreted and visualized, and how the overall man-machine interaction can usefully be modeled and supported. The KDD process can be viewed as a multidisciplinary activity that encompasses techniques beyond the scope of any one particular discipline such as machine learning. In this context, there are clear opportunities for other fields of AI (be-sides machine learning) to contribute to KDD. KDD places a special emphasis on find-ing understandable patterns that can be inter-preted as useful or interesting knowledge.Thus, for example, neural networks, although a powerful modeling tool, are relatively difficult to understand compared to decision trees. KDD also emphasizes scaling and ro-bustness properties of modeling algorithms for large noisy data sets.Related AI research fields include machine discovery, which targets the discovery of em-pirical laws from observation and experimen-tation (Shrager and Langley 1990) (see Kloes-gen and Zytkow [1996] for a glossary of terms common to KDD and machine discovery),and causal modeling for the inference of causal models from data (Spirtes, Glymour,and Scheines 1993). Statistics in particular has much in common with KDD (see Elder and Pregibon [1996] and Glymour et al.[1996] for a more detailed discussion of this synergy). Knowledge discovery from data is fundamentally a statistical endeavor. Statistics provides a language and framework for quan-tifying the uncertainty that results when one tries to infer general patterns from a particu-lar sample of an overall population. As men-tioned earlier, the term data mining has had negative connotations in statistics since the 1960s when computer-based data analysis techniques were first introduced. The concern arose because if one searches long enough in any data set (even randomly generated data),one can find patterns that appear to be statis-tically significant but, in fact, are not. Clearly,this issue is of fundamental importance to KDD. Substantial progress has been made in recent years in understanding such issues in statistics. Much of this work is of direct rele-vance to KDD. Thus, data mining is a legiti-mate activity as long as one understands how to do it correctly; data mining carried out poorly (without regard to the statistical as-pects of the problem) is to be avoided. KDD can also be viewed as encompassing a broader view of modeling than statistics. KDD aims to provide tools to automate (to the degree pos-sible) the entire process of data analysis and the statistician’s “art” of hypothesis selection.Data mining is a step in the KDD process that consists of ap-plying data analysis and discovery al-gorithms that produce a par-ticular enu-meration ofpatterns (or models)over the data.Articles40AI MAGAZINEly understandable patterns in data (Fayyad, Piatetsky-Shapiro, and Smyth 1996).Here, data are a set of facts (for example, cases in a database), and pattern is an expres-sion in some language describing a subset of the data or a model applicable to the subset. Hence, in our usage here, extracting a pattern also designates fitting a model to data; find-ing structure from data; or, in general, mak-ing any high-level description of a set of data. The term process implies that KDD comprises many steps, which involve data preparation, search for patterns, knowledge evaluation, and refinement, all repeated in multiple itera-tions. By nontrivial, we mean that some search or inference is involved; that is, it is not a straightforward computation of predefined quantities like computing the av-erage value of a set of numbers.The discovered patterns should be valid on new data with some degree of certainty. We also want patterns to be novel (at least to the system and preferably to the user) and poten-tially useful, that is, lead to some benefit to the user or task. Finally, the patterns should be understandable, if not immediately then after some postprocessing.The previous discussion implies that we can define quantitative measures for evaluating extracted patterns. In many cases, it is possi-ble to define measures of certainty (for exam-ple, estimated prediction accuracy on new data) or utility (for example, gain, perhaps indollars saved because of better predictions orspeedup in response time of a system). No-tions such as novelty and understandabilityare much more subjective. In certain contexts,understandability can be estimated by sim-plicity (for example, the number of bits to de-scribe a pattern). An important notion, calledinterestingness(for example, see Silberschatzand Tuzhilin [1995] and Piatetsky-Shapiro andMatheus [1994]), is usually taken as an overallmeasure of pattern value, combining validity,novelty, usefulness, and simplicity. Interest-ingness functions can be defined explicitly orcan be manifested implicitly through an or-dering placed by the KDD system on the dis-covered patterns or models.Given these notions, we can consider apattern to be knowledge if it exceeds some in-terestingness threshold, which is by nomeans an attempt to define knowledge in thephilosophical or even the popular view. As amatter of fact, knowledge in this definition ispurely user oriented and domain specific andis determined by whatever functions andthresholds the user chooses.Data mining is a step in the KDD processthat consists of applying data analysis anddiscovery algorithms that, under acceptablecomputational efficiency limitations, pro-duce a particular enumeration of patterns (ormodels) over the data. Note that the space ofArticlesFALL 1996 41Figure 1. An Overview of the Steps That Compose the KDD Process.methods, the effective number of variables under consideration can be reduced, or in-variant representations for the data can be found.Fifth is matching the goals of the KDD pro-cess (step 1) to a particular data-mining method. For example, summarization, clas-sification, regression, clustering, and so on,are described later as well as in Fayyad, Piatet-sky-Shapiro, and Smyth (1996).Sixth is exploratory analysis and model and hypothesis selection: choosing the data-mining algorithm(s) and selecting method(s)to be used for searching for data patterns.This process includes deciding which models and parameters might be appropriate (for ex-ample, models of categorical data are differ-ent than models of vectors over the reals) and matching a particular data-mining method with the overall criteria of the KDD process (for example, the end user might be more in-terested in understanding the model than its predictive capabilities).Seventh is data mining: searching for pat-terns of interest in a particular representa-tional form or a set of such representations,including classification rules or trees, regres-sion, and clustering. The user can significant-ly aid the data-mining method by correctly performing the preceding steps.Eighth is interpreting mined patterns, pos-sibly returning to any of steps 1 through 7 for further iteration. This step can also involve visualization of the extracted patterns and models or visualization of the data given the extracted models.Ninth is acting on the discovered knowl-edge: using the knowledge directly, incorpo-rating the knowledge into another system for further action, or simply documenting it and reporting it to interested parties. This process also includes checking for and resolving po-tential conflicts with previously believed (or extracted) knowledge.The KDD process can involve significant iteration and can contain loops between any two steps. The basic flow of steps (al-though not the potential multitude of itera-tions and loops) is illustrated in figure 1.Most previous work on KDD has focused on step 7, the data mining. However, the other steps are as important (and probably more so) for the successful application of KDD in practice. Having defined the basic notions and introduced the KDD process, we now focus on the data-mining component,which has, by far, received the most atten-tion in the literature.patterns is often infinite, and the enumera-tion of patterns involves some form of search in this space. Practical computational constraints place severe limits on the sub-space that can be explored by a data-mining algorithm.The KDD process involves using the database along with any required selection,preprocessing, subsampling, and transforma-tions of it; applying data-mining methods (algorithms) to enumerate patterns from it;and evaluating the products of data mining to identify the subset of the enumerated pat-terns deemed knowledge. The data-mining component of the KDD process is concerned with the algorithmic means by which pat-terns are extracted and enumerated from da-ta. The overall KDD process (figure 1) in-cludes the evaluation and possible interpretation of the mined patterns to de-termine which patterns can be considered new knowledge. The KDD process also in-cludes all the additional steps described in the next section.The notion of an overall user-driven pro-cess is not unique to KDD: analogous propos-als have been put forward both in statistics (Hand 1994) and in machine learning (Brod-ley and Smyth 1996).The KDD ProcessThe KDD process is interactive and iterative,involving numerous steps with many deci-sions made by the user. Brachman and Anand (1996) give a practical view of the KDD pro-cess, emphasizing the interactive nature of the process. Here, we broadly outline some of its basic steps:First is developing an understanding of the application domain and the relevant prior knowledge and identifying the goal of the KDD process from the customer’s viewpoint.Second is creating a target data set: select-ing a data set, or focusing on a subset of vari-ables or data samples, on which discovery is to be performed.Third is data cleaning and preprocessing.Basic operations include removing noise if appropriate, collecting the necessary informa-tion to model or account for noise, deciding on strategies for handling missing data fields,and accounting for time-sequence informa-tion and known changes.Fourth is data reduction and projection:finding useful features to represent the data depending on the goal of the task. With di-mensionality reduction or transformationArticles42AI MAGAZINEThe Data-Mining Stepof the KDD ProcessThe data-mining component of the KDD pro-cess often involves repeated iterative applica-tion of particular data-mining methods. This section presents an overview of the primary goals of data mining, a description of the methods used to address these goals, and a brief description of the data-mining algo-rithms that incorporate these methods.The knowledge discovery goals are defined by the intended use of the system. We can distinguish two types of goals: (1) verification and (2) discovery. With verification,the sys-tem is limited to verifying the user’s hypothe-sis. With discovery,the system autonomously finds new patterns. We further subdivide the discovery goal into prediction,where the sys-tem finds patterns for predicting the future behavior of some entities, and description, where the system finds patterns for presenta-tion to a user in a human-understandableform. In this article, we are primarily con-cerned with discovery-oriented data mining.Data mining involves fitting models to, or determining patterns from, observed data. The fitted models play the role of inferred knowledge: Whether the models reflect useful or interesting knowledge is part of the over-all, interactive KDD process where subjective human judgment is typically required. Two primary mathematical formalisms are used in model fitting: (1) statistical and (2) logical. The statistical approach allows for nondeter-ministic effects in the model, whereas a logi-cal model is purely deterministic. We focus primarily on the statistical approach to data mining, which tends to be the most widely used basis for practical data-mining applica-tions given the typical presence of uncertain-ty in real-world data-generating processes.Most data-mining methods are based on tried and tested techniques from machine learning, pattern recognition, and statistics: classification, clustering, regression, and so on. The array of different algorithms under each of these headings can often be bewilder-ing to both the novice and the experienced data analyst. It should be emphasized that of the many data-mining methods advertised in the literature, there are really only a few fun-damental techniques. The actual underlying model representation being used by a particu-lar method typically comes from a composi-tion of a small number of well-known op-tions: polynomials, splines, kernel and basis functions, threshold-Boolean functions, and so on. Thus, algorithms tend to differ primar-ily in the goodness-of-fit criterion used toevaluate model fit or in the search methodused to find a good fit.In our brief overview of data-mining meth-ods, we try in particular to convey the notionthat most (if not all) methods can be viewedas extensions or hybrids of a few basic tech-niques and principles. We first discuss the pri-mary methods of data mining and then showthat the data- mining methods can be viewedas consisting of three primary algorithmiccomponents: (1) model representation, (2)model evaluation, and (3) search. In the dis-cussion of KDD and data-mining methods,we use a simple example to make some of thenotions more concrete. Figure 2 shows a sim-ple two-dimensional artificial data set consist-ing of 23 cases. Each point on the graph rep-resents a person who has been given a loanby a particular bank at some time in the past.The horizontal axis represents the income ofthe person; the vertical axis represents the to-tal personal debt of the person (mortgage, carpayments, and so on). The data have beenclassified into two classes: (1) the x’s repre-sent persons who have defaulted on theirloans and (2) the o’s represent persons whoseloans are in good status with the bank. Thus,this simple artificial data set could represent ahistorical data set that can contain usefulknowledge from the point of view of thebank making the loans. Note that in actualKDD applications, there are typically manymore dimensions (as many as several hun-dreds) and many more data points (manythousands or even millions).ArticlesFALL 1996 43Figure 2. A Simple Data Set with Two Classes Used for Illustrative Purposes.。

你的新学校是什么样的英语作文

你的新学校是什么样的英语作文

你的新学校是什么样的英语作文全文共3篇示例,供读者参考篇1My New School: A Whole New WorldThe first day of school can be pretty intimidating, especially when you're the new kid. As I walked through the front gates of Oakwood Academy, my stomach was doing backflips. I clutched my backpack straps tightly, trying to keep my cool. This was a fresh start, a chance to reinvent myself after a rocky couple of years at my old school. Still, the prospect of navigating a giant new campus with hundreds of unfamiliar faces was unnerving. Little did I know, Oakwood would end up feeling like a second home within a matter of weeks.The campus itself is stunning, with historic brick buildings, lush green quads, and winding pathways lined with towering oak trees. From the moment I stepped foot on the grounds, I could sense the palpable history and tradition. Oakwood has been around for over a century, and the architecture gives it such an elegant, refined ambiance. My favorite spot is the outdoor amphitheater, with its curved stone benches nestled under acanopy of trees. I can already envision myself studying or just hanging out there when the weather is nice.Despite its grandeur, Oakwood isn't as intimidating as I initially feared. The students are remarkably friendly and welcoming. On my first day, an energetic group of seniors who serve as student ambassadors gave me and the other new students a comprehensive tour. They didn't just show us where our classes were located; they gave us an inside scoop on all the best clubs, events, and hangout spots. Their energy and school spirit were infectious. By the end of the tour, I was buzzing with excitement about joining clubs and getting involved.Speaking of clubs, Oakwood has an incredible range of extracurriculars on offer, from academic teams and cultural organizations to community service groups and nicheinterest-based clubs. There's seriously something for everyone here. I've already joined the Creative Writing Club, Environmental Club, and an intramural basketball team. Getting involved right off the bat has helped me make new friends and start feeling like part of the community.The classroom experience has been stellar so far too. The teachers all seem incredibly passionate about their subjects and genuinely invested in their students' learning. In many of myclasses, we spend just as much time engaging in dynamic discussions as we do taking notes on lectures. The teachers really emphasize critical thinking, analysis, and forming our own substantiated perspectives rather than just memorizing information. It's challenging in the best way possible.Oakwood also places a huge emphasis on fostering a diverse, inclusive community. Students come from all sorts of different backgrounds, cultures, and walks of life. I love how comfortable everyone seems expressing their authentic selves and how much we can all learn from each other's unique experiences and viewpoints. There are all kinds of cultural clubs and affinity groups that celebrate the school's diversity.One thing I've been pleasantly surprised by is Oakwood's focus on holistic wellbeing in addition to academics. Built right into our schedules are wellness periods for things like meditation, yoga, or just taking some down time to recharge. There are nutritious meals and snacks available at the dining hall. The gym facilities are top-notch, with an indoor pool, rock climbing wall, and tons of fun fitness classes offered. Oakwood really seems to prioritize mental health and work-life balance, which is so important for overworked high schoolers.Of course, it hasn't been all sunshine and rainbows. Navigating the sheer size of the campus made me late to class a few times those first couple of weeks (note to self: leave way more time than you think you'll need!). And starting fresh means I'm still in the process of developing my core friend group. But I've found that putting myself out there by sitting with new people at lunch, staying after class to chat with teachers, and just generally having an open, friendly attitude has helped me start making connections.Overall, my experience at Oakwood so far has exceeded my highest expectations. I've found a place where I'm constantly inspired to grow, both academically and personally. A place where individualism and free-thinking are celebrated. A place that feels warm and nurturing, yet also electrifying with opportunity. While my first few days were tinged with nervousness and self-doubt, Oakwood has already started feeling like home. I know this next chapter will be filled with amazing friendships, thought-provoking learning experiences, and enough magical memories to last a lifetime. I've found my people and my place. Bring it on, Oakwood!篇2My New School: A Whole New WorldThe first day of school is always nerve-wracking, but starting at a brand new school amps up those jitters to a whole new level. As I pulled into the parking lot that first morning, my stomach was doing backflips. Would I be able to find my classes okay? Would the teachers be nice? Most importantly, would I make any friends? My old school had felt like a second home, but this place was totally unfamiliar territory. I took a deep breath, grabbed my backpack, and headed towards the main entrance.The school building itself was massive, with long hallways branching off in every direction like a maze. Luckily, the main office had free maps to help newcomers like me navigate. I quickly located my first class – English Literature. The room was pretty standard as far as classrooms go, with rows of small desks and a whiteboard at the front. A "Welcome Back!" banner hung crookedly above the chalkboard. Mrs. Robertson, an older woman with a kind smile, introduced herself as I entered. She didn't seem too intimidating, I thought with relief.As the rest of the students filtered in, I realized I was one of the only new faces. Everyone else appeared to already have their friend groups established, chatting and laughing like they'd known each other for years. I shrank down in my desk chair,trying not to make eye contact. This was going to be harder than I thought.The morning passed in a blur as I bounced from English to History to Math, struggling to find each room amidst the maze of hallways. A few girls did smile and introduce themselves in the hallway, which was encouraging. Maybe I wouldn't be a total outcast after all.Finally, the bell rang for lunch. I followed the herd of hungry students towards the cafeteria, which was basically a huge concrete room with tables haphazardly scattered throughout. The line for hot food looked incredibly long, so I just grabbed a pre-made salad from the cooler and scanned the room for a friendly face.That's when I saw them - the a cappella group performing in the center of the cafeteria. There were about fifteen of them, split into movements like a choreographed dance. But instead of just moving, they were using their mouths to create an intricate melody, complete with harmonies and beat-boxing. I was totally transfixed. Their sound blended together into one powerful voice, ringing out with a vitality and passion unlike anything I'd heard before. As the song came to a close, the group was met with raucous cheering and applause from the tables aroundthem. A wave of adrenaline rushed through me. That was the most amazing thing I'd ever witnessed.At that moment, I knew I had to be a part of that group. The way they commanded that room with just their voices, the confidence and joy radiating from their faces – I craved that feeling more than anything. I spent the rest of my lunch period shyly approaching group members one by one, working up the courage to ask how I could audition. They all gave me friendly smiles and directed me to the director, Mr. Palmer.I finally tracked down Mr. Palmer in the hallway after lunch. He was a younger guy, probably in his late 20s, with a big personality and even bigger smile. "You're interested in joining Ocean Harmonies?" he asked when I admitted why I wanted to talk to him. His eyes lit up. "That's awesome! We're always looking for new vocal talent." He rapidly gave me information about the audition process, practice schedule, and time commitment required. It was a lot to take in, but the more he spoke, the more I knew this was exactly what I wanted. Finally, a chance to be part of something incredible.The next few weeks were a whirlwind of studying music theory, working on my vocal technique, and preparing myaudition song. I spent every spare minute I had practicing. This audition meant everything to me.Finally, the day arrived. As I stepped out onto the auditorium stage, I was terrified. But as soon as the first few notes left my lips, I was transported. Singing had always been a release for me, a way to get out of my own head and exist purely in the moment. When the final chorus rang out, I knew I had given it my absolute all.A few days later, I arrived at school early one morning to find the audition results posted on the call board. I dragged my finger down the list of names, not letting myself get my hopes up. And then, there it was - my name, printed in bold. I let out a shriek of joy that echoed through the empty hallway. I had made it. I was going to be part of Ocean Harmonies.The rest of the year passed in a happy blur. Rehearsals with the group were my favorite part of each day, as we bonded over our shared love of music. Shows and competitions allowed us to take our passion on the road. I had finally found my crew, my place to belong. What had once seemed like a terrifying new world was now my home.As I look back on that first day, driving up to the looming building with shaky hands, I can't help but smile. My new schoolhas given me a chance to discover talents and passions I never knew I had. It's pushed me out of my comfort zone in the best way possible. More than that, it's shown me the importance of taking risks and opening yourself up to new experiences. If I had allowed my fears to rule me that first day, I never would have stumbled upon the incredible group that is now my second family. This school has made me into a braver, more confident person. Though the hallways are still a bit of a maze, I now navigate them with pride, because this place is mine. This whole new world is where I've uncovered my true voice. Who knows what other amazing opportunities are just waiting to be seized? For the first time, I can't wait to find out.篇3My New School: A Whole New WorldThe first day of school is always nerve-wracking, but starting at a completely new school amps up those anxious butterflies tenfold. As I pulled up to the massive brick building of Woodbury High for the very first time, I felt a mixture of excitement and trepidation churning in my stomach. This was going to be my new home away from home for the next four years - a Fresh start in unfamiliar territory. Little did I know just how much this place would come to shape me.The sheer size of the campus was the first thing that struck me. Having come from a tiny middle school, the sprawling hallways and three separate buildings housing over 2,000 students seemed maze-like and daunting. How would I ever find my way around? I clutched my class schedule tightly, mentally mapping out each room number like a treasure map.As I wandered the halls before the first bell, I observed the different cliques and social groups that had already formed. Jocks with their letterman jackets, giggling cheerleaders with perfect curls, edgy kids with ripped jeans and bold hair colors. Where would I fit in, I wondered? The loner reading Stephen King paperbacks in the corner? The class clown? The studious kid with a bright future? High school presented that thrilling chance at reinvention.My first few classes passed by in a blur of syllabi, seating charts, and getting-to-know-you icebreakers. I recognized no familiar faces, but was surprised at how quickly I started putting names to those around me. Jessica with the green hair streak who loved rock music. Dan the basketball star who was also a low-key math whiz. Little snippets of personalities waiting to be uncovered.By lunchtime, my shyness had morphed into curiosity about this new microcosm of society. The cacophony of the cavernous cafeteria overwhelmed my senses at first, but I spotted an empty corner table and staked my claim. Slowly, I began to observe the interactions around me. The pockets of friends chatting and laughing, the overconfident seniors sauntering through like they owned the place, the teachers trying to maintain order in the chaos. So this was high school life.In the weeks and months that followed, Woodbury truly became my second home. I joined the creative writing club after discovering a talent for poetry. I mustered up the courage to audition for the school play and surprisingly landed a small role. I lent my voice to the political debates club, reveling in a newfound passion for civic engagement. Each new activity opened a door into different friend groups and allowed me to step outside my comfort zone.Of course, there were challenges too. The dreaded gym class where I felt like anawkward baby giraffe. The disappointment of being cut from the soccer team. The tough sociology class that forced me to reckon with uncomfortable topics like systemic racism. Woodbury's diversity prepared me for the harsh realities of the real world beyond our sheltered town's borders.My favorite spot on campus became the school library, that hallowed cathedral of knowledge and contemplation. Its sunlit reading nooks and endless bookshelves whispered of intellectual musings waiting to be discovered. It's where I fell in love with classic literature, investigated new scientific concepts, and even worked up the nerve to ask my crush Allie to prom (she, sadly, said no).With each passing month, I felt myself growing and changing in ways I didn't even notice at first. I walked the halls with more confidence, spoke up in class with hard-earned assertiveness, and forged inside jokes and bonds with my crew. High school pulled me out of my awkward teenage shell and pushed me to explore all the different aspects of myself.Woodbury's teachers became some of the most influential forces in my development. I'll never forget the way Mr. Stephens, my English teacher, encouraged my love of language and validated my writing dreams. Or the fire that Ms. Rodriguez's passionate history lectures lit under me to learn more about injustice and activism. Even seemingly boring subjects like statistics came alive through Mr. Patel's nerdy jokes andreal-world applications. More than just imparters of facts, these became life mentors.Of course, no high school journey would be complete without some high drama, courtesy of the classic cliques and social dynamics. I witnessed friend groups completely implode over silly jealousies, only to reform a month later as if nothing had happened. I became embroiled in petty feuds and rumors that now make me cringe. I even nursed a silly crush on a popular senior for weeks, only to realize we had nothing in common. Ah, the trivialities of adolescence!Through it all, the spirit of Woodbury pride and togetherness prevailed. We came together on crisp fall nights under the bright lights to scream our hearts out at football games. We put our minimmortal teenage souls into cheering on our sports teams. We bonded over shared complaints about cafeteria food, finals stress, and evil teachers. In the microcosm of halls and classrooms, we were crafting inside jokes and traditions that would become the foundations for our adult lives.As senior year drew to a close far too quickly, I realized just how much this school had shaped me over four short years. The timid girl who first walked those halls metamorphosed into a confident, passionate young woman ready to embrace the world ahead. While I looked forward to beginning the next chapter at college, a part of my heart would forever remain at Woodbury.On the last day of school, I soaked up every details like indelible memories being etched into my mind. The creaky wooden floors of the auditorium where I trod the boards as Juliet. The patch of grass under the oak tree where my friend circle held our boisterous lunch gatherings. The chem lab where I accidentally started a small explosion (oops). These weren't just spaces, but backdrops for crucial life events and characters that irrevocably shaped my identity.As I walked across that graduation stage, diploma in hand, I looked out at the beaming faculty members and my fellow classmates - those who stuck by me through thick and thin. These were the people who inspired me, lifted me up, frustrated me, made me laugh, and most importantly, helped me figure out who I am. Because of them, because of Woodbury High, I now felt ready to conquer the great unknown. Bring it on, world. This place transformed me into someone who can take you.。

TheSearchfortheAnti-_agingPill单词分析

TheSearchfortheAnti-_agingPill单词分析

READING PASSAGE 3You should spend about 20 minutes on Questions —2840, which are based on Reading Passage 3The Search for the Anti- aging·PillIn government laboratories and elsewhere, scientists are seeking a drug able to prolong life and youthful vigor .Studies of caloric restriction are showing the way.As researchers on aging noted recently, no treatment on the market today has been proved to slow human aging— the build-up of molecular1 and cellular 2 damage that increases vulnerability 3 to infirmity as we grow older. But one intervention 4,consumption5 of a low-calorie*yet nutritionally 6balanced diet. works incredibly well in a broad range of animals,increasing longevity 7 and prolonging good health.Those findings suggest that caloric restriction 8 could delay aging and increase longevity in humans, too.Unfortunately, for maximum benefit ,people would probably have to reduce their caloric intake by roughly thirty per cent ,equivalent9 to dropping from 2,500 calories a day to l,750.Few mortals10 could stick to that harsh a regimen11,especially for yearson end.But what if someone could create a pill effects of eating less without actually forcing that mimicked 12 the physiological people to eat less? Could sucha‘caloric-restriction mimetic 13’,as we call it ,enable people to stay healthy longer , postponing14 age-related disorders(such asdiabetes15, arteriosclerosis16,heart disease and cancer)until very late in life? Scientists first posed this question in the mid-1 990s. after researchers came upon a chemical agent that inrodents171 adj. [ 化学 ] 分子的;由分子构成的 2 n. 挪动电话;单元 adj. 细胞的;多孔的;由细胞构成的3 n. 易损性;短处 4 n. 介入;调解;阻碍 5 n. 花费;耗费;肺痨 6 adv. 滋润地 7 n. 长寿,长命;寿命8 n. 限制;拘束;约束9 n. 等价物,相等物 adj.等价的,相等的;赞同义的 10 adj. 凡人的;致死的;终有一死的;势不两立的n. 人类,凡人 11 n. [ 医] 养生法;生活规则;政体;支配 12 v. 模拟(活象) 13 adj. 模拟的;拟态的;近似的14 n. 推延 15 n. 糖尿病;多尿症16 动脉硬化 17 n. 啮齿动物seemed to reproduce many of caloric restriction's benefits. No compound that wouldsafely achieve the same feat in people has been found yet,but the search has been informative 1 and has fanned hope that caloric-restriction (CR) mimetics can indeed be developed eventually.The benefits of caloric restrictionThe hunt for CR mimetics grew out of a desire to better understand caloric restriction's many effects on the body .Scientists first recognized the value of the practice more than 60 years ago, when they found that rats fed a low-calorie diet lived longer on average than free-feeding rats and also had a reduced incidence2 of conditions that become increasingly common in old age.What is more ,some of the treated animals survived longer than the oldest—living animals in the control group ,which means that the maximum lifespan3(the oldest attainable4 age),not merely the normal lifespan ,increased.Various interventions,such as infection-fighting 5 drugs, can Increase a population's average survival time ,but only approaches that slow the body's rate of aging will increase the maximum lifespan.The rat findings have been replicated6 many times and extended to creatures7 ranging from yeast to fruit flies ,worms,fish ,spiders,mice and hamsters8.Until fairly recently, the studies were limited to short-lived 9 creatures genetically10 distant from humans.But caloric .restriction projects underway in two species more closely related to humans-rhesus and squirrel monkeys-have made scientists optimistic that CR mimetics could help people.1adj. 教育性的,有利的;情报的;见闻广博的 2 n.发生率;影响;[ 光]入射;影响范围 3 n.寿命;预期生命限期;预期使用期限 4 adj.可获得的;可达到的;可抵达的 5 防止传染 6 重复的 7 n.生物8 n.仓鼠9 adj.短暂的,短期的;短寿的;无常的10 adv.从遗传学角度;从基因方面The monkey projects demonstrate1 that, compared with control animals that eatnormally, caloric-restricted monkeys have lower body temperatures and levels of the pancreatic hormone insulin2,and they retain more youthful levels of certain hormones that tend to fall with age .The caloric-restricted animals also look better on indicators of risk for age-related diseases.For example ,they have lower blood pressure and triglyceride 3 levels(signifying 4 a decreasedlikelihood 5of heart disease),and they have more normal blood glucose6 levels(pointing to a reduced risk for diabetes,which is marked by unusually high blood glucose levels) .Further, it has recently been shown that rhesus monkeys kept on caloric —restricted diets for an extended time(nearly 15 years)have less chronic7disease.They and the other monkeys must be followed still longer, however, to know whether low-calorie intake8 can increase both average and maximum lifespans in monkeys.Unlike the multitude 9 of elixirs 10 being touted11 as thelatest anti-aging cure,CR mimetics would alter fundamental12 processes thatunderlie13 aging.We aim to develop compounds that fool cells into activating maintenance14 and repair.1 vt. 证明;展现;论证 vi. 示威2 胰腺胰岛素3 n. 甘油三酸酯4 n. 代表;预示 v. 象徵;预示5 n. 可能性,可能6血糖 7 adj. 慢性的;长久的;习惯性的8 n. 摄入量;通风口;引进口;引入的量9 n. 民众;多半10 n. 不老长寿药;全能药;炼金药 11 v. 招来顾客 adj. 被吹嘘的12 基本 13 vt. 成为的基础;位于之下14 n. 保护,维修;保持;生活花费How a prototype caloric— restriction mimetic worksThe best-studied candidate1for a caloric-restriction mimetic,2DG(2-deoxy-D-glucose) , works by interfering with the way cells process glucose . It has proved toxic 2 at some doses in animals and so cannot be used in humans. But it has demonstrated3 that chemicals can replicate4 the effects of caloric restriction ;the trick is finding the right one .Cells use the glucose from food to generate ATP (adenosine triphosphate5),the molecule that powers many activities in the body.By limiting food intake,caloric restriction minimizes the amount of glucose entering cells and decreases ATP generation.When 2DG is administered to animals that eat normally,glucose reaches6cells in abundance but the drug prevents most of it from being processed and thus reduces ATP synthesis. Researchers have proposed several explanations7 for why interruption 8 of glucose processing and ATP production might retard aging. One possibility relates to the ATP-making machinery9’s emission of free radicals10,whichare thought to contribute to aging and to such age-related diseases as cancer by damaging cells.Reduced operation of the machinery should limit their production and thereby constrain the damage.Another hypothesis11 suggests that decreased processing of glucose could indicate to cells that food is scarce(even if it isn induce12 them’to shift into an anti-aging mode that emphasizes preservation13 of the organism14 over such ‘luxuries15’ as growth and reproduction.1 n.候选人,候补者;应试者2 adj.有毒的;中毒的3 vt.证明;展现;论证vi.示威4 n.复制品;八音阶间隔的反覆音vt.复制;折叠adj.复制的;折叠的 5 三磷酸腺苷 6 大批的;丰富的;充分的7 解说 8 n.中止;扰乱;中止之事9 n.机械;机器;机构;机械装置 10 n. 自由基;激进分子;基础 11 n. 假定 12 vt. 引诱;惹起;引诱;感觉 13 n. 保存,保存 14 n. 有机体;生物体;微生物15 n. 豪侈品Ant IntelligenceWhen we think of intelligent members the animal kingdom, the creatures that spring immediately to mind are apes and monkeys. But in fact the social lives of some members of the insect kingdom are sufficiently 1 complex to suggest more than a hint2 of intelligence. Among these, the world of the ant has come in for considerable3 scrutiny4 lately, and the idea that ants demonstrate sparksof cognition 6 has certainly not been rejected by those involved in these investigations.Ants store food . repel 7attackers and use chemical signals to contact one another incase of attack.Such chemical communication can be compared to the human use of visual and auditory channels8(as in religious chants9,advertising images and jingles 10, political slogans and martial11 music)to arouse and propagate12 moods andattitudes.The biologist Lewis Thomas wrote ,Ants are so much like human beings as13 14 15 16to be an embarrassment . They farm fungi , raise aphids *as livestock , launch armies to war,use chemical sprays to alarm and confuse enemies,capture slaves,17engage in child labour, exchange information ceaselessly . They do everything but watch television .’However, in ants there is no cultural transmission-everything must be encoded in the genes19whereas in humans the opposite is true. Only basic instincts are carried in the genes of a newborn baby, other skills being learned from others in the community as the child grows up. It may seem that this cultural continuity gives us a huge advantage1 adv. 充分地;足够地2 n. 表示;线索 vt. 表示;表示 vi. 表示3 adj. 相当大的;重要的,值得考虑的4 n. 详尽审察;监督;细看;选票复查 6 n. 认识;知识;认识能力7 vt. 击退;抵制;使憎恶;使不快乐8 听觉通道 9 宗教圣歌 10 n. 叮当声 vt. 使押韵;使发出叮当声 vi. 发出叮当声;押韵 11 adj. 军事的;战争的;尚武的12 vt. 流传;传递;生殖;宣传13 n. 窘况,尴尬;令人犯难的人或事物;窘迫14 n. 真菌;菌类;蘑菇15 n. 蚜虫类 16 n. 牲口;牲口 17 adv. 不断地over ants. They have never mastered fire nor progressed. Their fungus farming andaphid herding crafts1 are sophisticated2 when compared to the agricultural skills of humans five thousand years ago but have been totally overtaken by modern human agribusiness.3Or have they? The farming methods of ants are at least sustainable4. They do not ruin environments or use enormous5 amounts of energy. Moreover, recent evidence suggests that the crop farming of ants may be more sophisticatedand adaptable than was thought. Ants were farmers fifty million years before humans were .Ants can ’ tdigest the cellulose 6in leaves-but some fungi can .The ants therefore cultivate 7 thesefungi in their nests ,bringing them leaves to feed on, and then use them as a source of food.Farmer ants secreteantibiotics 8to control other fungi that might act as‘ weeds’, and spread waste tofertilise 9 the crop.It was once thought that the fungus that ants cultivate was a single type that they had propagated10.Essentially unchanged from the distant past.Not so. Ulrich Mueller of Maryland and his colleagues genetically screened 11862 different types of fungi taken from ants’nests. These turned out to be highly diverse: it seems that ants are continually domesticating12 new species.Even more impressively, DNA analysis of the fungi suggests that the ants improve or modify the fungi by regularly swapping13 and sharing strains with neighbouring14 ant colonies. Whereas prehistoric18 man had no exposure19 to Urban lifestyles-the forcing house of intelligence — the evidence suggests that ants have lived in urban settings for close on a hundred million years,1放牧工艺品 2 adj.复杂的;雅致的;久经世故的;富裕经验的v.使变得世故;使诱惑;窜改 3 n.农业综合公司(包含农业设施、用品的制造、农产品的产销、制造加工等 4 可连续 5 adj.宏大的,巨大的;凶恶的,极恶的 6 n.纤维素;(植物的)细胞膜质7 vt.培育;陶冶;耕种8 n.抗生素;抗生学9 vt.使受精;施肥于;使肥饶10 vt.流传;传递;生殖;宣传vi.生殖;增殖14 adj.周边的;周边的;接壤的developing and maintaining underground cities of specialized chambers and tunnels.When we survey Mexico City, Tokyo , Los Angeles. we are amazed at what has been accomplished by humans.Yet Hoelldobler and Wilson’s magnificent 1 work for ant lovers, The Ants, describes a super colony of the ant Formica yessensis on the Ishikari Coast of Hokkaido .This‘ megalopolis2’was reported to be composed of 360 million workers and a million queens living in 4,500 Interconnected3 nests across aterritory 4of 2.7 square kilometres.Such enduring and intricately meshed6 levels of technical achievement outstrip5 by far6anything achieved by our distant ancestors. We hail as masterpieces the cave Paintings in southern France and elsewhere, dating back some 20,000 years. Ant societiesexisted in something like their present form more than seventy million years ago.Beside this, prehistoric man looks technologically primitive. Is this then some kind of intelligence , albeit7 of a different kind?Research conducted at Oxford,Sussex and Zurich Universities has shown that when desert ants return from a foraging trip, they navigate by integrating bearings8 and distances,which they continuously update9 in their heads.They combine the evidence of visual landmarks10 with a mental library of local directions, all within a framework 11Which is consulted and updated.So ants can learn too.And in a twelve-year Programme of work , Ryabko and Reznikova have found evidence that ants can transmit very complex messages.Scouts who had located food1 adj. 崇高的;壮丽的;华美的;雄伟的 2n. 特多半市;人口浓密地带 3 adj. 连通的;有联系的 v. 相互连结 4n. 国土,领域;范围;地区;疆域5vt. 超出;赛过;比跑得快 6 n. 杰作;绝无仅有的人 7 conj. 固然;即便 8 集成轴承 9 n. 更新;现代化vt. 更新;校订,修正;使现代化10 n.地标,陆标;标记11 n.框架,骨架;结构,构架in a maze returned to mobilise1 their foraging2 teams,They engaged in contact3,at the end of which the 4sessions scout was removed in order to observe what her team might do.Often the foragers5 proceeded to the exact spot in the maze where thefood had been.Elaborate precautions were taken to prevent the foraging team usingodour6 clues.Discussion now centres on whether the route through the maze iscommunicated as a‘left-right ’ sequence of turns or as a‘compass7 bearing anddistance’message.During the course of this exhaustive study, Reznikova has grown so attached to her laboratory ants that she feels she knows them as individuals-even without the paint spots used to mark them. It ’s no surprise that Edward Wilson ,in his essay,‘In the company of ants’,advises readers who ask what to do with the ants in their kitchen to:‘Watch where you step.Be careful of little lives ’.1 vt. 动员;调换;使流通vi. 动员起来2 n. 觅食3 n. 会议;会期4 n. 搜寻,侦探;侦探员;侦探机 vt. 侦探;追踪,监督;发现 vi. 侦探;巡视;嘲讽 5 n. 打劫者;强征队员 6 n. 气味;名誉7 n. 指南针,罗盘;圆规 vt. 包围volcanoes-earth-shattering newsWhen Mount Pinatubo suddenly erupted on 9 June 1991,the power of volcanoes past and present again hit the headlinesA Volcanoes are the ultimate earth-moving machinery . A violent eruption can blow the top few kilometres off a mountain ,scatter1 fine ash practically all over the globe and hurl rock fragments2 into the stratosphere 3to darken the skies a continent away.But the classic eruption-cone-shaped mountain, big bang, mushroom cloud and surges4 of molten lava5-is only a tiny part of a global story. Vulcanism6, the name given to volcanic 7processes,really has shaped the world. Eruptions have rifted 8 continents, raised mountain chains, constructed islands and shaped thetopography9 of10the earth. The entire ocean floor has abasement of volcanic basalt .Volcanoes have not only made the continents , they are also thought to have made the world ’s first stable atmosphere and provided all the water for the oceans, rivers and ice-caps.There are now about 600 active volcanoes. Every year they add two or three cubic kilometres of rock to the continents.Imagine a similar number of volcanoes smoking away for the last 3,500million years. That is enough rock to explain the continental crust.What comes out of volcanic craters11 is mostly gas . More than 90 %of this gas is water vapour12 from the deep earth :enough to explain, over 3,500 million years,the water in1 n. 分别;散布,撒播vt. 使散射;使散开,使分别;使散布,使撒播2 n. 碎片;片断;分段v. 破裂;打坏3 n. 同温层;最上层;最高阶段4 激增5 熔岩6 n. 岩石火成论者7 n. 火山岩adj. 火山的;剧烈的;易忽然发生的8n. 裂痕;不睦;[ 木 ] 裂口vt. 使断裂;使分开vi. 裂开9 地形10 n. 地下室;地窖11 n. 火山口;环形山v. 形成坑;破坏12 n. 蒸气;水蒸the oceans. The rest of the gas is nitrogen1, carbon dioxide 2, sulphur dioxide 3,methane4,ammonia5 and hydrogen6.The quantity of these gases, againmultiplied 7 over 3,500 million years ,js enough to explain the mass of the world’s atmosphere.We are alive because volcanoes provided the soil,air and water we need.B Geologists consider the earth as having a molten core,surrounded by a semi-molten mantle and a brittle 8, outer skin, lt helps to think of a soft-boiled 9 egg with a runny yolk ,a firm but squishy11 white and a hard shell.If the shell is even slightly cracked during boiling ,the white material bubbles out and sets like a tiny mountain chain over the crack-like an archipelago12 of volcanic islands such as the Hawaiian Islands .But the earth is so much bigger and the mantle below is so much hotter,Even though the mantle rocks are kept solid by overlying 13 pressure,they can still slowly ‘flow ’ like thick treacle14.The flow, thought to be in the form of convection currents,is powerful enough to fracture the‘ eggshell’of the crust into plates ,and keep them bumping and grinding against each other, or evenoverlapping 15,at the rate of a few centimetres a year. These fracture zones, where the collisions 16 occur, are where earthquakes happen.And ,very often ,volcanoes.C These zones are lines of weakness, or hot spots. Every eruption is different, but put at its simplest, where there are weaknesses, rocks deep in the mantle, heated to 1,350。

Searching for Atlantis

Searching for Atlantis

Searching for AtlantisThe search for Atlantis has been a topic of fascination and intrigue for centuries. The idea of a lost city, submerged beneath the ocean, has captured the imagination of people all over the world. Many have dedicated their lives to uncovering the truth behind the myth, while others remain skeptical of its existence. As we delve into this enigmatic quest, it's important to consider the various perspectives and emotions that surround the search for Atlantis. For those who believe in the existence of Atlantis, the search is a deeply emotional and personal journey. The idea of a once-great civilization, now lost to the depths of the ocean, evokes a sense of wonder and longing. The possibility of uncovering the remains of this ancient city brings a sense of hope and excitement. For these individuals, the search for Atlantis represents a quest for knowledge and a connection to the past. On the other hand, there are those who approach the search for Atlantis with skepticism and doubt. They view the myth of Atlantis as nothing more than a fictional tale, lacking any real evidence to support its existence. For these individuals, the search for Atlantis may seem like a futile endeavor, driven by romanticized notions of a lost civilization. They may feelthat the resources and efforts dedicated to this search could be better utilized in more practical and tangible pursuits. Despite the differing perspectives on the existence of Atlantis, the search for this fabled city has captured the attention of researchers, explorers, and historians around the world. Countless expeditions have been launched in an attempt to uncover the truth behind the myth. These efforts have led to the discovery of intriguing underwater structures and artifacts, fueling the belief that there may be some truth to the legend of Atlantis. The search for Atlantis also raises ethical and environmental considerations. The exploration of underwater sites, particularly those of historical significance, must be approached with care and respect. There is a delicate balance between satisfying our curiosity about the past and preserving the integrity of these underwater environments. The potential discovery ofAtlantis would undoubtedly raise questions about how to responsibly manage and protect such a significant archaeological site. Moreover, the search for Atlantis has sparked debates within the scientific community about the validity of theevidence and the methods used in the quest for this lost city. Some argue that the search for Atlantis is based on speculative interpretations of ancient texts and myths, rather than concrete evidence. Others believe that the search for Atlantis has the potential to expand our understanding of ancient civilizations and the history of human development. In conclusion, the search for Atlantis is a complex and multifaceted endeavor that elicits a wide range of emotions and perspectives. Whether driven by a sense of wonder and curiosity or met with skepticism and doubt, the quest for this mythical city continues to captivate the hearts and minds of people around the world. As the search for Atlantis persists, it is essential to approach this pursuit with a balance of scientific rigor, ethical responsibility, and a deep appreciation for the mysteries of the past.。

The Density Profile of Massive Galaxy Clusters from Weak Lensing

The Density Profile of Massive Galaxy Clusters from Weak Lensing

a r X i v :a s t r o -p h /0310549v 1 20 O c t 2003THE DENSITY PROFILE OF MASSIVE GALAXY CLUSTERS FROM WEAK LENSING H.DAHLE Institute of Theoretical Astrophysics,University of Oslo,P.O.Box 1029,Blindern,N-0315Oslo,Norway We use measurements of weak gravitational shear around a sample of massive galaxy clusters at z =0.3to constrain their average radial density profile.Our results are consistent with the density profiles of CDM halos in numerical simulations and inconsistent with simple models of self-interacting dark matter.Unlike some other recent studies,we are not probing the scales where the baryonic mass component becomes dynamically important,and so our results should be directly comparable to CDM N-body simulations.1IntroductionWhile the concordance flat ΛCDM model,in which the matter density is dominated by cold dark matter (CDM),provides a good fit to observed large scale-properties of the universe,there remain some possible small-scale problems for this model.Numerical simulations of structure formation in a CDM model predict that the dark matter (DM)halos of L ⋆galaxies such as the Milky Way should contain a number of subhalos that exceed the observed number of satellite dwarf galaxies by 1-2orders of magnitude (e.g.Klypin et al.1999;Moore et al.1999a).Strongly suppressed star formation in the subhalos could be a possible solution to this problem.Observations of anomalous flux ratios of strongly gravitationally lensed multiple quasar images (Kochanek &Dalal 2003)and observations of the dynamics of optically dark high-velocity gas clouds in the local group (Robishaw,Simon &Blitz 2002)appear to be qualitatively consistent with this proposed solution.In addition,the simulations predict that DM halos have cuspy inner density profiles ρ(r )∝r −α,with αsomewhere in the range between 1.0(Navarro,Frenk &White 1997;hereafter NFW)and 1.5(Moore et al.1999b).This appears to contradict the observed dynamics of DM-dominated low surface brightness galaxies which favour softer cores with α=0.2±0.2(de Blok,Bosma,&McGaugh 2003).On the scales of galaxy clusters,some studies indicate shallowerdensity profiles than those predicted from CDM simulations(Sand et al.2003),while others give αvalues that are consistent with CDM predictions(Bautz&Arabadjis2003).Attempts have been made to solve these small-scale problems of CDM by proposing DM models that modify its behavior on small scales.Some examples of these are models in which the DM is self-interacting(Spergel&Steinhardt2000),self-annihilating(Kaplinghat,Knox&Turner 2000),fluid(Peebles2000;Arbey,Lesgourgues&Salati2003),warm(e.g.,Sommer-Larsen& Dolgov2001),repulsive(Goodman2000),fuzzy(Hu,Barkana&Gruzinov2000),decaying(Cen 2001),is both self-interacting and warm(Hannestad&Scherrer2000),acts as mirror matter (Mohapatra,Nussinov&Teplitz2002)or has its gravitational interaction with baryonic matter suppressed on small scales(Piazza&Marioni2003).Of these,the self-interacting DM model of Spergel&Steinhardt is the one which has been explored in most detail.Here,we put limits on this model by using weak gravitational lensing to measure the average density profile of an ensemble of massive galaxy clusters.Details of this work are given by Dahle,Hannestad& Sommer-Larsen(2003).2Constraints on the DM halo profileOur data set is a subset of the weak gravitational lensing measurements of38X-ray luminous clusters presented by Dahle et al.(2002).This subset consists of6clusters at z=0.3for which weak gravitational shear has been measured out to a projected radius of3h−165Mpc.Wefit the average observed radial shear profile to a“generalized NFW profile”on the formρ(r)=δcρc3 1x2(cx)−α(1+cx)α−3dx −1.(2)This model has a concentration parameter c defined by c=r200/r s,whereFigure1:The contours show the68%and95%confidence intervals for the concentration c vir and inner slopeαof our average cluster halo.Also shown is the mean value and scatter in c vir for an NFW halo of similar mass, predicted by Bullock et al.(2001).The dashed lines indicate lines along which the two parameters are degenerate.See also Dahle et al.(2003).∆α∼0.3.On the other hand,Bautz&Arabadjis(2003)find1<α<2and Lewis,Buote &Stocke(2003)findα=1.19±0.04,based on Chandra observations of the X-ray luminous intracluster medium in four clusters and in one cluster,respectively.In contrast to our weak lensing study(which only probe the DM density profile at radii where the baryonic component is not dynamically dominant),these strong lensing and X-ray studies are not directly compara-ble to simulations that only contain collisionless CDM.The above results indicate that future observational studies should simultaneously take into account both the baryonic component in stars and in the X-ray luminous intracluster medium as well as the DM.Similarly,all these components must be properly modeled in numerical simulations,if the simulations are to be directly compared to cluster observations on small(≤10kpc)scales.In any case,all the recent studies indicate that the core sizes of massive clusters are too small to be consistent with any self-interacting dark matter having a cross section large enough to explain the rotation curves of dwarf galaxies.Like previous weak lensing studies(e.g.,Clowe&Schneider2001,Hoekstra et al.2002), we are not able to strongly distinguish between the outer slope of an isothermal sphere,ρ∝r−2,and the NFW slopeρ∝r−3.However,in a recent work,Kneib et al.(2003)use a combination of weak and strong gravitational lensing data based on HST imaging of the cluster CL0024+17tofind an outer slope>2.4.Their data is adequatelyfit by a NFW profile with c=22+9−5,significantly higher than typical observed concentration parameters of rich clusters (e.g.,Hoekstra et al.2002;Katgert,Biviano&Mazure2003),which are generally consistent with CDM predictions(see also Fig.1).However,Chandra X-ray data(Ota et al.2003),as well as dynamical studies based on galaxy spectroscopy(Czoske et al.2002),indicate that this is not a fully relaxed,spherically symmetric system.Weak lensing measurements of a representative sample of dynamically relaxed clusters out to even larger radii than we probe in our study should eventually settle the issue of the value of the outer slope.AcknowledgmentsI thank my collaborators Steen Hannestad and Jesper Sommer-Larsen,and acknowledge support from The Reseach Council of Norway through a post-doctoral research fellowship. References1.Arbey,A.,Lesgourgues,J.,&Salati,P.2003,Phys.Rev.D,68,235112.Bautz,M.W.&Arabadjis,J.S.2003,ArXiv Astrophysics e-prints,33133.Bullock,J.S.,Kolatt,T.S.,Sigad,Y.,Somerville,R.S.,Kravtsov,A.V.,Klypin,A.A.,Primack,J.R.,&Dekel,A.2001,MNRAS,321,5594.de Blok,W.J.G.,Bosma,A.,&McGaugh,S.2003,MNRAS,340,6575.Cen,R.2001,ApJL,546,L776.Clowe,D.&Schneider,P.2001,A&A,379,3847.Czoske,O.,Moore,B.,Kneib,J.-P.,&Soucail,G.2002,A&A,386,31.8.Dahle,H.,Kaiser,N.,Irgens,R.J.,Lilje,P.B.,&Maddox,S.J.2002,ApJS,139,3139.Dahle,H.,Hannestad,S.,&Sommer-Larsen,J.2003,ApJL,588,L7310.Dav´e,R.,Spergel,D.N.,Steinhardt,P.J.,&Wandelt,B.D.2001,ApJ,547,57411.Goodman,J.2000,New Astronomy,5,10312.Hannestad,S.,&Scherrer,R.J.2000,Phys.Rev.D,62,04352213.Hoekstra,H.,Franx,M.,Kuijken,K.,&van Dokkum,P.G.2002,MNRAS,333,91114.Hu,W.,Barkana,R.,&Gruzinov,A.2000,Phys.Rev.Lett.,85,115815.Jing,Y.P.2000,ApJ,535,3016.Kaplinghat,M.,Knox,L.,&Turner,M.S.2000,Phys.Rev.Lett.,85,333517.Katgert,P.,Biviano,A.,&Mazure,A.2003,ArXiv Astrophysics e-prints,1006018.Klypin,A.,Kravtsov,A.V.,Valenzuela,O.,&Prada,F.1999,ApJ,522,8219.Kneib,J.et al.2003,ArXiv Astrophysics e-prints,729920.Kochanek,C.S.&Dalal,N.2003,ArXiv Astrophysics e-prints,203621.Lewis,A.D.,Buote,D.A.,&Stocke,J.T.2003,ApJ,586,13522.Meneghetti,M.,Yoshida,N.,Bartelmann,M.,Moscardini,L.,Springel,V.,Tormen,G.,&White,S.D.M.2001,MNRAS,325,43523.Mohapatra,R.N.,Nussinov,S.,&Teplitz,V.L.2002,Phys.Rev.D,66,6300224.Moore,B.,Ghigna,S.,Governato,F.,Lake,G.,Quinn,T.,Stadel,J.,&Tozzi,P.1999a,ApJL,524,L1925.Moore,B.,Quinn,T.,Governato,F.,Stadel,J.,&Lake,G.1999b,MNRAS,310,114726.Navarro,J.F.,Frenk,C.S.,&White,S.D.M.1997,ApJ,490,49327.Ota,N.,Pointecouteau,E.,Hattori,M.,&Mitsuda,K.2003,ArXiv Astrophysics e-prints,658028.Peebles,P.J.E.2000,ApJL,534,L12729.Piazza,F.&Marioni C.2003,Phys.Rev.Lett.,91,14130130.Robishaw,T.,Simon,J.D.,&Blitz,L.2002,ApJL,580,L12931.Sand,D.J.,Treu,T.,Smith,G.P.,&Ellis,R.S.2003,ArXiv Astrophysics e-prints,946532.Sommer-Larsen,J.&Dolgov,A.2001,ApJ,551,60833.Spergel,D.N.&Steinhardt P.J.2000,Phys.Rev.Lett.,84,376034.Yoshida,N.,Springel,V.,White,S.D.M.,&Tormen,G.2000,ApJL,544,L87。

tricky的英语介绍

tricky的英语介绍

tricky的英语介绍Tricky: An IntroductionIntroductionTricky is an English trip-hop artist known for his unique blend of electronic music, dark lyrics, and experimental soundscapes. With a career spanning over three decades, he has left an indelible mark on the music industry and continues to evolve with each new release. In this article, we will delve into the intriguing world of Tricky, exploring his background, musical style, and significant contributions to the genre.Early Life and Musical InfluencesBorn as Adrian Nicholas Matthews Thaws on January 27, 1968, in Bristol, England, Tricky's upbringing greatly influenced his musical style. Growing up in the midst of Bristol's emerging music scene, which birthed legendary acts like Massive Attack and Portishead, he was exposed to a rich tapestry of experimental sounds. Tricky's love for hip-hop, reggae, punk, and soul played a pivotal role in shaping his musical identity.Musical CareerTricky's career took off when he joined Massive Attack as a collaborator and vocalist for their influential album "Blue Lines" in 1991. His distinct voice and enigmatic stage presence caught the attention of critics and fans alike. However, it wasn't until he released his debut solo album, "Maxinquaye," in 1995 that he truly established himself as a groundbreaking artist."Maxinquaye" received widespread critical acclaim for its innovative sound, fusing hip-hop beats, soulful vocals, and haunting samples. The album's introspective and dark themes resonate with listeners, earning it a place among the greatest albums of its time. Tricky's ability to blur the lines between genres and his fearless exploration of unconventional sounds set him apart as a true musical pioneer.Evolution of StyleThroughout his career, Tricky continued to push boundaries and experiment with his sound. His subsequent albums, such as "Pre-Millennium Tension" (1996) and "Angels with Dirty Faces" (1998), showcased his ever-evolving style. Incorporating elements of rock, electronica, and world music, Tricky's music remained unpredictable, captivating fans with each release.Tricky's CollaborationsTricky's collaborations with various artists further highlighted his versatility and willingness to explore new musical territories. He has worked with renowned musicians like Björk, PJ Harvey, and Grace Jones, adding his unique touch to their tracks. These collaborations not only showcased Tricky's stellar production skills but also led to some of his most memorable and critically acclaimed works.Notable Tracks and AlbumsTricky has produced numerous standout tracks throughout his career. Songs like "Black Steel," "Hell is Round the Corner," and "Overcome" have become anthems of the trip-hop genre. His albums, including "Nearly God"(1996), "False Idols" (2013), and "Ununiform" (2017), have garnered praise for their sonic experimentation and thought-provoking lyrics.Legacy and InfluenceTricky's musical legacy and influence cannot be overstated. His boundary-pushing approach to music has paved the way for future artists and has shaped the direction of trip-hop as a genre. His lyrical depth and ability to evoke emotion through his music continue to inspire artists across various genres.ConclusionIn conclusion, Tricky is a truly distinctive artist who has carved his own path in the music industry. With a career characterized by genre-bending innovation, he has earned a reputation as a trailblazer of trip-hop music. Tricky's fusion of electronic beats, haunting vocals, and thought-provoking lyrics continue to captivate audiences worldwide. As he continues to evolve as an artist, his contribution to the music landscape remains both intriguing and essential.。

如何选择一个合适的大学英语作文

如何选择一个合适的大学英语作文

如何选择一个合适的大学英语作文全文共5篇示例,供读者参考篇1Here's an essay on "How to Choose a Suitable University" written in a tone suitable for elementary school students, with a length of around 2,000 words:Picking the Right University: A Fun Adventure!Hey there, fellow kids! Are you starting to think about which university you want to attend after finishing high school? It's an exciting time, but it can also feel a bit overwhelming with so many options out there. Don't worry, though – I'm here to guide you through this journey and make it a fun adventure!First things first, let's talk about why choosing the right university is so important. It's not just about the fancy buildings or the cool mascot (although those things are pretty neat too!). The university you pick will shape your future in so many ways. It's where you'll learn new things, make lifelong friends, and develop skills that will help you achieve your dreams.So, how do you go about finding the perfect university for you? Well, it's like a treasure hunt – you'll need to gather cluesand follow the trail until you reach your prize! Here are some tips to help you on your quest:Discover Your InterestsWhat kind of subjects do you love learning about? Do you have a passion for science, art, history, or maybe even something like video game design? The first step is to figure out what you're really interested in studying. That way, you can look for universities that offer great programs in those areas.Consider Your Future CareerWhile it's okay if you're not 100% sure what you want to do when you grow up, it's a good idea to have some idea of the kind of career you might like. Do you dream of becoming a doctor, an engineer, a teacher, or maybe even an astronaut? Different universities have different strengths, so you'll want to find one that can help you get the education and training you need for your future profession.Location, Location, Location!Do you want to stay close to home, or are you ready for an adventure in a new city or even a different country? Think about whether you'd prefer a big, bustling city or a quieter, more rural setting. Don't forget to consider the weather too – would yourather experience all four seasons or enjoy sunshine all year round?Campus LifeUniversities aren't just about classrooms and libraries (although those are important too!). You'll want to find a place where you can get involved in clubs, sports teams, and other fun activities. Do some research to see what kinds of opportunities are available for students on each campus.Ask AroundDon't be afraid to ask your friends, family members, teachers, or anyone else you know for advice. They might have insights or experiences that can help you narrow down your choices. You can also reach out to current students at universities you're interested in to get the inside scoop.Visit and ExploreIf possible, try to visit the campuses of the universities you're considering. Walking around and getting a feel for the atmosphere can be really helpful. While you're there, be sure to ask lots of questions and take plenty of notes and pictures.Choosing a university is a big decision, but it's also an exciting adventure! By following these tips and trusting yourinstincts, you'll be well on your way to finding the perfect place to continue your educational journey. Remember, this is your chance to explore new horizons and discover all the amazing things the world has to offer. So, get out there, have fun, and happy hunting!篇2How to Pick the Right University for YouHello friends! Today I'm going to talk about something super important - how to choose which university or college you want to go to after high school. This is a really big decision that can impact your whole future, so it's crucial to pick the right one for you. Let me share some tips!The first thing to think about is what you want to study. Different universities have different strengths in terms of their programs and majors. If you dream of being a famous artist one day, you'll want to look at schools with great art and design programs. If you're really into science and want to cure diseases, you should find universities known for their pre-med programs. Do your research on the academic areas each school specializes in.Another key factor is size. Some universities are absolutely massive, with 40,000 or more students. Others are quite small and cozy, with just a few thousand students total. There are pros and cons to both. Larger schools usually have more clubs, sports teams, courses and majors to choose from. But smaller colleges can feel more personal and allow you to get to know your professors better. Think about whether you'd prefer a big, bustling campus or a smaller community feel.Location is something else to consider very carefully. Do you want to stay close to home, or get as far away as possible for a new adventure? If you pick a school across the country, you'll only be able to come home for holidays. But if you choose one nearby, it's easy to visit family on weekends. Think too about whether you'd prefer a city campus with tons to do nearby, or a quieter college town away from the hustle and bustle.Cost is a huge factor as well. The sad truth is that university is extremely expensive these days. Make sure to look at the tuition fees and overall cost of each school. Don't forget to factor in living expenses, meal plans, textbooks and other fees on top of just tuition. Apply for as many scholarships and financial aid opportunities as possible to bring those costs down. For many people, cost ends up being the deciding factor.Campus life and housing are other important elements to research. At some colleges, students are required to live on campus all four years. At others, it's only mandatory for one or two years. Consider whether you'd prefer to live indorms/residence halls, apartments, fraternity/sorority houses or off-campus housing. Check out the dining halls, student centers, libraries, athletics facilities and other resources too. You'll be spending a lot of time using those!These are just some of the major things to mull over, but there's so much more. Try to visit your top university choices in person if possible to get a real feel for the campuses and communities. That can make a huge difference in envisioning yourself there for several years. Don't be afraid to make pros and cons lists to sort through all the factors side-by-side.Most importantly, trust your gut instinct. If a school feels right, even if it's not the most prestigious one you got into, go for it. These will be some of the most formative, memorable years of your life. You want to be at a place where you'll be happy, supported and able to pursue your interests and talents to the fullest.Picking a university is one of the biggest decisions you'll make at this stage in your life, but try not to stress too much.Explore all your options, ask tons of questions, and stay true to yourself. No matter which path you take, I'm sure you'll end up exactly where you're meant to be. Wishing you all the wisdom to make this choice!篇3Choosing a Uni - The Biggest Decision Ever!Hi there! My name is Jamie and I'm 10 years old. I know I'm just a kid, but I've been thinking a lot about which university I want to go to after high school. It's a super important decision that will impact my whole life! My parents and teachers keep telling me I have years until I need to worry about it, but I want to be prepared. There are so many amazing universities out there and I don't want to mess this up. Here are some tips I've gathered on how to pick the perfect uni:Location, Location, LocationWhere the university is located is like, sooooo important. You'll be living there for at least 3-4 years, so you better like the area! Do you want to be in a big city with lots of fun things to do? Or would you prefer a smaller town that's more quiet andlaid-back? Maybe you're an outdoorsy kid and want to be near beaches, mountains or forests for hiking. The weather is anotherhuge factor - nobody wants to be freezing their butt off or sweating like a pig all year round!For me, I'm leaning towards a university in a medium-sized city. Somewhere with cool museums, concerts, sports teams and a decent shopping mall. But I also don't want it to be too big and crowded like New York or Tokyo. A few hours from the beach would be awesome for summer breaks. And ideally somewhere with mild temperatures year-round because I hate being either too hot or too cold. California could be perfect!Academic StuffOkay, this is obviously the most important part - the actual education you'll be getting! Every university has different strengths when it comes to their programs and professors. If you already know what you want to study, that will really narrow down your options.I'm honestly not 100% sure yet what I want my major to be. But I'm thinking maybe something with math and computers since I'm a huge nerd for that kind of stuff. Or maybe engineering because I love building robots and crazy contraptions. In that case, I'd want a university that's known for having a stellar math, computer science or engineering department. The quality of the professors is crucial too. I'd wantteachers that are super smart but also make lectures fun and engaging instead of boring.Another thing to consider is whether you'd prefer a uni with big lecture-hall classes or smaller, more interactive ones. I think I'd enjoy the small-group experience better. Oh, and I've heard study abroad opportunities are amazing so a university that offers that would be a huge plus.Sports, Clubs and Campus LifeAcademics are important, obviously, but university is about way more than just studying. You gotta make sure the campus has a lively social scene with tons of clubs, activities and sports teams to get involved with. That's a huge part of the full "university experience"!I'm a pretty outgoing guy so I'd love to attend a university with a great recreation center, lots of intramural sports teams to join and countless clubs for every interest you can imagine. Rowing team, chess club, video game club, rock climbing club, improv comedy group, volunteering organization - you name it! I'd be signing up for everything. College is a time to try new things and discover hidden talents or passions.The party scene would matter to me a little bit too, just being honest. Not like, insane raging parties every night. But a university where there's always something fun happening on weekends so you can let loose and blow off steam. Tailgates, Greek life, performing arts, video game tournaments - just no shortage of entertainment!Money MattersUnfortunately, university is stupid expensive nowadays so costs are something me and my family have to consider carefully. Tuition and fees, room and board, textbooks, meal plans - it adds up FAST. We're definitely going to need financial aid, scholarships, you name it.Some universities are wayyy more affordable than others for the same quality of education. Private schools especially can cost like 50,000 per year which is insanity! I'd likely look at in-state public universities first since those are heavily subsidized for residents. Or maybe an out-of-state university that gives great financial aid packages. Ideally, I'd want a uni that meets at least like 3/4 of my financial need through grants, work-study, etc. so I'm not drowning in debt by age 22.This is the hardest my brain has ever had to work trying to figure out the perfect university for me. There's just so manyfactors to weigh - academics, campus life, finances, location, you name it! No pressure though, it's only THE biggest decision of my life so far. I've still got a few years to ruminate on it. But already I can't wait to make college visits, tour campuses and imagine myself there. Wherever I end up, I just know it's going to be the best 4 years ever! The true beginning of adulthood. Well, wish me luck!篇4Picking a Good University for YouHi friends! Today I'm gonna tell you all about how to pick a totally awesome university when you get older. This is really important stuff, so listen up!First off, you gotta think about what you wanna study. Do you like science and experimenting? Maybe a university with an amazing science program is right for you. Or perhaps you're more of an artsy type who loves painting, music, and all that cool creative stuff. In that case, look for a school with a fantastic arts department.Some schools are famous for certain subjects. Like if you wanna be a doctor, you'll probably want to go to a university that has one of the best medical programs around. That way you canlearn from the smartest professors and get super prepared for being a amazing doctor later on.Next, think about the location. Does the university you're considering have a campus you'd enjoy spending your time at? Maybe you're a city kid who'd love going to school right in the middle of an exciting downtown area. Or perhaps you're more of a nature lover who'd feel right at home on a pretty campus surrounded by forests and mountains. Pick a place that fits your personality.Don't forget to consider the size too! Some universities are absolutely massive with tens of thousands of students. At a big school like that, your classes will probably have a lot of people and everything will feel really huge. Other universities are teeny-tiny with just a few thousand students total. There, you'd have smaller classes and it'd be much more intimate and personal. There are pros and cons to both!While we're on the topic of size, dorm life is another thing to think about. Living in the dorms is part of the classic university experience. But at some schools, the dorms are like insanely huge apartment buildings that are always noisy and crowded. At other schools, the dorms are more like cozy little homes whereyou can make close friends easily. Think about which one sounds better for you.Cost is another huge factor. Unfortunately, university is super expensive nowadays. But some schools offer way more financial aid and scholarships than others to help pay for it all. When you're looking at universities, pay close attention to how much it will actually cost you and your family once financial aid is factored in.Sporting events are a big deal at many universities too. If you're really into sports, either as a player or just a big fan, you may want to pick a university with an awesome sports program and teams that are competitive and do well. Getting to watch your school's teams play huge games can be crazy exciting!Don't forget to consider the social scene and the extracurricular clubs too. Maybe you're the ultimate party animal who wants to go somewhere with a vibrant social scene and tons of fun events always happening. Or perhaps you're more mellow and want a calmer environment focused on academics. There are party schools andStudyville schools out there for both types of people.Finally, try to actually visit the universities in person if you can. That'll give you a much better sense of whether a schoolfeels right for you or not. While you're there, talk to current students and get their honest opinions too. They'll give you the inside scoop that you can't get just from a website or brochure.Phew, that's a lot to think about! The university you choose will be your home for at least four years, so it's a hugely important decision. Take your time, consider all the factors, and pick the one that seems like the best overall fit for you. Your dream university is out there waiting for you! Let me know if you have any other questions.篇5Choosing the Right University for YouHi friends! Today I want to talk about something really important - how to pick the best university for you when you grow up. This is a super big decision that will impact your whole future, so you've got to get it right!First up, you need to think about what kind of job you might want to have one day. Different universities are good at different subjects. If you want to be a doctor, you'll need to go to a university with a great medical program. If you dream of being an engineer building rockets and robots, then look for universities known for their engineering degrees. Love numbersand want to be an accountant or banker? Then a school with a top business program could be for you.But maybe you're still not sure exactly what career path you want to follow yet. That's okay! A lot of people change their minds about their major once or twice before settling on the right one. In that case, it's smart to pick a university that has lots of different programs to choose from. That way you can explore your interests and figure out what you're really passionate about before locking in to one specific track.Location is another huge factor to think about. Do you want to stay close to home so you can easily visit your family on weekends? Or are you itching to get out and experience a totally new city or state? Consider the weather too - would you rather have your university years filled with sunshine and beaches, or snowy winters perfect for skiing and snowball fights?The campus itself is important too. When you go on college tours, pay close attention to things like the dorms, cafeterias, libraries, gyms, and other facilities. Are they nice and modern or kind of old and rundown? You'll be spending a lot of time in these places, so you want it to feel comfortable and have everything you need. The overall vibe and culture of the campus should feel like a good fit for your personality too.Don't forget to look into clubs, sports teams, volunteer opportunities, and other fun extracurricular activities! Getting involved will help you make friends, build skills, and create amazing memories outside of just academics.Of course, you'll also have to make sure the university is affordable for your family's financial situation. Tuition, room and board, meal plans, books, and all those other costs can really add up. But there's lots of financial aid available these days like scholarships, grants, and student loans to help make your dream school possible.This is just scratching the surface when it comes to university research and selection. It's a huge decision, but also a very exciting one! By considering all the factors I mentioned, you'll be able to find the absolute perfect place to spend your college years learning, growing, and getting ready for the bright future ahead of you.Just remember - work hard, stay focused, and have fun during this process! The right university is out there waiting for someone as awesome as you.。

评论音乐会的特点感受及意见英语作文

评论音乐会的特点感受及意见英语作文

评论音乐会的特点感受及意见英语作文My First Big Music ConcertWow, what an incredible night! I just went to my very first big music concert and I'm still buzzing with excitement. Mom and Dad surprised me with tickets to see my favorite band, The Stellar Beats, for my 10th birthday. I could hardly believe it when they told me - I've been a huge fan for over a year now and have all their albums. To actually get to see them perform live on stage was a dream come true!The concert was held at the massive Metro Arena downtown. Just driving up to the huge building and seeing the thousands of people lined up was an experience in itself. The line stretched so far down the street that we had to park what felt like miles away. Even from the parking lot you could hear the buzz and chatter of fans excitedly waiting to get inside.Once we finally made it through the doors, it was like entering another world. The arena was dimly lit with multicolored lights flashing everywhere. Huge speakers lined the walls, pumping out pre-show music that thundered in your chest. Merchandise stands selling Stellar Beats t-shirts, hats, posters and other souvenirs lined the hallways. The smells of hot dogs,nachos and other arena foods wafted through the air, making my stomach growl.We found our seats about 20 rows back from the stage. They were pretty good seats for being in the middle section - I could see the whole massive stage clearly. It was set up with a towering backdrop, multiple platforms, pyrotechnic equipment, and a dazzling light and video show ready to go. Instruments for the band were already set up on the main stage, including a sparkly purple drum set that must belong to Zara, the drummer.In the minutes leading up to the start time, you could feel the electricity in the air as the crowd's anticipation built. People were cheering, singing songs, waving glow sticks and phone flashlights. Finally, the lights went down and a deafening roar went up from the audience.Suddenly, blinding spotlights came on and pillars of fire shot into the air as the opening music started. Smoke poured across the stage as the band emerged one by one - first the bassist, then the two guitarists, then Zara at her drums, and finally Stella, the lead singer. She looked amazing in a silver jumpsuit covered in glittering sequins. As she grabbed the microphone, another explosion of light and pyrotechnics went off, sending a shockwave of sound through the arena.That was just the first few seconds, but it set an electrifying tone for what was to come over the next two hours. The Stellar Beats played hit after hit from their three albums, combining it with a mind-blowing production of lights, lasers, pyro, smoke, video screens and more. It was a non-stop barrage of music, physicality and sensory overload in the best way possible.Stella's voice sounded just as powerful and pitch-perfect live as on the recordings. She had such an incredible range and ability to convey deep emotion through her singing. Watching her feed off the crowd's energy was mesmerizing. The band members were all exceptionally talented too - Zara's drumming was precise and powerful, the basslines were funky and groovy, and the dual guitars created layers of crunch and ambience.They played all my favorite songs like "Electrique," "Heartbeam," and "Cosmic Love." The highlight might have been their breakthrough single "Supernova" where the entire arena was illuminated by thousands of swaying phone flashlights. It gave me chills. They also did some amazing covers of classic rock songs like "Bohemian Rhapsody" by Queen that had the whole crowd singing along.At one point, Stella took a moment to speak to the audience. She talked about how much their fans meant to them and thatthey wouldn't be anywhere without our support. She seemed so humble and genuine. You could tell she was pouring every ounce of her heart and soul into the performance. It made me appreciate the music even more, knowing it came from a place of real passion and emotion.By the end of the show, I had danced so much that I was drenched in sweat and my feet were aching. My voice was nearly gone from all the singing along too. But I didn't care one bit - it was worth every second to experience such an incredible display of talent and showmanship.As we filed out with the masses of other fans, I just kept replaying the highlights in my mind. The brilliant light show, the booming sound, the infectious energy, Stella's powerful vocals...it was all so overwhelming in the best way. I've never experienced anything quite like a top-tier concert production before. It's inspired me to want to learn an instrument and join my school's band.I'll never forget my first big music concert. It was a spectacle for the senses that combined real musical artistry with an unmatched entertainment extravaganza. I have such a profound appreciation for the talent, hard work and dedication it must take to put on a show like that. The Stellar Beats created anunforgettable night that I'll cherish forever. I'm counting down the days until their next tour so I can experience it all over again!。

innumberable英译 -回复

innumberable英译 -回复

innumberable英译-回复"Innumerable" in English refers to a large or countless number of something. Here is a step-by-step response to the topic of "innumerable," consisting of a 1500-2000 word article:Title: Exploring the Innumerable Wonders of the UniverseIntroduction (150 words):The universe is a vast expanse filled with innumerable wonders that have captivated human imagination for centuries. From the billions of stars in the night sky to the countless galaxies swirling around us, the scale and mysteries of the cosmos seem unfathomable. In this article, we will embark on a journey to explore some of these innumerable wonders and understand their significance in unraveling the secrets of the universe.1. The Immensity of Space (200 words):The first awe-inspiring aspect of the universe is its sheer immensity. It encompasses an innumerable number of stars, planets, and galaxies, stretching billions of light-years in every direction. Looking up at the night sky, it becomes difficult to comprehend the countless trillions of stars that exist. Further, recent discoverieshave revealed the existence of over two trillion galaxies, each containing billions of stars. The vastness of space is both humbling and exhilarating, challenging us to contemplate our place in the cosmos.2. Galaxies: Cosmic Island Chains (300 words):Within the universe, galaxies are the building blocks of cosmic structure. These vast systems consist of stars, planets, gas, dust, and dark matter, all held together by gravity. The most common type of galaxy is the spiral galaxy, characterized by its rotating arms and central bulge. Examples include our own Milky Way and the Andromeda Galaxy. However, other types, such as elliptical and irregular galaxies, are also innumerable in number.3. Black Holes: Cosmic Monsters (350 words):Black holes are one of the most mysterious and captivating objects in the universe. These gravitational powerhouses are formed from the remnants of massive stars that have exhausted their nuclear fuel. Their gravity is so strong that nothing, not even light, can escape their gravitational pull. Black holes are thought to be innumerable in number, ranging in sizes from stellar black holes to supermassive ones that exist at the centers of galaxies. Their studyprovides insights into the nature of spacetime and the behavior of matter under extreme conditions.4. Exoplanets: Homes Beyond Our Solar System (350 words):The discovery of exoplanets, or planets orbiting stars outside our solar system, has revolutionized our understanding of the universe. The exoplanet population is believed to be innumerable, with an estimated hundreds of billions in just our Milky Way galaxy alone. These distant worlds come in all shapes and sizes, some resembling Earth and potentially harboring conditions suitable for life as we know it. Understanding exoplanets is crucial in our quest to find extraterrestrial life and expand human exploration beyond our celestial neighborhood.5. Dark Matter: The Invisible Enigma (400 words):Dark matter is perhaps the greatest unsolved mystery in modern astrophysics. It is called "dark" because it neither emits nor absorbs light, making it invisible. Nevertheless, its gravitational effects have been observed throughout the universe, shaping the formation of galaxies and large-scale structures. Despite its innumerable presence, dark matter's nature and composition remain largely unknown, baffling scientists. Unlocking the secrets of dark matterwill provide a deeper understanding of the cosmos and the invisible forces that govern it.Conclusion (200 words):The universe is an ever-expanding tapestry of innumerable wonders, challenging our comprehension and pushing the boundaries of human knowledge. From the vastness of space to the mesmerizing beauty of galaxies, the existence of black holes, the discovery of exoplanets, and the enigma of dark matter, each aspect unravels a distinct piece of the cosmic puzzle. As we continue to explore and study these wonders, we inch closer to unraveling the mysteries of the universe and understanding our place within it. The only limit to our knowledge of the universe is our ability to imagine and inquire, urging us to continue the journey of discovery and exploration of the innumerable marvels that lie beyond our planet Earth.。

affixes

affixes
-pathy-
Feeling, suffering
-phil-
love
-phon-
sound
Examples
-pod-, -ped-
foot
-polis-
city
-port-
carry
-psych-
miind
-scopr-
See, look at
-scope-
Instrument for seeing or observing
Pseudo-science, pseudo-classic
Rebuild, rebound(回弹)
Retroact反向运动,起反作用
Semiaquatic水路两栖semicircle
Substandard, subhuman(低于人类的
Superman, supermarket
Synchronism影视制作中的声像同步
false假的
again, back再一次
half
lower/less than次于……
above, better超过的
with, together
across过度,跨越
three
extremely, beyond外的
not否定前缀
too little
one单一的
Amoral, asymmetry(不对称)
Selfless, penniless
Troublesome, burdensome
Poisonous, humorous
Meanings
Examples
-able, -ible, -ble
Capable of
Fit for
-ate
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precursors of ultracompact (UC) H regions, i.e. very young (< 105 yr), massive (M> 8M⊙ ) objects which have not yet ionised the surrounding medium. In particular, from CS and mm continuum observations, it has been noted that in the earliest stages prior to the onset of massive star formation, the radial distribution of the intensity is quite flat, resembling the structure of starless cores in more quiescent and less massive molecular clouds (Beuther et al. 2002). More evolved objects show more centrally-peaked density structures, with power-law indices once again resembling those found in low-mass cores (i.e. nH2 ∝ r−1.6 ; Shu 1977; Motte & Andr´ e 2001). These results strongly suggest to apply the investigative techniques that are successful in the study of low-mass star forming cores, to the high-mass regime. It has been found that when the starless core is on the verge of dynamical collapse, most of the high density tracers, including CS and the CO isotopologues, are frozen onto dust grains. CS observations of low-mass cores clearly show that this molecule is avoiding the central high density core nucleus, where the mm continuum peaks (Tafalla et al. 2002). The mor-
Key words. Stars: formation – Radio lines: ISM – ISM: molecules, continuum
1. Introduction
The initial conditions of the star formation process are still poorly understood. In recent years, studies of starless lowmass cores have begun to unveil the physical and chemical features that lead to the formation of low-mass stars (Kuiper et al. 1996; Caselli et al. 1999; Evans et al. 2001; Caselli et al. 2002a; 2002b; Bergin et al. 2002; Tafalla et al. 2002; 2004; 2006; Harvey et al. 2003; Crapsi et al. 2005). On the other hand, the characterisation of the earliest stages of the formation of high-mass stars is more difficult than for lowmass objects, given their shorter evolutionary timescales, larger distances, and strong interaction with their environments. In the last years various authors (Molinari et al. 2000, 2002; Sridharan et al. 2002; Beuther et al. 2002; Fontani et al. 2005) have performed extensive studies aimed at the identification of
Send offprint requests to: F. Fontani, e-mail: fontani@ira.inaf.it ⋆ Based on observations carried out with the IRAM Pico Veleta telescope. IRAM is supported by INSU/CNRS (France), MPG (Germany) and IGN (Spain).
Received date; accepted date
ABSTRACT
Aims. We have measured the deuterium fractionation and the CO depletion factor (ratio between expected and observed CO abundance) in a sample of high-mass protostellar candidates, in order to understand whether the earliest evolutionary stages of high-mass stars have chemical characteristics similar to those of low-mass ones. In fact, it has been found that low-mass starless cores on the verge of star formation have large values both of the column density ratio N (N2 D+ )/N (N2 H+ ) and of the CO depletion factor. Methods. We have observed with the IRAM-30m telescope and the JCMT two rotational lines of N2 H+ and N2 D+ , the (2–1) line of C17 O and DCO+ , and the sub-millimeter continuum towards a sample of 10 high-mass protostellar candidates. Results. We have detected N2 D+ emission in 7 of the 10 sources of our sample, and found an average value N (N2 D+ )/N (N2 H+ ) ∼ 0.015. This value is ∼ 3 orders of magnitude larger than the interstellar D/H ratio, indicating the presence of cold and dense gas, in which the physical– chemical conditions are similar to those observed in low–mass pre–stellar cores. Also, the integrated CO depletion factors show that in the majority of the sources the expected CO abundances are larger than the observed values, with a median ratio of 3.2. Conclusions. In principle, the cold gas that gives origin to the N2 D+ emission can be the remnant of the massive molecular core in which the high-mass (proto-)star was born, not yet heated up by the central object. If so, our results indicate that the chemical properties of the clouds in which high-mass stars are born are similar to their low-mass counterparts. Alternatively, this cold gas can be located into one (or more) starless core (cores) near the protostellar object. Due to the poor angular resolution of our data, we cannot decide which is the correct scenario.
F. Fontani1 , P. Caselli2 , A. Crapsi3 , R. Cesaroni2 , S. Molinari4 , L. Testi2 , and J. Brand1
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