卖朋友速聘:自媒体人生存状态调查报告:超60%月营收不足万元
a b c d e f g h i j k l m n o p q r s t u v w x y z
a b c d e f g h i j k l m n o p q r s t u v w x y z注:(1)r、v两个字母用来拼写普通话和外来语,拼写广州话时不用。
(2)广州话拼音字母有三个附加符号:ê、é、ü,其中é是和汉语拼音字母不同的。
这几个字母是e、u字母的变体,叫不列入表内。
二、声母表b波p婆m摸f科d多t拖n挪l罗g哥k卡ng我h何gu姑ku箍z左c初s梳j知q雌x思y也w华注:(1)z、c、s和j、q、x两组声母,广州话的读音没有区别,只是在拼写韵母时有不同,z、c、s拼写a、o、é及a、o、e、é、ê、u等字母开头的韵母,例如:za渣,ca茶,xa沙。
j、q、x拼写i、ü及i、ü字母开头的韵母,例如:ji知,qi次,xi思。
(2)gu姑、ku箍是圆唇的舌跟音,作为声母使用,不能单独注音,单独注音时是音节,不是声母。
(3)y也,w华拼音时作为声母使用,拼写出来的音节相当于汉语拼音方案的复韵母,但由于广州话当中这些韵母前面不再拼声母,因此只作为音节使用三、韵母表a呀o柯u乌i衣ū于ê(靴) é诶m唔n五ai挨 ei矮 oi哀 ui会éi(非)ao拗 eo欧 ou奥iu妖êu(去)am(监) em庵im淹an晏 en(恩) on安 un碗in烟ūn冤 ên(春)ang(横) eng莺 ong(康) ung瓮ing英êng(香) éng(镜)ab鸭 eb(急) ib叶ad押 ed(不) od(渴) ud活 id热ūd月 êd(律)ag(客) eg(德) og恶 ug屋 ig益êg(约) ég(尺)注:(1)例字外加( )号的,只取其韵母。
(2)i行的韵母,前面没有声母的时候,写成yi衣,yiu妖,yim淹,yin烟,ying 英,yib叶,yid热,yig益。
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$3$l$,5a$a$k$h$&$J$b$N$K$J$k!%$r2>Dj$9$k$H!$$9$Y$F$N$J$KBP$7!$$J$G$,O"B3$JC1D44X?t$H$J$k$h$&$J$b$N$,B8:_$9$k!%$r2>Dj$9$k!%$3$N$H$-$9$Y$F$N$J$KBP$7!$$J$G!$$,O"B3$K$J$k$h$&$J$b$N$,B8:_$9$k!%$+$i$,7kO@$G$-$k$+$i!$$"$H$O!$A0$NDjM}$HF1MM$K<($;$k!%$,@.$jN)$D$J$i!$$9$Y$F$N$O$r;}$D!%$7$?$,$C$F!$$3$N$H$-$K$O!$$9$Y$F$N$J$O$H$J$k!%$7$?$,$C$F!$$K$h$C$F!$$J$G!$$,O"B3$K$J$k$h$&$J$b$N$,$H$l$k!%:G8e$K$N7k2L$r0zMQ$9$k!%$,L5L7=b$J$i!$$K$9$Y$F$N4X?t$KBP$7!$$,O"B3$K$J$k$h$&$J!$$J$,B8:_$9$k$rIU2C$7$F$bL5L7=b$G$"$k!%$,L5L7=b$J$i!$$K$9$Y$F$N4X?t$KBP$7!$ $,O"B3$K$J$k$h$&$J!$$J$,B8:_$9$k$rIU2C$7$F$bL5L7=b$G$"$k!%$,L5L7=b$J$i!$$O!J$N!K$9$Y$F$N4X?t$KBP$7!$$,O"B3$K$J$k$h$&$J!$$J$,B8:_$9$k$bL5L7=b$G$"$k!%$,L5L7=b$J$i!$$O$9$Y$F$N4X?t$KBP$7!$$,O"B3$K$J$k$h$&$J!$$J$,B8:_$9$k$bL5L7=b$G $"$k!%。
简繁体字对照表(最新版最新版)
简繁体字对照表皑:皚蔼:藹碍:礙爱:愛袄:襖奥:奧坝:壩罢:罷摆:擺败:敗颁:頒办:辦绊:絆帮:幫绑:綁镑:鎊谤:謗剥:剝饱:飽宝:寶报:報鲍:鮑辈:輩贝:貝钡:鋇狈:狽备:備惫:憊绷:繃笔:筆毕:畢毙:斃币:幣闭:閉辟:闢边:邊编:編贬:貶变:變辩:辯辫:辮标:標鳖:鱉别:別瘪:癟濒:瀕滨:濱宾:賓摈:擯饼:餅并:並拨:撥钵:缽铂:鉑驳:駁补:補财:財采:採参:參残:殘惭:慚惨:慘灿:燦苍:蒼舱:艙仓:倉沧:滄厕:廁侧:側册:冊测:測层:層诧:詫搀:攙掺:摻蝉:蟬馋:饞谗:讒缠:纏铲:鏟产:產阐:闡颤:顫场:場尝:嘗长:長偿:償肠:腸厂:廠畅:暢钞:鈔车:車彻:徹尘:塵陈:陳衬:襯撑:撐称:稱惩:懲诚:誠骋:騁迟:遲驰:馳耻:恥齿:齒炽:熾冲:沖虫:蟲宠:寵畴:疇踌:躊筹:籌绸:綢丑:醜橱:櫥厨:廚锄:鋤雏:雛础:礎储:儲触:觸处:處传:傳疮:瘡闯:闖创:創锤:錘纯:純绰:綽辞:辭词:詞赐:賜聪:聰葱:蔥囱:囪从:從丛:叢凑:湊蹿:躥窜:竄错:錯达:達带:帶贷:貸担:擔单:單郸:鄲掸:撣胆:膽惮:憚诞:誕弹:彈当:當挡:擋党:黨荡:蕩档:檔捣:搗岛:島祷:禱导:導盗:盜灯:燈邓:鄧敌:敵涤:滌递:遞缔:締颠:顛点:點垫:墊电:電钓:釣调:調谍:諜叠:疊钉:釘顶:頂锭:錠订:訂丢:丟东:東动:動栋:棟冻:凍斗:鬥犊:犢独:獨读:讀赌:賭镀:鍍锻:鍛断:斷缎:緞兑:兌队:隊对:對顿:頓钝:鈍夺:奪堕:墮鹅:鵝额:額讹:訛恶:惡饿:餓儿:兒尔:爾饵:餌贰:貳发:發罚:罰阀:閥珐:琺矾:礬钒:釩烦:煩范:範贩:販饭:飯访:訪纺:紡飞:飛诽:誹废:廢费:費纷:紛坟:墳奋:奮愤:憤粪:糞丰:豐枫:楓锋:鋒风:風疯:瘋冯:馮缝:縫讽:諷凤:鳳肤:膚辐:輻抚:撫辅:輔赋:賦复:復负:負讣:訃妇:婦缚:縛该:該钙:鈣盖:蓋干:幹赶:趕秆:稈赣:贛冈:岡刚:剛钢:鋼纲:綱岗:崗镐:鎬搁:擱鸽:鴿阁:閣铬:鉻个:個给:給龚:龔宫:宮巩:鞏贡:貢钩:鉤沟:溝构:構购:購够:夠蛊:蠱顾:顧雇:僱剐:剮挂:掛关:關观:觀馆:館惯:慣贯:貫广:廣规:規硅:矽归:歸龟:龜闺:閨轨:軌诡:詭柜:櫃贵:貴刽:劊辊:輥滚:滾锅:鍋国:國过:過骇:駭韩:韓汉:漢号:號阂:閡鹤:鶴贺:賀横:橫轰:轟鸿:鴻红:紅后:後壶:壺护:護沪:滬户:戶哗:嘩华:華画:畫划:劃话:話怀:懷坏:壞欢:歡环:環还:還缓:緩换:換唤:喚痪:瘓焕:煥涣:渙黄:黃谎:謊挥:揮辉:輝毁:毀贿:賄秽:穢会:會烩:燴汇:匯讳:諱诲:誨绘:繪荤:葷浑:渾获:獲货:貨祸:禍击:擊机:機积:積饥:饑迹:跡讥:譏鸡:雞绩:績缉:緝极:極辑:輯级:級挤:擠几:幾蓟:薊剂:劑济:濟计:計记:記际:際继:繼纪:紀夹:夾荚:莢颊:頰贾:賈钾:鉀价:價驾:駕歼:殲监:監坚:堅笺:箋间:間艰:艱缄:緘检:檢碱:鹼硷:鹼拣:揀捡:撿简:簡俭:儉减:減荐:薦槛:檻鉴:鑒践:踐贱:賤见:見键:鍵舰:艦剑:劍饯:餞渐:漸溅:濺涧:澗将:將浆:漿蒋:蔣桨:槳奖:獎讲:講酱:醬胶:膠浇:澆骄:驕娇:嬌搅:攪铰:鉸矫:矯侥:僥脚:腳饺:餃缴:繳绞:絞轿:轎较:較阶:階节:節杰:傑洁:潔结:結诫:誡届:屆紧:緊锦:錦仅:僅谨:謹进:進晋:晉烬:燼尽:盡劲:勁荆:荊茎:莖鲸:鯨惊:驚经:經颈:頸静:靜镜:鏡径:徑痉:痙竞:競净:淨纠:糾厩:廄旧:舊驹:駒举:舉据:據锯:鋸惧:懼剧:劇鹃:鵑绢:絹觉:覺决:決诀:訣绝:絕钧:鈞军:軍骏:駿开:開凯:凱颗:顆壳:殼课:課垦:墾恳:懇抠:摳库:庫裤:褲夸:誇块:塊侩:儈宽:寬矿:礦旷:曠况:況亏:虧岿:巋窥:窺馈:饋溃:潰扩:擴阔:闊蜡:蠟腊:臘莱:萊来:來赖:賴蓝:藍栏:欄拦:攔篮:籃阑:闌兰:蘭澜:瀾谰:讕揽:攬览:覽懒:懶缆:纜烂:爛滥:濫捞:撈劳:勞涝:澇乐:樂镭:鐳垒:壘类:類泪:淚厘:釐篱:籬离:離里:裡鲤:鯉礼:禮丽:麗厉:厲励:勵砾:礫历:歷傈:栗沥:瀝隶:隸俩:倆联:聯莲:蓮连:連镰:鐮怜:憐涟:漣帘:簾敛:斂脸:臉链:鏈恋:戀炼:煉练:練粮:糧凉:涼两:兩辆:輛谅:諒疗:療辽:遼镣:鐐猎:獵临:臨邻:鄰鳞:鱗凛:凜赁:賃龄:齡铃:鈴灵:靈岭:嶺领:領馏:餾刘:劉龙:龍聋:聾咙:嚨笼:籠垄:壟拢:攏陇:隴楼:樓娄:婁搂:摟篓:簍芦:蘆卢:盧颅:顱庐:廬炉:爐掳:擄卤:鹵虏:虜鲁:魯赂:賂禄:祿录:錄陆:陸驴:驢吕:呂铝:鋁侣:侶屡:屢缕:縷虑:慮滤:濾绿:綠峦:巒挛:攣孪:孿滦:灤乱:亂抡:掄轮:輪伦:倫仑:侖沦:淪纶:綸论:論萝:蘿罗:羅逻:邏锣:鑼箩:籮骡:騾骆:駱络:絡妈:媽玛:瑪码:碼蚂:螞马:馬骂:罵吗:嗎买:買麦:麥卖:賣迈:邁脉:脈瞒:瞞馒:饅蛮:蠻满:滿谩:謾猫:貓锚:錨铆:鉚贸:貿么:麼酶:霉没:沒镁:鎂门:門闷:悶们:們锰:錳梦:夢谜:謎弥:彌觅:覓幂:冪绵:綿缅:緬庙:廟灭:滅悯:憫闽:閩鸣:鳴铭:銘谬:謬谋:謀亩:畝呐:吶钠:鈉纳:納难:難挠:撓脑:腦恼:惱闹:鬧馁:餒内:內拟:擬腻:膩撵:攆酿:釀鸟:鳥聂:聶啮:嚙镊:鑷镍:鎳柠:檸狞:獰宁:寧拧:擰钮:鈕纽:紐脓:膿浓:濃农:農疟:瘧诺:諾欧:歐鸥:鷗殴:毆呕:嘔沤:漚盘:盤庞:龐抛:拋赔:賠喷:噴鹏:鵬骗:騙飘:飄频:頻贫:貧苹:蘋凭:憑评:評泼:潑颇:頗扑:撲铺:鋪仆:僕朴:樸谱:譜脐:臍齐:齊骑:騎岂:豈启:啓气:氣弃:棄讫:訖牵:牽钎:釬铅:鉛迁:遷签:籤谦:謙钱:錢钳:鉗潜:潛浅:淺谴:譴堑:塹枪:槍呛:嗆墙:牆蔷:薔强:強抢:搶锹:鍬桥:橋乔:喬侨:僑翘:翹窍:竅窃:竊钦:欽亲:親寝:寢轻:輕氢:氫倾:傾顷:頃请:請庆:慶琼:瓊穷:窮趋:趨区:區躯:軀驱:驅龋:齲颧:顴权:權劝:勸却:卻鹊:鵲确:確让:讓饶:饒扰:擾绕:繞热:熱韧:韌认:認纫:紉荣:榮绒:絨软:軟锐:銳闰:閏润:潤洒:灑萨:薩鳃:鰓赛:賽叁:杬伞:傘丧:喪骚:騷扫:掃涩:澀杀:殺刹:剎纱:紗筛:篩晒:曬删:刪闪:閃陕:陝赡:贍缮:繕墒:濕伤:傷赏:賞烧:燒绍:紹赊:賒摄:攝慑:懾设:設绅:紳审:審婶:嬸肾:腎渗:滲声:聲绳:繩胜:勝圣:聖师:師狮:獅湿:濕诗:詩尸:屍时:時蚀:蝕实:實识:識驶:駛势:勢适:適释:釋饰:飾视:視试:試寿:壽兽:獸枢:樞输:輸书:書赎:贖属:屬术:術树:樹竖:豎数:數帅:帥双:雙谁:誰税:稅顺:順说:說硕:碩烁:爍丝:絲饲:飼耸:聳怂:慫颂:頌讼:訟诵:誦擞:擻苏:蘇诉:訴肃:肅虽:雖随:隨绥:綏岁:歲孙:孫损:損笋:筍缩:縮琐:瑣锁:鎖獭:獺挞:撻酞:太态:態摊:攤贪:貪瘫:癱滩:灘坛:壇谭:譚谈:談叹:嘆汤:湯烫:燙涛:濤绦:絛讨:討腾:騰誊:謄锑:銻题:題体:體屉:屜条:條贴:貼铁:鐵厅:廳听:聽烃:烴铜:銅统:統头:頭秃:禿图:圖涂:塗团:團颓:頹蜕:蛻脱:脫鸵:鴕驮:馱驼:駝椭:橢袜:襪弯:彎湾:灣顽:頑万:萬网:網韦:韋违:違围:圍为:爲潍:濰维:維苇:葦伟:偉伪:偽纬:緯谓:謂卫:衛温:溫闻:聞纹:紋稳:穩问:問挝:撾蜗:蝸涡:渦窝:窩卧:臥呜:嗚钨:鎢乌:烏诬:誣无:無芜:蕪吴:吳坞:塢雾:霧务:務误:誤锡:錫牺:犧袭:襲习:習铣:銑戏:戲细:細虾:蝦辖:轄峡:峽侠:俠狭:狹厦:廈吓:嚇锨:杴鲜:鮮纤:纖咸:鹹贤:賢衔:銜闲:閒显:顯险:險现:現献:獻县:縣馅:餡宪:憲线:線厢:廂镶:鑲乡:鄉详:詳响:響项:項萧:蕭嚣:囂销:銷晓:曉啸:嘯协:協挟:挾携:攜胁:脅谐:諧写:寫泻:瀉谢:謝锌:鋅衅:釁兴:興汹:洶锈:鏽绣:繡虚:虛嘘:噓须:須许:許叙:敘绪:緒续:續轩:軒悬:懸选:選癣:癬绚:絢学:學勋:勛询:詢寻:尋驯:馴训:訓讯:訊逊:遜压:壓鸦:鴉鸭:鴨哑:啞亚:亞讶:訝阉:閹烟:煙盐:鹽严:嚴颜:顏阎:閻艳:艷厌:厭砚:硯彦:彥谚:諺验:驗鸯:鴦杨:楊扬:揚疡:瘍阳:陽养:養样:樣瑶:瑤摇:搖尧:堯遥:遙窑:窯谣:謠药:藥爷:爺页:頁业:業叶:葉医:醫铱:銥颐:頤遗:遺仪:儀蚁:蟻艺:藝亿:億忆:憶义:義诣:詣议:議谊:誼译:譯异:異绎:繹荫:蔭阴:陰银:銀饮:飲隐:隱樱:櫻婴:嬰鹰:鷹应:應缨:纓莹:瑩萤:螢营:營荧:熒蝇:蠅赢:贏颖:穎哟:喲拥:擁佣:傭痈:癰咏:詠优:優忧:憂邮:郵铀:鈾犹:猶游:遊诱:誘于:於舆:輿余:餘鱼:魚渔:漁娱:娛与:與屿:嶼语:語郁:鬱狱:獄誉:譽预:預驭:馭鸳:鴛渊:淵辕:轅园:園员:員圆:圓缘:緣远:遠愿:願约:約跃:躍钥:鑰粤:粵悦:悅阅:閱云:雲郧:鄖匀:勻陨:隕运:運蕴:蘊酝:醞晕:暈韵:韻杂:雜灾:災载:載攒:攢暂:暫赞:贊赃:贓脏:髒凿:鑿枣:棗责:責择:擇则:則泽:澤贼:賊赠:贈轧:軋铡:鍘闸:閘栅:柵诈:詐斋:齋债:債毡:氈盏:盞斩:斬辗:輾崭:嶄栈:堆占:佔战:戰绽:綻张:張涨:漲帐:帳账:賬胀:脹赵:趙蛰:蟄辙:轍锗:鍺这:這贞:貞针:針侦:偵诊:診镇:鎮阵:陣挣:掙睁:睜狰:猙争:爭帧:幀郑:鄭证:證织:織职:職执:執纸:紙挚:摯掷:擲帜:幟制:製质:質滞:滯钟:鐘终:終种:種肿:腫众:眾诌:謅轴:軸皱:皺昼:晝骤:驟猪:豬诸:諸诛:誅烛:燭瞩:矚嘱:囑贮:貯铸:鑄筑:築注:註驻:駐专:專砖:磚转:轉赚:賺桩:樁装:裝妆:妝壮:壯状:狀锥:錐赘:贅坠:墜缀:綴谆:諄准:準着:著浊:濁兹:茲资:資渍:漬踪:蹤综:綜总:總纵:縱邹:鄒诅:詛组:組钻:鑽亘:亙鼗:淘芈:羋啬:嗇厍:厙厣:厴厮:廝靥:靨赝:贗匦:匭匮:匱赜:賾刭:剄刿:劌剀:剴劐:豁么:麼伛:傴伥:倀伧:傖繁简拼音声调皚皑ai 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ABSTRACT Progressive Simplicial Complexes
Progressive Simplicial Complexes Jovan Popovi´c Hugues HoppeCarnegie Mellon University Microsoft ResearchABSTRACTIn this paper,we introduce the progressive simplicial complex(PSC) representation,a new format for storing and transmitting triangu-lated geometric models.Like the earlier progressive mesh(PM) representation,it captures a given model as a coarse base model together with a sequence of refinement transformations that pro-gressively recover detail.The PSC representation makes use of a more general refinement transformation,allowing the given model to be an arbitrary triangulation(e.g.any dimension,non-orientable, non-manifold,non-regular),and the base model to always consist of a single vertex.Indeed,the sequence of refinement transforma-tions encodes both the geometry and the topology of the model in a unified multiresolution framework.The PSC representation retains the advantages of PM’s.It defines a continuous sequence of approx-imating models for runtime level-of-detail control,allows smooth transitions between any pair of models in the sequence,supports progressive transmission,and offers a space-efficient representa-tion.Moreover,by allowing changes to topology,the PSC sequence of approximations achieves betterfidelity than the corresponding PM sequence.We develop an optimization algorithm for constructing PSC representations for graphics surface models,and demonstrate the framework on models that are both geometrically and topologically complex.CR Categories:I.3.5[Computer Graphics]:Computational Geometry and Object Modeling-surfaces and object representations.Additional Keywords:model simplification,level-of-detail representa-tions,multiresolution,progressive transmission,geometry compression.1INTRODUCTIONModeling and3D scanning systems commonly give rise to triangle meshes of high complexity.Such meshes are notoriously difficult to render,store,and transmit.One approach to speed up rendering is to replace a complex mesh by a set of level-of-detail(LOD) approximations;a detailed mesh is used when the object is close to the viewer,and coarser approximations are substituted as the object recedes[6,8].These LOD approximations can be precomputed Work performed while at Microsoft Research.Email:jovan@,hhoppe@Web:/jovan/Web:/hoppe/automatically using mesh simplification methods(e.g.[2,10,14,20,21,22,24,27]).For efficient storage and transmission,meshcompression schemes[7,26]have also been developed.The recently introduced progressive mesh(PM)representa-tion[13]provides a unified solution to these problems.In PM form,an arbitrary mesh M is stored as a coarse base mesh M0together witha sequence of n detail records that indicate how to incrementally re-fine M0into M n=M(see Figure7).Each detail record encodes theinformation associated with a vertex split,an elementary transfor-mation that adds one vertex to the mesh.In addition to defininga continuous sequence of approximations M0M n,the PM rep-resentation supports smooth visual transitions(geomorphs),allowsprogressive transmission,and makes an effective mesh compressionscheme.The PM representation has two restrictions,however.First,it canonly represent meshes:triangulations that correspond to orientable12-dimensional manifolds.Triangulated2models that cannot be rep-resented include1-d manifolds(open and closed curves),higherdimensional polyhedra(e.g.triangulated volumes),non-orientablesurfaces(e.g.M¨o bius strips),non-manifolds(e.g.two cubes joinedalong an edge),and non-regular models(i.e.models of mixed di-mensionality).Second,the expressiveness of the PM vertex splittransformations constrains all meshes M0M n to have the same topological type.Therefore,when M is topologically complex,the simplified base mesh M0may still have numerous triangles(Fig-ure7).In contrast,a number of existing simplification methods allowtopological changes as the model is simplified(Section6).Ourwork is inspired by vertex unification schemes[21,22],whichmerge vertices of the model based on geometric proximity,therebyallowing genus modification and component merging.In this paper,we introduce the progressive simplicial complex(PSC)representation,a generalization of the PM representation thatpermits topological changes.The key element of our approach isthe introduction of a more general refinement transformation,thegeneralized vertex split,that encodes changes to both the geometryand topology of the model.The PSC representation expresses anarbitrary triangulated model M(e.g.any dimension,non-orientable,non-manifold,non-regular)as the result of successive refinementsapplied to a base model M1that always consists of a single vertex (Figure8).Thus both geometric and topological complexity are recovered progressively.Moreover,the PSC representation retains the advantages of PM’s,including continuous LOD,geomorphs, progressive transmission,and model compression.In addition,we develop an optimization algorithm for construct-ing a PSC representation from a given model,as described in Sec-tion4.1The particular parametrization of vertex splits in[13]assumes that mesh triangles are consistently oriented.2Throughout this paper,we use the words“triangulated”and“triangula-tion”in the general dimension-independent sense.Figure 1:Illustration of a simplicial complex K and some of its subsets.2BACKGROUND2.1Concepts from algebraic topologyTo precisely define both triangulated models and their PSC repre-sentations,we find it useful to introduce some elegant abstractions from algebraic topology (e.g.[15,25]).The geometry of a triangulated model is denoted as a tuple (K V )where the abstract simplicial complex K is a combinatorial structure specifying the adjacency of vertices,edges,triangles,etc.,and V is a set of vertex positions specifying the shape of the model in 3.More precisely,an abstract simplicial complex K consists of a set of vertices 1m together with a set of non-empty subsets of the vertices,called the simplices of K ,such that any set consisting of exactly one vertex is a simplex in K ,and every non-empty subset of a simplex in K is also a simplex in K .A simplex containing exactly d +1vertices has dimension d and is called a d -simplex.As illustrated pictorially in Figure 1,the faces of a simplex s ,denoted s ,is the set of non-empty subsets of s .The star of s ,denoted star(s ),is the set of simplices of which s is a face.The children of a d -simplex s are the (d 1)-simplices of s ,and its parents are the (d +1)-simplices of star(s ).A simplex with exactly one parent is said to be a boundary simplex ,and one with no parents a principal simplex .The dimension of K is the maximum dimension of its simplices;K is said to be regular if all its principal simplices have the same dimension.To form a triangulation from K ,identify its vertices 1m with the standard basis vectors 1m ofm.For each simplex s ,let the open simplex smdenote the interior of the convex hull of its vertices:s =m:jmj =1j=1jjsThe topological realization K is defined as K =K =s K s .The geometric realization of K is the image V (K )where V :m 3is the linear map that sends the j -th standard basis vector jm to j 3.Only a restricted set of vertex positions V =1m lead to an embedding of V (K )3,that is,prevent self-intersections.The geometric realization V (K )is often called a simplicial complex or polyhedron ;it is formed by an arbitrary union of points,segments,triangles,tetrahedra,etc.Note that there generally exist many triangulations (K V )for a given polyhedron.(Some of the vertices V may lie in the polyhedron’s interior.)Two sets are said to be homeomorphic (denoted =)if there ex-ists a continuous one-to-one mapping between them.Equivalently,they are said to have the same topological type .The topological realization K is a d-dimensional manifold without boundary if for each vertex j ,star(j )=d .It is a d-dimensional manifold if each star(v )is homeomorphic to either d or d +,where d +=d:10.Two simplices s 1and s 2are d-adjacent if they have a common d -dimensional face.Two d -adjacent (d +1)-simplices s 1and s 2are manifold-adjacent if star(s 1s 2)=d +1.Figure 2:Illustration of the edge collapse transformation and its inverse,the vertex split.Transitive closure of 0-adjacency partitions K into connected com-ponents .Similarly,transitive closure of manifold-adjacency parti-tions K into manifold components .2.2Review of progressive meshesIn the PM representation [13],a mesh with appearance attributes is represented as a tuple M =(K V D S ),where the abstract simpli-cial complex K is restricted to define an orientable 2-dimensional manifold,the vertex positions V =1m determine its ge-ometric realization V (K )in3,D is the set of discrete material attributes d f associated with 2-simplices f K ,and S is the set of scalar attributes s (v f )(e.g.normals,texture coordinates)associated with corners (vertex-face tuples)of K .An initial mesh M =M n is simplified into a coarser base mesh M 0by applying a sequence of n successive edge collapse transforma-tions:(M =M n )ecol n 1ecol 1M 1ecol 0M 0As shown in Figure 2,each ecol unifies the two vertices of an edgea b ,thereby removing one or two triangles.The position of the resulting unified vertex can be arbitrary.Because the edge collapse transformation has an inverse,called the vertex split transformation (Figure 2),the process can be reversed,so that an arbitrary mesh M may be represented as a simple mesh M 0together with a sequence of n vsplit records:M 0vsplit 0M 1vsplit 1vsplit n 1(M n =M )The tuple (M 0vsplit 0vsplit n 1)forms a progressive mesh (PM)representation of M .The PM representation thus captures a continuous sequence of approximations M 0M n that can be quickly traversed for interac-tive level-of-detail control.Moreover,there exists a correspondence between the vertices of any two meshes M c and M f (0c f n )within this sequence,allowing for the construction of smooth vi-sual transitions (geomorphs)between them.A sequence of such geomorphs can be precomputed for smooth runtime LOD.In addi-tion,PM’s support progressive transmission,since the base mesh M 0can be quickly transmitted first,followed the vsplit sequence.Finally,the vsplit records can be encoded concisely,making the PM representation an effective scheme for mesh compression.Topological constraints Because the definitions of ecol and vsplit are such that they preserve the topological type of the mesh (i.e.all K i are homeomorphic),there is a constraint on the min-imum complexity that K 0may achieve.For instance,it is known that the minimal number of vertices for a closed genus g mesh (ori-entable 2-manifold)is (7+(48g +1)12)2if g =2(10if g =2)[16].Also,the presence of boundary components may further constrain the complexity of K 0.Most importantly,K may consist of a number of components,and each is required to appear in the base mesh.For example,the meshes in Figure 7each have 117components.As evident from the figure,the geometry of PM meshes may deteriorate severely as they approach topological lower bound.M 1;100;(1)M 10;511;(7)M 50;4656;(12)M 200;1552277;(28)M 500;3968690;(58)M 2000;14253219;(108)M 5000;029010;(176)M n =34794;0068776;(207)Figure 3:Example of a PSC representation.The image captions indicate the number of principal 012-simplices respectively and the number of connected components (in parenthesis).3PSC REPRESENTATION 3.1Triangulated modelsThe first step towards generalizing PM’s is to let the PSC repre-sentation encode more general triangulated models,instead of just meshes.We denote a triangulated model as a tuple M =(K V D A ).The abstract simplicial complex K is not restricted to 2-manifolds,but may in fact be arbitrary.To represent K in memory,we encode the incidence graph of the simplices using the following linked structures (in C++notation):struct Simplex int dim;//0=vertex,1=edge,2=triangle,...int id;Simplex*children[MAXDIM+1];//[0..dim]List<Simplex*>parents;;To render the model,we draw only the principal simplices ofK ,denoted (K )(i.e.vertices not adjacent to edges,edges not adjacent to triangles,etc.).The discrete attributes D associate amaterial identifier d s with each simplex s(K ).For the sake of simplicity,we avoid explicitly storing surface normals at “corners”(using a set S )as done in [13].Instead we let the material identifier d s contain a smoothing group field [28],and let a normal discontinuity (crease )form between any pair of adjacent triangles with different smoothing groups.Previous vertex unification schemes [21,22]render principal simplices of dimension 0and 1(denoted 01(K ))as points and lines respectively with fixed,device-dependent screen widths.To better approximate the model,we instead define a set A that associates an area a s A with each simplex s 01(K ).We think of a 0-simplex s 00(K )as approximating a sphere with area a s 0,and a 1-simplex s 1=j k 1(K )as approximating a cylinder (with axis (j k ))of area a s 1.To render a simplex s 01(K ),we determine the radius r model of the corresponding sphere or cylinder in modeling space,and project the length r model to obtain the radius r screen in screen pixels.Depending on r screen ,we render the simplex as a polygonal sphere or cylinder with radius r model ,a 2D point or line with thickness 2r screen ,or do not render it at all.This choice based on r screen can be adjusted to mitigate the overhead of introducing polygonal representations of spheres and cylinders.As an example,Figure 3shows an initial model M of 68,776triangles.One of its approximations M 500is a triangulated model with 3968690principal 012-simplices respectively.3.2Level-of-detail sequenceAs in progressive meshes,from a given triangulated model M =M n ,we define a sequence of approximations M i :M 1op 1M 2op 2M n1op n 1M nHere each model M i has exactly i vertices.The simplification op-erator M ivunify iM i +1is the vertex unification transformation,whichmerges two vertices (Section 3.3),and its inverse M igvspl iM i +1is the generalized vertex split transformation (Section 3.4).Thetuple (M 1gvspl 1gvspl n 1)forms a progressive simplicial complex (PSC)representation of M .To construct a PSC representation,we first determine a sequence of vunify transformations simplifying M down to a single vertex,as described in Section 4.After reversing these transformations,we renumber the simplices in the order that they are created,so thateach gvspl i (a i)splits the vertex a i K i into two vertices a i i +1K i +1.As vertices may have different positions in the different models,we denote the position of j in M i as i j .To better approximate a surface model M at lower complexity levels,we initially associate with each (principal)2-simplex s an area a s equal to its triangle area in M .Then,as the model is simplified,wekeep constant the sum of areas a s associated with principal simplices within each manifold component.When2-simplices are eventually reduced to principal1-simplices and0-simplices,their associated areas will provide good estimates of the original component areas.3.3Vertex unification transformationThe transformation vunify(a i b i midp i):M i M i+1takes an arbitrary pair of vertices a i b i K i+1(simplex a i b i need not be present in K i+1)and merges them into a single vertex a i K i. Model M i is created from M i+1by updating each member of the tuple(K V D A)as follows:K:References to b i in all simplices of K are replaced by refer-ences to a i.More precisely,each simplex s in star(b i)K i+1is replaced by simplex(s b i)a i,which we call the ancestor simplex of s.If this ancestor simplex already exists,s is deleted.V:Vertex b is deleted.For simplicity,the position of the re-maining(unified)vertex is set to either the midpoint or is left unchanged.That is,i a=(i+1a+i+1b)2if the boolean parameter midp i is true,or i a=i+1a otherwise.D:Materials are carried through as expected.So,if after the vertex unification an ancestor simplex(s b i)a i K i is a new principal simplex,it receives its material from s K i+1if s is a principal simplex,or else from the single parent s a i K i+1 of s.A:To maintain the initial areas of manifold components,the areasa s of deleted principal simplices are redistributed to manifold-adjacent neighbors.More concretely,the area of each princi-pal d-simplex s deleted during the K update is distributed toa manifold-adjacent d-simplex not in star(a ib i).If no suchneighbor exists and the ancestor of s is a principal simplex,the area a s is distributed to that ancestor simplex.Otherwise,the manifold component(star(a i b i))of s is being squashed be-tween two other manifold components,and a s is discarded. 3.4Generalized vertex split transformation Constructing the PSC representation involves recording the infor-mation necessary to perform the inverse of each vunify i.This inverse is the generalized vertex split gvspl i,which splits a0-simplex a i to introduce an additional0-simplex b i.(As mentioned previously, renumbering of simplices implies b i i+1,so index b i need not be stored explicitly.)Each gvspl i record has the formgvspl i(a i C K i midp i()i C D i C A i)and constructs model M i+1from M i by updating the tuple (K V D A)as follows:K:As illustrated in Figure4,any simplex adjacent to a i in K i can be the vunify result of one of four configurations in K i+1.To construct K i+1,we therefore replace each ancestor simplex s star(a i)in K i by either(1)s,(2)(s a i)i+1,(3)s and(s a i)i+1,or(4)s,(s a i)i+1and s i+1.The choice is determined by a split code associated with s.Thesesplit codes are stored as a code string C Ki ,in which the simplicesstar(a i)are sortedfirst in order of increasing dimension,and then in order of increasing simplex id,as shown in Figure5. V:The new vertex is assigned position i+1i+1=i ai+()i.Theother vertex is given position i+1ai =i ai()i if the boolean pa-rameter midp i is true;otherwise its position remains unchanged.D:The string C Di is used to assign materials d s for each newprincipal simplex.Simplices in C Di ,as well as in C Aibelow,are sorted by simplex dimension and simplex id as in C Ki. A:During reconstruction,we are only interested in the areas a s fors01(K).The string C Ai tracks changes in these areas.Figure4:Effects of split codes on simplices of various dimensions.code string:41422312{}Figure5:Example of split code encoding.3.5PropertiesLevels of detail A graphics application can efficiently transitionbetween models M1M n at runtime by performing a sequence ofvunify or gvspl transformations.Our current research prototype wasnot designed for efficiency;it attains simplification rates of about6000vunify/sec and refinement rates of about5000gvspl/sec.Weexpect that a careful redesign using more efficient data structureswould significantly improve these rates.Geomorphs As in the PM representation,there exists a corre-spondence between the vertices of the models M1M n.Given acoarser model M c and afiner model M f,1c f n,each vertexj K f corresponds to a unique ancestor vertex f c(j)K cfound by recursively traversing the ancestor simplex relations:f c(j)=j j cf c(a j1)j cThis correspondence allows the creation of a smooth visual transi-tion(geomorph)M G()such that M G(1)equals M f and M G(0)looksidentical to M c.The geomorph is defined as the modelM G()=(K f V G()D f A G())in which each vertex position is interpolated between its originalposition in V f and the position of its ancestor in V c:Gj()=()fj+(1)c f c(j)However,we must account for the special rendering of principalsimplices of dimension0and1(Section3.1).For each simplexs01(K f),we interpolate its area usinga G s()=()a f s+(1)a c swhere a c s=0if s01(K c).In addition,we render each simplexs01(K c)01(K f)using area a G s()=(1)a c s.The resultinggeomorph is visually smooth even as principal simplices are intro-duced,removed,or change dimension.The accompanying video demonstrates a sequence of such geomorphs.Progressive transmission As with PM’s,the PSC representa-tion can be progressively transmitted by first sending M 1,followed by the gvspl records.Unlike the base mesh of the PM,M 1always consists of a single vertex,and can therefore be sent in a fixed-size record.The rendering of lower-dimensional simplices as spheres and cylinders helps to quickly convey the overall shape of the model in the early stages of transmission.Model compression Although PSC gvspl are more general than PM vsplit transformations,they offer a surprisingly concise representation of M .Table 1lists the average number of bits re-quired to encode each field of the gvspl records.Using arithmetic coding [30],the vertex id field a i requires log 2i bits,and the boolean parameter midp i requires 0.6–0.9bits for our models.The ()i delta vector is quantized to 16bitsper coordinate (48bits per),and stored as a variable-length field [7,13],requiring about 31bits on average.At first glance,each split code in the code string C K i seems to have 4possible outcomes (except for the split code for 0-simplex a i which has only 2possible outcomes).However,there exist constraints between these split codes.For example,in Figure 5,the code 1for 1-simplex id 1implies that 2-simplex id 1also has code 1.This in turn implies that 1-simplex id 2cannot have code 2.Similarly,code 2for 1-simplex id 3implies a code 2for 2-simplex id 2,which in turn implies that 1-simplex id 4cannot have code 1.These constraints,illustrated in the “scoreboard”of Figure 6,can be summarized using the following two rules:(1)If a simplex has split code c12,all of its parents havesplit code c .(2)If a simplex has split code 3,none of its parents have splitcode 4.As we encode split codes in C K i left to right,we apply these two rules (and their contrapositives)transitively to constrain the possible outcomes for split codes yet to be ing arithmetic coding with uniform outcome probabilities,these constraints reduce the code string length in Figure 6from 15bits to 102bits.In our models,the constraints reduce the code string from 30bits to 14bits on average.The code string is further reduced using a non-uniform probability model.We create an array T [0dim ][015]of encoding tables,indexed by simplex dimension (0..dim)and by the set of possible (constrained)split codes (a 4-bit mask).For each simplex s ,we encode its split code c using the probability distribution found in T [s dim ][s codes mask ].For 2-dimensional models,only 10of the 48tables are non-trivial,and each table contains at most 4probabilities,so the total size of the probability model is small.These encoding tables reduce the code strings to approximately 8bits as shown in Table 1.By comparison,the PM representation requires approximately 5bits for the same information,but of course it disallows topological changes.To provide more intuition for the efficiency of the PSC repre-sentation,we note that capturing the connectivity of an average 2-manifold simplicial complex (n vertices,3n edges,and 2n trian-gles)requires ni =1(log 2i +8)n (log 2n +7)bits with PSC encoding,versus n (12log 2n +95)bits with a traditional one-way incidence graph representation.For improved compression,it would be best to use a hybrid PM +PSC representation,in which the more concise PM vertex split encoding is used when the local neighborhood is an orientableFigure 6:Constraints on the split codes for the simplices in the example of Figure 5.Table 1:Compression results and construction times.Object#verts Space required (bits/n )Trad.Con.n K V D Arepr.time a i C K i midp i (v )i C D i C Ai bits/n hrs.drumset 34,79412.28.20.928.1 4.10.453.9146.1 4.3destroyer 83,79913.38.30.723.1 2.10.347.8154.114.1chandelier 36,62712.47.60.828.6 3.40.853.6143.6 3.6schooner 119,73413.48.60.727.2 2.5 1.353.7148.722.2sandal 4,6289.28.00.733.4 1.50.052.8123.20.4castle 15,08211.0 1.20.630.70.0-43.5-0.5cessna 6,7959.67.60.632.2 2.50.152.6132.10.5harley 28,84711.97.90.930.5 1.40.453.0135.7 3.52-dimensional manifold (this occurs on average 93%of the time in our examples).To compress C D i ,we predict the material for each new principalsimplex sstar(a i )star(b i )K i +1by constructing an ordered set D s of materials found in star(a i )K i .To improve the coding model,the first materials in D s are those of principal simplices in star(s )K i where s is the ancestor of s ;the remainingmaterials in star(a i )K i are appended to D s .The entry in C D i associated with s is the index of its material in D s ,encoded arithmetically.If the material of s is not present in D s ,it is specified explicitly as a global index in D .We encode C A i by specifying the area a s for each new principalsimplex s 01(star(a i )star(b i ))K i +1.To account for this redistribution of area,we identify the principal simplex from which s receives its area by specifying its index in 01(star(a i ))K i .The column labeled in Table 1sums the bits of each field of the gvspl records.Multiplying by the number n of vertices in M gives the total number of bits for the PSC representation of the model (e.g.500KB for the destroyer).By way of compari-son,the next column shows the number of bits per vertex required in a traditional “IndexedFaceSet”representation,with quantization of 16bits per coordinate and arithmetic coding of face materials (3n 16+2n 3log 2n +materials).4PSC CONSTRUCTIONIn this section,we describe a scheme for iteratively choosing pairs of vertices to unify,in order to construct a PSC representation.Our algorithm,a generalization of [13],is time-intensive,seeking high quality approximations.It should be emphasized that many quality metrics are possible.For instance,the quadric error metric recently introduced by Garland and Heckbert [9]provides a different trade-off of execution speed and visual quality.As in [13,20],we first compute a cost E for each candidate vunify transformation,and enter the candidates into a priority queueordered by ascending cost.Then,in each iteration i =n 11,we perform the vunify at the front of the queue and update the costs of affected candidates.4.1Forming set of candidate vertex pairs In principle,we could enter all possible pairs of vertices from M into the priority queue,but this would be prohibitively expensive since simplification would then require at least O(n2log n)time.Instead, we would like to consider only a smaller set of candidate vertex pairs.Naturally,should include the1-simplices of K.Additional pairs should also be included in to allow distinct connected com-ponents of M to merge and to facilitate topological changes.We considered several schemes for forming these additional pairs,in-cluding binning,octrees,and k-closest neighbor graphs,but opted for the Delaunay triangulation because of its adaptability on models containing components at different scales.We compute the Delaunay triangulation of the vertices of M, represented as a3-dimensional simplicial complex K DT.We define the initial set to contain both the1-simplices of K and the subset of1-simplices of K DT that connect vertices in different connected components of K.During the simplification process,we apply each vertex unification performed on M to as well in order to keep consistent the set of candidate pairs.For models in3,star(a i)has constant size in the average case,and the overall simplification algorithm requires O(n log n) time.(In the worst case,it could require O(n2log n)time.)4.2Selecting vertex unifications fromFor each candidate vertex pair(a b),the associated vunify(a b):M i M i+1is assigned the costE=E dist+E disc+E area+E foldAs in[13],thefirst term is E dist=E dist(M i)E dist(M i+1),where E dist(M)measures the geometric accuracy of the approximate model M.Conceptually,E dist(M)approximates the continuous integralMd2(M)where d(M)is the Euclidean distance of the point to the closest point on M.We discretize this integral by defining E dist(M)as the sum of squared distances to M from a dense set of points X sampled from the original model M.We sample X from the set of principal simplices in K—a strategy that generalizes to arbitrary triangulated models.In[13],E disc(M)measures the geometric accuracy of disconti-nuity curves formed by a set of sharp edges in the mesh.For the PSC representation,we generalize the concept of sharp edges to that of sharp simplices in K—a simplex is sharp either if it is a boundary simplex or if two of its parents are principal simplices with different material identifiers.The energy E disc is defined as the sum of squared distances from a set X disc of points sampled from sharp simplices to the discontinuity components from which they were sampled.Minimization of E disc therefore preserves the geom-etry of material boundaries,normal discontinuities(creases),and triangulation boundaries(including boundary curves of a surface and endpoints of a curve).We have found it useful to introduce a term E area that penalizes surface stretching(a more sophisticated version of the regularizing E spring term of[13]).Let A i+1N be the sum of triangle areas in the neighborhood star(a i)star(b i)K i+1,and A i N the sum of triangle areas in star(a i)K i.The mean squared displacement over the neighborhood N due to the change in area can be approx-imated as disp2=12(A i+1NA iN)2.We let E area=X N disp2,where X N is the number of points X projecting in the neighborhood. To prevent model self-intersections,the last term E fold penalizes surface folding.We compute the rotation of each oriented triangle in the neighborhood due to the vertex unification(as in[10,20]).If any rotation exceeds a threshold angle value,we set E fold to a large constant.Unlike[13],we do not optimize over the vertex position i a, but simply evaluate E for i a i+1a i+1b(i+1a+i+1b)2and choose the best one.This speeds up the optimization,improves model compression,and allows us to introduce non-quadratic energy terms like E area.5RESULTSTable1gives quantitative results for the examples in thefigures and in the video.Simplification times for our prototype are measured on an SGI Indigo2Extreme(150MHz R4400).Although these times may appear prohibitive,PSC construction is an off-line task that only needs to be performed once per model.Figure9highlights some of the benefits of the PSC representa-tion.The pearls in the chandelier model are initially disconnected tetrahedra;these tetrahedra merge and collapse into1-d curves in lower-complexity approximations.Similarly,the numerous polyg-onal ropes in the schooner model are simplified into curves which can be rendered as line segments.The straps of the sandal model initially have some thickness;the top and bottom sides of these straps merge in the simplification.Also note the disappearance of the holes on the sandal straps.The castle example demonstrates that the original model need not be a mesh;here M is a1-dimensional non-manifold obtained by extracting edges from an image.6RELATED WORKThere are numerous schemes for representing and simplifying tri-angulations in computer graphics.A common special case is that of subdivided2-manifolds(meshes).Garland and Heckbert[12] provide a recent survey of mesh simplification techniques.Several methods simplify a given model through a sequence of edge col-lapse transformations[10,13,14,20].With the exception of[20], these methods constrain edge collapses to preserve the topological type of the model(e.g.disallow the collapse of a tetrahedron into a triangle).Our work is closely related to several schemes that generalize the notion of edge collapse to that of vertex unification,whereby separate connected components of the model are allowed to merge and triangles may be collapsed into lower dimensional simplices. Rossignac and Borrel[21]overlay a uniform cubical lattice on the object,and merge together vertices that lie in the same cubes. Schaufler and St¨u rzlinger[22]develop a similar scheme in which vertices are merged using a hierarchical clustering algorithm.Lue-bke[18]introduces a scheme for locally adapting the complexity of a scene at runtime using a clustering octree.In these schemes, the approximating models correspond to simplicial complexes that would result from a set of vunify transformations(Section3.3).Our approach differs in that we order the vunify in a carefully optimized sequence.More importantly,we define not only a simplification process,but also a new representation for the model using an en-coding of gvspl=vunify1transformations.Recent,independent work by Schmalstieg and Schaufler[23]de-velops a similar strategy of encoding a model using a sequence of vertex split transformations.Their scheme differs in that it tracks only triangles,and therefore requires regular,2-dimensional trian-gulations.Hence,it does not allow lower-dimensional simplices in the model approximations,and does not generalize to higher dimensions.Some simplification schemes make use of an intermediate vol-umetric representation to allow topological changes to the model. He et al.[11]convert a mesh into a binary inside/outside function discretized on a three-dimensional grid,low-passfilter this function,。
X-ray Photoelectron Spectroscopy
200
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1.X光电子峰的命名及非S态双峰结构
X光电子的命名按光电子发射的轨道能谱项名称而命名, 即用主量子数n,角量子数l,总角动量j来描述:
主量子数 角量子数 n l=0,1,2…n-1 (s,p,d,…) 总角动量 j=| l± ½ | 能谱项 nlj 能级符号
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峰强;
(3)内量子数J大的 峰比J小的峰强; ( J = L±S ;自旋 裂分峰)
• 定性分析 • (1) 先找出C 1s、O 1s 峰 • (2)找出主峰位置,注意自旋双峰,如 p1/2,3/2;d3/2,5/2;f5/2,f7/2,并注 意两峰的强度比 • (3)与手册对照 • Handbook of X-ray Photoelectron Spectroscopy, Perkin-Elmer Corporation, 1992
• • • • XPS- X-ray Photoelectron Spectroscopy ESCA Electron Spectroscopy for Chemical Analysis UPS Ultraviolet Photoelectron Spectroscopy PES Photoemission Spectroscopy
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Take x0 , . . . , xl as homogeneous coordinates in P . With the notation of the previous section, suppose mj = (m1j , . . . , mnj ), j = 0, . . . , and consider the (n + 1) × ( + 1) matrix 1 1 ... 1 m10 m11 . . . m1 A+ = . . . . . . . . . . mn0 mn1 . . . mn Observe that if u ∈ Z +1 , then we may write u uniquely as u = u+ − u− , where u+ , u− ∈ N +1 , but u+ and u− have no non-zero components in common. For instance, if u = (1, −2, 1, 0), then u+ = (1, 0, 1, 0) and u− = (0, 2, 0, 0) (Sottile’s notation). We therefore have: Theorem 1.4 ([8], Corollary 2.3) I = xu − xu |u ∈ ker(A+ ) and u ∈ Z
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161
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163
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25
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27
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29
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33
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3、字母点名
4、找亲戚
教师把有大小写字母的印刷体和手写体的卡片 发给学生, 教师读一个字母, 持有该字母卡( 一个是 印刷体大写字母, 一个是印刷体小写字母, 一个是手 写体大写, 一个是手写体小写字母) 的四个学生立刻 走到黑板前, 按印刷体大写、小写、手写体大写、小写 的顺序排成一列。
5、唱字母歌
小学英语字母教学研究
詹蓓
主要内容
1
字母教学意义
字母教学内容 字母教学建议
2 3 4 5
字母教学活动
字母教学难点
字母教学的目标与要求
能够听、说、读、写26个字母;
能认字母的音和形,能读准字母;
能按正确的笔顺和规格书写;
能按顺序背诵和默写字母; 能初步掌握字母在单词中的发音; 初步了解与26个字母相关的音素; 为进一步学习单词的读音和拼读打下基础。
身份(证) 国际长途直播 国际奥委会 智商
IT
信息技术
RMB
SAR TV
人民币
特别行政区 电视;电视机
MBA 工商管理硕士 NBA 全美篮球协会
英文缩略字母及其含义
UFO 不明飞行物 p.m. 下午 cm 厘米 mm 毫米 kg 公斤;千克 km 公里;千米
UK
UN
K-9可选配件,微维克斯硬度试验机剪子订单号型号及描述说明书
G
steel ball 1471N(150kgf) beryllium copper, phosphor bronze
H
1/8”
588.4N(60kgf) Bearing metal
E
diameter 980.7N(100kgf)
K
steel ball 1471N(150kgf)
L
1/4”
588.4N(60kgf) Plastics, lead
50x50mm travel stage
Dimensions: 4.92x4.92”(125x125mm) Minimum reading: 0.01mm 810-012
Clamping devices (Vises)
Vise Max. opening: 1.77”(45mm) Standard for the MH series. 810-016
Indenters
Order No. 19BAA061 19BAA058 19BAA062 19BAA059 19BAA060
Type Knoop Indenter Vickers Indenter Knoop Indenter Vickers Indenter Vickers Indenter
Model H, HM Standard Series H, HM Standard Series MVK-H2, H3, HM114 MVK-H2, H3, HM114 HV, AVK-C Series
Micro-Vickers/Vickers Hardness Testing Machine
Test Blocks
Order No. 64BAA173 64BAA174 64BAA175 64BAA176 64BAA177 64BAA178 64BAA179 64BAA180 64BAA181 64BAA182 64BAA183 64BAA184 64BAA185 64BAA186 64BAA187 64BAA188 64BAA189 64BAA190 64BAA191 64BAA192 64BAA193 64BAA194 64BAA195 64BAA196 64BAA197 64BAA198 64BAA199 64BAA200 64BAA201 64BAA202 64BAA203 64BAA204 64BAA205 64BAA206 64BAA207 64BAA208 64BAA209 64BAA210 64BAA211 64BAA212 64BAA213 64BAA214 64BAA215 64BAA216 64BAA217 64BAA218 64BAA219 64BAA220
CJK汉字拼音表
汉字拼音音1音2音3音4音5音6音7音8d s cdàn/shàn/chǎn(dan4/shan4/chan3)bānɡ(bang1)bōu/ou5(ou1/ou5)o owù/wò/ě(wu4/wo4/e3)w w eōu(ou1)ozōnɡ(zong1)zlǔn/lùn(lun3/lun4)l lɡānɡ(gang1)gláo(lao2)lshàn/chǎn(shan4/chan3)s cwéi/wěi(wei2/wei3)w wxínɡ(xing2)xhuà(hua4)hxiān/yǎn/jìn(xian1/yan3/jin4)x y jzé/cè(ze2/ce4)z cɡuī/zuī(gui1/zui1)g zmǎn(man3)msong2(song2)slì(li4)lwéi(wei2)wdié/dì(die2/di4)d dhū/wú(hu1/wu2)h wlán(lan2)lxīn/qiàn(xin1/qian4)x qkōu(kou1)kc z zchōu/zǒu/zhū(chou1/zou3/zhu1)wěi(wei3)wxiàn(xian4)xhū/wǔ/méi(hu1/wu3/mei2)h w mz c t zzhūn/chún/tún/zhuō(zhun1/chun2/tun2/zhuo1)yǎn(yan3)yjiā(jia1)jzhì(zhi4)zmàn/ǒu/wàn(man4/ou3/wan4)m o wtuán/zhuān(tuan2/zhuan1)t zpèi(pei4)pɡuó(guo2)gwú(wu2)wōu/òu(ou1/ou4)o oxún/qián(xun2/qian2)x qchóu(chou2)cc d cchǎn/dǎn/chàn(chan3/dan3/chan4)hé(he2)hhuī/xūn(hui1/xun1)h xsānɡ(sang1)slú(lu2)ldànɡ(dang4)dxún(xun2)xyíng(ying2)ylàn(lan4)lsuì(sui4)sjì(ji4)jxián/jiàn(xian2/jian4)x jdài(dai4)dquè/hú(que4/hu2)q hdá(da2)dlán(lan2)lɡōnɡ(gong1)gtuán(tuan2)tchá(cha2)cxún(xun2)xdǎn(dan3)dyīn(yin1)ytīnɡ(ting1)thuán/huàn/wàn(huan2/huan4/wan4)h h wq q z qiàn/qīnɡ/zhēnɡ(qian4/qing1/zheng1)chēn/shēn(chen1/shen1)c szhǔn/zhùn(zhun3/zhun4)z zyǎn/yǐn(yan3/yin3)y ymò(mo4)mr x s rǎnɡ/xiānɡ/sānɡ(rang3/xiang1/sang1)màn(man4)mliǎnɡ(liang3)lpín/pínɡ(pin2/ping2)p pyì(yi4)ydōnɡ(dong1)dxū/xǔ(xu1/xu3)x xxuān(xuan1)xjiàn(jian4)jhé(he2)hhěn(hen3)hzhì(zhi4)zlián(lian2)lé/ě(e2/e3)e eyīn(yin1)yshì/dì(shi4/di4)s dyǐn(yin3)yhuì(hui4)hshènɡ(sheng4)smǔ(mu3)mxié(xie2)xbà(ba4)bqí(qi2)qhuàn/huán(huan4/huan2)h hzhì(zhi4)zxún(xun2)xmào(mao4)mnónɡ(nong2)nɡānɡ/ɡōnɡ(gang1/gong1)g gyì(yi4)ywéi(wei2)wpī/bī/bǐ(pi1/bi1/bi3)p b b chǎnɡ(chang3)cjīn/yǐn/yín(jin1/yin3/yin2)j y y lún/fēn(lun2/fen1)l fshù/xù(shu4/xu4)s xlú(lu2)lh s s huán/shēn/shén(huan2/shen1/shen2)zhāo(zhao1)zmǔ(mu3)myónɡ/yánɡ(yong2/yang2)y ymài(mai4)mdù(du4)dhónɡ(hong2)hpiān(pian1)ppénɡ/bènɡ(peng2/beng4)p bd c d duì/chún/duò(dui4/chun2/duo4)bō(bo1)bzhēn/qián(zhen1/qian2)z qxiàn(xian4)xhóu(hou2)hɡē(ge1)glv4(lv4)ljiàn(jian4)jwēnɡ(weng1)wwèi(wei4)wpiě(pie3)pxǐ(xi3)xsù(su4)shēi(hei1)hlín(lin2)lsuì(sui4)sjiān/xì/mǎ(jian1/xi4/ma3)j x m ɡē(ge1)gyīn(yin1)yɡāi/ái/qí(gai1/ai2/qi2)g a q jī(ji1)jtuí(tui2)twěi/xuē(wei3/xue1)w xdí(di2)dwěi(wei3)wtái(tai2)tbì(bi4)bài/hé(ai4/he2)a hyì/yē/èn(yi4/ye1/en4)y y epī(pi1)plónɡ/zǎnɡ(long2/zang3)l zjiōnɡ(jiong1)jshēn(shen1)stú(tu2)tlánɡ/liánɡ(lang2/liang2)l lfēi(fei1)fhuō(huo1)hxiá(xia2)xlín(lin2)lhuān(huan1)hjiè(jie4)jjū/qú/ɡǒu(ju1/qu2/gou3)j q gtuó(tuo2)tzhào(zhao4)zwéi(wei2)wqí/yì(qi2/yi4)q ylà(la4)lliàn(lian4)ljì(ji4)jwēnɡ(weng1)wxián(xian2)xjì(ji4)jxǐ/xī(xi3/xi1)x xzhēn(zhen1)zjué/ɡuī(jue2/gui1)j gchú(chu2)cbū/pū/pú/bǔ(bu1/pu1/pu2/bu3)b p p b yǎn(yan3)yyuè(yue4)yxiān(xian1)xzhuó(zhuo2)zfán(fan2)fmóu(mou2)mxiè(xie4)xyǐ/qǐ(yi3/qi3)y qchǔ(chu3)czhòu/zhū(zhou4/zhu1)z zwāi(wai1)whǎn(han3)hhǎn(han3)hzhòu(zhou4)zɡānɡ(gang1)gkuǎi(kuai3)ksǒnɡ(song3)ssǒnɡ(song3)sɡānɡ(gang1)gkuì(kui4)ktà(ta4)tlóu(lou2)lcǎn/shān/cēn(can3/shan1/cen1)c s cchōu(chou1)cbà/bēi(ba4/bei1)b bbà/bēi(ba4/bei1)b bz c c zzhuān/chuán/chún/zhuǎn(zhuan1/chuan2/chun2/zhuan3) qiónɡ(qiong2)qkuì/huì(kui4/hui4)k hkuì/huì(kui4/hui4)k hxīn(xin1)xyàn(yan4)yqínɡ(qing2)qqínɡ(qing2)qzǔ(zu3)zshàn(shan4)syé/yá(ye2/ya2)y ypō(po1)pshàn(shan4)szhuō(zhuo1)zshàn(shan4)sjué(jue2)jchuài(chuai4)czhènɡ(zheng4)zchuài(chuai4)czhènɡ(zheng4)zyú(yu2)yyìn(yin4)ychūn(chun1)cqiū(qiu1)qyú(yu2)yténɡ(teng2)tshī(shi1)sjiāo(jiao1)jliè(lie4)ljīnɡ(jing1)jjú(ju2)jtī(ti1)tpì(pi4)pyǎn(yan3)y吖ā/yā(a1/ya1)a y啊ā/á/ǎ/à/ɑ/è(a1/a2/a3/a4/a5/e4)a a a a a eā/xiànɡ(a1/xiang4)a x锕ā(a1)aā(a1)aā(a1)a錒ā/kē(a1/ke1)a k嗄á/ɑ/shà/xià(a2/a5/sha4/xia4)a a s xāi(ai1)a哎āi(ai1)a哀āi(ai1)a埃āi/zhì(ai1/zhi4)a zāi(ai1)a唉āi/ǎi/ài(ai1/ai3/ai4)a a a㶼āi/xī(ai1/xi1)a xa a e e e e x 欸āi/ǎi/ēi/éi/ěi/èi/xiè(ai1/ai3/ei1/ei2/ei3/ei4/xie4)āi(ai1)a溾āi(ai1)aāi(ai1)a锿āi(ai1)aāi(ai1)a鎄āi(ai1)a挨āi/ái(ai1/ai2)a aái(ai2)a捱āi/ái(ai1/ai2)a a啀ái(ai2)a皑ái(ai2)a娾ái/ǎi/è(ai2/ai3/e4)a a e凒yí(yi2)y嵦ái/kǎi(ai2/kai3)a k溰ái(ai2)a㱯ái(ai2)a嘊ái(ai2)a敱ái/zhú(ai2/zhu2)a z皚ái(ai2)aái(ai2)aái(ai2)aái(ai2)a癌ái/yán(ai2/yan2)a yái(ai2)aái(ai2)a䶣ái/ɡái(ai2/gai1)a g毐ǎi(ai3)a昹ǎi(ai3)a㢊ǎi/yǐ(ai3/yi3)a y矮ǎi(ai3)aǎi(ai3)aǎi(ai3)aǎi/yá(ai3/ya2)a y躷ǎi(ai3)aǎi(ai3)a濭ǎi/kài/kè(ai3/kai4/ke4)a k k 䨠ǎi(ai3)a䑂ǎi(ai3)a藹ǎi(ai3)a霭ǎi(ai3)a譪ài(ai4)a靄ǎi(ai3)a艾ài/yì(ai4/yi4)a y伌ài(ai4)aài(ai4)aài(ai4)a㘷ài(ai4)a㤅ài/jì/xì(ai4/ji4/xi4)a j x ài(ai4)a㕌ài(ai4)a砹ài(ai4)a爱ài(ai4)a硋ài(ai4)aài(ai4)a㗒ài(ai4)a隘ài/è(ai4/e4)a e塧ài(ai4)a碍ài(ai4)aài(ai4)aài(ai4)a嗳āi/ǎi/ài(ai1/ai3/ai4)a a a 嗌ài/wò/yì(ai4/wo4/yi4)a w y 愛ài(ai4)a㾢ài(ai4)aài/xì(ai4/xi4)a x嫒ài(ai4)a瑷ài(ai4)a叆ài(ai4)a暧ài/nuǎn(ai4/nuan3)a nài(ai4)a䔽ài(ai4)a䝽ài(ai4)a䅬ài(ai4)a僾ài(ai4)a壒ài(ai4)aài(ai4)a鴱ài(ai4)a薆ài(ai4)a㿄ài(ai4)aài(ai4)a懓ài(ai4)a嬡ài(ai4)a璦ài(ai4)aài(ai4)aài(ai4)aài/kē(ai4/ke1)a kài(ai4)a賹ài/yì(ai4/yi4)a y曖ài(ai4)aài(ai4)aài(ai4)aài(ai4)a瞹ài(ai4)aài(ai4)a馤ài(ai4)a皧ài(ai4)aài/chī(ai4/chi1)a c礙ài/yí(ai4/yi2)a yài(ai4)aài(ai4)aài(ai4)a鑀ài(ai4)aa n y y y 譺ài/nǐ/yí/yǐ/yì(ai4/ni3/yi2/yi3/yi4)ài(ai4)aài(ai4)a鱫ɑi(ai5)a安ān(an1)aān(an1)a㸩ān(an1)a侒ān/ǎn(an1/an3)a a䢿ān(an1)a峖ān(an1)a桉ān/àn(an1/an4)a a㫨ān(an1)a氨ān(an1)a㞄ān(an1)a庵ān/è/yǎn(an1/e4/yan3)a e y䀂ān(an1)a谙ān(an1)aān(an1)a葊ān(an1)a萻ān(an1)a啽ān/án(an1/an2)a a媕ān/è/yǎn(an1/e4/yan3)a e ya a y y y 䅖ān/ǎn/yān/yǎn/yè(an1/an3/yan1/yan3/ye4)腤ān(an1)a痷ān/è/yè(an1/e4/ye4)a e y蓭ān(an1)aān(an1)a誝ān(an1)a鞍ān(an1)aān(an1)aān(an1)a鞌ān(an1)a盦ān(an1)aān(an1)a諳ān/tǒu(an1/tou3)a ta a a y y 闇ān/ǎn/àn/yīn/yǐn(an1/an3/an4/yin1/yin3)馣ān(an1)a鮟ān/àn(an1/an4)a a盫ān(an1)aān/hàn(an1/han4)a hān/àn(an1/an4)a aān(an1)a鵪ān/yā(an1/ya1)a y䨄yàn(yan4)y韽ān(an1)a鶕ān(an1)aān(an1)a䳺yàn(yan4)yān(an1)aán(an2)a雸án(an2)aán(an2)aán(an2)a䜙án/è(an2/e4)a e垵ǎn(an3)a俺ǎn/yàn(an3/yan4)a yǎn/yǎn(an3/yan3)a y埯ǎn/yǎn(an3/yan3)a y唵ǎn/n/nɡ(an3/n5/ng5)a n n铵ǎn(an3)a隌ǎn(an3)a揞ǎn/yàn/yè(an3/yan4/ye4)a y y晻ǎn/àn/yǎn(an3/an4/yan3)a a yǎn/yǎn(an3/yan3)a y㽢ǎn(an3)a罯ǎn(an3)a銨ǎn(an3)a㜝ǎn/yǎn(an3/yan3)a yǎn(an3)aǎn(an3)aǎn(an3)aa a h j 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pbào(bao4)b虣bào(bao4)b鮑bāo/bào/pāo(bao1/bao4/pao1)b b p曓bào(bao4)bbào(bao4)b儤bào(bao4)bbào(bao4)bbào(bao4)b爆bào/bó(bao4/bo2)b bbào(bao4)b忁bào(bao4)b䤖bào(bao4)bbào(bao4)bbáo/bào(bao2/bao4)b b鑤bào(bao4)b萡bo(bo5)b陂bēi/bì/pí/pō(bei1/bi4/pi2/po1)b b p p杯bēi(bei1)bb b b b p 卑bān/bēi/bǐ/bì/pí(ban1/bei1/bi3/bi4/pi2)盃bēi(bei1)bbēi(bei1)bbēi(bei1)b桮bēi(bei1)bbēi(bei1)b揹bēi(bei1)b悲bēi(bei1)bbēi(bei1)bbēi(bei1)b碑bēi(bei1)b㽡bēi(bei1)b㗗bēi(bei1)bbēi(bei1)b鹎bēi(bei1)bbēi(bei1)bbēi(bei1)b鵯bēi(bei1)bbēi(bei1)b䎱bà/bēi(ba4/bei1)b bbēi(bei1)b䥯bà/bēi(ba4/bei1)b bbēi(bei1)b北běi/bèi(bei3/bei4)b b北běi(bei3)b㤳běi(bei3)bběi(bei3)b鉳běi(bei3)bběi(bei3)b䋳běi(bei3)b贝bèi(bei4)bbèi/pō(bei4/po1)b p孛bèi/bó(bei4/bo2)b b邶bèi(bei4)b貝bèi(bei4)b狈bèi(bei4)b苝bèi(bei4)bbèi(bei4)bbèi/pèi(bei4/pei4)b pbèi/lù(bei4/lu4)b lbèi(bei4)b昁bèi(bei4)b㸬bèi(bei4)b牬bèi(bei4)b备bèi(bei4)b背bēi/bèi(bei1/bei4)b b钡bèi(bei4)bbèi(bei4)bbèi(bei4)bbèi(bei4)b俻bèi(bei4)b倍bèi/péi(bei4/pei2)b p狽bèi(bei4)b悖běi/bèi(bei3/bei4)b b被bèi/bì/pī/pì(bei4/bi4/pi1/pi4)b b p p 㛝bèi(bei4)b珼bèi(bei4)b梖bèi(bei4)bbèi(bei4)b鄁bèi(bei4)bbèi/fú(bei4/fu2)b f㫲bèi(bei4)b㔨bèi(bei4)b琲bèi(bei4)b辈bèi(bei4)b軰bèi(bei4)b備bèi(bei4)b僃bèi(bei4)bbèi(bei4)bbèi(bei4)b惫bèi(bei4)b焙bèi(bei4)b蓓bèi(bei4)b䔒bèi(bei4)b愂bèi(bei4)b碚bèi(bei4)b㻗bèi(bei4)b蛽bài(bai4)b禙bei(bei5)b㣁bèi(bei4)bbèi(bei4)bbèi(bei4)bbèi(bei4)b䟺bèi/pèi(bei4/pei4)b p骳bèi(bei4)b犕bèi(bei4)b㸢bèi(bei4)b誖bèi(bei4)b褙bèi(bei4)bbèi(bei4)bbèi(bei4)b輩bèi(bei4)b䩀bèi(bei4)b鋇bèi(bei4)b䰽bèi(bei4)bbèi(bei4)b憊bèi(bei4)bbèi(bei4)b糒bèi(bei4)bbèi(bei4)bbèi(bei4)bb b b f 鞴bài/bèi/bù/fú(bai4/bei4/bu4/fu2)㰆bèi(bei4)b㶔bèi(bei4)b鐾bèi(bei4)b呗bài/bei(bai4/bei5)b b唄bài/bei(bai4/bei5)b bbēn(ben1)b倴bēn/bèn(ben1/ben4)b b逩bēn/bèn(ben1/ben4)b b喯bēn/pèn(ben1/pen4)b p渀bēn/bèn(ben1/ben4)b bbēn(ben1)bb b b f f f l p 賁bān/bēn/bì/féi/fén/fèn/lù/pān(ban1/ben1/bi4/fei2/fen2/fen4/lu4/pan1)犇bēn(ben1)b锛bēn(ben1)b錛bēn(ben1)bbēn(ben1)bbēn(ben1)b本bēn/běn(ben1/ben3)b b夲běn/tāo(ben3/tao1)b t苯běn(ben3)b㡷běn(ben3)b奙běn(ben3)b畚běn(ben3)b翉běn(ben3)b楍běn(ben3)b㮺běn(ben3)bběn(ben3)b坌bèn(ben4)b㤓bèn(ben4)bbèn(ben4)bbèn(ben4)b捹bèn(ben4)b桳bèn(ben4)b笨bèn(ben4)bbèn(ben4)b㨧bèn(ben4)b䬱bèn(ben4)b㮥bèn/fàn(ben4/fan4)b f撪bèn(ben4)bbèn(ben4)bbèn(ben4)b輽bèn(ben4)bbèn(ben4)b伻bēnɡ(beng1)bbēnɡ(beng1)bbēnɡ(beng1)bbēnɡ/yònɡ(beng1/yong4)b y㔙bēnɡ(beng1)b挷pénɡ(peng2)pbēnɡ(beng1)b奟bēnɡ/kēnɡ(beng1/keng1)b k崩bēnɡ(beng1)bbēnɡ/hé(beng1/he2)b hbēnɡ(beng1)bb b b 绷bēnɡ/běnɡ/bènɡ(beng1/beng3/beng4)bēnɡ(beng1)b閍bēnɡ(beng1)b䑫bēnɡ(beng1)bbēnɡ(beng1)bb b p 絣bēnɡ/bīnɡ/pēnɡ(beng1/bing1/peng1)嵭bēnɡ(beng1)b傰bēnɡ/pénɡ(beng1/peng2)b p痭bēnɡ/bìnɡ/pénɡ(beng1/bing4/peng2)b b p 䙀běnɡ(beng3)bbēnɡ(beng1)bbēnɡ(beng1)b嘣bēnɡ(beng1)bbēnɡ(beng1)bbēnɡ(beng1)b綳bēnɡ(beng1)bbēnɡ/pénɡ(beng1/peng2)b p䨜bēnɡ(beng1)bbēnɡ(beng1)bb b b 繃bēnɡ/běnɡ/bènɡ(beng1/beng3/beng4)bēnɡ(beng1)b甭bénɡ/qì(beng2/qi4)b q㑟běnɡ(beng3)bběnɡ(beng3)bběnɡ(beng3)b埲bànɡ/běnɡ(bang4/beng3)b b菶běnɡ(beng3)bběnɡ(beng3)b琫běnɡ(beng3)b琣běnɡ/pěi(beng3/pei3)b pběnɡ/lèi(beng3/lei4)b lbānɡ/běnɡ(bang1/beng3)b bběnɡ(beng3)bběnɡ(beng3)b䋽běnɡ(beng3)b䩬běnɡ/fěnɡ(beng3/feng3)b f鞛běnɡ(beng3)bběnɡ(beng3)b䳞běnɡ(beng3)b泵bènɡ/liú/pìn(beng4/liu2/pin4)b l p 㼜ànɡ(ang4)abènɡ(beng4)bbènɡ(beng4)bb b p 跰bènɡ/bǐnɡ/pián(beng4/bing3/pian2)bènɡ(beng4)bbènɡ(beng4)b塴bènɡ(beng4)bbènɡ(beng4)bbènɡ(beng4)b㷯bènɡ(beng4)b甏bènɡ(beng4)b镚bènɡ(beng4)bbènɡ(beng4)b䭰bènɡ(beng4)bbènɡ(beng4)bbènɡ(beng4)bbènɡ(beng4)b蹦bènɡ(beng4)bbènɡ(beng4)b鏰bènɡ(beng4)bbènɡ(beng4)b䨻bènɡ(beng4)b皀bī/jí/xiānɡ(bi1/ji2/xiang1)b j x 屄bī(bi1)bbī(bi1)b悂bī/pī/pǐ(bi1/pi1/pi3)b p p 偪bī/fù(bi1/fu4)b f逼bī(bi1)b毴bī(bi1)b鈚bī/bǐ/pī(bi1/bi3/pi1)b b p bī(bi1)b楅bī(bi1)b榌pi(pi5)p㡙bī(bi1)bbī(bi1)bbī(bi1)b䫾bī/bì(bi1/bi4)b bbī(bi1)bbī(bi1)b豍bī/biǎn(bi1/bian3)b bbī(bi1)b䚜bēi/bī(bei1/bi1)b bbī(bi1)bbī(bi1)bbì(bi4)b鵖bī(bi1)b鲾bī(bi1)b鰏bī(bi1)b柲bì/bié(bi4/bie2)b b荸bí(bi2)bbí(bi2)b鼻bí(bi2)bpí(pi2)pbí(bi2)b嬶bi(bi5)b匕bǐ/pìn(bi3/pin4)b p比bǐ/bì/pí/pǐ(bi3/bi4/pi2/pi3)b b p p 㠲bǐ(bi3)b朼bǐ(bi3)b夶bǐ(bi3)b吡bǐ/bì/pǐ(bi3/bi4/pi3)b b p佊bǐ(bi3)b疕bǐ(bi3)b沘bǐ(bi3)bbǐ(bi3)b妣bǐ(bi3)b彼bǐ(bi3)b䃾bǐ(bi3)b柀bǐ(bi3)b䣥bǐ(bi3)b秕bǐ(bi3)bbǐ(bi3)b䏢bǐ(bi3)b䘡bǐ(bi3)b粊bì(bi4)b笔bǐ(bi3)b俾bēi/bǐ/bì/pì(bei1/bi3/bi4/pi4)b b b p 舭bǐ(bi3)b粃bǐ/pī(bi3/pi1)b p娝bǐ/pōu(bi3/pou1)b pbǐ(bi3)b啚bǐ/tú(bi3/tu2)b tbǐ(bi3)b筆bǐ(bi3)b㪏bǐ(bi3)bbǐ(bi3)bbǐ(bi3)b鄙bǐ(bi3)b聛bǐ(bi3)bbǐ(bi3)bbǐ(bi3)bbǐ(bi3)bbǐ(bi3)bbǐ(bi3)bbà/bǐ(ba4/bi3)b bbǐ(bi3)bbǐ(bi3)b币bì/yìn(bi4/yin4)b ybì(bi4)b必bì(bi4)bbì(bi4)bbèi/bì(bei4/bi4)b b毕bì(bi4)b闭bì(bi4)b㘩bì(bi4)b坒bì(bi4)bbì(bi4)b佖bì(bi4)bbì/pí(bi4/pi2)b p庇bì/pí/pǐ(bi4/pi2/pi3)b p p 㡀bì(bi4)b邲bì/biàn(bi4/bian4)b bbì(bi4)b诐bì(bi4)bbì/fèi/fú(bi4/fei4/fu2)b f f bì/fú(bi4/fu2)b fbì(bi4)b㧙bì/bié(bi4/bie2)b b苾bì/bié/mì(bi4/bie2/mi4)b b m 枈bì/pī(bi4/pi1)b p畀bì(bi4)b畁qí(qi2)qbì(bi4)b㘠bì(bi4)b怭bì(bi4)b㢰bì(bi4)b妼bì(bi4)b珌bì(bi4)b荜bì(bi4)b毖bì(bi4)b㿫bì(bi4)bbì(bi4)b哔bì(bi4)bbì(bi4)b疪bì(bi4)bbì(bi4)bbì(bi4)b。
定积分习题及答案
(A层次)1. 4.7. 兀f 。
2 s in x cos3 xdx ; r xdx -1✓5-4x ,e 2dx f 1 x ✓l +I n x ;10. f 一冗九x 4s in 汕; 冗13. f f-�dx; 4 Sill X 冗16. f 。
2产co sx dx ;冗第五章定积分2. f 。
a x 2✓a 2—x 2dx; 5.「I✓x dx +l ;8. f -o 2 x 2 + d 2xx + 2 ; 冗11. f� 冗4c os 4xdx ;14. 17. 2f14 Jn X`dx ;f 。
兀(xsinx)2dx ;冗19. f� ✓cosx-cos 3 xdx;20. f 。
4 smx dx · 1 + S lll . X , 22. 4If 0 2 xln l +x dx ; l -x25. f +00dx0 (1 + x 2 XI + xa \ (B层次)23. f +oo l +x 2 dx · -oo 1 +X 4' 心(a�o )。
3. 6.9. 厂dx1 X 飞l +x2 r dx`3 斤言-1;f。
冗✓1+ c os2xdx;3· 212 fs x sm xdx · ·-5 x 4 + 2x 2 + 1' 15. f 。
1 xa rct gxdx ; 18. {es in(lnx 雇21. 24. f 。
冗xs mx dx .1 +C OS 2X 冗f 。
2 ln sin x dx ;d y 1. 求由f 。
:e r dt+f x costd t=O所确定的隐函数对x 的导数odx 2. 当x 为何值时,函数I(x)= f x t e -t 2dt有极值?。
3.d厂cos矿t。
dx si n x(}Ix+l, x�14. 设八x )�{归,X > 1'求l。
勹(x )dx 。
2f x(a rc tg t) 2d t5. lirn 。
中韩语汉字对照表
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聚四氟乙烯材料力学性能参数表
1.聚四氟乙烯聚四氟乙烯是用于密封的氟塑料之一。
聚四氟乙烯以碳原子为骨架,氟原子对称而均匀地分布在它的周围,构成严密的屏障,使它具有非常宝贵的综合物理机械性能(表14—9)。
聚四氟乙烯对强酸、强碱、强氧化剂有很高的抗蚀性,即使温度较高,也不会发生作用,其耐腐蚀性能甚至超过玻璃、陶瓷、不锈钢以至金、铂,所以,素有“塑料王”之称。
除某些芳烃化合物能使聚四氟乙烯有轻微的溶胀外,对酮类、醇类等有机溶剂均有耐蚀性。
只有熔融态的碱金属及元素氟等在高温下才能对它起作用。
聚四氟乙烯的介电性能优异,绝缘强度及抗电弧性能也很突出,介质损耗角正切值很低,但抗电晕性能不好。
聚四氟乙烯不吸水、不受氧气、紫外线作用、耐候性好,在户外暴露3年,抗拉强度几乎保持不变,仅伸长率有所下降。
聚四氟乙烯薄膜与涂层由于有细孔,故能透过水和气体。
表14-9聚四氟乙烯性能聚四氟乙烯在200℃以上,开始极微量的裂解,即使升温到结晶体熔点327℃,仍裂解很少,每小时失重为万分之二。
但加热至400℃以上热裂解速度逐渐加快,产生有毒气体,因此,聚四氟乙烯烧结温度一般控制在375~380℃。
聚四氟乙烯分子间的范德华引力小,容易产生键间滑动,故聚四氟乙烯具有很低的摩擦系数及不粘性,摩擦系数在已知固体材料中是最低的。
聚四氟乙烯的导热系数小,该性能对其成型工艺及应用影响较大。
其不但导热性差,且线膨胀系数较大,加入填充剂可适当降低线膨胀系数。
在负荷下会发生蠕变现象,亦称作“冷流”,加入填充剂可减轻蠕变程度。
聚四氟乙烯可以添加不同的填充剂,选择的填充剂应基本满足下述要求:能耐380℃高温即四氟制品的烧结温度;与接触的介质不发生反应;与四氟树脂有良好的混入性;能改善四氟制品的耐磨性、冷流性、导热性及线膨胀系数等。
常用的填充剂有无碱无蜡玻璃纤维、石墨、碳纤维、MoS2、A123、CaF2、焦炭粉及各种金属粉。
如填充玻璃纤维或石墨,可提高四氟制品的耐磨、耐冷流性,填充MoS2可提高其润滑性,填充青铜、钼、镍、铝、银、钨、铁等,可改善导热性,填充聚酰亚胺或聚苯酯,可提高耐磨性,填充聚苯硫醚后能提高抗蠕变能力,保证尺寸稳定等。
9笔画的所有字
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福建省厦门市2024届高三下学期第二次质量检测试题 化学 含解析
厦门市2024届高三年级第二次质量检测化学试题本试卷共6页。
总分100分。
考试时间75分钟。
可能用到的相对原子质量:H 1 C 12 N 14 0 16 S 32 Cl 35.5 Zn 65一、选择题:本题共10小题,每小题4分,共40分。
每小题只有一个选项符合题目要求。
l.巴豆中含有巴豆素、蛋白质等。
《雷公炮炙论》中记载巴豆音的制备方法为“凡修事巴豆,浓碎,以麻油并酒等煮巴豆,研吾后用“。
下列说法错误的是A浓碎能提高反应速率C酒有利千巴豆素溶解Cl Cl2.常用作萃取剂。
下列说法错误是A含有的官能团有碳碳双键、碳氯键ClC与\=\互为同分异构体ClB.麻油屈于高分子化合物D.煮巴豆时蛋白质会变性B分子中叮建和7t键的个数比为5:1D 可用千萃取浪水中的浪3制取催化剂BCl 3的原理为:B 203+3C+3Cl 2 =2BCl 3+3CO 。
下列说法错误的是2s2pA基态碳原子价电子轨道表示式为[ill[ill]B.Cl 2中3p-3p 轨道重叠示意图为C.BC13分子的空间结构为平面三角形D.CO 电子式为:C 扫0:4."6HCl+2Na 3[ A g(Sp 山]=6NaCl+Ag 2沪+3St +3S02个+H 2S04+2H 20 "为定影液回收Ag 2S 的原理。
NA是阿伏加德罗常数的值。
下列说法正确的是A.36.Sg HCI 中电子数为8NAB 含lmol Na[ A g(Sp 山]的溶液中阳离子数为4N AC .lmol H 2S04中含有-OH 数为2NAD生成2.24LS02(已折算为标准状况)时,转移电子数为2N A5某电池的电解液部分微观结构如图,“一”表示微粒间存在较强静电作用。
M 、N 、W 、X 、Y 、Z为原子序数依次增大的短周期元素。
下列说法错误的是zz飞ZZN ::《:NA.未成对电子数:M>Y C.最简单氢化物的沸点:N>WB .电负性:N>Z>Y D.熔点:X 2N 3>XZ 36太阳能驱动NO 3和CO 2制备CO(NH山的装置如图。
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卖朋友速聘:自媒体人生存状态调查报告:超60%月营收不足万元
2015年下半载,互联网创业遭遇“资本寒冬”。
然而在自媒体领域,众多内容创业者却逆流而上,捷报频传。
先是吴晓波领衔的狮享家基金为一众优质大号注入资本,自媒体标杆“罗辑思维”也完成亿元级别B轮融资。
11月9日,知名媒体人范卫锋又宣布其创办的高樟资本将专注于自媒体产业投资,高调杀入战场。
此外,今日头条张一鸣宣布要为其平台上的优质头条号提供每月一万元保底收入,这样的新闻也颇受自媒体圈关注。
自媒体行业似乎迎来了一个爆发期。
然而,受到资本青睐的自媒体创业者,在整个行业中仍属极少数。
在塔尖之外,支撑起这座金字塔的、规模庞大却鲜为人知的基层自媒体从业者,其生存状态究竟如何,则被淹没在知名大号的融资喜讯中,不为人知。
自媒体是这个社会最为年轻的产业,并日渐成为整个互联网创业生态中的基石。
为了还原这个行业的本来面貌,了解千万计自媒体人真实的职业与生存状态,新榜于2015年11月发起了《自媒体人生存状态调查》,通过多种渠道,收集样本共1964份,从盈利状况、商业模式、职业满意度等多角度解读自媒体人的生存现状。
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专业化程度低,多新手
你在为谁做自媒体?
你从事自媒体有多久?
你的年龄是?
数据显示,23.73%的自媒体从业者目前仅将自媒体视作一项业余爱好,另有18.46%的自媒体人则是兼职运营者,全职从事自媒体工作者约为58%,比例较低。
不仅如此,自媒体从业者年龄普遍较低,年龄在25岁以下的“90后”比例最高,约36%,30岁以下的从业者占整体三分之二以上。
这部分年轻的从业者普遍是刚刚进入自媒体行业的新手,32%的人入行不满1年,超过80%不满2年,并表示自己正在“摸索门道”。
总体看来,自媒体从业者是一个年轻群体,资历和经验较浅,专业化程度不足。
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自媒体变现困难,半数未盈利
你运营的自媒体是否实现盈利?
你运营的自媒体每月收入有多少?
自媒体主要的收入来源是什么?
你觉得做自媒体行业最难的是?
从本次调查所揭示的情况来看,自媒体面临的盈利压力非常严峻。
已经实现盈利的自媒体不到半数,有超过60%的自媒体每月营收不足1万元。
除盈利状况不佳,自媒体还面临盈利模式单调的问题。
主要通过原生广告(软文)方式盈利的自媒体有32.25%,主要通过广点通、头条号广告等平台广告分成盈利的自媒体有35.29%,两者相加近70%。
换言之,在广告、软文服务之外,自媒体缺乏有效盈利手段。
在“你觉得做自媒体最难的是……”这一问题上,30%的人选择了“规划成熟的商业化变现模式”。
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职业满意度低,付出收获不成正比
你幸福吗?
你经常加班吗?
你平均每天工作多长时间?
作为机构的自媒体盈利困难,作为从业者的自媒体人也对职业感到不满。
面对“你幸福吗?”这个问题,作出肯定回答的不到20%。
显著高于其他行业水平的工作强度,可能是自媒体人对职业不满的重要原因。
约37%的自媒体人日均工作时间超过了11小时。
近80%的被访者表示加班是工作常态,甚至有32%的人经常需要在双休日加班工作。
在自媒体缺乏盈利手段的大背景下,自媒体人对职业的不满并不令人意外。
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半数自媒体人表示“最缺钱”
你个人的月收入是多少?
你觉得你现在最缺的是什么?
如果现在你的收入有多少,你就满足了?
在“你觉得你现在最缺什么”这个问题上,约46%的从业者选择了“钱”这一项。
43%的自媒体人个人月收入不足5000元,虽然并未区分个人从自媒体运营中获得的收入和个人的全部收入,但收入偏低,是自媒体人普遍的现实写照。
如果考虑到超过40%的自媒体人都是业余爱好或者兼职,可以推测有相当数量的自媒体从业者,其实希望通过运营自媒体来改善目前的收入水平。
在预期收入方面,超过三分之一选择了“8000-1万”“1万-3万”两个选项,足见1万元左右的月收入,对于相当数量的自媒体人来说,是可望而不可及的。
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内容创业者变现模式亟需多元化
调查结果显示,与资本圈和行业的热闹形成对比,数量最为庞大的自媒体人的生存状况并不尽如人意。
已实现盈利的自媒体不到50%,超过64%的自媒体每月营收不足1万元,超三成自媒体认为寻找投资和变现模式颇为艰难。
收入低、缺乏成熟的商业模式,自媒体人最大的痛点都与钱有关。
加之工作强度大,绝大多数的自媒体人幸福感不强。
全职做自媒体的人只有一半左右,总体来说,职业化程度并不高。
尽管融资捷报频传,自媒体在发展的过程中不可避免地暴露出越来越多的问题。
自媒体作为一个新兴行业,并无多少前人的成功经验可供借鉴,商业变现模式匮乏。
较低的准入门槛又决定了许多自媒体初创期就缺少准确的定位和运营规划,行业水平参差不齐,很大程度上导致了收入水平的低下。
从整个行业来看,大多数自媒体陷入了一个变现瓶颈,盈利仍靠承接营销软文和广告等业务,并未找到更好的商业模式。
尽管大环境如此,一些日渐分明的趋势正在显现。
无论是罗辑思维的“卖书”,还是吴晓波的“卖酒”,粉丝经济、社群经济已然成为未来自媒体必然的生态。
另外,类似头条号平台对帐号进行直接的现金补贴,也可能别开生面,成为自媒体盈利模式一种可能的解决之道。
内容创业者对盈利模式的探索才刚刚开始。