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Development of prognostic techniques for batteries in application relies on an adequate model to describe the processes involved. The work of Randles’ [7] is widely regarded as the reference work in this field (fig. 1 ).
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geroscience manuscript 格式 -回复
geroscience manuscript 格式-回复Geroscience Manuscript Format: A Step-by-Step GuideIntroduction [Introduction to Geroscience]Geroscience, an interdisciplinary field studying the biology of aging, has garnered significant attention in recent years. As researchers strive to understand the underlying mechanisms of aging and develop interventions for age-related diseases, proper manuscript format becomes crucial for effectively communicating scientific findings. In this article, we will provide a step-by-step guide to formatting a geroscience manuscript, ensuring its adherence to recognized standards in the field.Title [Choosing an Appropriate Title]The title of a geroscience manuscript should be concise, yet informative. It should accurately reflect the content of the study while piquing the interest of readers. For instance, a suitable title for a study investigating the impact of calorie restriction on lifespan in mice could be "The Effects of Calorie Restriction on Lifespan in Mouse Models: Implications for Aging Interventions."Abstract [Constructing an Informative Abstract]The abstract should succinctly summarize the purpose, methods, key findings, and implications of the study. These short paragraphs should provide enough information for readers to understand the study's foundations and whether it is relevant to their own research. Ideally, the abstract should be no longer than 250 words and be written in a clear and concise manner.Introduction [Providing Context and Research Objectives]The introduction of a geroscience manuscript should provide background information on the topic of study, highlight knowledge gaps in the field, and clearly state the research objectives. By contextualizing the study within existing literature, the introduction lays the foundation for the research, guiding readers towards its significance and potential contributions.Methods [Detailed Account of Study Design and Procedures]The methods section should provide a clear and precise account of the study design, including the experimental models, interventions, sample sizes, data collection, and statistical analyses. This section should be detailed enough to allow other researchers to replicate the study accurately. Including ethical considerations, such as the use of animals or human subjects, is also essential.Results [Presenting Findings and Statistical Analyses]In the results section, the findings should be presented objectively, backed by appropriate statistical analyses. Data can be presented using graphs, tables, or figures, which should be appropriately labeled and accompanied by detailed captions. It is crucial to focus on the most significant findings and avoid redundant information.Discussion [Interpretation of Findings and Implications]In the discussion section, the results should be interpreted in light of existing literature, and any limitations or unexpected observations should be addressed. Conclusions should be drawn, and the implications of the study for geroscience and related fields should be highlighted. It is essential to discuss potential future directions for research and any practical applications that might arise from the findings.Conclusion [Summarizing Key Findings and Contributions]The conclusion should provide a concise summary of the study's key findings and contributions. It should reiterate the implications of the findings and emphasize their relevance to the field of geroscience. A well-crafted conclusion leaves a lasting impact onreaders and can help drive further research in the area.References [Citing Relevant Literature]In a geroscience manuscript, references play a crucial role in supporting claims and giving credit to previous research. Following the recognized citation style, such as APA or MLA, is essential. Ensure that all cited works are formatted correctly and listed alphabetically.In conclusion, adhering to the appropriate format for a geroscience manuscript is vital for effectively communicating research findings to the scientific community. By following the step-by-step guide outlined above, researchers can ensure that their work is presented in a clear, informative, and impactful manner, contributing to the advancement of geroscience and its potential applications in improving health and longevity.。
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PolymerChemistry高聚物化学Accepted Manuscript接受的手稿This article can be cited before page numbers have been issued, to do this please use: J. Hou, C. Li, Y.Guan, Y. Zhang and J. X. X. Zhu, Polym. Chem., 2015, DOI: 10.1039/C4PY01757A.这篇文章可以已经发出页码前引，要做到这一点，请使用：：J. Hou, C. Li, Y.Guan, Y. Zhang and J. X. X. Zhu, Polym. Chem., 2015, DOI: 10.1039/C4PY01757A.This is an Accepted Manuscript, which has been through the Royal Society of Chemistry peer review process and has been accepted for publication.这是一个公认的手稿,已通过英国皇家化学学会的同行评审过程和已经发表。
Accepted Manuscripts are published online shortly after acceptance, before technical editing, formatting and proof ing this free service, authors can make their results available to the community, in citable form, before we publish the edited article. We will replace this Accepted Manuscript with the edited and formatted Advance Article as soon as it is available.接受的手稿是在不久后发表的验收，在技术编辑，格式化和校对。
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Chemical Communications Accepted Manuscript
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Yuan-Qiang Sun, Jing Liu, Jingyu Zhang, Ting Yang, and Wei Guo*
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the damned human race课后grsmmer
the damned human race课后grsmmerI have been studying the traits and dispositions of the "lower animals," and contrasting them with the traits and dispositions of man. I find the result humiliating to me. For it obliges me to renounce my allegiance to the Darwinian theory of the Ascent of Man from the Lower Animals and to name it the Descent of Man from the Higher Animals.In proceeding toward this unpleasant conclusion I have not guessed or speculated or conjectured, but have used what is commonly called the scientific method. That is to say, I have subjected every postulate that presented itself to the crucial test of actual experiment, and have adopted it or rejected it according to the result. These experiments were made in the London Zoological Gardens, and covered many months of painstaking and fatiguing work.Some of my experiments were quite curious. In the course of my reading, I had come across a case where, many years ago, some hunters on our Great Plains organized a buffalo hunt for the entertainment of an English earl—that, and to provide some fresh meat for his table. They had charming sport. They killed seventy-two of those great animals; and ate part of one of them and left the seventy-one to rot. In order to determine thedifference between an anaconda and an earl—if any—I caused seven young calves to be turned into the anaconda's cage. The grateful reptile immediately crushed one of them and swallowed it, then lay back satisfied. It showed no further interest in the calves and no disposition to harm them. I tried this experiment with other anacondas; always with the same result. The facts stood proven that the difference between an earl and an anaconda is that the earl is cruel and the anaconda isn't; and that the earl wantonly destroys what he had no use for, but the anaconda doesn't. This seemed to suggest that the anaconda was not descended from the earl. It also seemed to suggest that the earl was descended from the anaconda, and had lost a good deal in the transition.。
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Accepted Manuscript
Accepted ManuscriptThis is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our authors and readers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. .CHANGES IN PHYSIOLOGICAL PARAMETERSINDUCED BY SIMULATED DRIVING TASKS: MORNING VS. AFTERNOON SESSIONWen-Chieh Liang, John Yuan, D. C. Sun, and Ming-Han LinReference: 2007028To appear in: Journal of the Chinese Institute ofIndustrial EngineersReceived date: April 2007 Revised date: May 2007 Accepted date: April 2008CHANGES IN PHYSIOLOGICAL PARAMETERS INDUCED BY SIMULATED DRIVING TASKS: MORNING VS.AFTERNOON SESSIONWen-Chieh Liang* and John YuanIndustrial Engineering and Engineering Management, National Tsing Hua University 101, Section 2, Kuang-Fu Road, Hsinchu City, Taiwan 300, R.O.C.D. C. SunGeneral Manager, Taiwan Scientific CorporationMing-Han LinAutomation Engineering, Ta Hwa Institute of TechnologyABSTRACTIntroduction: Driving fatigue is one of the most common causes for traffic accidents. Im-mobilization of legs, hip, and waist is thought to play a major role in driving fatigue, as ithinders blood circulation and induce hemodynamic changes. Objective: the objective of thestudy was to monitor changes in physiological parameters before and after indoor simulateddriving tasks conducted in the morning as well as afternoon sessions. Method: 40 youngmale subjects were randomly divided into morning (group A) and afternoon (group B) ses-sions and participated in the 90-min simulated in-door driving task. Before and after the task,BP (blood pressure), HR (heart rate), and HRV (heart rate variability) parameters weremeasured using a novel wrist monitor ANSWatch® which utilized built-in bio-sensors in thecuff to acquire radial pulse waves directly. Palm temperatures were measured by ahigh-precision thermometer. A questionnaire ranking driving fatigue was filled by eachvolunteer before and after the driving task. Results: (1) from paired T-tests, both themorning and afternoon driving tasks caused decreases in HR and palm temperatures, andincreases in HRV and VLF(AU) (Very Low Frequency(Absolute Unit)); For the morningsession, LF(AU) (Low Frequency(Absolute Unit)) and LF(NU)(Low Fre-quency(Normalized Unit)) increased while HF(NU) (High Frequency(Normalized Unit))decreased; In contrast, LF(NU) and LF/HF decreased while HF(NU) increased for the af-ternoon session (all changes p<0.05). Systolic pressure was maintained in the morning ses-sion but dropped in the afternoon session (p<0.05). (2) From One-way and Two-wayMANOVA analyses, there was no significant difference between morning and afternoonsession for the entire group of physiological parameters measured before or after drivingtasks; However, LF(AU), LF(NU), and LF/HF three individual parameters measured beforedriving were higher in the afternoon session than in the morning session (p<0.05). (3) Fromwritten questionnaire, all subjects felt some degree of fatigue following the driving task. Nostatistical difference existed between the two driving sessions in terms of fatigue scorebaseline or score change due to driving. Conclusion: Multiple physiological parametersshowed significant changes after simulated driving tasks.Distinct trends were found be-tween the two driving sessions. In the morning session, poor circulation in the lower body(limbs, abdomen, and hip) caused decrease in palm temperatures and heart rate, but bloodpressures were maintained due to activation of the sympathetic nervous system as evidencedby increased HRV, LF(AU), and LF(NU). For the afternoon session, palm temperatures,heart rate, and systolic pressure were all lowered. Para-sympathetic nervous system was ac-tivated (indicated by increased HF(NU)) prompting the body to enter a sleepy state, whichgreatly increases accident risks in actual road driving. Monitoring of multiple physiologicalparameters in the study had gained great insight into mechanisms of homeostasis and pro-vided a foundation in the future work to quantify driving fatigue in terms of degree of de-viation from homeostatic states.Keywords:Driving Fatigue, Heart Rate Variability (HRV), Homeostasis, Autonomic* Corresponding author: richard168@Nervous System, Blood Pressure, Simulated Driving, ANSWatch1.INTRODUCTIONWhile driving fatigue is still a vaguely defined term physiologically, its effect on traffic accidents is well documented. Numerous statistics and studies have shown that long hour driving resulted in physical tiredness and slowdown in mental judgment. In the report published by Shinar in 1978 [18], a significant portion of highway accidents were attributed to driv-ing fatigue. National Transportation Safety Board in U.S. investigated 286 accidents involving commercial vehicles and discovered that 38% of accidents were caused by the drivers’ drowsiness or neglect (Harris and Mackie, 1972). Overall, driving fatigue remains one of the most probable causes for traffic accidents. A better understanding in driving fatigue on the physio-logical level will lead to new development for effec-tive prevention.In one aspect of driving, drivers often fail to maintain fresh concentration on the road with repeti-tious and unexciting scenery. In another aspect of driving, the limited waist, hip and leg spaces constrain the lower body (limbs, abdomen, and hip)from active movement. The “pumping” action by the leg muscle contraction, which forces the venous blood back to the heart (such as during walking or exercise), is largely lost. It is our belief that immobilization of the lower body plays a major role in driving fatigue, as it hinders systemic blood circulation and induces significant hemodynamic changes. This belief is consistent with widely discussed mechanisms in driving fatigue, in-cluding hypoxia in brain, blood pressure drop, and below-normal heart rate.It is well known that when local or systemic cir-culation is obstructed, ANS(Autonomic Nervous Sys-tem) in the body is activated swiftly. Through its sympathetic and parasympathetic branches, ANS helps the cardiovascular system to maintain proper blood supply under these compromised circumstances. If the activation and execution of ANS is effective, deviations of physiological parameters from the ho-meostatic states can be avoided or minimized. On the other hand, any significant change in vital physio-logical parameters from baseline (such as body tem-perature or blood pressures) may point to an “ex-hausting” body which is unable to respond to physiological needs.HRV (Heart rate variability) has been used in various studies for the assessment of physiological states. The subconscious cyclic variation in heart rate period is commonly analyzed in both time and fre-quency domains to give rise to parameters that are linked to total ANS activity (HRV or SDNN, TP or total power), sympathetic activity (LF (AU) and LF (NU)), parasympathetic (or vagal) activity (HF (AU) and HF (NU)), and sympatho-vagal balance (LF/HF) indexes. Hjortskov et al. [7] and Garde et al. [5] both monitored HRV parameter changes in volunteers before and after a computer task during which various degrees of mental stresses were introduced. Hjortskov et al. [7] indicated that stressors led to changes in HRV (increase in LF(AU), HF(AU), and LF/HF compared to those under resting conditions), and a sustained increase in blood pressures (SYS and DIA). Garde et al. [5] also reported an increase in heart rate, blood pressure, and LF (NU), and a decrease in TP(AU) and HF (NU) in response to a physically demanding ref-erence computer task. Wahlstrom et al. [26] also in-troduced time and verbal stresses during a mouse - driven computer task to investigate the physiological and psychological changes based upon heart rate, blood pressures (SYS and DIA), and HRV. Increases in both the physiological (HR, BP, LF/HF) and psy-chological reactions were observed compared to con-trol conditions. These reports suggest that physical and mental stresses may cause the activation of sympa-thetic nervous system as indicated by increased BP, HR, LF, and LF/HF.In a similar manner, several authors investigated the effect of simulated flight on physiological pa-rameters [9][11][25]. Their general finding is that the complexity of a pilot’s task in operating a flight often caused an increase in HR and BP (SYS and DIA), and a decrease in HRV. Lee [11] clearly showed that when the pilots conducted tasks that required high concen-tration, such as during take-off and landing, their heart rates increased significantly. Among various tasks performed by pilots (take off, climb and cruise, de-scent and approach, and landing), HRV was seen lowest during approach as it was the most critical period of piloting.In the area of indoor simulated driving tests [8][14][15][16][17][27], Yang et al. [27] utilized ECG to monitor the drivers’ HRV changes. They discovered four HRV parameters that were significantly changed after driving, namely increased HRV (or SDNN), increased LF (AU), decreased HF (NU), and increased LF/HF. Yang et al. [27] also reported that as the degree of fatigue increased (indicated by increasing driving hour), SDNN (equivalent to HRV in this study), LF(NU) and LF/HF all increased while HF(NU) de-creased progressively. The authors believed that the increase in LF/HF was an indication of increase in degree of driving fatigue, as the balance of ANS shifted towards the sympathetic branch. Li et al. (2003) [16] also based their HRV study on ECG and found three HRV parameters with significant changes after simulated driving, including increased LF (NU), de-creased HF (NU), and increased LF/HF. After three hours of continuous driving, the drivers showed an increase in response time, a drop in judgment accuracy,and a lower heart rate. Subjective written question-naire also showed increased symptoms of driving fatigue. They proposed using HRV as a quantitativeindex of driving fatigue. Li et al. [14,15,17] furtherstudied the effect of acupuncture on driving fatigue.Their findings suggested that driving fatigue induced physiological changes could be attenuated by acu-puncture. Actual road driving involves much highermental and physical loads than the indoor simulation.Both Fumio et al. [4] and Miloševic et al. [21] ob-served an increase in BP on taxi drivers on long duty schedules. It is to be noted that the levels of mental andphysical workloads, time duration, as well as the de-gree of body immobilization are all different amongthe above were cited studies as well as in this research.We thus expected to see unique body responses in the volunteers during the 90-min indoor driving employedin this study.In this study, we monitored multiple physio-logical parameters, including palm temperatures (leftand right), HR, BP (SYS and DIA), and HRV pa-rameters before and after a 90-min indoor driving task.In addition, a written questionnaire was filled by each participant before and after the driving task to gaugethe subjective evaluation of driving fatigue. The studywas divided into two sub-groups, one conducted in the morning, and the other in the afternoon, so that body reactions to long-hour driving at different times of theday could be investigated. It is our hope that the resultsof this first phase in a series of studies could provideuseful information for the definition of driving fatiguebased upon physiological parameter changes.2.METHODSIn-door simulated driving (instead of road driv-ing) was selected in consideration of cost, safety, andcontrol of variables.2.1SubjectsAll volunteers gave their informed consent beforethe study. To avoid the influences of gender and ageon HRV [13][28], a total of 40 male subjects in the ageof 23.3±1.9 years old (Table 1; all college students or graduates) were selected to take the driving test. Allsubjects were currently healthy and without anymedical treatments. They were instructed to have sufficient sleep in the previous night and not to eat,drink, or exercise one hour prior to the test. All sub-jects were confirmed to be in fresh or non-fatigue conditions before driving when reporting to the labo-ratory.Table 1. Characteristics of subjectItem AverageAge 23.3±1.9 (years-old)Height 169.2±6.2 (cm) Weight 70.6±9.6 (kg)Body Fat Index*22.5±6.1 (%)* Body fat index measured by a commercial instrument manufactured by TANITA corporation (Model: ULT 2000 / ULT 2001, Tokyo, Japan)2.2VariablesIn the experimental design, gender, age and am-bient temperature (and humidity) were controlled. The independent variables (effects) were driving session (morning or afternoon) and driving task (before or after). The dependent variables were physiological parameters which included blood pressures [systolic (SYS) and diastolic (DIA)], heart rate (HR), heart rate variability (HRV), sympathetic nerve activity indexes [LF(AU) and LF(NU)], parasympathetic nerve activ-ity indexes [HF(AU) and HF(NU)], sympatho-vagal balance index (LF/HF), and temperature of left and right palms.2.3In-door simulated drivingThe test room was temperature controlled at 22±2.℃ A simulate highway scenery was projected onto a 178 (cm) x 178 (cm) white screen using a computer and a projector (Figure 1). The driver’s seat was about 3-4 m away from the screen. There were trees on the left and walls on the right side of the four-lane, two-way highway. The driver must operate the wheel to keep the vehicle on the designated lane without hitting trees or walls. A red warning scale appeared on the left side of the windshield which would expand in area vertically if the vehicle location deviated from the designated lane. Laud sounds would go off if the vehicle got too close to or made contact with road trees or walls. The driving task lasted 90 minutes. While the driver’s main task was to operate the wheel, he was not required to step the gas or the break peddle (both not equipped). Instead, a constant driving speed (the road view) was provided by the computer. Such a simulation is close to a highway driving where the traffic conditions are more constant as compared to a local in-town driving where the driver must change the speed frequently using gas and break peddles.Figure 1. Driving simulator2.4Apparatus and materialsExperimental apparatus consisted of a HP note-book computer, a computer projector, a driving wheel, a timer watch, a body weight and fat balance, a high precision thermometer (+0.1C), and ANSWatch®. Software included highway scenery simulator, Win-dows XP, SPSS 12.0, and “ANSWatch Manager Pro” data analyzer.2.5Experimental procedures40 subjects were randomly divided into two groups (A&B). Group A conducted driving tests in the morning (8:30~11:00AM) while Group B in the af-ternoon (2:00~4:30PM). When reported to the test room, each volunteer took a 20-min rest first and then underwent thermometer (both palms) and ANSWatch ® tests. The two tests needed about 7 minutes. Data in ANSWatch® was downloaded to a notebook com-puter immediately following the test for review and storage. The driving task followed which lasted for 90 minutes. After driving, each volunteer was tested again for palm temperatures and ANSWatch®. In addition, a written questionnaire consisting of 14 questions related to fatigue (similar to those developed by authors in [17]) was filled by the volunteers before and after driving. The entire testing program is illus-trated in Figure 2. The list of questions is shown in Table 2, while the quantitative scale for each question is shown in Table 3. A score of 4 or higher is an in-dication of positive response to the question.Table 2. Questionnaire for feeling of driving fatigueNo Symptom1 Bodytiredness2 Loss of concentration3 Desire to lie down4 Anxiety5 Lack of energy6 Mental response slowdown7 Headache8 Shoulderstiffening9 Waistpain10 Lower body numbness11 Eyefatigue12 Feeling of sleepiness13 Feeling of vomit14 Hand and foot tremblingTable 3. Quantitative scale (1-7)Scale Fatiguedescription1 No such feeling2 Negligiblefeeling3 Somefeeling4 Clearfeeling5 Strongfeeling6 Very strong feeling7 Extremely strong feeling2.6Physiological parameters analysesDuring the 6-min test, ANSWatch® (Figure 3)first used the oscillatory method to obtain heart rate,systolic pressure, and diastolic pressure. It then con-ducted a standard 5-min HRV test. Thepiezo-electrical sensors in the cuff picked up bloodpressure waveforms produced by the radial artery,with the aid of an air pouch pressure controlled by anair pump and a release valve. Peak-to-peak intervalswere determined followed by time and frequencydomain analyses. The HRV analysis followed closelythe 1996 international standard [24], consisting of thefollowing steps:(1).The original data was fed through a low passFIR filter at 0 to 14 Hz.(2).Fundamental frequency was determined basedupon the first 5-second data.(3).The primary peak in each cycle was determined.(4).Peak-to-peak intervals were calculated.(5).Time-domain HRV parameters (mean period orheart rate; variance and standard deviation ofpeak-to-peak intervals) were calculated. Peakintervals greater than 4*standard deviation wereremoved and not replaced.(6).Peak-to-peak intervals were re-sampled to 1024points with interpolation and Hamming windowadjustment.(7).Fast Fourier Transform (FFT) was performedwith Hamming window adjustment.(8).Integrations of power spectral density between0.0001 and 0.04 Hz for the very low frequencycomponent (VLF), between 0.04 and 0.15 Hzfor the low frequency component (LF), andbetween 0.15 and 0.4 Hz for the high frequencycomponent (HF) respectively were conducted.(9).Frequency-domain HRV parameters {VLF(AU), LF (AU), HF (AU), LF (NU) [equal toLF/(LF+HF)*100], and HF (NU) [equal toHF/(LF+HF)*100]} were calculated.Figure 3. ANSWatch® wrist monitorIt is noted above that irregular heartbeats (defined as those with peak intervals greater than 4 standard deviations in the 5-min test data, as caused by cardiac arrhythmia or body movement) were excluded from the raw data prior to HRV analysis (as recommended by the 1996 Standard [24]). For clarity, the HRV pa-rameters used in the study are listed below with asso-ciated physiological meanings and units:(1).HR：Heart rate (beat/min)(2).HRV：Total ANS activity index (ms); equal tostandard deviation of adjacent peak-to-peak in-tervals SDNN defined in 1996 standard. (3).VLF(AU)：Very Low Frequency (AbsoluteUnit) (frequency range 0.0001~0.04 Hz) (ms2);its physiological meaning not defined by 1996Standard(4).LF(AU)：Low Frequency (Absolute Unit)(frequency range 0.04 ~0.15 Hz) (ms2); sym-pathetic (and some parasympathetic) nervousactivity index(5).HF(AU)：High Frequency (Absolute Unit)(frequency range 0.15~0.4 Hz) (ms2); para-sympathetic nervous activity index(6).LF(NU)(%)：Low Frequency(Normal Unit),[LF/(TP-VLF)]*100; contribution of sympa-thetic nervous activity(7).HF(NU)(%)：High Frequency(Normal Unit)[HF/(TP-VLF)]*100; contribution of parasym-pathetic nervous activity(8).LF/HF：Ratio of LF(AU) to HF(AU);sympatho-vagal balance indexAlthough the physiological meaning for VLF (AU) was reported by ANSWatch, it is not defined in the 1996 Standard. The authors decided to report VLF (AU) data to aid discussions.2.7Data collectionUp to date, most HRV studies have been using ECG due to its availability in research laboratories. A few studies have based their HRV measurements on finger blood pressure waveforms using an optical sensor [1][6][20]. They reported data accuracy in terms of correlation coefficient in the range of 0.75 to 0.99 when compared to ECG. In this paper, we are introducing a new wrist monitor ANSWatch® (Tai-wan Scientific Corporation, Taipei, Taiwan; Taiwan DOH (Department of Health) Approval number 001525) which employs multiple piezo-electrical sensors enclosed in the cuff to directly measure the blood pressure waveforms in the radial artery. Ac-cording to the company documents submitted to Tai-wan Department of Health and published literature [12][22][23], the device accuracy (correlation coeffi-cient) is in the range of 0.90 to 1.0 using ECG as the control. This portable device requires neither elec-trodes nor other disposables, and can conduct tests in sitting or lying postures. Each ANSWatch® test takes about 6-minutes and outputs eight patient parameters on the LCD screen (heart rate HR, systolic pressure SYS, diastolic pressure DIA, heart rate variability HRV (or standard deviation of 5-min peak-to-peak intervals SDNN), low frequency (normalized) LF (NU), high frequency (normalized) HF(NU), sym-patho-parasympathetic balance index LF/HF, and number of irregular heartbeats (cardiac arrhythmia). Upon data download to a PC and using the accompa-nied software (ANSWatch® Manager Pro), more HRV parameters can be calculated (such as low fre-quency (absolute) LF (AU), high frequency (absolute) HF (AU), total power TP, very low frequency (abso-lute) VLF (AU), and square root of the mean of the sum of the squares of differences between adjacent peak intervals RMMSD etc.)2.8Statistical analysesStudent’s T tests (two-tailed) were used throughout the entire study to determine the signifi-cance of parameter changes before and after the driv-ing task for respective driving sessions. Furthermore, One-way and Two-way MANOVA (Multivariate analysis of variance) analyses were used to examine any group difference or interactions. The question-naire results were analyzed using the same methods. 3.RESULTS3.1Variation in physiological parameters before and after driving (pair T test analyses)Table 4 and Table 5 show the test results for the morning session (Group A) and the afternoon session (Group B) respectively.Table 4. Physiological parameters before and after driving task for the morning session Parameters Before driving After driving t-value DF a p-value SYS 113.8±9.0 113.8±9.2 0.02 19 0.987DIA 73.4±1.8 73.6±1.9 0.44 19 0.666HR 70.2±11.3 65.8±8.6 -3.09 19 0.006HRV 44.5±14.7 58.7±16.4 6.20 19 0.000LF (AU)468.4±302.7716.7±434.5 3.12 19 0.006LF (NU)46.3±17.1 54.3±14.5 2.26 19 0.036HF (AU)580.0±518.1591.5±383.4 0.11 19 0.916HF (NU)53.7±17.1 45.6±14.5 -2.26 19 0.036 VLF (AU)1142.4±983.82366.2±1584.3 5.62 19 0.000LF/HF 1.1±0.8 1.3±0.7 1.45 19 0.164T LP36.5±0.6 35.4±1.7 -3.01 19 0.007T RP36.6±0.7 35.6±1.7 -2.65 19 0.016: DF (degree of freedom)From Table 4, HR, HRV, HF(NU), LF(AU) & LF(NU), VLF(AU), left palm temperature (T LP) and right palm temperature (T RP) exhibited significant changes (p<0.05) after the driving task conducted in the morning for Group A, while changes in SYS, DIA, HF (AU) or LF/HF did not reach statistical signifi-cance.Table 5. Physiological parameters before and after driving task for the afternoon session Parameters Before driving After driving t-value DF a p-value SYS 118.7±7.7 111.4±5.0 -4.16 190.001DIA 73.9±2.3 73.9±2.0 0.11 190.917HR 71.4±9.2 67.0±9.7 -3.33 190.003HRV 48.7±16.9 56.3±17.7 2.71 190.014LF (AU) 879.8±847.6 817.9±545.1 -0.39 190.700LF (NU) 63.2±14.8 53.5±16.7 -3.21 190.005HF (AU) 510.9±465.7 742.4±565.3 3.02 190.007HF (NU) 36.8±14.8 46.6±16.7 3.21 190.005 VLF (AU) 1253.7±823.9 1907.1±1372.8 2.70 190.014LF/HF 2.1±1.2 1.5±1.0 -2.69 190.015T LP36.7±0.8 35.7±1.8 -3.78 190.001T RP36.8±0.8 36.0±1.9 -2.87 190.010: DF (degree of freedom)From Table 5, SYS, HR, HRV, LF(NU), HF(AU), HF(NU), VLF(AU), LF/HF, left palm tem-perature(T LP) and right palm temperature (T RP) all exhibited significant changes (p<0.05) after the driv-ing task conducted in the afternoon for Group B, while changes in DIA and LF(AU) did not reach statistical significance. It is noted that average systolic pressure went down from 118.7 (before driving) to 111.4 mmHg (after driving) with a p-value of 0.001.3.2Variation in physiological parameters (Multivariate Analysis of Variance,MANOVA)3.2.1 One-way MANOVA (morning vs. after-noon)(1). Before drivinga. Entire group of physiological parametersThis analysis was based upon the entire group of physiological parameters measured before driving in the study (a total of 12, see Table 4 or 5) to examine any statistical difference between the morning and the afternoon session. The results are shown in Table 6. Table 6. Comparison between sessions for the entire group of physiological parameters before driving Effect Test Value F Hypothesis DF a Error DF a p-valueDriving session Wilks'λ0.673 1.23 11 28 0.309: DF (degree of freedom)From Table 6, there was no significant group difference (p=0.309) between the morning and the afternoon session for the 12 physiological parameters taken before driving.b. Individual physiological parameters (inde-pendent T-test)Individual physiological parameters were exam-ined by independent T-tests for any group difference between the morning and the afternoon session. Re-sults are shown in Table 7.Table 7. Comparison between sessions for individual physiological parameters before drivingSession averageParametersMorning AfternoonDifferenceb betweensessionStan-darddevia-tionDF a p-value SYS 113.80118.65 4.852.65380.075 DIA 73.4573.900.450.65380.498 HR 70.2071.40 1.203.27380.716 HRV 44.5548.70 4.155.02380.414 HF (AU)580.00510.85-69.15 155.77 380.660 HF (NU)53.7036.80-16.90 5.06 380.002 LF (AU)468.45879.75411.30 201.26 380.048 LF (NU)46.3063.2016.90 5.06 380.002 VLF (AU)1142.401253.70111.30 286.95 380.700 LF/HF 1.11 2.13 1.020.32380.003 T LP 36.5436.710.160.22380.474 T RP 36.6136.780.170.25380.507 : DF (degree of freedom)b: Difference was defined as value (afternoon ses-sion) – value (morning session)From Table 7, LF(AU), LF(NU) and LF/HF were higher while HF(NU) was lower in the afternoon ses-sion as compared to those in the morning session (p<0.05). In other words, a slight shift towards the sympathetic activity was found in the afternoon group before driving. Other authors have reported HRV differences measured at different hours of the day [2][3]. This difference does not affect the paired T-tests shown in Tables 4 and 5 for the effect of driv-ing, but the authors plan to investigate this effect in the future studies.(2). After drivinga. Entire group of physiological parametersThis analysis examined any statistical difference between the morning and the afternoon session based upon the entire group of physiological parameters taken after driving. The results (not shown here for brevity) indicated that there was no significant group difference (Wilks’λvalue 0.764; p=0.652) between the morning and the afternoon session for the 12 physiological parameters taken after driving.。
This un-edited manuscript has been accepted for publication in
Biophys J BioFAST, published on April 20, 2007 as doi:10.1529/biophysj.106.103770 This un-edited manuscript has been accepted for publication in Biophysical Journal and is freely available on BioFast at . The final copyedited version of the paper may be found at .Running title: Ste2p receptor fragment structureNMR studies in DPC of a fragment containing the seventh transmembrane helix of a GPCR from Saccharomyces cerevisiaeAlexey Neumoin1, Boris Arshava3, Jeff Becker2, Oliver Zerbe1, Fred Naider31Institute of Organic Chemistry, University of Zurich, Switzerland2Department of Microbiology, University of Knoxville, Tennessee, USA3Department of Chemistry, College of Staten Island, CUNY, USAAddress reprint requests toFred Naider, College of Staten Island, CUNY, USA, Tel: +1-718- 982 3896. Fax: +1-718-982 3910 , E-mail address: naider@or toOliver Zerbe, Institute of Organic Chemistry, University of Zurich, Switzerland, Tel: +41-44-635 42 63. Fax: 0041-44-635 68 82. E-mail address: oliver.zerbe@oci.unizh.chAbbreviations:GPCR, G-protein coupled receptor; DPC, dodecylphosphocholine; HFIP, hexafluoro-, vicinal spin-spini-propanol; HPLC, high performance liquid chromatography; 3J HNαcoupling constant between the backbone amide proton and the α proton;LPPG, 1-palmitoyl-2-hydroxy-sn-glycero-3-[phospho-rac-(1-glycerol)]; DOTA, 1,4,7,10-tetraazocyclododecane-N,N-acetic acid; NOE, nuclear Overhauser effect; NOESY, nuclear Overhauser enhancement spectroscopy; HSQC, heteronuclear single quantum coherence; 15N{1H}-NOE, heteronuclear Overhauser enhancement of 15N after saturation of 1H; RMSD, root-mean-square deviation; SDS, sodium dodecyl sulphate; TOCSY, total correlation spectroscopy; 2D, two-dimensional; CD, circular dichroism.AbstractThe structure and dynamics of a large segment of Ste2p the G-protein coupled α-factor receptor from yeast were studied in dodecylphosphocholine (DPC) micelles using solution NMR spectroscopy. We investigated the 73-residue peptide EL3-TM7-CT40 consisting of the third extracellular loop 3 (EL3), the 7th transmembrane helix (TM7) and 40 residues from the cytosolic C-terminal domain (CT40). The structure reveals the presence of an α-helix in the segment encompassing residues 10 to 30, which is perturbed around the internal Pro24 residue. RMSD values of individually superimposed helical segments 10-20 and 25-30 were 0.91 ± 0.33 Å and 0.76 ± 0.37 Å, respectively. 15N-relaxation and RDC data support a rather stable fold for the TM7 part of EL3-TM7-CT40, whereas the EL3 and CT40 segments are more flexible. Spin-label data indicate that the TM7 helix integrates into DPC micelles, but is flexible around the internal Pro24 site, exposing residues 22 to 26 to solution and reveal a second site of interaction with the micelle within a region comprising residues 43-58, which forms part of a less well-defined nascent helix. These findings are discussed in the light of previous studies in organic-aqueous solvent systems.IntroductionG protein-coupled receptors (GPCRs) constitute a large family of integral membrane proteins of prime biological importance. They are involved in various important physiological processes such as signal transduction associated with cell growth, pain perception, blood pressure control and sensing of light, odour and taste(1). Approximately thirty percent of drugs currently used to treat various pathologies target GPCRs.(2,3) Despite the widespread occurrence of GPCRs and the fact that they have been studied intensively during the last two decades, fundamental information concerning their three-dimensional structure and about the molecular details of ligand binding and signal transduction is still missing. Although more than 1000 GPCRs have been identified, presently only a single high-resolution X-ray structure that for bovine rhodopsin a light-sensing GPCR is available(4). The atomic details of the seven transmembrane helical bundle from this crystal structure have served as a scaffold for modelling of other GPCRs(5), since all members of this super-family are believed to share a common topology of seven membrane-spanning helices, connected either by extracellular or cytoplasmic loops. The amino and carboxy-termini are always located at the extracellular and cytoplasmic side, respectively(6-8). The tremendous difficulties encountered in obtaining refraction-grade crystals of membrane proteins, and the large size of their complexes with detergents and lipids complicate structural studies by X-ray crystallography or NMR. Furthermore, expression, purification and reconstitution in a membrane-mimicking environment are technically extremely demanding, and only slow progress has been made despite intense efforts(9-11).To address these issues much attention was recently devoted to the study of relatively short peptides corresponding to loops and single transmembrane domains (TMDs) of GPCRs to expand our knowledge on local details of the three-dimensional structure of the intact molecules (12,13). Most of the previous structural investigations on fragments of GPCRs have been limited to fragments containing up to about 50 residues. Even for these relatively short peptides, only few high-resolution structures in detergent micelles have been published, indicating the practical difficulties encountered in conducting such biophysical studies.We have performed intensive studies on individual TMDs of the α-factor receptor (Ste2p) from Saccharomyces cerevisiae (14-20). Signaling by Ste2p, triggered by binding the tridecapeptide-α-factor mating pheromone, results in growth arrest and gene regulation in preparation for sexual conjugation of yeast cells(21). Like other GPCRs, the 431-residue Ste2p contains seven hydrophobic transmembrane domains (TMDs), with its carboxyl terminus located in the cytosolic milieu. Mutagenesis studies have revealed a key role of the TMDs in α-factor receptor activation. The carboxy-terminus was shown to be involved in Ste2p down-regulation through endocytosis, and in desensitization by phosphorylation(22).To determine their structure in hydrophobic environments fragments corresponding to the individual TMDs were studied by CD, IR and NMR spectroscopy in trifluoroethanol (TFE)/water mixtures(19). In three of these domains the α-helices were disrupted by a kink centered around a Pro residue in the case of the sixth and seventh TMDs, and around two Gly residues in the case of first TMD. The solubility of constructs corresponding to the third and fourth TMDs was very low, such that they could not be effectively purified by HPLC, requiring addition of several lysine residues at both termini of the peptides(23). Furthermore, the sixth TMD of Ste2p displayed a high tendency for aggregation on SDS-PAGE(16). To minimize sample preparation problems and spectroscopic difficulties resulting from poor solubility we envisaged synthesizing constructs of the receptor in which appreciable parts of the hydrophilic cytosolic domain were added to the hydrophobic seventh TMD. (18) Inaddition to increasing solubility, the cytosolic extension may aid in folding of the construct, and information on its structure could be relevant to its biological role in signal transduction and regulation.For convenient production of this larger domain we have chosen a recombinant approach in E. coli. The presently described polypeptide is composed of 9 residues of the third extracellular loop (EL3, Ste2p residues 267-275), 24 residues comprising the putative seventh transmembrane domain (TM7, Ste2p residues 276-299) and 40 residues of the cytosolic carboxy-terminus (CT40, Ste2p residues 300-339) of the Ste2p receptor (residues 1-9, 10-33 and 34-73 of EL3-TM7-CT40 respectively, Fig. 1). The desired 73-residue TMD peptide was expressed as a TrpΔLE fusion protein and liberated from its fusion partner using cyanogen bromide cleavage (20). The recombinant method facilitated expression of EL3-TM7-CT40 in uniformly 15N or 15N, 13C labeled forms required for triple-resonance NMR spectroscopy. Recently we demonstrated that upon addition of 15N-labeled amino acids to rich growth media, peptide selectively labeled with Ala, Ser or Leu residues with acceptable percentages of isotope cross-labeling(24) were produced.Herein we report data on the structure and internal backbone dynamics of the multi-domain peptide EL3-TM7-T40 in dodecylphosphocholine (DPC) micelles. The 1H, 13C and 15N resonances could be assigned to a very large extent. The computed structure, based onrestraints from NOESY experiments, reveals the presence of an α-helix in the segment 10-30, corresponding to residues 276-296 of the Ste2p receptor, that is disrupted around the internal Pro residue. The internal backbone dynamics derived from 15N relaxation data support the view that the TM part of EL3-TM7-CT40 is rather stably folded, whereas the cytosolic part is much more flexible. Micelle-integrating spin labels support the conclusion that the TM7 helix integrates into DPC micelles, but also demonstrate that motion around the internal Pro site partially brings residues, that would be deeply buried in the micelle interior, closer to the detergent headgroups. The C-terminal decapeptide of the polypeptide is unstructured, but large segments (e.g. from residues 43 to 58) with significant propensity for adopting helical conformations exist. The micelle insertion/association topology of the peptide is fully supported by our understanding of amino acid partitioning into the membrane interior or the membrane-water interface. These studies further validate the approach of using fragments of GPCRs as surrogates to probe receptor structure.Materials and Methods NMR sample preparationPerdeuterated d38-DPC, perdeuterated MES and deuterated water were purchasedfrom CAMBRIDGE ISOTOPES. The spin labels 5- and 16-doxylstearates were obtained from SIGMA-ALDRICH and Gd-DOTA (DOTAREM ) from LABORATOIRE GUERBET. All other chemical used were ordered from FLUKA.For preparation of the 0.5mM EL3-TM7-CT40 NMR sample 26.4mg d38-DPC and1mg of peptide were dissolved together in approximately 1 ml of hexafluoro-i-propanol (HFIP), the solution was sonicated for 10 min at 50°C and subsequently lyophilized until an oily residue (12-15hrs) remained. This mixture was dissolved in 250µl of 20mM MES (2-morpholinoethanesulfonic acid, monohydrate) buffer (pH ~ 6), 750µl of water were added and the solution was lyophilized until dryness again. The lyophilized powder consisting ofDPC and the peptide was dissolved in 250µl H2O:D2O (9:1), mixed by vortexing until all ofthe solid material is dissolved, incubated for 15 minutes at 37 ºC and transferred to a shigemiNMR tube. The final concentration of d38-DPC was always 300mM. The E3-M7-T40concentration used for the 13C and 15N-resolved NOESY spectra was 0.5mM, for supporting experiments (e.g. relaxation, spin-label studies etc.) concentrations of 0.1-0.4mM were used. Samples used for the residual dipolar couplings (RDCs) measurements contained EL3-TM7-CT40 and d38-DPC at concentrations of 0.25mM and 200mM, respectively. All NMRmeasurements were conducted on a Bruker AV700 spectrometer at 310K using a triple-resonance cryoprobe.For the RDC measurements the peptide-micelle complex was oriented in a stretched polyacrylamide gel (25,26). The gel was polymerized from a 4% (w/v) solution of acrylamide and bisacrylamide with a monomer to cross-linker ratio of 37.5:1 (w/w). The dry gel was soaked for 24 h in plain buffer followed by equilibration with a solution of 15N-labelled EL3-TM7-CT40/d38-DPC for 48 h, after which the gel was compressed from 6mm to a final diameter of 4 mm.Spin label experiments were performed using 5-doxyl stearic acid, 16-doxyl stearic acid or Gd-DOTA in separate experiments. Small aliquots of concentrated solutions of 5- or16-doxylstearate in d3-methanol were dissolved in the solution of the 15N-E3-M7-T40/d38-DPC sample to obtain a final concentration of approximately 7mM of spin label corresponding to slightly more than one spin-label per micelle. In case of the experiment utilizing Gd-DOTA an appropriate volume of a 5mM aqueous solution of Gd-DOTA was lyophilized and the remaining powder mixed with the detergent solution of the peptide resulting in a Gd-DOTA concentration of about 6 mM. [15N,1H]–HSQC spectra in the presence and absence of spin labels were recorded and attenuations were computed from the relative peak volumes in these experiments. In cases of overlap peak intensities were used instead of peak volumes and severely or completely overlapped residues were generally excluded from the analysis. In all cases, the relative intensity of residue i was computed from the average of residues i-1, i and i+1, whenever this was possible, to reduce the extent of smaller fluctuations.Cloning, expression and purification of 15N,13C-labeled EL3-TM7-CT40The cloning, expression, and isolation of [13C/15N]-EL3-TM7-CT40 {S1LKPN QGTDV L11TTVA TLLAV L21SLPL SSLWA T31AANN ASKTN T41ITSD FTTST D51RFYP GTLSS F61QTDS INNDA K71SS}were carried out using procedures described in the literature (20).EL3-TM7-CT40 selectively labelled with [15N]-alanine, [15N]-leucine or [15N]-serine was prepared in rich medium containing excess of the [15N]-labelled amino acid as described by Englander et al (24).NMR spectroscopySequence-specific resonance assignment was accomplished based on a set of 15N-resolved proton-proton correlation spectra, e.g. a 40ms 15N-resolved TOCSY and 75ms 15N-resolved NOESY(27,28), as well as a set of triple-resonance experiments. Backbone assignment was performed based on a CBCA(CO)NH(29) (1024*40(15N)*128(13C) complex data points; t 3max 122ms, t 2max 12.8ms, t 1max 6.1ms), a HNCACB experiment(30) (1024*64(15N)*128(13C) complex data points; t 3max 122ms, t 2max 20.5, t 1max 6.1ms), and a H(CCC)(CO)NH(31) experiment (1024*20(15N)*64(13C) complex data points; t 3max 127ms, t 2max 10.9, t 1max 8.0ms). Sidechain resonances were assigned based on HCCH-TOCSY experiments (1024*32*64 complex points, t 3max 104ms, t 2max 7.9ms, t 1max 9.1ms)(32,33) using a B 1 field of 8.3 kHz for the TOCSY spin-lock as well as from a 70ms 13C-resolved NOESY experiment. The aromatic ring systems were correlated with β-carbons via the HBCBCGCDHD and HBCBCGCDCEHE experiments introduced by Kay(34). Assignment within the aromatic moieties was done using a 23 ms constant-time HMQC-TOCSY experiment(35), in which the proton TOCSY relay was tuned for direct (12ms) and relayed (40ms) transfer. Chemical shifts were finally picked in the [15N,1H]-HSQC and the 13.3ms constant-time [13C,1H]-HSQC spectra and indirectly referenced to the water line at 4.63 ppm using the conversion factors of 0.10132900 (15N) and 0.25144954 (13C)(36). All experiments employed pulsed-field gradients.The extent of amide hydrogen exchange was probed by recording a [15N,1H]-HSQC experiment, in which low-power irradiation was applied on the water resonance during the relaxation delay. Peak volumes were determined in this experiment and their values relative to a reference experiment conducted in the absence of irradiation but with otherwise identical parameter computed. 15N-Relaxation data were recorded using proton detected version of the 15N{1H} steady-state NOE experiment(37). A recycle delay of 2.7 s was used for the 15N{1H} NOE experiment and 128 scans were recorded per increment.Data were usually extend by a factor of two using linear-prediction in the indirect dimensions and processed within the Bruker spectrometer software TOPSPIN 1.3. Integration of peak volumes was performed within the program SPSCAN. 3J HN α scalar coupling constants were derived from the splitting of the in-phase doublets of [15N,1H]-HSQC peaks using the INFIT algorithm(38) in XEASY(39). Processed data were transferred into the program CARA for data analysis(40).Structure calculationDistance restraints were obtained from NOESY spectra recorded with a mixing time of 70 ms either in 90% H 2O/10% 2H 2O (15N-resolved NOESY) or in 99.9% 2H 2O(13C-resolved NOESY). In addition dihedral angle restraints were derived from TALOS(41) using 13C chemical shifts of C α and C β atoms, and further such restraints were added by the CANDID/ATNOS suite of programs. Structures were calculated using a simulated-annealing protocol for molecular dynamics in torsion angle space as implemented in the program CYANA(42,43). The final CYANA calculation was performed with 100 randomized starting structures, and the 20 CYANA conformers with the lowest target function values were selected to present the NMR ensemble. The conformers were analyzed, including calculation of RMSD values, and figures were prepared within the program MOLMOL(44).ResultsSample preparationDirect dissolution of EL3-TM7-CT40 in DPC solution resulted in poor quality [15N,1H]-HSQC spectra with little signal, indicating that the peptide was not properly inserted into the micelle. Therefore, the protocol developed by Killian et al.(45) was applied, in which the peptide was dissolved in a 50:50 (v/v) mixture of hexafluoro-i -propanol (HFIP)/water followed by dilution into micellar solution, lyophilization and redissolving in pure water. A sample prepared by this protocol resulted in moderate quality [15N,1H]-HSQC spectra in which approximately 60 out of the 70 expected backbone resonance peaks were visible. We subsequently modified the protocol to include two steps of lyophilization. The peptide and DPC were initially dissolved in HFIP and lyophilized until an oily residue remained. The latter was taken up in aqueous buffer and thoroughly lyophilized to complete dryness to eliminate residual HFIP. Following this procedure reproducible [15N,1H]-HSQC spectra containing the expected 70 peaks could be measured (Fig. 2), indicating that the EL3-TM7-CT40 was well-integrated into the DPC micelles. Such samples were sufficiently stable for measurement of 3D and 4D NMR spectra at 310K, and only displayed indications of additional peaks after more than 2 weeks. At that time a spectrum with the original quality could be recovered when the sample was lyophilized and redissolved, but after 3-4 weeks additional signals due to degradation appeared.Resonance assignmentSequence specific sequential resonance assignment of EL3-TM7-CT40 was accomplished by triple-resonance NMR spectroscopy using uniformly 13C,15N and 15N uniformly labelled samples. Data evaluation was performed using the recently developed program CARA(40). For backbone assignment 3D HNCACB(30) and CBCA(CO)NH(29) spectra provided the most useful information. In the [15N, 1H]-HSQC spectra we were able to observe over 60 cross-peaks, for which intra- and/or interresidual C α and C β cross-peaks occurred in the HNCACB and CBCA(CO)NH spectra. For the remaining 10 cross-peaks in the [15N, 1H]-HSQC either one or several resonances were missing in the corresponding strips from the HNCACB or CBCA(CO)NH spectra. The unique chemical shifts observed for Gly and Ala residues provided starting points in the assignment process. A set of strips corresponding to the assignment of residues Ala15 to Val20 of the TM segment is depicted in Fig. 3 and the completely assigned [15N, 1H]-HSQC spectrum is shown is Fig. 2. Additionally we recorded [15N, 1H]-HSQC spectra on samples of the peptide that were selectively labeled by Ala, Ser and Leu (see Fig. 4). These data served to confirm the position of corresponding residues in the [15N, 1H]-HSQC spectra despite some cross-labeling of Ile42 and Ile66 (Fig.4). Cross peaks from Leu2 and Leu25 could not be found. We experienced significant difficulties in making assignments for residues 21 to 28 and 46 to 51. Due to a lack of correlations in the triple resonance spectra no assignments of 1H and 15N resonances corresponding to Leu2 and Thr50 could be obtained. In order to provide an additional check for resonance assignments, which uses further information from the type of side-chain spin systems, we also recorded an H(CCC)(CO)NH experiment(31).H α/C α cross-peaks from the backbone assignment were subsequently used as anchoring points for further assignment of the aliphatic side chains. Most likely due to short T2 relaxation times of many C α and C β resonances the HCCH-TOCSY spectra(32,33) were unfortunately of moderate quality only, and we were forced to make extensive use of 15N-resolved TOCSY and NOESY and 13C-resolved NOESY spectra to complete the assignment.In order to accomplish assignment of aromatic side-chains, two-dimensional versions of the (HB)CB(CGCD)HD and (HB)CB(CGCDCE)HE experiments(34) were recorded. Assignments of aromatic protons were completed and verified by data from a [1H,1H]-TOCSY relayed constant-time [13C,1H]-HMQC experiment(35) and a 13C-resolved NOESY centered at the aromatic carbons. The chemical shifts of all assigned 1H, 13C and 15N nuclei are listed in the supplementary material. The completeness of the backbone and side chain assignments was over 90% for all resonances. Assignment of labile protons from sidechains of Asp, Asn, Gln, Glu, Arg, Lys was generally not possible.Determination of the structure of EL3-TM7-CT40The structure of EL3-TM7-CT40 was determined by solution NMR methods using uniformly 13C, 15N or 15N labeled 0.5mM peptide in the presence of 300mM DPC at pH 6.0. The final structure calculations utilized a total of 1018 meaningful NOE upper distance constraints, and 46 angle constraints for the backbone dihedral angles derived from C α chemical shifts and from 3J HN α scalar couplings. A graphical representation of the restraints used in the structure calculation is presented in Fig. 5. Characteristic medium-range H α,β(i,i+3) NOEs have been observed in the region 10 to 21 and 29-34. The average CYANA target function value obtained was 1.01 ± 0.10 Å indicating the presence of only a few minor violations, the average backbone RMSD to the mean coordinates was 11.80 ± 1.74 Å, and no systematic distance constraint violations remained.The ensemble of low-energy NMR conformations is depicted in Fig. 6 and displays two helices in the putative TM region of the polypeptide. When individually superimposing backbone atoms from these helical segments the RMSD values are 0.91 ± 0.33 Å and 0.76 ± 0.37 Å for residues 10 to 20 and 25-30, respectively. A calculation of secondary structure according to the Kabsch-Sander algorithm(46) reveals that the first α-helix extends from residues 10 to 22 in 13 of the 20 lowest energy conformers, and of the remaining conformers, 7 possessed a helix C-terminally extended by 1-4 residues. The second α-helix extends from residues 25 to 30 in 9 of the 20 conformers, 5 conformers display helices C-terminally extended by 1-2 residues helix and the remaining ones present less regular helical fragments for residues 25 to 38. Among the low energy conformers one is found with an α-helix encompassing residues 11 to 33, but generally the region 23-27 is poorly defined. Hydrogen bonds between carbonyl oxygen atoms of residue i and amide hydrogen atoms of residue i+4 are observed in more than 50% of the cases in the segments 10 to 22 and 25 to 36. Considering that residues 23-27 exhibited only weak cross-peaks in the [15N,1H]-HSQC spectrum and that only a few correlations in the corresponding 3D NOESY spectrum were detected, we suspect that this region undergoes slow conformational exchange corresponding to a kink motion of the two helices with respect to each other (vide infra ). The helical nature of residues 10 to 20 computed from NOEs are supported by lowered values of the scalar coupling constants 3J HN α in this segment of EL3-TM7-CT40 (Fig. 5), and a few couplings below 6 Hz are additionally observed in the segment 27 to 33. In contrast to the putative TM region of the peptide, no elements of regular secondary structure were observed within the CT part throughout all conformers, but 2 conformers possessed backbone dihedral angles corresponding to an α-helix for residues 46 to 48, one conformer exhibited such dihedral angles for residues 55 to 57 and one for residues 60 to 62. We additionally noticed significantly lowered values for the 3J HN α coupling constants for most residues in the segment comprising residues 44 to 60. However, we have only observed a few α,N (i,i+2) NOEs and only a single α,β (i,i+3) NOE. The fact that NOEs between sequential amide protons are measured throughout this part of EL3-TM7-CT40, but only a few medium-range NOEs couldbe detected indicates the presence of transient helical conformations with considerable residual flexibility. Considering that also the values for the 15N{1H}-NOE are reduced to about 0.4 to 0.55 in that segment (vide infra), we conclude that strong preference for helical conformations exists in that part, but that the persistence of helix conformations is low, similar to what has been referred to in literature as a nascent helix (47). We suspect that structure in the cytosolic segment is controlled by partitioning of residues into the water-micelle interface (vide infra). When superimposing residues 33 to 73 the RMSD of the backbone atoms is 9.87 ± 2.61 Å indicating high flexibility of this part of the molecule.In order to further characterize to which extent parts of the polypeptide chain are structured we have measured residual dipolar couplings (RDCs) in stretched polyacrylamide gels. The data are depicted in Fig. 7 and reveal that the RDCs are comparably small, indicating that scaling due to motion occurs. Two segments with increased absolute values (> 1Hz) are observed between residues 10 and 20 and between residues 44 and 53. In other regions the values are below 1 Hz indicating extensive motional averaging.To further investigate to which extent amide protons were protected from solvent exchange we measured reductions in amide proton intensities due to saturation transfer in an [15N,1H]-HSQC spectrum where the water line was saturated by low-power irradiation during the relaxation delay. Markedly reduced saturation transfer (>70% remaining peak intensity) was observed in the segment 10 to 30 while rapid exchange was found at the termini of thepeptide as well as in the region Asn34 to Thr41 (Fig. 8). Reduced 3JHNαand amide protonexchange rates are also observed for residues 44 to 61 supporting the view that this segment is partially structured.Dynamics of TM7 as derived from 15N relaxation:It has been generally recognized that less well-defined regions of protein structures computed from NMR solution data may be due to either the intrinsic flexibility of the backbone in that particular segment or to an insufficient number of resolved and assigned NOEs, thereby preventing convergence of structure calculations towards a particular conformation. The determination of internal backbone dynamics in principle can be used to distinguish the two cases. In particular, values of the 15N{1H}-NOE allow discrimination between well-structured regions of the protein chain from those that display flexibility.The values of the heteronuclear NOE are depicted in Fig. 9. High values (> 0.6) are usually observed in elements of secondary structure as well as in rather rigid short loops. In TM7 only the segment encompassing residues Val10 to Trp29 fall into this category. The values around Pro24 in this segment are significantly reduced. A second region of relatively high values NOE (>0.5) values can be found in the segment comprising the putative cytosolic residues Asp51 to Ser59. From residue Gln62 to the C-terminus of the peptide the values of the NOE steadily decrease and adopt (large) negative values towards the termini indicating that the last 10 residues of CT freely diffuses in solution. Residues preceding the putative transmembrane helix (Asp9-Ser1) also exhibit increasingly low values. Thus, based on heteronuclear NOEs both termini are rather flexible.Orientation and Membrane Integration Topology:Tools from bioinformatics such as secondary structure prediction based on position-specific scoring matrices (48,49) predicted the segments Asp9 to Ser22 and Pro24 to Ala32 to。
Accepted Manuscript
polyedrum (Draisci et al., 1999) and Gonyaulax spinifera (Rhodes et al., 2006). In recent
(FAO/IOC/WHO, 2004; Amzil et al., 2008). YTXs may contribute significantly to the outcome of the traditional mouse bioassay for DSP toxins when injected intraperitoneally (i.p.). However, the mechanisms of action of OA/DTXs and YTXs are different, since it has
Accepted Manuscript
Title: Combined oral toxicity of azaspiracid-1 and yessotoxin in female NMRI mice Authors: John A.B. Aasen, Arild Espenes, Christopher O. Miles, Ingunn A. Samdal, Philipp Hess, Tore Aune PII: DOI: Reference: To appear in: S0041-0101(11)00100-0 10.1016/j.toxicon.2011.03.014 TOXCON 4078 Toxicon
the oral toxicity of YTX is not enhanced in the presence of sub-lethal levels of AZA1.
AC C
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preference to manuscripts -回复
preference to manuscripts -回复"Preference to Manuscripts: The Art of Handwritten Wisdom"Introduction:In today's digital age, where typing on keyboards and swiping on touchscreens prevail, the preference for manuscripts seems to have been overshadowed. However, there is a certain charm, a unique essence that emanates from handwritten manuscripts that cannot be replicated by any electronic means. In this article, we will delve into the reasons behind the preference for manuscripts and explore the intricate art of handwritten wisdom.Section 1: Rediscovering the Elegance and Intimacy of Manuscripts1.1. Historical Significance: Manuscripts have played a significant role throughout history, serving as the primary means of recording and preserving knowledge. From ancient scrolls to meticulously crafted medieval manuscripts, these handwritten treasures offer glimpses into the past and connect us to our cultural heritage.1.2. Personal Touch: Handwriting holds a personal touch thatbreathes life into words. The unique strokes, curves, and nuances reflect the individuality of the writer, allowing for a more intimate connection between the author and the reader. The imperfections and idiosyncrasies contained within each line make manuscripts a deeply personal and cherished form of communication.1.3. Mindful Process: Engaging in the act of writing by hand requires a deliberate and conscious effort. It encourages focus, patience, and a connection with the words being written. This mindful process allows for a deeper connection to the content and enhances both the writer's and reader's intellectual and emotional experience.Section 2: The Artistry of Handwritten Wisdom2.1. Calligraphy: Manuscripts often showcase the exquisite art of calligraphy. Calligraphers meticulously design each stroke, carefully balancing form and aesthetics. The elegant curves, smoothness of ink, and attention to detail create a harmonious symphony that transforms words into visual art.2.2. Illumination: Many manuscripts feature intricate illuminationsthat embellish the text. These richly colored and elaborately designed decorations add depth and beauty to the words, enhancing the overall visual experience. Illuminations provide insights into the cultural and artistic influences of the time, truly making each manuscript a work of art.2.3. Materiality: Unlike digital texts that exist solely in virtual space, manuscripts have a tangible presence. The texture of the paper, the weight of the book, and the smell of the ink all contribute to the sensory experience. The physicality of manuscripts engages our senses, creating a more immersive and memorable encounter.Section 3: Preserving the Tradition and the Future3.1. Cultural Heritage: Manuscripts are invaluable artifacts that preserve our collective cultural heritage. They hold the stories and wisdom of past civilizations, offering us a window into their thoughts, beliefs, and discoveries. By preserving and appreciating manuscripts, we maintain a vital connection to our history.3.2. Slow and Deliberate Reading: Unlike the fast-paced nature of digital reading, manuscripts encourage slow and deliberatereading. Each word and sentence is given the attention it deserves, fostering a deep understanding and contemplation of the text. This unhurried approach can lead to enhanced comprehension and appreciation of the subject matter.3.3. Integration with Technology: Manuscripts and technology need not be mutually exclusive. In an era where digitization is prevalent, efforts to digitize manuscripts have allowed for wider accessibility and preservation of these invaluable documents. The digital realm can provide platforms for showcasing and studying manuscripts, complementing their physical existence.Conclusion:While the world may be shifting towards digital mediums, the preference for manuscripts endures. The elegance, intimacy, and artistry of handwritten wisdom continue to captivate individuals who appreciate the depth and authenticity that manuscripts offer. By embracing this centuries-old tradition and integrating it with modern technology, we can ensure that the treasure trove of handwritten wisdom remains accessible and cherished forgenerations to come.。
RT-PCR实验完整版(英文)
肩袖损伤的研究进展
肩袖损伤的研究进展发布时间：2021-01-07T11:13:16.533Z 来源：《中国医学人文》2020年24期作者：谢树林,卢宽，杨珂，杨文彬[导读] 随着我国老年人口数量不断增加，老年人长期劳累损伤及参加健身运动损伤越来越多谢树林,卢宽，杨珂，杨文彬安徽蒙城县第一人民医院骨二科，安徽蒙城县，233500【摘要】：随着我国老年人口数量不断增加，老年人长期劳累损伤及参加健身运动损伤越来越多，肩关节疼痛的发生也越来越多，其中大部分是肩袖损伤[1]。
据文献报道[1-3]，肩袖损伤在肩部疾病中约占60%左右。
肩袖全层撕裂在60岁以下发生率最低，约6%，60岁以上达25%，70岁以上就更高了，可达75%，超过一半的80岁人群有肩袖撕裂。
鉴于肩袖损伤的发生率越来越高，本文将从肩袖解剖、损伤原因、病理生理及治疗对肩袖损伤做一综述，以利于人们对肩袖疾病有更深入的认识。
【关键词】：肩袖损伤；损伤原因；病理生理；治疗Research progress of rotator cuff injuryXie Shulin, Lu Kuan， Yang Ke，Yang WenbinAbstract: with the continuous increase of the elderly population in China, there are more and more long-term fatigue injuries and fitness sports injuries of the elderly, and the occurrence of shoulder pain is also increasing, most of which are rotator cuff injuries[1]. According to literature reports[1-3], rotator cuff injuries account for about 60% of shoulder diseases. The incidence of full-thickness rotator cuff tears is the lowest under 60 years old, about 6% of people over 60 years old and 25% of people over 70 years old are even higher, up to 75%, and more than half of 80-year-olds have rotator cuff tears. In view of the increasing incidence of rotator cuff injury, this article will review the rotator cuff injury from the rotator cuff anatomy, injury causes, pathophysiology and treatment, in order to facilitate people to have a better understanding of rotator cuff diseases.Key words: Rotator cuff tear；Cause of injury； pathophysiology ； treatment1、肩袖的解剖肩袖别名旋转袖，呈袖套样，是包绕肱骨头周围的肌腱复合体，由冈上肌、冈下肌、小圆肌和肩胛下肌围着肱骨大结节与肱骨小结节共同组成。
核磁管清洗新方法
Subscriber access provided by Maastricht University Library CommunicationVacuum Desiccator as a Simple, Robust and Inexpensive NMR Tube CleanerThanh Binh NguyenOrg. Process Res. Dev., Just Accepted Manuscript • DOI: 10.1021/acs.oprd.6b00001 • Publication Date (Web): 06 Jan 2016Downloaded from on January 11, 2016Just Accepted“Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are postedonline prior to technical editing, formatting for publication and author proofing. The American ChemicalSociety provides “Just Accepted” as a free service to the research community to expedite thedissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscriptsappear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have beenfully peer reviewed, but should not be considered the official version of record. They are accessible to allreaders and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offeredto authors. Therefore, the “Just Accepted” Web site may not include all articles that will be publishedin the journal. After a manuscript is technically edited and formatted, it will be removed from the “JustAccepted” Web site and published as an ASAP article. Note that technical editing may introduce minorchanges to the manuscript text and/or graphics which could affect content, and all legal disclaimersand ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errorsor consequences arising from the use of information contained in these “Just Accepted” manuscripts.Vacuum Desiccator as a Simple, Robust and Inexpensive NMR Tube Cleaner Thanh Binh Nguyen* Institut de Chimie des Substances Naturelles - CNRS-ICSN UPR 2301, Université Paris-Sud, 1 avenue de la Terrase, 91198 Gif-sur-Yvette Cedex (France)Page 1 of 6Organic Process Research & Development 12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758Table of Contents GraphicPage 2 of 6Organic Process Research & Development 12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758Abstract: A simple, robust and inexpensive apparatus for cleaning several NMR tubes is easily fit up and used from readily available glasswares, including a beaker, a desiccator and a rotary evaporator vacuum pump. Keywords: NMR tube cleaner, high-throughput screening, vacuum desiccatorPage 3 of 6Organic Process Research & Development 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657581. INTRODUCTIONAs part of our everyday work on the finding and optimization of new reactions, we were struck by the need for an effective method to clean rapidly several NMR tubes in a convenient manner with as little as solvent as possible from readily available labwares. Commercially available glasswares for this purpose are expensive, fragile, solvent consuming, not easy to handle, and more importantly, not suitable for cleaning many tubes at once. Solutions for these drawbacks have been proposed,1 but none of them fulfills all the above-mentioned requirements. We present here a simple way to deal with this task. All we need is a vauum desiccator, a beaker that can fit inside the desiccator and a rotary evaporator vacuum pump.2. MATERIALS AND METHODSThe operating instructions are presented in Scheme 1.First, NMR tubes to be wash are emptied and put upside down inside a beaker (step A). Cleaning solvent or solution (acetone, methanol, ethanol, water, nitric acid, aqueous NaOH solution...) is next added to the beaker (about 4 mL for each tube). The beaker is put inside the vacuum desiccator (step B). A vacuum is subsequently applied to the system to remove air inside the tubes. The desiccator is next vented with air and solvent will raise and clean inside the tubes. The vacuum/air vent cycle is repeated 3-4 times to remove all the air inside the tubes. The whole system can be left one night for better results. Sonication of the beaker can also be performed if necessary as an aid to cleaning (step C). New solvent is changed and the cleaning is finished with clean acetone (step D). This acetone can be used for the next time of cleaning. The number of NMR tubes that can be cleaned at once depends only on the size of the beaker and the desiccator. Caution: the desiccator should be opened in fume hoods. It is also recommended that the usual Page 4 of 6Organic Process Research & Development 12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758precautions (goggles, gloves, etc.) are taken. The NMR tubes can also be placed directly in the desiccator. Scheme 1. NMR tube cleaner 3. CONCLUSION In this communication we present a simple and easy-to-use cleaning setup for several NMR tubes at once from a vacuum desiccator, a rotary evaporator vacuum pump and/or a beaker. We strongly believe that this apparatus will be useful for organic chemists, especially for those whowork on high-throughput screening.Page 5 of 6Organic Process Research & Development 12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758AUTHOR INFORMATIONCorresponding AuthorThanh Binh Nguyen*nguyen@rs-gif.frInstitut de Chimie des Substances Naturelles - CNRS-ICSN UPR 2301, Université Paris-Sud, 1 avenue de la Terrase, 91198 Gif-sur-Yvette Cedex (France)REFERENCES1 (a) Landrie, C. L.; Marszalek, R. J. Chem. Educ.2011, 88, 1734. (b) Zhang, B.; Hodgson, J.; Hancock, W.; Powers, R. Anal Biochem.2011, 416, 234. (c) Mastbrook, D. W.; Hansen, E.. A. Applied Spectroscopy1970, 24, 612. Page 6 of 6Organic Process Research & Development 12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758。
基于改进YOLOX的移动机器人目标跟随方法
基于改进YOLOX 的移动机器人目标跟随方法万 琴 1, 2李 智 1李伊康 1葛 柱 1王耀南 2, 3吴 迪1摘 要 针对移动机器人在复杂场景中难以稳定跟随目标的问题, 提出基于改进YOLOX 的移动机器人目标跟随方法, 主要包括目标检测、目标跟踪以及目标跟随三个部分. 首先, 以 YOLOX 网络为基础, 在其框架下将主干网络采用轻量化网络 MobileNetV2X, 提高复杂场景中目标检测的实时性. 然后, 通过改进的卡尔曼滤波器获取目标跟踪状态并采用数据关联进行目标匹配, 同时通过深度直方图判定目标发生遮挡后, 采用深度概率信息约束及最大后验概率(Maximum a posteri-ori, MAP)进行匹配跟踪, 确保机器人在遮挡情况下稳定跟踪目标. 再采用基于视觉伺服控制的目标跟随算法, 当跟踪目标丢失时, 引入重识别特征主动搜寻目标实现目标跟随. 最后, 在公开数据集上与具有代表性的目标跟随方法进行了定性和定量实验, 同时在真实场景中完成了移动机器人目标跟随实验, 实验结果均验证了所提方法具有较好的鲁棒性和实时性.关键词 移动机器人, YOLOX, 重识别, 目标跟随引用格式 万琴, 李智, 李伊康, 葛柱, 王耀南, 吴迪. 基于改进YOLOX 的移动机器人目标跟随方法. 自动化学报, 2023,49(7): 1558−1572DOI 10.16383/j.aas.c220344Target Following Method of Mobile Robot Based on Improved YOLOXWAN Qin 1, 2 LI Zhi 1 LI Yi-Kang 1 GE Zhu 1 WANG Yao-Nan 2, 3 WU Di 1Abstract A target following method of mobile robot based on improved YOLOX is proposed to solve the problem that mobile robots are difficult to follow the target stably in complex scene. This method mainly includes three parts: Target detection, target tracking and target following. Firstly, the lightweight MobileNetV2X network is ad-opted under the YOLOX framework to improve the real-time performance of target detection in complex scene.Then, the improved Kalman filter is proposed to obtain the tracking state and data association is used for target matching. When the target is judged by depth-histogram, the depth probability constraint and maximum a posteri-ori (MAP) probability are utilized for matching, which ensure that the robot tracks the target stably under occlu-sion. Moreover, target-following algorithm based on servo control is proposed, and re-id feature is introduced to act-ively search for disappeared targets. Finally, qualitative and quantitative experiments on public data set and in real-world environments demonstrate the efficiency of the proposed method.Key words Mobile robot, YOLOX, re-id, target followingCitation Wan Qin, Li Zhi, Li Yi-Kang, Ge Zhu, Wang Yao-Nan, Wu Di. Target following method of mobile robot based on improved YOLOX. Acta Automatica Sinica , 2023, 49(7): 1558−1572移动机器人在安防、物流和医疗等领域应用广泛[1−2], 其中机器人目标跟随算法引起了广泛关注,但移动机器人目标跟随算法的鲁棒性和实时性仍是亟待解决的关键问题[3−4].机器人目标跟随算法分为生成式模型方法和检测跟踪方法两大类[5−6]. 生成式模型主要通过构建目标模型实现跟随, 如Yoshimi 等[7]利用视觉传感器获取行人颜色和纹理特征, 机器人在视野范围内寻找与之相匹配的区域, 融合行人与位置速度信息构建模型, 采用基于生成式的目标跟踪算法跟随行人.然而, 此类算法关注目标本身, 忽略背景信息, 经常出现跟踪丢失的情况.为同时考虑目标与背景信息, 检测跟踪方法得收稿日期 2022-04-27 录用日期 2022-09-26Manuscript received April 27, 2022; accepted September 26,2022国家自然科学基金 (62006075), 湖南省自然科学杰出青年基金(2021JJ10002), 湖南省重点研发计划(2021GK2024), 湖南省教育厅重点项目(21A 0460), 湖南省自然科学基金面上项目(2020JJ4246, 2022JJ30198)资助Supported by National Natural Science Foundation of China (62006075), Foundation Project for Distinguished Young Schol-ars of Hunan Province (2021JJ10002), Key Research and Devel-opment Projects of Hunan Province (2021GK2024), Key Projects of Hunan Provincial Department of Education (21A0460), and General Project of Hunan Natural Science Foundation (2020JJ 4246, 2022JJ30198)本文责任编委 程龙Recommended by Associate Editor CHENG Long1. 湖南工程学院电气与信息工程学院 湘潭 4111042. 湖南大学机器人视觉感知与控制技术国家工程研究中心 长沙 4100823. 湖南大学电气与信息工程学院 长沙 4100821. College of Electrical and Information Engineering, Hunan Institute of Engineering, Xiangtan 4111042. National Engin-eering Research Center for Robot Visual Perception and Control Technology, Hunan University, Changsha 4100823. College ofElectrical and Information Engineering, Hunan University,Changsha 410082第 49 卷 第 7 期自 动 化 学 报Vol. 49, No. 72023 年 7 月ACTA AUTOMATICA SINICAJuly, 2023到了越来越多的关注, 此方法通过构建分类器区分目标及背景, 其跟踪效果普遍优于生成式模型方法.余铎等[3] 通过快速判别尺度空间切换相关滤波算法与卡尔曼滤波算法实现稳定跟踪. 另外, 移动机器人在跟随控制过程中常受到背景杂斑、光照变化、目标遮挡、尺度变化等干扰, 导致跟随目标丢失. 因此传统的检测跟踪方法不适用于移动机器人在复杂多变场景中的目标跟随[2].基于深度学习的移动机器人目标跟随算法具有鲁棒性强等优势[8]. Zhang等[9] 通过基于目标轮廓带采样策略来提高移动机器人跟踪性能, 但未对遮挡、行人消失等情况进行处理. Pang等[10] 提出一种基于深度学习的目标检测器, 引入卡尔曼滤波来预测目标位置, 加入重识别模块处理遮挡问题, 但此类算法需先获取精度较高的目标检测结果. 鉴于上述问题, JDE (Jointly learns the detector and em-bedding model)检测模型可用来融合重识别与检测分支[11], 提高目标检测精度. YOLO (You only look once) 系列算法则是一类基于JDE检测模型的一阶段框下的目标检测算法, 具有高效、灵活和泛化性能好的优点.YOLO算法包括了YOLOV1 ~ YOLOV7系列算法以及一系列基于改进YOLO的目标检测算法. Redmon等[12] 提出YOLO算法进行目标检测,直接采用回归的方法进行坐标框的检测以及分类,使用一个端到端的简单网络实现坐标回归与分类,能够极大地提升目标的检测速度. 此后, YOLO的网络结构不断优化, 已经成为目标检测领域主流的算法. Hsu等[13]引入比率感知机制, 动态调整YOLOV3的输入层长度和宽度超参数, 从而解决了长宽比差异较大的问题, 能够有效地提高平均跟踪精度. Huang等[14] 引入改进的YOLOV3模型, 此模型将预测尺度从3个增加到4个, 并使用额外的特征图来提取更多的细节. YOLOV3的目标位置识别精度较差, 在目标分布密集、尺寸差异较大的复杂场景中, 检测效果较差. YOLOV4[15] 开发了Darknet53目标检测模型, 此模型具有更高的网络输入分辨率,网络层参数多, 计算复杂度高, 对小目标检测效果较差. 对此, YOLO-Z[16] 提出了一系列不同尺度的模型, 提高YOLOV5检测小目标的性能. Cheng等[17]提出一种单阶段SSD (Single shot multibox de-tector) 微小目标检测方法, 此方法可提高微小目标检测的实时性, 但其使用的两阶段式目标检测器使目标定位精度有所下降. YOLOV6[18]设计了更高效的主干网络和网络层. YOLOV7[19]扩展了高效长程注意力网络, 加入了基于级联的模型缩放方法,均可一定程度提高检测精度和推理效率, 但由于未引入重识别分支, 无法提取浅层特征用于后续跟踪. YOLOX[20]在YOLO系列的基础上做出了一系列改进, 相比于YOLO系列目标检测算法, 其最大的不同是采用了无锚框检测器. 而YOLOV1 ~ YOLOV5采用有锚框的检测器, 由于可能会被多个锚框同时检测且与检测框中心存在误差, 并不适用于JDE 检测模型. 因此, 采用无锚框的YOLOX目标检测算法更加适合于JDE检测模型.移动机器人检测与跟踪跟随目标的核心问题是其在运动过程中, 复杂场景干扰影响其检测精度以及跟随性能. YOLOX以Darknet53网络结构为主干, 有较高的检测精度, 但模型较大、推理速度较慢, 不适用于移动机器人实时跟随. 在YOLOV5的网络模型中, 虽然网络的特征提取能力随着深度的增加而增强, 但下采样次数的增加会导致梯度的消失, 这极大影响了移动机器人的检测精度[21]. 为了提升移动机器人的检测精度, DeepSORT目标跟踪算法[22]采用卡尔曼滤波更新目标位置, 并与当前检测目标关联匹配, 但未解决因遮挡跟踪造成的目标丢失问题. Han等[23]提出PSR (Peak side-lobe rate)目标跟踪算法, 引入深度信息来评估跟踪可信度,并可主动检测跟踪丢失目标. 但其采用相关滤波法实现目标跟踪, 在复杂场景下的跟踪鲁棒性低. 可见, 改进网络结构的同时引入深度信息, 是提升移动机器人检测跟随性能的一种亟待探索的方法.综上所述, 基于YOLO系列的移动机器人目标跟随算法的鲁棒性强且精度高, 但对于变化环境迁移和泛化能力弱, 且运行速率低. 传统移动机器人目标跟随算法速度快, 但是当目标发生形变、尺度变化和严重遮挡等情况时, 跟踪过程容易出现目标跟踪丢失. 因此, 为实现复杂场景下移动机器人稳定跟随目标, 本文提出改进YOLOX的移动机器人目标跟随方法(Improved YOLOX target-follow-ing algorithm, IYTFA). 主要工作如下:1)为提高目标检测精度和速度, 提出基于YOLOX-MobileNetV2X网络 (YOLOX-M2X) 的目标检测算法, 使用交叉熵损失、回归损失以及重识别损失函数, 共同训练检测与重识别分支.2)为提高目标预测与更新速率, 采用改进的卡尔曼滤波器获取目标跟踪状态. 同时加入基于深度直方图的遮挡检测机制, 并通过深度概率约束帧间目标匹配, 提高遮挡跟踪准确率.3)在目标跟随过程中, 提出基于视觉伺服控制的主动搜寻策略, 并在目标消失时引入重识别特征进行跟踪跟随, 保证移动机器人稳定跟随目标.本文内容安排如下: 第1节介绍IYTFA算法,7 期万琴等: 基于改进YOLOX的移动机器人目标跟随方法1559包括目标检测部分、目标跟踪部分和目标跟随控制部分; 第2节为实验验证, 简要说明移动机器人和深度学习平台, 定性、定量分析目标跟踪算法, 并进行移动机器人目标跟随实验; 第3节对本文工作进行总结与展望.1 IYTFA 算法IYTFA 移动机器人目标跟随方法的结构框图如图1所示, 主要由目标检测、目标跟踪及目标跟随控制三部分组成. 首先, 将YOLOX 的主干网络Darknet53替换为MobileNetV2X, 通过获取的RGB 视频序列输入训练完成的MobileNetV2X 网络得到特征图, 再将重识别损失函数和检测损失函数分别训练重识别分支及检测分支, 从而得到目标检测结果. 然后采用改进的卡尔曼滤波器获取跟踪状态, 通过轨迹关联实现目标匹配, 同时引入遮挡判别机制, 如判断目标被遮挡则加入深度概率约束进行遮挡目标跟踪匹配. 最后采用基于视觉伺服控制的主动搜寻策略完成移动机器人目标跟随.1.1 改进YOLOX 的目标检测算法目标检测是移动机器人目标跟随的关键问题,目标检测精度很大程度上决定了移动机器人跟随的稳定性. 本文以YOLOX 体系架构为基础进行改进, 优化网络结构与损失函数, 提高检测实时性. 主干网络使用MobileNetV2X 网络, 再通过检测分支与重识别分支得到检测结果.1.1.1 YOLOX-MobileNetV2X 网络YOLOX 算法[20]将解耦头、数据增强、无锚框以及标签分类等算法与传统的YOLO 算法进行融合, 算法泛化能力强, 检测小目标精度高.YOLOX 算法网络主要分为三个部分, 分别为主干网络、网络层和预测层. 其主干网络采用Darknet53特征提取网络, 网络层采用特征金字塔网络, 预测层使用了3个解耦头. 输入图片在主干网络部分进行浅层特征提取, 输出3个特征层传入网络层进行深层特征提取, 输出分别传入3个解耦头进行目标检测. 但是YOLOX 主干网络通常使用Darknet53网络, 存在模型尺寸大、推理速度慢等问题. 因此为实现移动机器人实时目标检测, 本文提出YOLOX-M2X 网络, 将YOLOX 主干网络采用轻量级的特征提取网络MobileNetV2X, 该网络的卷积核心层是深度可分离卷积层, 可将输出的特征图的通道数缩减至一半, 并再与原卷积层提取的特征图合并,与仅使用一组深度可分离卷积的MobileNetV2[24]相比, 该网络可获得更多特征图的语义信息.330×103220×103250×103在YOLOX-M2X 网络上, 先采用COCO2017训练集训练得到网络参数, 再移植至移动机器人平台进行实时检测. COCO2017数据集是一个可用于图像检测的大规模数据集, 包含超过 幅图像(其中 幅是有标注的图像), 涵盖150万个目标及80个目标类别(行人、汽车、大象等)、91种材料类别(草、墙、天空等), 每幅图像包含5句语句描述, 且有 个带关键点标注的行人.RGB 视频序列深度视频序列跟踪结果检测结果重识别分支分支分支目标分支网络层重识别头解耦头相机ZED 相机坐标系图像坐标系跟随行人移动机器人坐标系世界坐标系 M前景机器人跟随运动学模型MobileNetV2X主干网络ZED 相机模型浅层特征深层特征特征图F R F R F F f (t )X X Y Y Z R = O −z XYOww q q O R =x y z P = ∑ w f (x x 重识别−低维向量改进卡尔曼滤波器图 1 本文方法结构框图Fig. 1 Structure block diagram of our method1560自 动 化 学 报49 卷H ×W H W F ∈R H ×W ×C H W C MobileNetV2X 网络将目标检测时的分类分为7个阶段, 输入图片分辨率为 ( 为图片高度, 为图片宽度). 假设输入特征图表示为 , 其中 为高度、 为宽度、 为通道数.每个阶段的核心层为瓶颈层, 每个阶段的瓶颈层中包括4个步骤.F 1×1∈R H ×W ×C ′步骤 1. 使用1×1卷积核扩展特征图为 , 大幅减少计算量.F 1×1∈R H ×W ×C ′F 3×3∈R H ′×W ′×C ′步骤 2. 特征图 进行逐点卷积,再采用3×3深度可分离卷积得到特征图 .F 3×3∈R H ′×W ′×C ′F (3×3)/2∈R H ′×W ′×(C ′/2)F ′(3×3)/2∈R H ′×W ′×(C ′/2)F ′(3×3)/2∈R H ′×W ′×(C ′/2)F ′′(3×3)/2∈RH ′′×W ′′×(C ′/2)F ′′(3×3)/2∈R H′′×W ′′×(C ′/2)F ′(3×3)/2∈R H′×W ′×(C ′/2)F ′3×3∈RH ′′′×W ′′′×C ′步骤 3. 为进一步获得更多的语义信息, 将特征图 一分为二, 首先通过普通卷积将特征映射减少到原始通道数的一半, 得到特征图和 ,再将特征图 进行深度可分离卷积得到 , 然后将 与 两者结合在一起得到新的特征图 .F ′3×3∈RH ′′′×W ′′′×C ′F ′∈R H ′′′×W ′′′×C ′′步骤 4. 将新特征图 使用卷积核为1×1的投影卷积层再次卷积, 得到特征图为 , 即得到每个瓶颈层的输出特征图.F 7∈R 15×15×320F 1∈R 240×240×15在MobileNetV2X 网络中的第7个阶段得到深层特征图 , 在第1个阶段得到浅层特征图 , 经网络层后得到检测分支和重识别分支的输入特征图.1.1.2 目标检测分支及损失函数F 7∈R 15×15×320F detction ∈R H d ×W d ×C d F obj ∈R H ′o ×W ′o ×1F reg ∈R H ′r ×W ′r ×4(x y w h )F cls ∈R H ′c ×W ′c ×1F detection ∈R H ′d ×W ′d ×6MobileNetV2X 网络输出的检测分支特征图, 经网络层后得到特征图 , 再经过解耦头后得到检测分支, 包括目标、分类和回归三个分支. 输入目标分支的特征图为 , 分支中每个特征点代表对应预测框内被检测目标属于前景的概率, 据此判断目标是前景还是背景. 为稳定训练过程并加快收敛速度、精确定位目标, 该分支估计每个像素相对于目标中心的连续漂移, 以减少下采样的影响; 输入回归分支的特征图为 , 该分支对目标框的中心坐标点及高度宽度 , , , 进行预测; 输入分类分支的特征图为 ,该分支得到对目标所属类别的预测评分, 如目标属于行人、车辆、动物等不同类别的评分, 其代表目标属于各个类别的概率值. 最后将三个分支的输出结果合并相加得到特征图 , 即为目标检测分支的信息.L obj L reg L cls L detection 为度量目标检测信息和真实目标信息之间的差值, 进一步定义损失函数, 损失函数值越小则差值越小, 训练模型准确度越高. 由于MobileNetV2X 网络中的目标检测分支包括目标分支、回归分支和分类分支, 其对应损失函数由目标损失函数 、回归损失函数 和分类损失函数 三部分组成,总的训练损失函数 表示为λ1λ2λ3L obj L cls L reg 其中, , 和 是损失平衡系数. 和 采用二值交叉熵损失函数(Binary cross entropy,BCE), 采用交并比 (Intersection over union,IoU) 损失函数.L obj 在目标检测中, 需首先判定预测的目标属于前景或者背景, 目标损失函数 采用Focal 交叉熵损失函数度量其与真实值的差值, 即N obj L obj y s s p s s 其中, 代表用于计算 损失函数的视频帧目标总个数; 表示测试样本 的标签, 前景标为1,背景标为0; 表示测试样本 预测为前景的概率.L reg IoU IoU IoU 回归损失函数使用 损失函数来度量预测检测框与真实目标框的交并比(面积重叠度). 指标范围为[0, 1], 当面积重叠率越大时, 指标数值越大, 即IoU 其中, 表示当前帧目标预测框和目标真实框的面积重叠率,即交并比.为评判当前视频帧目标所属的类别与真实值的差值, 分类损失函数采用多分类交叉熵损失函数对目标所属类别的预测进行评分, 即N cls L cls M y dc d c y dc p dc d c 其中, 代表用于计算 损失函数的视频帧目标总个数; 表示类别的数量; 为符号函数, 如果当前视频帧目标 的真实类别等于 , 为1,否则取0; 为当前帧目标 属于类别 的预测概率.1.1.3 重识别分支及损失函数为在目标消失再出现时完成视频连续帧间的目标匹配识别(即目标重识别), 在YOLOX-M2X 网络中加入重识别分支提取目标的颜色、纹理等浅层外观特征作为重识别特征.MobileNetV2X 网络输出的重识别分支特征图7 期万琴等: 基于改进YOLOX 的移动机器人目标跟随方法1561F 1∈R 240×240×16F re-id ∈R H ri ×W ri ×C riF ′re-id∈R H ′ri ×W ′ri ×C ri F ′′re-id∈R H ′′ri ×W ′′ri ×128x y C ={c (b ),b ∈[1,B ]} 经网络层得到 ,首先使用3×3卷积核依次与输入特征图卷积, 得到特征图 , 再通过128组1×1的卷积, 得到具有128个通道的特征图 , 则在特征图中提取对应的目标框中心点( , )处的浅层外观特征作为该目标重识别特征. 同时使用全连接层和归一化操作将其映射到特征分布向量 .L id 为评判重识别特征图准确度, 定义重识别损失函数, 其值越小, 表示重识别特征图越准确. 并将重识别损失函数 定义为L la (b )B N re-id 其中, 目标真实框的标签编码为 , 是训练数据中所有身份(ID)的编号, 使用特征图对应的目标中心点重识别特征在YOLOX-M2X 网络进行训练, 表示当前帧中目标所属类别的总数.L id L detection 最后, 将检测和重识别损失函数相加, 同时使用不确定性损失函数[11]来自动平衡检测和重识别损失函数. 与单独使用 和 训练模型相比, 训练效果得到提升, 同时减少了计算复杂度, 可达到实时性要求.1.2 基于改进卡尔曼滤波的目标跟踪首先使用第1帧检测的目标框初始化目标轨迹及跟踪状态, 然后通过改进的卡尔曼滤波器预测下一帧目标位置, 最后采用连续帧间的数据关联确定目标跟踪状态.t M i =1,···,M t N j =1,···,N t i x t,i j z t,j 在当前视频帧下, 设 时刻检测到 个目标,, 时刻跟踪 个目标, ,每一帧检测及跟踪结果实时更新, 则当前 时刻的第 个检测目标状态为 , 第 个跟踪目标状态为.x t,i =(β,˙β)T β={u,v,γ,h }β(u,v )γh (˙u,˙v )˙γ˙h本文使用改进的卡尔曼滤波器对行人轨迹的状态进行预测和更新, 设目标状态为 ,. 其中 表示目标的观测值, 表示边界框中心位置, 高宽比为 , 高度为 . 目标中心点变化速率为 , 高宽比变化速率为 , 高度变化速率为 . 考虑带非加性噪声的一般非线性系统模型w t −1v t w t −1v t 其中, 和 分别是过程噪声序列和量测噪声序列, 并假设 和 是均值为0的高斯白噪声, 其Q t R t w t −1Q t V t R t 方差分别为 和 , 即 ~(0, ), ~(0, ).为详细说明改进卡尔曼滤波器预测与更新的过程, 算法1给出此部分的伪代码. 算法1. 改进卡尔曼滤波算法x 0,i P Q t R t 输入. , , , .x t +1输出. .x 0,i P Q tR t t =0初始化. 和协方差矩阵 , 确定噪声协方差矩阵 和 , 并且设置时间 .[1,t +1]1) for .ψ=V √DV [V,D ]=eig (P )ψP 2) , 其中, , eig 表示矩阵特征值分解, 为正半定平方根矩阵, 为协方差矩阵.φP i ρi =|⟨φ,P i ⟩|/(|φ|×|P i |)3) 计算均值 和协方差矩阵 之间余弦相似度 .ξt,i =φ+√∑M i =1ρi /(λρi )ψt 4) 计算容积点 .ωt,i (ε)=λρi /(4∑Mi =1ρi )5) 计算权重 .ξt,i ωt,i 6) 生成容积点 和 .ˆx t +1,i P t +17) 通过以下公式估计一步状态预测 和 方差.ˆx t +1,i =M ∑i =1w t,i f (ξt ,i) P t +1=n ∑i =1w t,i f (ξt,i )f T (ξt,i )−ˆx t +1,i ˆx T t +1,i +Q t ξt +1,i ωt +1,i 8) 与步骤3)类似, 生成容积点 和 .ˆz t +1,j P z t +19) 估计输出预测 , 协方差 .ˆx t +1,i =ˆx t +1,i +K t +1(z t +1,j −ˆz t +1,j ) K t +1=P z t +1 P t +1=P t +1−K t +1P z t +1K T t +1 .10) end for .i z t,j F ′′t,re-id ∈R H ′′ri ×W ′′ri ×128F ′′t −1,re-id ∈R H ′ri ×W ′ri ×128q (i,j )F ′′t,re-id∈R H ′′ri ×W ′′ri ×128F ′′t −1,re-id ∈R H ′ri ×W ′ri ×128采用改进卡尔曼滤波器获取上一帧目标 的中心点在当前帧的预测位置 , 同时通过重识别特征图 中对应该预测中心位置, 得到上一帧目标在当前帧的预测外观特征. 移动机器人在跟随过程中, 会出现遮挡、快速移动等情况, 余弦距离具有快速度量的优点. 采用余弦距离 [19]判别当前帧中心点对应的外观特征向量 与上一帧在当前帧的预测外观特征向量 是否关联.b i,j λb i,j λi j b i,j λ其中, 为正确关联轨迹集合. 在训练数据集上训练网络参数得到余弦距离, 并与训练集基准之间的余弦距离进行比较, 得到阈值 . 式(7)中, 当 小于阈值 , 表示当前帧检测目标 与上一帧跟踪目标 关联, 则跟踪正常; 当 大于阈值 , 表示未成功关联, 则继续判断目标是否遮挡或消失.1562自 动 化 学 报49 卷1.3 基于深度概率约束的遮挡目标跟踪跟踪目标由于被遮挡, 目标外观会发生显著变化, 导致目标特征减少, 移动机器人跟踪目标丢失.本文提出一种有效的遮挡处理机制, 当判断遮挡发生时, 采用深度概率对目标周围区域进行空间约束,并通过最大后验概率(Maximum a posteriori,MAP)关联匹配实现遮挡跟踪.1)遮挡判断由于多个目标相互遮挡时, RGB 外观被遮挡,只可从深度信息区分不同遮挡目标, 而ZED 相机获取的深度信息为多个遮挡目标中离该相机最近的目标深度信息. 因此将目标框在RGB 图中的位置区域映射到深度图中并设定为深度遮挡区域, 若判定其他目标进入此区域表示发生遮挡, 具体判定如图2所示.(a) 遮挡前(a) Before occlusion(b) 遮挡后(b) After occlusionRGB 图深度图深度直方图深度遮挡区域目标1目标2RGB 图深度图深度直方图图 2 遮挡前后深度直方图Fig. 2 Depth histogram before and after occlusion目标1遮挡前深度直方图最大峰值为4 000, 目标2遮挡前深度直方图的最大峰值为2 500, 发生遮挡后深度遮挡区域深度直方图最大峰值为2 500, 深度直方图的峰值从4 000下降到2 500. 显然, 此时目标1的深度遮挡区域的深度直方图出现新的上升峰值2 500, 且小于遮挡前的峰值4 000, 则可见目标被遮挡后的深度直方图峰值明显减少.j t −1t (d j t −d j t −1)N (w t ,ξ2t )因此, 可根据深度变化大小判定是否发生遮挡.设跟踪目标 在 帧和 帧之间的深度变化均值可以近似为高斯分布 ~ , 在此基础上判定是否发生遮挡.,d j t t j M j |(d jt −d j t −1)|t −1t |(ωt −ξt )/(ωt −1−ξt −1)|t t −1∑w t −ξt j|(d jt −d jt −1)|w t −ξt 式中 是第 帧中跟踪目标 的深度值; 表示第 与第 帧之间所有目标深度差之和; 表示第 帧与第 帧之间深度值变化率, 其值足够大表示发生遮挡. 代表小于 的所有跟踪目标深度值差之和. 其遮挡判断准则为d j t D jt T j T j 当目标未被遮挡时, 接近 , 接近于1; 当目标被遮挡时, 则 接近于0.2)遮挡匹配跟踪S 当目标发生遮挡时, 通过最大后验概率关联当前帧检测目标与上一帧跟踪目标, 可有效解决遮挡跟踪问题. 假设所有运动目标之间相互独立, 设单个目标轨迹组成为 , 似然概率具有条件独立性,则关联遮挡目标的目标函数为P (z t −1,j )P (x t,i |z t −1,j )式中, 是所有跟踪目标的先验概率; 表示当前检测目标属于跟踪目标的条件概率, 该条件概率通过检测目标与上一帧跟踪目标框的重叠率计算得到.x t,i b (x t,i )z t −1,j b (z t −1,j )b (x t,i )b (z t −1,j )设当前帧检测目标 的深度图对应的边界框为 , 跟踪目标 的深度图对应的边界框为 , 通过判断 与 的重叠率来表示跟踪置信度, 式(11)用于求目标框的重叠率, 即σC σx t,j z t −1,j 式中, 为重叠区域, 若 大于 , 表示 与 关联匹配.1.4 基于视觉伺服控制的目标跟随在获取目标跟踪结果后, 选定感兴趣的一个目标作为移动机器人的跟随目标. 为使移动机器人实7 期万琴等: 基于改进YOLOX 的移动机器人目标跟随方法1563现目标跟随, 本文采用基于视觉伺服控制的目标跟随算法, 使跟随目标框的中心点保持为视野范围中心点. 如目标消失, 则移动机器人按照目标运动轨迹进行主动搜索, 重新识别目标并使移动机器人继续跟随目标.1.4.1 基于ZED 相机的移动机器人运动学模型由于ZED 相机具有成像分辨率高、可获取远距离深度图像等优点, 本文采用ZED 相机作为移动机器人视觉传感器, 其内参已标定.Y P =(x cn ,y cn ,z cn )z n 假设ZED 相机的镜头畸变小到可以忽略, 相机固有参数用针孔模型表示, ZED 相机成像原理图如图3所示. 在图像坐标系 的跟踪目标坐标为, 是从图像坐标和ZED 相机的固有参数中获得f b f b d x l x r 其中, 为相机焦距, 为左右相机基线, 和 是通过先验信息或相机标定得到. 其中由极线约束关系, 视差 可由左相机中的像素点 与右相机中的像素点 对应关系计算得到.YXX rX lX − bZf像平面相机基线左相机右相机P = (x cn , y cn , z cn )图 3 ZED 相机成像图Fig. 3 ZED camera imageryG P R Z Y C (x,y )D θ本文算法将移动机器人平台简化为基于ZED相机的两轮差速模型, 如图4所示. 图4中包括世界坐标系 、机器人坐标系 、ZED 相机坐标系 和图像坐标系 . 图中, 为移动机器人运动中心点, 为两轮之间的距离, 为方向角.G O T O M R rw =O T −O M Z TM O T O M 在世界坐标系 中, 跟踪目标位置 与机器人位置 之间的距离可表示为 .在ZED 相机坐标系中, 目标到机器人的距离 是由跟踪目标位置 和机器人位置 通过式(13) 得到R (θQ ,θC )Q Z δd M 其中, 表示从世界坐标系 到ZED 相机坐标系 旋转矩阵. 表示在世界坐标系 中,移动机器人与摄像机的距离.1.4.2 机器人主动控制策略前述跟踪算法完成目标跟踪, 并获取目标跟踪框的深度信息, 但直接使用目标跟踪框的深度信息来计算机器人与跟随目标的距离, 会引入大量的背景信息. 因此需要对目标中心进行重定位, 为跟踪区域找到合适的位置, 提高机器人跟随精度.(x l ,y l )∈ˆβˆβˆβˆkr ˆβ⊙∗目标跟踪框中心设为 , 表示目标跟踪框区域内所有像素坐标. 区域的精确位置在 内重定位, 利用循环矩阵 与 进行同或 运算得ˆy ∗ˆy ∗j (∆x,∆y )(x ∗,y ∗)(x l ,y l )(x ∗,y ∗)在 中最大值的位置 即为精确目标跟踪中心 与 之间的位置偏差. 跟踪区域的精确位置 计算为(x ∗,y ∗)(x ∗,y ∗)f (t )f ∗(t )得到精确位置 后, 获取以 为中心区域框的4个顶点坐标, 计算中心点和顶点对应深度信息平均值 , 其值表示为移动机器人与目标的距离. 设移动机器人期望到达位置为 , 误 X control =[U (t )=v t ,W (t )=w t ]v t w t 机器人控制变量为 , 代表移动机器人的线速度,代表移动机器人的角速度, PID 控制器设计为k P k I k D λ其中, , 和 为PID 系数, 是调整因子.G目标位置w M T = x cny cnz cn图 4 基于ZED 相机的两轮差速驱动模型Fig. 4 Two-wheel differential drive model based on ZED1564自 动 化 学 报49 卷。
17John-Steinbeck-(1902-1968)
Influence
Prior to the speech, R. Sandler, Member of the Royal Academy of Sciences, commented, «Mr. John Steinbeck - In your writings, crowned with popular success in many countries, you have been a bold observer of human behaviour in both tragic and comic situations. This you have described to the reading public of the entire world with vigour and realism. Your Travels with Charley is not only a search for but also a revelation of America, as you yourself say: ‹This monster of a land, this mightiest of nations, this spawn of the future turns out to be the macrocosm of microcosm me.› Thanks to your instinct for what is genuinely American you stand out as a true representative of American life.»
Nobel Acceptance Spextbooks.
The Grapes of Wrath
---- John Steinbeck
01 Anal resting
Manometric Measurement of Anal CanalResting ToneComparison of a Rectosphincteric Balloon Probe with a Water-Perfused Catheter AssemblyMELVIN L.ALLEN,PhD,SAEED ZAMANI,MD,ANTHONY J.DiMARINO,Jr.,MD, SUDEEP SODHI,MD,LENORE A.MIRANDA,and MOREYE NUSBAUM,MD The purpose of this study was to compare the manome tric measurements of a rectosphinc-teric balloon probe with a water-perfused cathe ter assembly on anal canal resting tone.Ten normal subje cts(9male s,1female;mean age:32years;range27±46years)unde rwent station pull-through(0.5cm/3sec)beginning in the rectum with a water-perfused cathe ter assembly and a rectosphincte ric balloon probe.Both the probe and the catheter were5mm in diameter.Three cathe ter side ports were perfused at1ml/min,and the rectal balloon was in¯ated with5ml of air.Measure ments were take n on the same day in a counterbalance d manne r.Data were analyze d on a computerized system.Mean(SEM)value s with the balloon were82.3(8.9)mm Hg and97.1(9.3)mm Hg with the cathe ter.These value s were not signi®cantly different(P0.22).A signi®cant order effect(P0.04)was found where the rst measure(101.310.2mm Hg)was highe r than the second measure(78.16.6mm Hg),which was controlle d for in the experimental design.A rectosphincte ric balloonprobe can accurately measure the resting tone of the anal canal compare d to a water-perfused cathe ter assembly.Caution should be used when measuring anal canal resting tone early in an anore ctal manometry assessment.KEY WORDS:anore ctal manome try;anal canal resting tone;rectosphincteric balloon probe.The two most common measuring devices by which anore ctal functioning is assessed today are the recto-sphincte ric balloon(1)and the water-perfused cath-eter assembly(2).Each device has its own inhe rent advantage s and disadvantage s(Table1).Both device s are connected to external pressure transduce rs that relay electrical signals to a pape r-chart recorde r or computer for analysis.An important variable to be measured during ano-rectal manome try is the resting tone of the anal canal, which make s a signi®cant contribution to the mainte-nance of fecal contine nce(3±5).The rectosphincte ric balloon probe has been avoide d in assessing anal canal resting tone,because it has been conside red to provide less physiologic measurements than the wa-ter-perfused catheter(68).The purpose of this study was to compare the manometric measurements of a rectosphincte ric bal-loon probe with a water-perfused cathe ter on anal canal resting tone.Manuscript receive d Novembe r25,1997;revise d manuscript rece ived Fe bruary17,1998;acce pted March3,1998.From the Division of Gastroenterology,Presbyterian Medical Center of Philadelphia,University of Pennsylvania School of Me d-icine,Philadelphia,Pennsylvania.Address for reprint requests:Melvin L.Allen,Division of Gas-troenterology and He patology,Thomas Jefferson University Hos-pital,132South10th Street,480Main,Philadelphia,Pennsylvania 19107.Digestive Diseases and Sciences,Vol.43,No.7(July1998),pp.1411±1415MATERIALS AND METHODSSubjects.Ten normal subjects (9males,1female;mean age :32years;age range:27±46years)participated in the study.No subject had a complaint of fecal incontinence,constipation,hemorrhoids,bleeding per rectum ,rectal pain,or abdominal pain or had a history of colorectal or anal surgery.All subjects had solid bowel movements no more than twice daily or no less than every other day.The study was approved by the Institutional Review Board of Presby-terian Medical Center of Philadelphia.Each subject gave informed written consent and was paid for their participa-tion.Ap paratu s.A rectosphincteric balloon probe (Sandhill Scienti®c,Highlands Ranch,Colorado)and a wate r-perfused catheter asse mbly (Arndorfer Me dical Special-tie s,Greendale,Wisconsin)with eight side ports spaced 2mm apart recorded anal canal re sting tone (Figure 1A and 1B).Both the probe and the catheter were 5mm in diame ter.Catheter side ports 1,4,and 7oriente d at 0,135,and 270degre es were perfused with distilled wate rFig 1.(A)Rectosphincteric balloon probe;(B)water-perfusedcatheter.T ABLE 1.C OMPARISONOFR ECTOSPHINCTER B ALLOON P ROBEWITHW ATER -P ERFUSED C ATHETER A SSEMBLY **EAS:external anal sphincter;IAS:internal anal sphincter;PR:puborectalis;RAIR:rectoanal inhibitory response.ALLEN ET ALat a rate of 1ml/min.Exte rnal pressure transducers (Mede x,Hilliard,Ohio)recorded pressures that were collected,stored,and analyze d on a compute rized system (Sandhill Scienti®c).Study Protocol.Study participants reported to the Mo-tility Laboratory between 9:00AM and 4:00PM on the study day.No study preparation was required.Subjects dressed in a hospital gown and assumed the left lateral decubitus position on a stretcher and underwent a digital examina-tion.Either a lubricated rectosphincteric balloon probe or a lubricated wate r-perfused catheter was inserted per rectum in a counterbalanced manner whereby half the subjects received the probe rst and half received the catheter rst.The catheter was perfused with distilled water until all air bubbles were out of the system and the 5.5-cm-long rectal balloon on the probe was in¯ated with 5ml of air.A station pull-through was then performed for both the catheter and probe in turn at a rate of 0.5cm/3sec.Subjects were instructed to maintain a relaxe d anal canal.Anal canal resting tone was calculated by subtracting baseline intrarectal pressure from the highest pressure re-corded in the anal canal.The rectosphincteric balloon probe provided a single measure and the water-perfused catheter provided three measures from each of the side ports which were ave raged.Statistical analysis involved the Student’s t test for pairedcomparisons and was performed using computer software (9).The alpha level required to reject the null hypothesis was 0.05.RESULTSMean (SEM )value s for anal canal resting tone as measure d by the rectosphincte ric balloon probe were 82.3(8.9)mm Hg and as measure d by the water-perfused cathe ter were 97.1(9.3)mm Hg.These value s were not signi®cantly different (P 0.22).Figure 2graphically displays example s of anal canal resting tone in the same subje ct as measure d by the rectosphincte r balloon probe and the water-perfused catheter.A signi®cant orde r effect (P 0.04)was found where the rst measure (101.310.2mm Hg)was highe r than the second measure (78.1 6.6mm Hg),regardle ss of which measuring device was used.This order effect was controlle d for by the experimental design.Fig 1.Continued.METHODS OF MEASURING ANAL CANAL TONEDISCUSSIONAnore ctal manome tric studie s using the water-perfused catheter may be uncomfortable and embar-rassing for the patie nt,since the perfused water,often noisome ,escapes the rectum and anal canal onto the patient’s buttocks and bedding.The rectosphincte ric balloon probe avoids these disadvantage s of a proce -dure that is associate d with apprehension by most patients.The most signi®cant advantage in using the water-perfused cathe ter,historically,has been its ability to provide a more physiologic measure of anal canal resting tone than the rectosphincte ric balloon probe.The results of this study using a 5.5-cm-long balloon in¯ated with 5ml of air now refute this contention in regard to asymptom atic normals.Fecally incontine nt individuals who often display abnormally low anal canal resting tone need to be studied using each of these devices in orde r to reinforce the ndings of the present study on contine nt individuals.The rectosphincte ric balloon probe is the apparatus of choice when performing biofeedback for fecal in-contine nce and pelvic ¯oor dyssyne rgia (6,10).The balloons on the rectosphincte ric probe position the device in the anal canal consistently in the same location each time they are in¯ated.This consiste ncy from treatment to treatment is important in demon-strating to the patient how much progress is being made (ie,the incre asing strength of the external anal sphincte r during voluntary contraction or the de-crease in anal canal resting pressure during voluntary attempts to expel the probe).The water-perfused catheter doe s not provide this consistency of place -ment,allowing change s in pressure which may not be a true measure ment of anal canal strength or relax-ation.An inte resting nding of this study was the in-creased pressure manifested in the anal canal during the rst of two evaluations.The cause of these ele-vate d pressures,which occurre d in 80%of the sub-Fig 2.Example of tracings from the same individual depicting measure me nt of the resting tone of the anal canal with the rectosphincteric balloon probe (left,channe l 1,pressure 111.1mm Hg)and the water-perfused cathete r (right,channe ls 1±3,mean pressure 115.8mm Hg).ALLEN ET ALjects,cannot be explaine d at this time,although, conceivably,anxie ty at the onse t of the study may have been a contributing factor.Caution might be used when measuring anal canal resting tone early in an anore ctal manometry assessment to circumvent recording arti®cially high pressures.A rectosphincte ric balloon probe can accurate ly measure the resting tone of the anal canal compare d to a water-perfused cathe ter.We recommend the use of the balloon probe because of its inhe rent advan-tages over the water-perfused cathe ter in regard to patient comfort,reliability of place ment,and superi-ority in biofe edback therapy for fecal incontine nce and pelvic¯oor dyssyne rgia.REFERENCES1.Alva J,Me ndeloff AI,Schuster MM:Re¯ex and electromyo-graphic abnormalities associated with fecal incontinence.Gas-troenterology53:101±186,19672.Hill JR,Ke lley ML,Schlegel JF:Pressure pro®le of the rectumand anus of healthy persons.Dis Colon Rectum3:203±209, 19603.Schiller LR,Santa Ana CA,Schmulen AC,He ndler RS,Harford WV,Fordtran JS:Pathoge nesis of fecal incontinence in diabetes mellitus.N Engl J Med307:16661671,19824.Read NW,Haye s WG,Bartolo DCC,Hall J,Read MG,Donnelly TC,Johnson AG:Use of anore ctal manometry during rectal infusion of saline to inve stigate sphincter function in incontinent patients.Gastroente rology85:105±113, 19835.Read NW,Bartolo DCC,Read MG:Differences in anal func-tion in patients with incontinence to solids and in patients with incontinence to liquids.Br J Surg71:3942,19846.Wald A:Anorectum.In Atlas of Gastrointestinal Motility:InHe alth and Disease.MM Schuster(ed).Baltimore,Williams& Wilkins,1993,pp2292497.Allen ML,Orr WC,Robinson MG:Anorectal functioning infecal incontinence.Dig Dis Sci33:3640,19888.Taylor BM,Beart RW,Phillips SF:Longitudinal and radialvariations of pressure in the human anal sphincter.Gastroen-terology86:693±697,19849.SAS Institute:SAS/STAT user’s guide,6.03ed.Cary,NorthCarolina,SAS Institute Inc,198810.Engel BT,Nikoomanesh P,Schuster MM:Operant recto-sphincteric response s in the treatment of fecal incontinence.N Engl J Med290:646649,1974METHODS OF MEASURING ANAL CANAL TONE。
medicinal plant 录用函 -回复
medicinal plant 录用函-回复Medicinal Plant Acceptance Letter[Medicinal Plant]Dear [Author's Name],We are delighted to inform you that your manuscript titled "[Title of the manuscript]" has been accepted for publication in our esteemed journal, [Journal's Name]. Your research on medicinal plants has been well acclaimed by our expert reviewers, and we believe that your work will make a significant contribution to the field of herbal medicine.Your manuscript provided a comprehensive analysis of the medicinal potential of [Medicinal Plant]. The research findings presented in your study have added valuable insights to our understanding of the therapeutic properties and applications of this plant. We appreciate your efforts in conducting a thorough investigation and providing experimental evidence to support your conclusions.In your manuscript, you have discussed the phytochemical profile of [Medicinal Plant]. The identification and characterization of bioactive compounds are essential steps towards understanding the underlying mechanisms of the plant's medicinal properties. Your study demonstrated the presence of several important secondary metabolites, including phenolic compounds, flavonoids, terpenoids, and alkaloids. These findings contribute significantly to the knowledge of the chemical composition and potential pharmacological activities of [Medicinal Plant].Furthermore, your research explored the diverse pharmacological actions attributed to [Medicinal Plant]. The evaluation of its antioxidant, anti-inflammatory, antimicrobial, and anticancer potential showcased the plant's versatility as a therapeutic agent. The outcomes of your study revealed encouraging results, suggesting the potential utilization of [Medicinal Plant] in the development of novel drugs and treatments for various diseases.We commend your meticulous experimental design and accurate data analysis throughout the manuscript. The clarity and relevance of your results have played a pivotal role in the decision to accept your work for publication. We believe that sharing your researchoutcomes will inspire further investigations in the field, fostering advancements in herbal medicine.Our journal is renowned for its commitment to publishinghigh-quality research articles. As an accepted author, you will be making a valuable contribution to our mission of disseminating knowledge and promoting evidence-based science. Your work will be published in our upcoming issue, and we anticipate that it will attract significant attention from researchers, academicians, and medical practitioners worldwide.To proceed with the publication process, we kindly request that you carefully address the minor revisions suggested by the reviewers. These revisions pertain to enhancing the clarity of few sections, providing additional details where needed, and citing relevant recent studies. Once you have incorporated these changes, please submit the revised manuscript through our online submission system within three weeks. A detailed guideline on manuscript formatting and submission instructions is enclosed for your reference.Once again, we extend our heartiest congratulations on theacceptance of your manuscript. We remain confident that your work will have a lasting impact on the field of medicinal plants and contribute towards improving healthcare worldwide. Thank you for considering [Journal's Name] as a platform to share your valuable research.We look forward to your revised manuscript and its subsequent publication in [Journal's Name].Sincerely,[Editor-in-Chief's Name][Journal's Name]。
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prediction scheme is based on Variable length Markov models (VLMMs) that can efficiently encode local dynamics as well as long temporal dependencies. Our novel evaluation scheme is based on volumetric reconstruction and blobfitting and allows a large number of model candidates to be tested in a very efficient manner. The tracker is also capable of self-initialisation and recovery from tracking failures by using the motion prototypes as new starting points.
Interfaces Group, School of Computer Science,
University of Manchester, Manchester M13 9PL, UK
In this paper, we introduce a 3-D human-body tracker capable of handling fast and complex motions in real-time. We build upon the Monte-Carlo Bayesian framework, and propose novel prediction and evaluation methods improving the robustness and efficiency of the tracker. The parameter space, augmented with first order derivatives, is automatically partitioned into Gaussian clusters each representing an elementary motion: hypothesis propagation inside each cluster is therefore accu-
Accepted Manuscript
Real-Time 3-D Human Body Tracking using Learnt Models of Behaviour Fabrice Caillette, Aphrodite Galata, Toby Howard PII: DOI: Reference: To appear in: Received Date: Revised Date: Accepted Date: S1077-3142(07)00083-5 10.1016/j.cviu.2007.05.005 YCVIU 1372 Computer Vision and Image Understanding 14 September 2005 8 July 2006 16 May 2007
environments.
With motion analysis, computers could assess the recovery of patients and help sportsmen improve their performances. Computers could also become
In this paper, we present a full body tracker based on a Monte-Carlo Bayesian framework. Real-time tracking of challenging human motions is made possible by novel prediction and evaluation schemes. We use a high-order temporal
Preprint submitted to CVIU
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Using Monte-Carlo methods, evaluation of model candidates is critical for both
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Likewise, tracking motions can be used to control realistic avatars in virtual
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Movements and gestures are essential vehicles of communication thatቤተ መጻሕፍቲ ባይዱcan be
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Introduction
Full human-body tracking has a wide and promising range of applications.
used to interact with computers in a more natural and expressive way than current computer-centred devices. The domain of computer interfaces could be reshaped by gesture-based interactions, allowing users to interact freely with virtual objects. Video games are an obvious example of application which would greatly benefit from body tracking to enhance the immersion of players.
length Markov model which can explain high-level behaviours over a long history.
speed and robustness. We present a new evaluation scheme based on hierarchical 3-D reconstruction and blob-fitting, where appearance models and image evidences are represented by mixtures of Gaussian blobs. Our tracker is also capable of automatic initialisation and self-recovery. We demonstrate the application of our tracker to long video sequences exhibiting rapid and diverse movements. Key words: Real-Time, Human-Body Tracking, Variable Length Markov Models, Bayesian, Monte-Carlo, Volumetric Reconstruction, Visual-Hull, Blobs, Entropy, Kullback-Leibler
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ing, shadows or camera noise may further complicate the inference problem. Despite a very high level of interest in the computer-vision community, the general human-body tracking problem remains largely unsolved and current markerless trackers still cannot compete in accuracy and robustness with commercial motion capture systems.
Please cite this article as: F. Caillette, A. Galata, T. Howard, Real-Time 3-D Human Body Tracking using Learnt Models of Behaviour, Computer Vision and Image Understanding (2007), doi: 10.1016/j.cviu.2007.05.005
instructing students and correcting their errors. Last but not the least, the film
of realistic computer graphics. The capture and re-targeting of the movements of actors towards animated characters is a very important application, used not only in films, but also in video games and in live broadcasts. Tracking people is difficult because of the high dimensionality of full body kinematics, fast movements and frequent self-occlusions. Moreover, loose cloth∗ Corresponding author. Email address: a.galata@ (Aphrodite Galata).