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Analysis of Genetic Diversity and Population Structure
Agricultural Sciences in China2010, 9(9): 1251-1262September 2010Received 30 October, 2009 Accepted 16 April, 2010Analysis of Genetic Diversity and Population Structure of Maize Landraces from the South Maize Region of ChinaLIU Zhi-zhai 1, 2, GUO Rong-hua 2, 3, ZHAO Jiu-ran 4, CAI Yi-lin 1, W ANG Feng-ge 4, CAO Mo-ju 3, W ANG Rong-huan 2, 4, SHI Yun-su 2, SONG Yan-chun 2, WANG Tian-yu 2 and LI Y u 21Maize Research Institute, Southwest University, Chongqing 400716, P.R.China2Institue of Crop Sciences/National Key Facility for Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences,Beijing 100081, P.R.China3Maize Research Institute, Sichuan Agricultural University, Ya’an 625014, P.R.China4Maize Research Center, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100089, P.R.ChinaAbstractUnderstanding genetic diversity and population structure of landraces is important in utilization of these germplasm in breeding programs. In the present study, a total of 143 core maize landraces from the South Maize Region (SR) of China,which can represent the general profile of the genetic diversity in the landraces germplasm of SR, were genotyped by 54DNA microsatellite markers. Totally, 517 alleles (ranging from 4 to 22) were detected among these landraces, with an average of 9.57 alleles per locus. The total gene diversity of these core landraces was 0.61, suggesting a rather higher level of genetic diversity. Analysis of population structure based on Bayesian method obtained the samilar result as the phylogeny neighbor-joining (NJ) method. The results indicated that the whole set of 143 core landraces could be clustered into two distinct groups. All landraces from Guangdong, Hainan, and 15 landraces from Jiangxi were clustered into group 1, while those from the other regions of SR formed the group 2. The results from the analysis of genetic diversity showed that both of groups possessed a similar gene diversity, but group 1 possessed relatively lower mean alleles per locus (6.63) and distinct alleles (91) than group 2 (7.94 and 110, respectively). The relatively high richness of total alleles and distinct alleles preserved in the core landraces from SR suggested that all these germplasm could be useful resources in germplasm enhancement and maize breeding in China.Key words :maize, core landraces, genetic diversity, population structureINTRODUCTIONMaize has been grown in China for nearly 500 years since its first introduction into this second biggest pro-duction country in the world. Currently, there are six different maize growing regions throughout the coun-try according to the ecological conditions and farming systems, including three major production regions,i.e., the North Spring Maize Region, the Huang-Huai-Hai Summer Maize Region, and the Southwest MaizeRegion, and three minor regions, i.e., the South Maize Region, the Northwest Maize Region, and the Qingzang Plateau Maize Region. The South Maize Region (SR)is specific because of its importance in origin of Chi-nese maize. It is hypothesized that Chinese maize is introduced mainly from two routes. One is called the land way in which maize was first brought to Tibet from India, then to Sichuan Province in southwestern China. The other way is that maize dispersed via the oceans, first shipped to the coastal areas of southeast China by boats, and then spread all round the country1252LIU Zhi-zhai et al.(Xu 2001; Zhou 2000). SR contains all of the coastal provinces and regions lie in southeastern China.In the long-term cultivation history of maize in south-ern China, numerous landraces have been formed, in which a great amount of genetic variation was observed (Li 1998). Similar to the hybrid swapping in Europe (Reif et al. 2005a), the maize landraces have been al-most replaced by hybrids since the 1950s in China (Li 1998). However, some landraces with good adapta-tions and yield performances are still grown in a few mountainous areas of this region (Liu et al.1999). Through a great effort of collection since the 1950s, 13521 accessions of maize landraces have been cur-rently preserved in China National Genebank (CNG), and a core collection of these landraces was established (Li et al. 2004). In this core collection, a total of 143 maize landrace accessions were collected from the South Maize Region (SR) (Table 1).Since simple sequence repeat ( SSR ) markers were firstly used in human genetics (Litt and Luty 1989), it now has become one of the most widely used markers in the related researches in crops (Melchinger et al. 1998; Enoki et al. 2005), especially in the molecular characterization of genetic resources, e.g., soybean [Glycine max (L.) Merr] (Xie et al. 2005), rice (Orya sativa L.) (Garris et al. 2005), and wheat (Triticum aestivum) (Chao et al. 2007). In maize (Zea mays L.), numerous studies focusing on the genetic diversity and population structure of landraces and inbred lines in many countries and regions worldwide have been pub-lished (Liu et al. 2003; Vegouroux et al. 2005; Reif et al. 2006; Wang et al. 2008). These activities of documenting genetic diversity and population structure of maize genetic resources have facilitated the under-standing of genetic bases of maize landraces, the utili-zation of these resources, and the mining of favorable alleles from landraces. Although some studies on ge-netic diversity of Chinese maize inbred lines were con-ducted (Yu et al. 2007; Wang et al. 2008), the general profile of genetic diversity in Chinese maize landraces is scarce. Especially, there are not any reports on ge-netic diversity of the maize landraces collected from SR, a possibly earliest maize growing area in China. In this paper, a total of 143 landraces from SR listed in the core collection of CNG were genotyped by using SSR markers, with the aim of revealing genetic diver-sity of the landraces from SR (Table 2) of China and examining genetic relationships and population struc-ture of these landraces.MATERIALS AND METHODSPlant materials and DNA extractionTotally, 143 landraces from SR which are listed in the core collection of CNG established by sequential strati-fication method (Liu et al. 2004) were used in the present study. Detailed information of all these landrace accessions is listed in Table 1. For each landrace, DNA sample was extracted by a CTAB method (Saghi-Maroof et al. 1984) from a bulk pool constructed by an equal-amount of leaves materials sampled from 15 random-chosen plants of each landrace according to the proce-dure of Reif et al. (2005b).SSR genotypingA total of 54 simple sequence repeat (SSR) markers covering the entire maize genome were screened to fin-gerprint all of the 143 core landrace accessions (Table 3). 5´ end of the left primer of each locus was tailed by an M13 sequence of 5´-CACGACGTTGTAAAACGAC-3´. PCR amplification was performed in a 15 L reac-tion containing 80 ng of template DNA, 7.5 mmol L-1 of each of the four dNTPs, 1×Taq polymerase buffer, 1.5 mmol L-1 MgCl2, 1 U Taq polymerase (Tiangen Biotech Co. Ltd., Beijing, China), 1.2 mol L-1 of forward primer and universal fluorescent labeled M13 primer, and 0.3 mol L-1 of M13 sequence tailed reverse primer (Schuelke 2000). The amplification was carried out in a 96-well DNA thermal cycler (GeneAmp PCR System 9700, Applied Biosystem, USA). PCR products were size-separated on an ABI Prism 3730XL DNA sequencer (HitachiHigh-Technologies Corporation, Tokyo, Japan) via the software packages of GENEMAPPER and GeneMarker ver. 6 (SoftGenetics, USA).Data analysesAverage number of alleles per locus and average num-ber of group-specific alleles per locus were identifiedAnalysis of Genetic Diversity and Population Structure of Maize Landraces from the South Maize Region of China 1253Table 1 The detailed information about the landraces used in the present studyPGS revealed by Structure1) NJ dendragram revealed Group 1 Group 2 by phylogenetic analysis140-150tian 00120005AnH-06Jingde Anhui 0.0060.994Group 2170tian00120006AnH-07Jingde Anhui 0.0050.995Group 2Zixihuangyumi00120007AnH-08Zixi Anhui 0.0020.998Group 2Zixibaihuangzayumi 00120008AnH-09Zixi Anhui 0.0030.997Group 2Baiyulu 00120020AnH-10Yuexi Anhui 0.0060.994Group 2Wuhuazi 00120021AnH-11Yuexi Anhui 0.0030.997Group 2Tongbai 00120035AnH-12Tongling Anhui 0.0060.994Group 2Yangyulu 00120036AnH-13Yuexi Anhui 0.0040.996Group 2Huangli 00120037AnH-14Tunxi Anhui 0.0410.959Group 2Baiyumi 00120038AnH-15Tunxi Anhui 0.0030.997Group 2Dapigu00120039AnH-16Tunxi Anhui 0.0350.965Group 2150tianbaiyumi 00120040AnH-17Xiuning Anhui 0.0020.998Group 2Xiuning60tian 00120042AnH-18Xiuning Anhui 0.0040.996Group 2Wubaogu 00120044AnH-19ShitaiAnhui 0.0020.998Group 2Kuyumi00130001FuJ-01Shanghang Fujian 0.0050.995Group 2Zhongdouyumi 00130003FuJ-02Shanghang Fujian 0.0380.962Group 2Baixinyumi 00130004FuJ-03Liancheng Fujian 0.0040.996Group 2Hongxinyumi 00130005FuJ-04Liancheng Fujian 0.0340.966Group 2Baibaogu 00130008FuJ-05Changding Fujian 0.0030.997Group 2Huangyumi 00130011FuJ-06Jiangyang Fujian 0.0020.998Group 2Huabaomi 00130013FuJ-07Shaowu Fujian 0.0020.998Group 2Huangbaomi 00130014FuJ-08Songxi Fujian 0.0020.998Group 2Huangyumi 00130016FuJ-09Wuyishan Fujian 0.0460.954Group 2Huabaogu 00130019FuJ-10Jian’ou Fujian 0.0060.994Group 2Huangyumi 00130024FuJ-11Guangze Fujian 0.0010.999Group 2Huayumi 00130025FuJ-12Nanping Fujian 0.0040.996Group 2Huangyumi 00130026FuJ-13Nanping Fujian 0.0110.989Group 2Hongbaosu 00130027FuJ-14Longyan Fujian 0.0160.984Group 2Huangfansu 00130029FuJ-15Loangyan Fujian 0.0020.998Group 2Huangbaosu 00130031FuJ-16Zhangping Fujian 0.0060.994Group 2Huangfansu 00130033FuJ-17Zhangping Fujian0.0040.996Group 2Baolieyumi 00190001GuangD-01Guangzhou Guangdong 0.9890.011Group 1Nuomibao (I)00190005GuangD-02Shixing Guangdong 0.9740.026Group 1Nuomibao (II)00190006GuangD-03Shixing Guangdong 0.9790.021Group 1Zasehuabao 00190010GuangD-04Lechang Guangdong 0.9970.003Group 1Zihongmi 00190013GuangD-05Lechang Guangdong 0.9880.012Group 1Jiufengyumi 00190015GuangD-06Lechang Guangdong 0.9950.005Group 1Huangbaosu 00190029GuangD-07MeiGuangdong 0.9970.003Group 1Bailibao 00190032GuangD-08Xingning Guangdong 0.9980.002Group 1Nuobao00190038GuangD-09Xingning Guangdong 0.9980.002Group 1Jinlanghuang 00190048GuangD-10Jiangcheng Guangdong 0.9960.004Group 1Baimizhenzhusu 00190050GuangD-11Yangdong Guangdong 0.9940.006Group 1Huangmizhenzhusu 00190052GuangD-12Yangdong Guangdong 0.9930.007Group 1Baizhenzhu 00190061GuangD-13Yangdong Guangdong 0.9970.003Group 1Baiyumi 00190066GuangD-14Wuchuan Guangdong 0.9880.012Group 1Bendibai 00190067GuangD-15Suixi Guangdong 0.9980.002Group 1Shigubaisu 00190068GuangD-16Gaozhou Guangdong 0.9960.004Group 1Zhenzhusu 00190069GuangD-17Xinyi Guangdong 0.9960.004Group 1Nianyaxixinbai 00190070GuangD-18Huazhou Guangdong 0.9960.004Group 1Huangbaosu 00190074GuangD-19Xinxing Guangdong 0.9950.005Group 1Huangmisu 00190076GuangD-20Luoding Guangdong 0.940.060Group 1Huangmi’ai 00190078GuangD-21Luoding Guangdong 0.9980.002Group 1Bayuemai 00190084GuangD-22Liannan Guangdong 0.9910.009Group 1Baiyumi 00300001HaiN-01Haikou Hainan 0.9960.004Group 1Baiyumi 00300003HaiN-02Sanya Hainan 0.9970.003Group 1Hongyumi 00300004HaiN-03Sanya Hainan 0.9980.002Group 1Baiyumi00300011HaiN-04Tongshi Hainan 0.9990.001Group 1Zhenzhuyumi 00300013HaiN-05Tongshi Hainan 0.9980.002Group 1Zhenzhuyumi 00300015HaiN-06Qiongshan Hainan 0.9960.004Group 1Aiyumi 00300016HaiN-07Qiongshan Hainan 0.9960.004Group 1Huangyumi 00300021HaiN-08Qionghai Hainan 0.9970.003Group 1Y umi 00300025HaiN-09Qionghai Hainan 0.9870.013Group 1Accession name Entry code Analyzing code Origin (county/city)Province/Region1254LIU Zhi-zhai et al .Baiyumi00300032HaiN-10Tunchang Hainan 0.9960.004Group 1Huangyumi 00300051HaiN-11Baisha Hainan 0.9980.002Group 1Baihuangyumi 00300055HaiN-12BaishaHainan 0.9970.003Group 1Machihuangyumi 00300069HaiN-13Changjiang Hainan 0.9900.010Group 1Hongyumi00300073HaiN-14Dongfang Hainan 0.9980.002Group 1Xiaohonghuayumi 00300087HaiN-15Lingshui Hainan 0.9980.002Group 1Baiyumi00300095HaiN-16Qiongzhong Hainan 0.9950.005Group 1Y umi (Baimai)00300101HaiN-17Qiongzhong Hainan 0.9980.002Group 1Y umi (Xuemai)00300103HaiN-18Qiongzhong Hainan 0.9990.001Group 1Huangmaya 00100008JiangS-10Rugao Jiangsu 0.0040.996Group 2Bainian00100012JiangS-11Rugao Jiangsu 0.0080.992Group 2Bayebaiyumi 00100016JiangS-12Rudong Jiangsu 0.0040.996Group 2Chengtuohuang 00100021JiangS-13Qidong Jiangsu 0.0050.995Group 2Xuehuanuo 00100024JiangS-14Qidong Jiangsu 0.0020.998Group 2Laobaiyumi 00100032JiangS-15Qidong Jiangsu 0.0050.995Group 2Laobaiyumi 00100033JiangS-16Qidong Jiangsu 0.0010.999Group 2Huangwuye’er 00100035JiangS-17Hai’an Jiangsu 0.0030.997Group 2Xiangchuanhuang 00100047JiangS-18Nantong Jiangsu 0.0060.994Group 2Huangyingzi 00100094JiangS-19Xinghua Jiangsu 0.0040.996Group 2Xiaojinhuang 00100096JiangS-20Yangzhou Jiangsu 0.0010.999Group 2Liushizi00100106JiangS-21Dongtai Jiangsu 0.0030.997Group 2Kangnandabaizi 00100108JiangS-22Dongtai Jiangsu 0.0020.998Group 2Shanyumi 00140020JiangX-01Dexing Jiangxi 0.9970.003Group 1Y umi00140024JiangX-02Dexing Jiangxi 0.9970.003Group 1Tianhongyumi 00140027JiangX-03Yushan Jiangxi 0.9910.009Group 1Hongganshanyumi 00140028JiangX-04Yushan Jiangxi 0.9980.002Group 1Zaoshuyumi 00140032JiangX-05Qianshan Jiangxi 0.9970.003Group 1Y umi 00140034JiangX-06Wannian Jiangxi 0.9970.003Group 1Y umi 00140038JiangX-07De’an Jiangxi 0.9940.006Group 1Y umi00140045JiangX-08Wuning Jiangxi 0.9740.026Group 1Chihongyumi 00140049JiangX-09Wanzai Jiangxi 0.9920.008Group 1Y umi 00140052JiangX-10Wanzai Jiangxi 0.9930.007Group 1Huayumi 00140060JiangX-11Jing’an Jiangxi 0.9970.003Group 1Baiyumi 00140065JiangX-12Pingxiang Jiangxi 0.9940.006Group 1Huangyumi00140066JiangX-13Pingxiang Jiangxi 0.9680.032Group 1Nuobaosuhuang 00140068JiangX-14Ruijin Jiangxi 0.9950.005Group 1Huangyumi 00140072JiangX-15Xinfeng Jiangxi 0.9960.004Group 1Wuningyumi 00140002JiangX-16Jiujiang Jiangxi 0.0590.941Group 2Tianyumi 00140005JiangX-17Shangrao Jiangxi 0.0020.998Group 2Y umi 00140006JiangX-18Shangrao Jiangxi 0.0310.969Group 2Baiyiumi 00140012JiangX-19Maoyuan Jiangxi 0.0060.994Group 260riyumi 00140016JiangX-20Maoyuan Jiangxi 0.0020.998Group 2Shanyumi 00140019JiangX-21Dexing Jiangxi 0.0050.995Group 2Laorenya 00090002ShangH-01Chongming Shanghai 0.0050.995Group 2Jinmeihuang 00090004ShangH-02Chongming Shanghai 0.0020.998Group 2Zaobaiyumi 00090006ShangH-03Chongming Shanghai 0.0020.998Group 2Chengtuohuang 00090007ShangH-04Chongming Shanghai 0.0780.922Group 2Benyumi (Huang)00090008ShangH-05Shangshi Shanghai 0.0020.998Group 2Bendiyumi 00090010ShangH-06Shangshi Shanghai 0.0040.996Group 2Baigengyumi 00090011ShangH-07Jiading Shanghai 0.0020.998Group 2Huangnuoyumi 00090012ShangH-08Jiading Shanghai 0.0040.996Group 2Huangdubaiyumi 00090013ShangH-09Jiading Shanghai 0.0440.956Group 2Bainuoyumi 00090014ShangH-10Chuansha Shanghai 0.0010.999Group 2Laorenya 00090015ShangH-11Shangshi Shanghai 0.0100.990Group 2Xiaojinhuang 00090016ShangH-12Shangshi Shanghai 0.0050.995Group 2Gengbaidayumi 00090017ShangH-13Shangshi Shanghai 0.0020.998Group 2Nongmeiyihao 00090018ShangH-14Shangshi Shanghai 0.0540.946Group 2Chuanshazinuo 00090020ShangH-15Chuansha Shanghai 0.0550.945Group 2Baoanshanyumi 00110004ZheJ-01Jiangshan Zhejiang 0.0130.987Group 2Changtaixizi 00110005ZheJ-02Jiangshan Zhejiang 0.0020.998Group 2Shanyumibaizi 00110007ZheJ-03Jiangshan Zhejiang 0.0020.998Group 2Kaihuajinyinbao 00110017ZheJ-04Kaihua Zhejiang 0.0100.990Group 2Table 1 (Continued from the preceding page)PGS revealed by Structure 1) NJ dendragram revealed Group1 Group2 by phylogenetic analysisAccession name Entry code Analyzing code Origin (county/city)Province/RegoinAnalysis of Genetic Diversity and Population Structure of Maize Landraces from the South Maize Region of China 1255Liputianzi00110038ZheJ-05Jinhua Zhejiang 0.0020.998Group 2Jinhuaqiuyumi 00110040ZheJ-06Jinhua Zhejiang 0.0050.995Group 2Pujiang80ri 00110069ZheJ-07Pujiang Zhejiang 0.0210.979Group 2Dalihuang 00110076ZheJ-08Yongkang Zhejiang 0.0140.986Group 2Ziyumi00110077ZheJ-09Yongkang Zhejiang 0.0020.998Group 2Baiyanhandipinzhong 00110078ZheJ-10Yongkang Zhejiang 0.0030.997Group 2Duosuiyumi00110081ZheJ-11Wuyi Zhejiang 0.0020.998Group 2Chun’an80huang 00110084ZheJ-12Chun’an Zhejiang 0.0020.998Group 2120ribaiyumi 00110090ZheJ-13Chun’an Zhejiang 0.0020.998Group 2Lin’anliugu 00110111ZheJ-14Lin’an Zhejiang 0.0030.997Group 2Qianhuangyumi00110114ZheJ-15Lin’an Zhejiang 0.0030.997Group 2Fenshuishuitianyumi 00110118ZheJ-16Tonglu Zhejiang 0.0410.959Group 2Kuihualiugu 00110119ZheJ-17Tonglu Zhejiang 0.0030.997Group 2Danbaihuang 00110122ZheJ-18Tonglu Zhejiang 0.0020.998Group 2Hongxinma 00110124ZheJ-19Jiande Zhejiang 0.0030.997Group 2Shanyumi 00110136ZheJ-20Suichang Zhejiang 0.0030.997Group 2Bai60ri 00110143ZheJ-21Lishui Zhejiang 0.0050.995Group 2Zeibutou 00110195ZheJ-22Xianju Zhejiang 0.0020.998Group 2Kelilao00110197ZheJ-23Pan’an Zhejiang 0.0600.940Group 21)The figures refered to the proportion of membership that each landrace possessed.Table 1 (Continued from the preceding page)PGS revealed by Structure 1) NJ dendragram revealed Group 1 Group 2 by phylogenetic analysisAccession name Entry code Analyzing code Origin (county/city)Province/Regoin Table 2 Construction of two phylogenetic groups (SSR-clustered groups) and their correlation with geographical locationsGeographical location SSR-clustered groupChi-square testGroup 1Group 2Total Guangdong 2222 χ2 = 124.89Hainan 1818P < 0.0001Jiangxi 15621Anhui 1414Fujian 1717Jiangsu 1313Shanghai 1515Zhejiang 2323Total5588143by the software of Excel MicroSatellite toolkit (Park 2001). Average number of alleles per locus was calcu-lated by the formula rAA rj j¦1, with the standarddeviation of1)()(12¦ r A AA rj jV , where A j was thenumber of distinct alleles at locus j , and r was the num-ber of loci (Park 2001).Unbiased gene diversity also known as expected heterozygosity, observed heterozygosity for each lo-cus and average gene diversity across the 54 SSR loci,as well as model-based groupings inferred by Struc-ture ver. 2.2, were calculated by the softwarePowerMarker ver.3.25 (Liu et al . 2005). Unbiased gene diversity for each locus was calculated by˅˄¦ 2ˆ1122ˆi x n n h , where 2ˆˆ2ˆ2¦¦z ji ijij i X X x ,and ij X ˆwas the frequency of genotype A i A jin the sample, and n was the number of individuals sampled.The average gene diversity across 54 loci was cal-culated as described by Nei (1987) as follows:rh H rj j ¦1ˆ, with the variance ,whereThe average observed heterozygosity across the en-tire loci was calculated as described by (Hedrick 1983)as follows: r jrj obsobs n h h ¦1, with the standard deviationrn h obs obsobs 1V1256LIU Zhi-zhai et al.Phylogenetic analysis and population genetic structureRelationships among all of the 143 accessions collected from SR were evaluated by using the unweighted pair group method with neighbor-joining (NJ) based on the log transformation of the proportion of shared alleles distance (InSPAD) via PowerMarker ver. 3.25 (FukunagaTable 3 The PIC of each locus and the number of alleles detected by 54 SSRsLocus Bin Repeat motif PIC No. of alleles Description 2)bnlg1007y51) 1.02AG0.7815Probe siteumc1122 1.06GGT0.639Probe siteumc1147y41) 1.07CA0.2615Probe sitephi961001) 2.00ACCT0.298Probe siteumc1185 2.03GC0.7215ole1 (oleosin 1)phi127 2.08AGAC0.577Probe siteumc1736y21) 2.09GCA T0.677Probe sitephi453121 3.01ACC0.7111Probe sitephi374118 3.03ACC0.477Probe sitephi053k21) 3.05A TAC0.7910Probe sitenc004 4.03AG0.4812adh2 (alcohol dehydrogenase 2)bnlg490y41) 4.04T A0.5217Probe sitephi079 4.05AGATG0.495gpc1(glyceraldehyde-3-phosphate dehydrogenase 1) bnlg1784 4.07AG0.6210Probe siteumc1574 4.09GCC0.719sbp2 (SBP-domain protein 2)umc1940y51) 4.09GCA0.4713Probe siteumc1050 4.11AA T0.7810cat3 (catalase 3)nc130 5.00AGC0.5610Probe siteumc2112y31) 5.02GA0.7014Probe sitephi109188 5.03AAAG0.719Probe siteumc1860 5.04A T0.325Probe sitephi085 5.07AACGC0.537gln4 (glutamine synthetase 4)phi331888 5.07AAG0.5811Probe siteumc1153 5.09TCA0.7310Probe sitephi075 6.00CT0.758fdx1 (ferredoxin 1)bnlg249k21) 6.01AG0.7314Probe sitephi389203 6.03AGC0.416Probe sitephi299852y21) 6.07AGC0.7112Probe siteumc1545y21)7.00AAGA0.7610hsp3(heat shock protein 3)phi1127.01AG0.5310o2 (opaque endosperm 2)phi4207018.00CCG0.469Probe siteumc13598.00TC0.7814Probe siteumc11398.01GAC0.479Probe siteumc13048.02TCGA0.335Probe sitephi1158.03A TAC0.465act1(actin1)umc22128.05ACG0.455Probe siteumc11218.05AGAT0.484Probe sitephi0808.08AGGAG0.646gst1 (glutathione-S-transferase 1)phi233376y11)8.09CCG0.598Probe sitebnlg12729.00AG0.8922Probe siteumc20849.01CTAG0.498Probe sitebnlg1520k11)9.01AG0.5913Probe sitephi0659.03CACCT0.519pep1(phosphoenolpyruvate carboxylase 1)umc1492y131)9.04GCT0.2514Probe siteumc1231k41)9.05GA0.2210Probe sitephi1084119.06AGCT0.495Probe sitephi4488809.06AAG0.7610Probe siteumc16759.07CGCC0.677Probe sitephi041y61)10.00AGCC0.417Probe siteumc1432y61)10.02AG0.7512Probe siteumc136710.03CGA0.6410Probe siteumc201610.03ACAT0.517pao1 (polyamine oxidase 1)phi06210.04ACG0.337mgs1 (male-gametophyte specific 1)phi07110.04GGA0.515hsp90 (heat shock protein, 90 kDa)1) These primers were provided by Beijing Academy of Agricultural and Forestry Sciences (Beijing, China).2) Searched from Analysis of Genetic Diversity and Population Structure of Maize Landraces from the South Maize Region of China1257et al. 2005). The unrooted phylogenetic tree was finally schematized with the software MEGA (molecular evolu-tionary genetics analysis) ver. 3.1 (Kumar et al. 2004). Additionally, a chi-square test was used to reveal the correlation between the geographical origins and SSR-clustered groups through FREQ procedure implemented in SAS ver. 9.0 (2002, SAS Institute, Inc.).In order to reveal the population genetic structure (PGS) of 143 landrace accessions, a Bayesian approach was firstly applied to determine the number of groups (K) that these materials should be assigned by the soft-ware BAPS (Bayesian Analysis of Population Structure) ver.5.1. By using BAPS, a fixed-K clustering proce-dure was applied, and with each separate K, the num-ber of runs was set to 100, and the value of log (mL) was averaged to determine the appropriate K value (Corander et al. 2003; Corander and Tang 2007). Since the number of groups were determined, a model-based clustering analysis was used to assign all of the acces-sions into the corresponding groups by an admixture model and a correlated allele frequency via software Structure ver.2.2 (Pritchard et al. 2000; Falush et al. 2007), and for the given K value determined by BAPS, three independent runs were carried out by setting both the burn-in period and replication number 100000. The threshold probability assigned individuals into groupswas set by 0.8 (Liu et al. 2003). The PGS result carried out by Structure was visualized via Distruct program ver. 1.1 (Rosenberg 2004).RESULTSGenetic diversityA total of 517 alleles were detected by the whole set of54 SSRs covering the entire maize genome through all of the 143 maize landraces, with an average of 9.57 alleles per locus and ranged from 4 (umc1121) to 22 (bnlg1272) (Table 3). Among all the alleles detected, the number of distinct alleles accounted for 132 (25.53%), with an av-erage of 2.44 alleles per locus. The distinct alleles dif-fered significantly among the landraces from different provinces/regions, and the landraces from Guangdong, Fujian, Zhejiang, and Shanghai possessed more distinct alleles than those from the other provinces/regions, while those from southern Anhui possessed the lowest distinct alleles, only counting for 3.28% of the total (Table 4).Table 4 The genetic diversity within eight provinces/regions and groups revealed by 54 SSRsProvince/Region Sample size Allele no.1)Distinct allele no.Gene diversity (expected heterozygosity)Observed heterozygosity Anhui14 4.28 (4.19) 69 (72.4)0.51 (0.54)0.58 (0.58)Fujian17 4.93 (4.58 80 (79.3)0.56 (0.60)0.63 (0.62)Guangdong22 5.48 (4.67) 88 (80.4)0.57 (0.59)0.59 (0.58)Hainan18 4.65 (4.26) 79 (75.9)0.53 (0.57)0.55 (0.59)Jiangsu13 4.24 700.500.55Jiangxi21 4.96 (4.35) 72 (68.7)0.56 (0.60)0.68 (0.68)Shanghai15 5.07 (4.89) 90 (91.4)0.55 (0.60)0.55 (0.55)Zhejiang23 5.04 (4.24) 85 (74)0.53 (0.550.60 (0.61)Total/average1439.571320.610.60GroupGroup 155 6.63 (6.40) 91 (89.5)0.57 (0.58)0.62 (0.62)Group 2887.94 (6.72)110 (104.3)0.57 (0.57)0.59 (0.58)Total/Average1439.571320.610.60Provinces/Regions within a groupGroup 1Total55 6.69 (6.40) 910.57 (0.58)0.62 (0.62)Guangdong22 5.48 (4.99) 86 (90.1)0.57 (0.60)0.59 (0.58)Hainan18 4.65 (4.38) 79 (73.9)0.53 (0.56)0.55 (0.59)Jiangxi15 4.30 680.540.69Group 2Total887.97 (6.72)110 (104.3)0.57 (0.57)0.59 (0.58)Anhui14 4.28 (3.22) 69 (63.2)0.51 (0.54)0.58 (0.57)Fujian17 4.93 (3.58) 78 (76.6)0.56 (0.60)0.63 (0.61)Jiangsu13 4.24 (3.22) 71 (64.3)0.50 (0.54)0.55 (0.54)Jiangxi6 3.07 520.460.65Shanghai15 5.07 (3.20) 91 (84.1)0.55 (0.60)0.55 (0.54)Zhejiang23 5.04 (3.20) 83 (61.7)0.53 (0.54)0.60 (0.58)1258LIU Zhi-zhai et al.Among the 54 loci used in the study, 16 (or 29.63%) were dinucleotide repeat SSRs, which were defined as type class I-I, the other 38 loci were SSRs with a longer repeat motifs, and two with unknown repeat motifs, all these 38 loci were defined as the class of I-II. In addition, 15 were located within certain functional genes (defined as class II-I) and the rest were defined as class II-II. The results of comparison indicated that the av-erage number of alleles per locus captured by class I-I and II-II were 12.88 and 10.05, respectively, which were significantly higher than that by type I-II and II-I (8.18 and 8.38, respectively). The gene diversity re-vealed by class I-I (0.63) and II-I (0.63) were some-what higher than by class I-II (0.60) and II-II (0.60) (Table 5).Genetic relationships of the core landraces Overall, 143 landraces were clustered into two groups by using neighbor-joining (NJ) method based on InSPAD. All the landraces from provinces of Guangdong and Hainan and 15 of 21 from Jiangxi were clustered together to form group 1, and the other 88 landraces from the other provinces/regions formed group 2 (Fig.-B). The geographical origins of all these 143 landraces with the clustering results were schematized in Fig.-D. Revealed by the chi-square test, the phylogenetic results (SSR-clustered groups) of all the 143 landraces from provinces/regions showed a significant correlation with their geographical origin (χ2=124.89, P<0.0001, Table 2).Revealed by the phylogenetic analysis based on the InSPAD, the minimum distance was observed as 0.1671 between two landraces, i.e., Tianhongyumi (JiangX-03) and Hongganshanyumi (JiangX-04) collected from Jiangxi Province, and the maximum was between two landraces of Huangbaosu (FuJ-16) and Hongyumi (HaiN-14) collected from provinces of Fujian and Hainan, respectively, with the distance of 1.3863 (data not shown). Two landraces (JiangX-01 and JiangX-21) collected from the same location of Dexing County (Table 1) possessing the same names as Shanyumi were separated to different groups, i.e., JiangX-01 to group1, while JiangX-21 to group 2 (Table 1). Besides, JiangX-01 and JiangX-21 showed a rather distant distance of 0.9808 (data not shown). These results indicated that JiangX-01 and JiangX-21 possibly had different ances-tral origins.Population structureA Bayesian method was used to detect the number of groups (K value) of the whole set of landraces from SR with a fixed-K clustering procedure implemented in BAPS software ver. 5.1. The result showed that all of the 143 landraces could also be assigned into two groups (Fig.-A). Then, a model-based clustering method was applied to carry out the PGS of all the landraces via Structure ver. 2.2 by setting K=2. This method as-signed individuals to groups based on the membership probability, thus the threshold probability 0.80 was set for the individuals’ assignment (Liu et al. 2003). Accordingly, all of the 143 landraces were divided into two distinct model-based groups (Fig.-C). The landraces from Guangdong, Hainan, and 15 landraces from Jiangxi formed one group, while the rest 6 landraces from the marginal countries of northern Jiangxi and those from the other provinces formed an-other group (Table 1, Fig.-D). The PGS revealed by the model-based approach via Structure was perfectly consistent with the relationships resulted from the phy-logenetic analysis via PowerMarker (Table 1).DISCUSSIONThe SR includes eight provinces, i.e., southern Jiangsu and Anhui, Shanghai, Zhejiang, Fujian, Jiangxi, Guangdong, and Hainan (Fig.-C), with the annual maize growing area of about 1 million ha (less than 5% of theTable 5 The genetic diversity detected with different types of SSR markersType of locus No. of alleles Gene diversity Expected heterozygosity PIC Class I-I12.880.630.650.60 Class I-II8.180.600.580.55 Class II-I8.330.630.630.58。
IKCS12F60F2A_C_Rev1_0_20100628(10)
F o r P o w e r M a n a g e m e n t A p p l i c a t i o nControl Integrated POwer System (CIPOS™)I K C S 12F 60F 2A I K C S 12F 60F 2CD a t a S he e t ,J un. 2010CIPOS™ IKCS12F60F2AIKCS12F60F2CRevision History: 2010-06Rev.1.0Authors: Junho Song*, Junbae Lee* and Daewoong Chung*, W. Frank**, W. Brunnbauer**LS Power Semitech*, Infineon Technologies**Edition 2010-01Published byLS Power Semitech Co., Ltd. Seoul, Korea© LS Power Semitech Co., Ltd.All Rights Reserved.Attention please!The information given in this data sheet shall in no event be regarded as a guarantee of conditions or characteristics. With respect to any examples or hints given herein, any typical values stated herein and/or any information regarding the application of the device, LS Power Semitech Co., Ltd. hereby disclaims any and all warranties and liabilities of any kind, including without limitation warranties of non-infringement of intellectual property rights of any third party.InformationFor further information on technology, delivery terms and conditions and prices please contact your nearest LS Power Semitech Co., Ltd. office or representatives ().WarningsDue to technical requirements components may contain dangerous substances. For information on the types in question please contact your nearest LS Power Semitech Co., Ltd. office or representatives.LS Power Semitech Co., Ltd. components may only be used in life-support devices or systems with the express written approval LS Power Semitech Co., Ltd., if a failure of such components can reasonably be expected to cause the failure of that life-support device or system, or to affect the safetyor effectiveness of that device or system. Life support devices or systems are intended to be implantedin the human body, or to support and/or maintain and sustain and/or protect human life. If they fail, it is reasonable to assume that the health of the user or other persons may be endangered.TRENCHSTOP® is a registered trademark of Infineon Technologies AG.CIPOS™ IKCS12F60F2AIKCS12F60F2CTable of contents:CIPOS™ Control Integrated POwer System (4)Features (4)Target Applications (4)Description (4)System Configuration (4)Certification (4)Internal Electrical Schematic (5)Pin Assignment (6)Pin Description (6)HIN1,2,3 and /LIN1,2,3 (Low side and high side control pins, Pin 15 - 20) (6)FLT-TEMP (temperature NTC, Pin 24) (7)ITRIP (Over-current detection function, Pin 21) (7)VDD, VSS (control side supply and reference, Pin 22, 23) (7)VB1,2,3 and VS1,2,3 (High side supplies, Pin 1, 2, 4, 5, 7, 8) (7)VRU, VRV, VRW (low side emitter, Pin 12, 13, 14) (7)V+ (positive bus input voltage, Pin 10) (7)Absolute Maximum Ratings (8)Module Section (8)IGBT and Diode Section (8)Control Section (9)Recommended Operation Conditions (9)Static Characteristics (10)Dynamic Characteristics (11)Integrated Components (12)Typical Application (12)Characteristics (13)Package Outline IKCS12F60F2A (17)Package Outline IKCS12F60F2C (18)CIPOS™ IKCS12F60F2AIKCS12F60F2CCIPOS™C ontrol I ntegrated PO wer S ystem Single In-Line Intelligent Power Module3Φ-bridge 600V / 12A @ 25°CFeatures•DCB isolated Single In-Line molded module •FAULT signal•TrenchStop® IGBTs with lowest V CE(sat)•Optimal adapted antiparallel diode for low EMI •Integrated bootstrap diode and capacitor •Rugged SOI gate driver technology with stability against transient and negative voltage •Fully compliant to 3.3V and 5V microcontrollers •Temperature sense•Under voltage lockout at all channels •Matched propagation delay for all channels •Low side emitter pins accessible for all phase current monitoring (open emitter)•Cross-conduction prevention•Lead-free terminal plating; RoHS compliant •Qualified according to JEDEC1 (high temperature stress tests for 1000h) for target applicationsTarget Applications•Washing machines•Consumer Fans and Consumer Compressors DescriptionThe CIPOS™ module family offers the chance for integrating various power and control components to increase reliability, optimize PCB size and system costs.This SIL-IPM is designed to control AC motors in variable speed drives for applications like air conditioning, compressors and washing machines. The package concept is specially adapted to power applications, which need extremely good thermal conduction and electrical isolation, but also EMI-save control and overload protection. The features of TrenchStop®IGBTs and antiparallel diodes are combined with a new optimized Infineon SOI gate driver for excellent electrical performance. The product provides a FAULT signal, which is significantly simplifying the system.System Configuration• 3 half-bridges with TrenchStop®IGBT & FW-diodes•3Φ SOI gate driver•Bootstrap diodes for high side supply •Integrated 100nF bootstrap capacitance •Temperature sensor, passive components for adaptions•Isolated heatsink•Creepage distance typ 3.2mmCertificationUL 1577 (UL file E314539)CIPOS™ IKCS12F60F2A IKCS12F60F2CInternal Electrical SchematicFigure 1: Internal SchematicVSS (23)/LIN3 (20)/LIN2 (19)/LIN1 (18)/HIN3 (17)/HIN2 (16)/HIN1 (15)VDD (22)VB1 (7)VB2 (4)VB3 (1)VRW (14)VRV (13)VRU (12)W, VS3 (2)V, VS2 (5)U, VS1 (8)V+ (10)/FLT-TEMP (24)ITRIP (21)CIPOS™ IKCS12F60F2A IKCS12F60F2CPin AssignmentPin Description/HIN1,2,3 and /LIN1,2,3 (Low side and high side control pins, Pin 15 - 20)These pins are active low and they are responsible for the control of the integrated IGBTsuch to guarantee LSTTL and CMOS compatibility down to 3.3V controller outputs. The maximum voltage at these pins is 5.5V and therefore fully compliant to 3.3V-microcontrollers. Pull-up resistor of about 75k Ω is internally provided to pre-bias inputs during supply start-up and a zener clamp is provided for pin protection purposes. Input schmitt-trigger and noise filter provide beneficial noise rejection to short input pulses. It is recommended for proper work of CIPOS™ not to provide an input pulse-width and PWM deadtimes lower than 1us.The integrated gate drive provides additionally a shoot through prevention capability which avoids the simultaneous on-state of two gate drivers ofFigure 2: Input pin structureCIPOS™ IKCS12F60F2A IKCS12F60F2Cthe same leg (i.e. HO1 and LO1, HO2 and LO2, HO3 and LO3).A minimum deadtime insertion of typ 380ns is also provided, in order to reduce cross-conduction of the external power switches./FLT-TEMP (temperature NTC, Pin 24)The TEMP terminal provides direct access to the NTC, which is referenced to VSS. An external pull-up resistor connected to +5V ensures, that the resulting voltage can be directly connected to the microcontroller.The same pin indicates a module failure in case of under voltage at pin VDD or in case of triggered over current detection at ITRIP. A pull-up resistor is externally required to bias the NTC. No temperature information is available during fault. ITRIP (Over-current detection function, Pin 21) CIPOS™ provides an over-current detection function by connecting the ITRIP input with the motor current feedback. The ITRIP comparator threshold (typ 0.46V) is referenced to VSS ground. A input noise filter (typ: t ITRIPMIN = 225ns) prevents the driver to detect false over-current events. Over-current detection generates a hard shut down of all outputs of the gate driver after the shutdown propagation delay of typically 900ns. The fault-clear time is set to typically to 4.7ms. VDD, VSS (control side supply and reference, Pin 22, 23)VDD is the low side supply and it provides power both to input logic and to low side output power stage. Input logic is referenced to VSS ground as well as the under-voltage detection circuit. The under-voltage circuit enables the device to operate at power on when a supply voltage of at least a typical voltage of V DDUV+ = 12.1V is at least present.The IC shuts down all the gate drivers power outputs, when the VDD supply voltage is below V DDUV- = 10.4V. This prevents the external power switches from critically low gate voltage levels during on-state and therefore from excessive power dissipation.VB1,2,3 and VS1,2,3 (High side supplies, Pin 1, 2, 4, 5, 7, 8)VB to VS is the high side supply voltage. The high side circuit can float with respect to VSS following the external high side power device emitter/source voltage.Due to the low power consumption, the floating driver stage is supplied by an integrated bootstrap circuit connected to VDD. This includes also integrated bootstrap capacitors of 100nF at each floating supply, which are located very close to the gate drive circuit.The under-voltage detection operates with a rising supply threshold of typical V BSUV+ = 12.1V and a falling threshold of V DDUV- = 10.4V according to Figure 4.VS1,2,3 provide a high robustness against negative voltage in respect of VSS of -50V. This ensures very stable designs even under rough conditions.Figure 4: Operation modesVRU, VRV, VRW (low side emitter, Pin 12, 13, 14)The low side emitters are available for current measurements of each phase leg. It is recommended to keep the connection to pin VSS as short as possible in order to avoid unnecessary inductive voltage drops.V+ (positive bus input voltage, Pin 10)The high side IGBT are connected to the bus voltage. It is recommended, that the bus voltage does not exceed 500V.CIPOS™ IKCS12F60F2AIKCS12F60F2CAbsolute Maximum Ratings(T J = 25°C, V DD = 15V Unless Otherwise Specified): Module SectionIGBT and Diode Section1 Monitored by pin 24CIPOS™ IKCS12F60F2A IKCS12F60F2CControl SectionRecommended Operation ConditionsAll voltages are absolute voltages referenced to V SS -Potential unless otherwise specified.IKCS12F60F2CStatic Characteristics(T c = 25°C, V DD = 15V, if not stated otherwise)1 Allowed number of short circuits: <1000; time between short circuits: >1s.Dynamic Characteristics(T c = 25°C, V DD = 15V, if not stated otherwise)Integrated ComponentsTypical Application1Characteristics(T c = 25°C, V DD = 15V, if not stated otherwise)I C , C O L L E C T O R C U R R E N TI F , f o r w a r d C U R R E N TV CE , COLLECTOR EMITTER VOLTAGEV F FORWARD VOLTAGEFigure 4. Typical IGBT output characteristicFigure 5. Typical diode forward current as afunction of forward voltaget , S W I T C H I N G T I M E S0A 5A 10A 15At , S W I T C H I N G T I M E S25℃50℃75℃100℃125℃I C , COLLECTOR CURRENTT vJ , JUNCTION TEMPERATUREFigure 6. Typical switching times as afunction of collector current (inductive load,T vJ =150°C,V CE =300VDynamic test circuit in Figure A)Figure 7. Typical switching times as afunction of junction temperature (inductive load, V CE = 300V, I C = 6A Dynamic test circuit in Figure A)E , S W I T C H I N G E N E R G YE , S W I T C H I N G E N E R G YI C , COLLECTOR CURRENTT vJ , JUNCTION TEMPERATUREFigure 8. Typical switching energy losses asa function of collector current (inductive load, T vJ =150°C, V CE =300VDynamic test circuit in Figure A)Figure 9. Typical switching energy losses asa function of junction temperature (inductive load, V CE = 300V, I C = 6A Dynamic test circuit in Figure A)R T S , N T C r e s i s t a n c eZ t h J C , T R A N S I E N T T H E R M A L R E S I S T A N C E10-210-1100 T NTC , NTC TEMPERATUREt P , PULSE WIDTHFigure 10. Characteristic of NTC as afunction of NTC temperatureFigure 11. Transient thermal impedance as afunction of pulse width (D =t P /T )Test Circuits and Parameter DefinitionFigure A: Dynamic test circuit Leakage inductance L σ =180nH Stray capacitance C σ =39pFFigure B: Definition of diodes switching characteristicsFigure C: Definition of Enable propagation delayFigure D: Switching times definition and switching energy definitionI RRMI FLIN1,2,3HIN1,2,3i CU , i CV , i v CEU , v CEV ∫⋅=Cx CEx dti v Eoff 0∫⋅=Eont Cx CEx dti v Eon 0Figure E: Short Pulse suppressionPackage Outline IKCS12F60F2ANote: There may occur discolorations on the copper surface without any effect of the thermal properties.Package Outline IKCS12F60F2CPackage Data。
Effect of Alkali-NaOH Solution on the Nature of Sy
J. Chem. Chem. Eng. 5 (2011) 246-249Effect of Alkali-NaOH Solution on the Nature of Synthesized Zeolite from 2:1 Tunisian Clays: XRD and MAS-NMR InvestigationMahdi Meftah1, Walid Oueslati1, 2 and Abdesslem Ben Haj Amara11. Laboratoire de Physique des Matériaux Lamellaires et Nanomatériaux Hybrides, UR05/13-01 (PMLNMH) Faculté des Sciences de Bizerte, 7021 Zarzouna, Tunisia2. Faculté des Sciences de Gafsa, Département de Physique, Campus Universiatire Sidi Ahmed Zarrouk, 2112 Gafsa, Tunisia Received: October 12, 2010 / Accepted: November 17, 2010 / Published: March 30, 2011.Abstract: This work focuses the effect of alkali-NaOH solution on the nature of synthesized zeolite from 2:1 Tunisian clays. This study was achieved using correlation between results obtained from X-ray diffraction (XRD) and MAS-NMR analysis. Preliminary treatment was adopted to prepare the starting sample that is placed in contact with NaOH solution at variable concentration. A specific hydrothermal reactor, allowing the control of pH > 9, temperature and a continuous stirring of the sample in the NaOH solution, was used to achieve these syntheses. The obtained results showed that, for concentration value ≈1N, the final complex presented characteristic XRD and MAS-NMR line of zeolite P. For 3N solution concentration we obtained zeolite HS. All synthesize process are controlled by XRD and MAS-NMR investigation.Key words: Alkali-NaOH solution, hydrothermal reactor, zeolite P, HS.1. IntroductionZeolites are crystalline aluminosilicates with a 3-dimensional and open anion framework consisting of oxygen-sharing TO4 tetrahedral, where T is Si or Al. Their framework contains interconnected voids which can be occupied with adsorbed molecules or cations. The general empirical formula is M x/n Al x Si(2-x)O4·mH2O where n is the valence of the exchangeable cation M, m water content and 0 ≤ x ≤ 1. The flexibility of the zeolite Si-O-Si bond explains the fact that more than 200 structures have been determined. The synthesized process of zeolite from natural clay minerals (i.e. 1:1 and 2:1 clay) was studied by several authors [1, 2]. In 1948, the first confirmation of zeolite synthesis had been traced by Barrer who reported the synthesis of the modernite [3].Corresponding author:Mahdi Meftah, Ph.D., research fields: materiel sciences, zeolite synthesize, spectroscopic methods, condensed matter. E-mail:********************.At the same time Milton and Back succeeded in synthesizing other zeolite, using lower temperature (≈100 ℃) and higher alkalinity [4]. Later, great successful progress is recorded by discovering one of the most commercially zeolite type Linde A (LTA) [5]. After that, the applied zeolite field was integrated in all industry aspect with the use of zeolite A: (1) to substitute the phosphate in detergent. Later zeolite P and X, AX (80% A, 20% X) were also introduced into the marked for detergent [6, 7], (2) in catalysis, ion exchange, molecular sieves, photochemistry and solar energy conversion [8]. In other way, zeolite type HS was synthesized using well and poorly ordered kaolinites and metakaolinites [9]. Indeed, the experimental protocol adopted on zeolite synthesis process does not be considered like novelty but some experimental parameters as the starting material, the particle size and the preparation mode influence the resulting material andcrystallisation rate. The main objective of this workAll Rights Reserved.Effect of Alkali-NaOH Solution on the Nature of Synthesized Zeolite from 2:1 Tunisian Clays: XRD andMAS-NMR Investigation247consists of characterizing zeolite synthesis process from 2:1 Tunisian clay and demonstrating the effect of alkali-NaOH concentration on the final obtained product.2. Materials and Methods2.1 Starting MaterialsThe starting materials are originated from the region Bir El Hfay (southern Tunisia). It is an irregular interstratified illite-smectite. The < 2 µm fraction was prepared according to the classic protocol of extraction which was developed by Tessier et al. [10]. The obtained structural formula per half unit cell is: (Si 4.00)(Al 1.10, Fe 0.50, Mg 0.40)O10(OH)2(M+ 0.4) with M+ is a monovalent cation. Preliminary treatment consisted of preparing an amorphous phase by heating the host mineral. This process is assured by heating ~50 g of solid at T > 800 ℃ [11].2.2 Experimental ProtocolA total of 100 mL of a given NaOH solution was heated to 100 ℃ in 250 mL reactor provided with a refrigerant system. A total of 10 g of clay was introduced. Reaction was maintained with magnetic stirring for periods of time ranging from 2 to 24 h. The final mixture was centrifuged to 10,000 rpm. The solid phase was washed several times with distilled water until pH 9.5-10, dialyzed with distilled water and dried at 80 ℃.2.3 Characterizing Method2.3.1 XRD AnalysisPowder X-ray diffraction patterns were obtained by a BRUKER D8 Advance diffractometer using Cu-Kαradiation and the 2θ range between 5-50° and operating at 40 KV and 30 mA. The determination of the lattice parameters from the XRD patterns requires identification of the peak positions, which can normally be achieved using a peak-search process, provided that all systematic errors have been eliminated by careful measurements of the zero-point detector position. The pattern indexing was performed using the indexing software TOPAS.2.3.2 MAS-NMR AnalysisThe Magic Angle Spinning Nuclear Magnetic Resonance (MAS-NMR) spectra were recorded on a BRUKER-300 MHz Ulrashield spectrometer. Experiments were performed using a 7.1 T magnetic field intensity corresponding to resonance frequencies 78.22 MHz and 59.62 MHz respectively for the core 27Al and 29Si. Impulse period has been optimized for each signal and does not exceed some μs. The numberof accumulation is higher than 500 in the case of the core 29Si (4.6% of abundance) and about 200 for the core 27Al (100% of abundance) for the two cores (27Al and 29Si).3. Results and Discussion3.1 XRD InvestigationWe reported in Fig. 1 that the XRD spectra of the solids obtained after reaction of clay with 1N NaOH solutions during different periods of time (i.e. 2 h, 4 h and 24 h). We noted that little change is observed for reaction times (Fig. 1) of 2 and 4 h. After 24 h, new peaks appeared, the most intense ones were situated at 12.44, 17.67, 21.62, 27.97 and 33.30° 2θ (Cu-Kα). They correspond to the P-zeolite as it was described by Ref. [2]. After a reaction time of 24 h the diffraction peaks of clay became very weak.Fig. 1 Experimental XRD patterns of heated illite-smectite and 1N NaOH treated at T = 100 ℃ during (a) 2 h; (b) 4 h; (c) 24 h, phases of zeolite P.All Rights Reserved.Effect of Alkali-NaOH Solution on the Nature of Synthesized Zeolite from 2:1 Tunisian Clays: XRD andMAS-NMR Investigation248When 3N NaOH solutions were used, changesappeared after a reaction time of 4 hours (Fig. 2). A newphase appeared having the following XRD peaks, 14,24.3, 27.99, 33.28 and 34.65° 2θ (Cu-Kα), according toRefs. [12, 13], this corresponds to the HS zeolite. Fromthe comparison of the patterns reported in Fig. 2, wenoted that after 24 h of reaction, it is clear that the peaksintensity related to the HS phase increase. This is in linewith the increasing amount of the zeolite phase.3.2 MAS-NMR AnalysisAccording to the NMR study of zeolite [14], the 29Sisignal of the sample obtained from treated startingmateriel with 1N NaOH solution. Fig. 3a presents achemical shifts observed at 79.82, 86.52, 91.36, and102.97 ppm with a low intensity corresponding tozeolite P. After 24 h of alkaline treatment, the 27AlMAS-RMN spectrum in Fig. 3b shows a line ofresonance at 58.21 ppm which can be attributed totetrahedral aluminium.The 29Si MAS-NMR and 27Al MAS-NMR spectra ofHS zeolite obtained by 3N NaOH solution treatmentare reported respectively in Figs. 4a and 4b. After 24 htreatment, we obtained five lines of chemical shiftlocated at -107.35, -106.92, -97.28, -91.87, -87.25 ppmfor 29Si and -58.32 ppm for 27Al. These shifts arerelated to zeolite HS [14, 15].Fig. 2 Experimental XRD patterns of heated illite-smectite and 1.5N NaOH treated at T = 100 ℃ during (a) 2 h; (b) 4 h;(c) 24 h, phases of zeolite HS. Fig. 3 (a) 29Si MAS-NMR spectrum of zeolite P obtained from heated illite-smectites. (b) 27Al MAS-NMR spectrum of zeolite P obtained from heated illite-smectites.These results demonstrate that the concentration of alkaline NaOH solution affect the final product nature (i.e synthesized zeolite). Indeed, zeolite can be synthesized using respectively low and high concentration value of NaOH solution.The characteristics and structural parameters for all synthesized phases are summarised in Table 1.4. ConclusionsIn this work we demonstrate that zeolite P is the main crystalline products obtained when heated interstratified illite-smectite is used as a starting materials with a low value of NaOH concentration.(a)(b)All Rights Reserved.Effect of Alkali-NaOH Solution on the Nature of Synthesized Zeolite from 2:1 Tunisian Clays: XRD andMAS-NMR Investigation249Fig. 4 (a) 29Si MAS-NMR spectrum of zeolite HS obtainedfrom heated illite-smectites. (b) 27Al MAS-NMR spectrumof zeolite HS obtained from heated illite-smectites.Table 1 Characteristics and structural parameters for allsynthesized phases.Sample heated illite-smectite T > 800 ℃NaOH solution 1.5N 3NTemp (℃) 100 100Time reaction (h) 24 24XRD analysis zeolite P zeolite HSComposition of material Na6(H2O)12[Si10Al6O32]Na6(H2O)8|[Si6Al6O24]Cell parameters a = b = c = 10.043 Åα = β = γ = 90°a =b =c = 8.848 Åα = β = γ = 90°NMR spectroscopy Si/Al ratio ≈1= 1Whereas zeolite HS is obtained by increasing the amount of NaOH solution.AcknowledgmentsThe manuscript was much improved by the constructive reviews of two anonymous reviewers. The editorial assistance of the editorial staff of the Journal of Chemistry and Chemical Engineering is acknowledged.References[1]M. Murat, A. Amokrane, J.P. Bastide, L. Montanaro,Synthesis of zeolites from thermally activated kaolinite,Some observations on nucleation and growth, Clay Miner.27 (1992) 119-130.[2] D.W. Breck, Zeolite Molecular Sieves: Structure,Chemistry and Uses, Wiley, New York, 1974.[3]R.M. Barrer, Syntheses and reactions of mordenite, J.Chem. Soc. 23(1948) 2158- 2163.[4]R.M. Milton, U.S. Patent 2 882 244, 1959.[5] A. Carlos, R. Ríos, D.W. Craig, M.C. Oscar, Synthesis ofzeolite LTA from thermally treated kaolinite, Rev. Fac. Ing.Univ. Antioquia 53 (2010) 30-41.[6]R.C. Adams, L. Xu, K. Moller, T. Bein, W.N. Delgass,Zeolite encapsulated vanadium oxo species for the catalyticreduction of NO by NH3, Catalysis and Photocatalysis onMetal Oxides 33 (1-3) (1997) 263-278.[7]H.G. Hautal, Laundry, Detergent Zeolites in anEcobalance Spotligt-Sepawa, Tagung Bad Diirkheim, 1996.[8] A. Corma, C. Corell, J. Perez-Pariente, Synthesis andcharacterization of the MCM-22 zeolite, Zeolites 15 (1995)2-8.[9] D.S. Coombs, T. Whetten, Geological society of americacomposition of 4-analcime from sedimentary and burialmetamorphic rocks, GSA Bulletin 78 (2) (1967) 269-282.[10]H.B. Rhaim, D. Tessier, A.B.H. Amara, Mineralogy of the< 2 µm fraction of three mixed-layer clays from southernand central Tunisia, Clay Mineral 35 (2) (2000) 375-381.[11]M. Meftah, W. Oueslati, A.B.H. Amara, Synthesis processof zeolite P using a poorly crystallized kaolinite, PhysicsProcedia (2009) 1081-1086.[12]R.M. Barrer, E.A.D. White, The hydrothermal chemistryof silicates, part I: Synthesis lithium aluminosilicates, J.Chem. Soc. (1951) 1267.[13]I. Hassan, H.D. Grundy, The crystal structures ofsodalite-group minerals, Acta Cryst. B 40 (1984) 6-13. [14] A. Madani, A. Aznar, J. Sanz, J.M. Serratosa, 29Si and27Al NMR study of zeolite formation from alkali-leachedkaolinites: Influence of thermal preactivation, J. Phys.Chem. 94 (1990) 760-765.[15]N. Benharrats, M. Belbachir, A.P. Legrand, J.B.D’Espinose de la Caillerie, 29Si and 27Al MAS NMR studyof the zeolitization of kaolin by alkali leaching, ClayMiner. 38 (2003) 49-61.(a)(b) All Rights Reserved.。
OECD绿色增长战略阶段性报告2010英文版
Box 1. Contribution of the Green Growth Strategy ................................. 14 Box 2. Progress on key environmental challenges.................................. 16 Box 3. Environmental externalities and market failures ....................... 19 Box 4. Key pillars for pro-poor Green Growth ......................................... 25 Box 5. Employment potential of green components of stimulus packages – some examples ........................................................................ 27 Box 6. The scope for moving forward public infrastructure investment .................................................................................................... 29 Box 7. Car-scrapping schemes and green growth................................... 30 Box 8. Agricultural subsidies and green growth ..................................... 35 Box 9. Examples of renewed interest in CO2-related taxes.................... 38 Box 10. Proceeds from auctioned emissions trading permits: some examples ....................................................................................................... 40 Box 11. Addressing carbon leakage and competitiveness impacts of climate policies............................................................................................. 41 Box 12. Patents and international technology transfer.......................... 47 Box 13. Transport – a growing source of CO2 emissions1 ....................... 52 Box 14. An extension of the OECD ENV-Linkages model....................... 56 Box 15. Regional and local implications of a transition towards a low-carbon economy and green growth .................................................. 58 Box 16. Key principles in selecting indicators to monitor progress with green growth........................................................................................ 62 Box II.1. The role of regulatory policy and reform .................................. 77 Box II.2. Markets and competition............................................................. 79 Box II.3. Consumer policy ........................................................................... 80 Box II.4. Responsible business conduct in support of a low carbon economy ........................................................................................................ 81 Box II.5. Taxation, innovation and the environment ............................. 82 Box II.6. “Smart” ICT applications enabling green growth .................... 84 Box II.7. Regional innovation systems for eco-innovation .................... 85 Box II.8. New models for international co-operation on ecoinnovation ..................................................................................................... 86 Box II.9. Enhancing the cost-effectiveness of biodiversity policies...... 87 Box II.10. Outcome of the February 2010 OECD Agriculture Ministerial Meeting ...................................................................................... 88 Box II.11. Relevant work for green growth measurements ................... 89
SCI收录期刊――生物多样性保护学科(精)
SCI收录期刊——生物多样性保护学科万跃华2009年9月27日截至到2009年9月SCI扩展版收录生物多样性保护学科期刊34种(SCI核心版12种,其中2009年开始被SCI收录的生物多样性保护学科期刊1种,2008年开始被SCI收录的生物多样性保护学科期刊3种,出版地为的美国生物多样性保护期刊17种,英国4种,荷兰3种,南非2种,德国、澳大利亚、巴西、加拿大、阿富汗、日本、斯里兰、墨西哥、智利各1种。
2005-2009年9月SCI共收录至少有一位中国作者(不包括台湾的生物多样性保护学科论文415篇,其中2009年125篇(30.1205%, 2008年110篇(26.5060%,2007年60篇(14.4578%,2006年68篇(16.3855 %,2005年51篇(12.2892%,2004年1篇(0.2410%。
415篇论文包括学术论文390篇、评论15篇、会议论文4篇、社论3篇、更正2篇、通讯1篇。
2005-2009年9月中国研究论文主要发表在18种SCI收录的生物多样性保护期刊上:其中CONSERV ATION GENETICS《资源保护遗传学》116篇、JOURNAL OF NATURAL HISTORY《博物学杂志》75篇、GLOBAL CHANGE BIOLOGY 《全球变化生物学》60篇、BIODIVERSITY AND CONSERV ATION《生物品种与保护》55篇、CONSERV ATION BIOLOGY《自然保护生物学》23篇、BIOLOGICAL INVASIONS《生物入侵》19篇、BIOLOGICAL CONSERVATION《生物保护》17篇、DIVERSITY AND DISTRIBUTIONS《生物多样性与分布》10篇、AMERICAN MUSEUM NOVITATES《美国博物馆通讯》9篇、POLAR BIOLOGY 《极地生物学》9篇。
主要研究单位有中国科学院(CHINESE ACAD SCI183篇、中国海洋大学(OCEAN UNIV CHINA28篇、浙江大学(ZHEJIANG UNIV19篇、中国水产研究院(CHINESE ACAD FISHERY SCI18篇、复旦大学(FUDAN UNIV16篇、兰州大学(LANZHOU UNIV16篇、四川大学(SICHUAN UNIV15篇、香港大学(UNIV HONG KONG15篇、中国农业科学院(CHINESE ACAD AGR SCI13篇.2005-2009年9月中国学者发表在18种生物多样性保护期刊415篇论文共被引用1017次,其中2005年被引用11次,2006年被引用67次, 2007年被引用155次,2008年被引用365次,2009年被引用421次,平均引用2.45次,平均引用次数/年203.40,H指数为12(有12篇文章每篇最少被引用12次。
民族药理学作者须知
JOURNAL OF ETHNOPHARMACOLOGYAn Interdisciplinary Journal Devoted to Indigenous DrugsAUTHOR INFORMATION PACK TABLE OF CONTENTS• Description• Audience• Impact Factor• Abstracting and Indexing • Editorial Board• Guide for Authors p.1p.2p.2p.2p.2p.4ISSN: 0378-8741DESCRIPTIONThe Journal of Ethnopharmacology is dedicated to the exchange of information and understandings about people's use of plants, fungi, animals, microorganisms and minerals and their biological and pharmacological effects based on the principles established through international conventions. Early people confronted with illness and disease, discovered a wealth of useful therapeutic agents in the plant and animal kingdoms. The empirical knowledge of these medicinal substances and their toxic potential was passed on by oral tradition and sometimes recorded in herbals and other texts on materia medica. Many valuable drugs of today (e.g., atropine, ephedrine, tubocurarine, digoxin, reserpine) came into use through the study of indigenous remedies. Chemists continue to use plant-derived drugs (e.g., morphine, taxol, physostigmine, quinidine, emetine) as prototypes in their attempts to develop more effective and less toxic medicinals.In recent years the preservation of local knowledge, the promotion of indigenous medical systems in primary health care, and the conservation of biodiversity have become even more of a concern to all scientists working at the interface of social and natural sciences but especially to ethnopharmacologists. Recognizing the sovereign rights of States over their natural resources, ethnopharmacologists are particularly concerned with local people's rights to further use and develop their autochthonous resources.Accordingly, today's ethnopharmacological research embraces the multidisciplinary effort in the:• documentation of indigenous medical knowledge,• scientific study of indigenous medicines in order to contribute in the long-run to improved health care in the regions of study, as well as• search for pharmacologically unique principles from existing indigenous remedies.The Journal of Ethnopharmacology publishes original articles concerned with the observation and experimental investigation of the biological activities of plant and animal substances used in the traditional medicine of past and present cultures. The journal will particularly welcome interdisciplinary papers with an ethnopharmacological, an ethnobotanical or an ethnochemical approach to the study of indigenous drugs. Reports of anthropological and ethnobotanical field studies fall within the journal's scope. Studies involving pharmacological and toxicological mechanisms of action are especially welcome. Clinical studies on efficacy will be considered if contributing to the understanding of specific ethnopharmacological problems. The journal welcomes review articles in the above mentioned fields especially those highlighting the multi-disciplinary nature of ethnopharmacology. Commentaries are by invitation only.AUDIENCEEthnopharmacologists, Medicinal Chemists, Pharmacologists, Toxicologists, Anthropologists, Pharmacognosists, Ethnobotanists, Economic Botanists, EthnobiologistsIMPACT FACTOR2014: 2.998 © Thomson Reuters Journal Citation Reports 2015ABSTRACTING AND INDEXINGAGRICOLABIOSISCambridge Scientific AbstractsChemical AbstractsCurrent Contents/Life SciencesMEDLINE®International Pharmaceutical AbstractsEMBASENAPRALERT (Natural Products Alert)Science Citation IndexCAB AbstractsScopusEMBiologyEDITORIAL BOARDEditor-in-Chief:R. Verpoorte, Gorlaeus Lab., Universiteit Leiden, Einsteinweg 55, 2333 CC, Leiden, NetherlandsDeputy Editor-in-ChiefA.M. Viljoen, Tshwane University of Technology, Pretoria, South AfricaAssociate Editor:D. Guo, Chinese Academy of Sciences (CAS), Shanghai, ChinaA.K. Jäger, University of Copenhagen, Copenhagen O, DenmarkG. Lin, Chinese University of Hong Kong, Hong Kong, Hong KongP.K. Mukherjee, Jadavpur University, Kolkata, IndiaG. Schmeda Hirschmann, Universidad de Talca, Talca, ChileA. Shikov, Saint Petersburg Institute of Pharmacy, Kuzmolovo P 245, Russian FederationE. Yesilada, Yeditepe University, Erenkoy-Istanbul, TurkeyReviews Editor (including Commentaries and Book Reviews):M. Heinrich, The School of Pharmacy, University of London, 29-39 Brunswick Square, London, WC1N 1AX, UK If you want to suggest a review, please provide a structured abstract and include an annotated table of contents and a short CV of the lead author(s).Managing Editor:B. Pomahacova, Leiden University, Leiden, NetherlandsI. Vermaak, Tshwane University of Technology, Pretoria, South AfricaM. Sandasi, Tshwane University of Technology, Pretoria, South AfricaL.J. McGaw, University of Pretoria, Pretoria, South AfricaEditorial Board:S. Alban, Kiel, GermanyM.J. Balick, Bronx, New York, USAR. BauerG. Bourdy, Cayenne, French GuianaJ.B. Calixto, Florianópolis, BrazilC-T. Che, Hong Kong, Hong KongG.A. Cordell, Evanston, Illinois, USAV.S. da Silva Bolzani, Araraquara, BrazilJ. Ding, Shanghai, ChinaV.M. Dirsch, Vienna, AustriaE. Elisabetsky, Porto Alegre, BrazilJ. Fleurentin, Metz, FranceB.L. Furman, Glasgow, UKM.P. Germano, Messina, ItalyJ. Gertsch, Bern, SwitzerlandA.H. Gilani, Karachi, PakistanM.P. Gupta, Panama City, PanamaA. Hensel, Münster, GermanyP.J. Houghton, London, UKZ. Ismail, Penang, MalaysiaW. Jia, Kannapolis, North Carolina, USAT. Johns, Ste. Anne de Bellevue, Quebec, Canada A.K. Jäger, Copenhagen O, DenmarkG. Kavalali, Istanbul, TurkeyH-S. Kim, Cheongju, South KoreaJ. Kim, Seoul, South KoreaY. Kimura, Ehime, JapanM.A. Lacaille-Dubois, Dijon, FranceM. Leonti, Cagliari, ItalyE. Matteucci, Pisa, ItalyI. Merfort, Freiburg, GermanyJ.J.M. Meyer, Pretoria, South AfricaD.E. MoermanD.A. Mulholland, Guildford, England, UKA. Panthong, Chiang Mai, ThailandX. Peigen, Beijing, ChinaA. Pieroni, Pollenzo/Bra, ItalyD.D. Soejarto, Chicago, Illinois, USAE. Speroni, Bologna, ItalyA.J. Vlietinck, Antwerpen, BelgiumH. Wagner, München, GermanyC.S. Weckerle, Zurich, SwitzerlandC.W. Wright, Bradford, UKS. Zacchino, Rosario, ArgentinaFounding Editors:J.G. BruhnL. Rivier, Lausanne, SwitzerlandGUIDE FOR AUTHORSINTRODUCTIONThe Journal of Ethnopharmacology is dedicated to the exchange of information and understandings about people's use of plants, fungi, animals, microorganisms and minerals and their biological and pharmacological effects based on the principles established through international conventions. Early people, confronted with illness and disease, discovered a wealth of useful therapeutic agents in the plant and animal kingdoms. The empirical knowledge of these medicinal substances and their toxic potential was passed on by oral tradition and sometimes recorded in herbals and other texts on materia medica. Many valuable drugs of today (e.g., atropine, ephedrine, tubocurarine, digoxin, reserpine) came into use through the study of indigenous remedies. Chemists continue to use plant-derived drugs (e.g., morphine, taxol, physostigmine, quinidine, emetine) as prototypes in their attempts to develop more effective and less toxic medicinals.Please note that figures and tables should be embedded in the text as close as possible to where they are initially cited. It is also mandatory to upload separate graphic and table files as these will be required if your manuscript is accepted for publication.Classification of your paperPlease note that upon submitting your article you will have to select at least one classification and at least three of the given keywords. You can preview the list of classifications and keywords (here). This information is needed by the Editors to more quickly process your article. In addition to this, you can submit free keywords as described below under "Keywords".The "rules of 5"The Editors and Editorial Board have developed the "Rules of 5" for publishing in JEP. We have produced five clear criteria that each author needs to think about before submitting a manuscript and setting the whole process of editing and reviewing at work. Click here.For more details on how to write a world class paper, please visit our Pharmacology Author Resources page.Authors are encouraged to submit video material or animation sequences to support and enhance your scientific research. For more information please see the paragraph on video data below. Types of paperThe Journal of Ethnopharmacology will accept the following contributions:1. Original research articles - whose length is not limited and should include Title, Abstract, Methods and Materials, Results, Discussion, Conclusions, Acknowledgements and References. As a guideline, a full length paper normally occupies no more than 10 printed pages of the journal, including tables and illustrations.2. 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Outlines for potential reviews need to include: A detailed abstract using the structure provided in the guidelines An annotated table of contents A short CV of the lead author5. Book reviews - Books for review should be sent to the Reviews Editor.6. Commentaries - invited, peer-reviewed, critical discussion about crucial aspects of the field but most importantly methodological and conceptual-theoretical developments in the field and should also provide a standard, for example, for pharmacological methods to be used in papers in the Journal of Ethnopharmacology. The scientific dialogue differs greatly in the social / cultural and natural sciences, the discussions about the common foundations of the field are ongoing and thepapers published should contribute to a transdisciplinary and multidisciplinary discussion. The length should be a maximum of 2-3 printed pages or 2500 words. Please contact the Reviews Editor j.ethnopharmacol@ with an outline.7. Conference announcements and news.BEFORE YOU BEGINEthics in publishingFor information on Ethics in publishing and Ethical guidelines for journal publication see /publishingethics and /journal-authors/ethics. Policy and ethicsIn the covering letter, the author must also declare that the study was performed according to the international, national and institutional rules considering animal experiments, clinical studies and biodiversity rights. See below for further information. The ethnopharmacological importance of the study must also be explained in the cover letter.Animal and clinical studies - Investigations using experimental animals must state in the Methods section that the research was conducted in accordance with the internationally accepted principles for laboratory animal use and care as found in for example the European Community guidelines (EEC Directive of 1986; 86/609/EEC) or the US guidelines (NIH publication #85-23, revised in 1985). 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Authors who feel their English language manuscript may require editing to eliminate possible grammatical or spelling errors and to conform to correct scientific English may wish to use the English Language Editing service available from Elsevier's WebShop (/languageediting/) or visit our customer support site () for more information.SubmissionOur online submission system guides you stepwise through the process of entering your article details and uploading your files. The system converts your article files to a single PDF file used in the peer-review process. Editable files (e.g., Word, LaTeX) are required to typeset your article for final publication. All correspondence, including notification of the Editor's decision and requests for revision, is sent by e-mail.Additional informationAuthors who want to submit a manuscript should consult and peruse carefully recent issues of the journal for format and style. Authors must include the following contact details on the title page of their submitted manuscript: full postal address; fax; e-mail. All manuscripts submitted are subject to peer review. The minimum requirements for a manuscript to qualify for peer review are that it has been prepared by strictly following the format and style of the journal as mentioned, that it is written in good English, and that it is complete. Manuscripts that have not fulfilled these requirements will be returned to the author(s).In addition, you are recommended to adhere to the research standards described in the following articles:Cos P., Vlietinck A.J., Berghe D.V., et al. (2006) Anti-infective potential of natural products: how to develop a stronger in vitro 'proof-of-concept'. Journal of Ethnopharmacology, 106: 290-302.Matteucci, E., Giampietro, O. (2008) Proposal open for discussion: defining agreed diagnostic procedures in experimental diabetes research. Journal of Ethnopharmacology,115: 163-172.Froede, T.SA. and Y.S. Medeiros, Y.S. (2008) Animal models to test drugs with potential antidiabetic activity. Journal of Ethnopharmacology 115: 173-183. Gertsch J. (2009) How scientific is the science in ethnopharmacology? Historical perspectives and epistemological problems. Journal of Ethnopharmacology, 122: 177-183.Chan K., et al. (2012) Good practice in reviewing and publishing studies on herbal medicine, with special emphasis on traditional Chinese medicine and Chinese Materia Medica. Journal of Ethnopharmacology 140: 469-475.Heinrich, M., Edwards. S., Moerman. D.E.. and Leonti. M. (2009), Ethnopharmacological field studies: a critical assessment of their conceptual basis and methods. J. Ethnopharmacol, 124: 1-17. PREPARATIONUse of word processing softwareIt is important that the file be saved in the native format of the word processor used. The text should be in single-column format. Keep the layout of the text as simple as possible. 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Peters (2010) Episodic Future Thinking Reduces Reward Delay Discounting
NeuronArticleEpisodic Future Thinking ReducesReward Delay Discounting through an Enhancement of Prefrontal-Mediotemporal InteractionsJan Peters1,*and Christian Bu¨chel11NeuroimageNord,Department of Systems Neuroscience,University Medical Center Hamburg-Eppendorf,Hamburg20246,Germany*Correspondence:j.peters@uke.uni-hamburg.deDOI10.1016/j.neuron.2010.03.026SUMMARYHumans discount the value of future rewards over time.Here we show using functional magnetic reso-nance imaging(fMRI)and neural coupling analyses that episodic future thinking reduces the rate of delay discounting through a modulation of neural decision-making and episodic future thinking networks.In addition to a standard control condition,real subject-specific episodic event cues were presented during a delay discounting task.Spontaneous episodic imagery during cue processing predicted how much subjects changed their preferences toward more future-minded choice behavior.Neural valuation signals in the anterior cingulate cortex and functional coupling of this region with hippo-campus and amygdala predicted the degree to which future thinking modulated individual preference functions.A second experiment replicated the behavioral effects and ruled out alternative explana-tions such as date-based processing and temporal focus.The present data reveal a mechanism through which neural decision-making and prospection networks can interact to generate future-minded choice behavior.INTRODUCTIONThe consequences of choices are often delayed in time,and in many cases it pays off to wait.While agents normally prefer larger over smaller rewards,this situation changes when rewards are associated with costs,such as delays,uncertainties,or effort requirements.Agents integrate such costs into a value function in an individual manner.In the hyperbolic model of delay dis-counting(also referred to as intertemporal choice),for example, a subject-specific discount parameter accurately describes how individuals discount delayed rewards in value(Green and Myer-son,2004;Mazur,1987).Although the degree of delay discount-ing varies considerably between individuals,humans in general have a particularly pronounced ability to delay gratification, and many of our choices only pay off after months or even years. It has been speculated that the capacity for episodic future thought(also referred to as mental time travel or prospective thinking)(Bar,2009;Schacter et al.,2007;Szpunar et al.,2007) may underlie the human ability to make choices with high long-term benefits(Boyer,2008),yielding higher evolutionaryfitness of our species.At the neural level,a number of models have been proposed for intertemporal decision-making in humans.In the so-called b-d model(McClure et al.,2004,2007),a limbic system(b)is thought to place special weight on immediate rewards,whereas a more cognitive,prefrontal-cortex-based system(d)is more involved in patient choices.In an alternative model,the values of both immediate and delayed rewards are thought to be repre-sented in a unitary system encompassing medial prefrontal cortex(mPFC),posterior cingulate cortex(PCC),and ventral striatum(VS)(Kable and Glimcher,2007;Kable and Glimcher, 2010;Peters and Bu¨chel,2009).Finally,in the self-control model, values are assumed to be represented in structures such as the ventromedial prefrontal cortex(vmPFC)but are subject to top-down modulation by prefrontal control regions such as the lateral PFC(Figner et al.,2010;Hare et al.,2009).Both the b-d model and the self-control model predict that reduced impulsivity in in-tertemporal choice,induced for example by episodic future thought,would involve prefrontal cortex regions implicated in cognitive control,such as the lateral PFC or the anterior cingulate cortex(ACC).Lesion studies,on the other hand,also implicated medial temporal lobe regions in decision-making and delay discounting. In rodents,damage to the basolateral amygdala(BLA)increases delay discounting(Winstanley et al.,2004),effort discounting (Floresco and Ghods-Sharifi,2007;Ghods-Sharifiet al.,2009), and probability discounting(Ghods-Sharifiet al.,2009).Interac-tions between the ACC and the BLA in particular have been proposed to regulate behavior in order to allow organisms to overcome a variety of different decision costs,including delays (Floresco and Ghods-Sharifi,2007).In line with thesefindings, impairments in decision-making are also observed in humans with damage to the ACC or amygdala(Bechara et al.,1994, 1999;Manes et al.,2002;Naccache et al.,2005).Along similar lines,hippocampal damage affects decision-making.Disadvantageous choice behavior has recently been documented in patients suffering from amnesia due to hippo-campal lesions(Gupta et al.,2009),and rats with hippocampal damage show increased delay discounting(Cheung and Cardinal,2005;Mariano et al.,2009;Rawlins et al.,1985).These observations are of particular interest given that hippocampal138Neuron66,138–148,April15,2010ª2010Elsevier Inc.damage impairs the ability to imagine novel experiences (Hassa-bis et al.,2007).Based on this and a range of other studies,it has recently been proposed that hippocampus and parahippocam-pal cortex play a crucial role in the formation of vivid event repre-sentations,regardless of whether they lie in the past,present,or future (Schacter and Addis,2009).The hippocampus may thus contribute to decision-making through its role in self-projection into the future (Bar,2009;Schacter et al.,2007),allowing an organism to evaluate future payoffs through mental simulation (Johnson and Redish,2007;Johnson et al.,2007).Future thinking may thus affect intertemporal choice through hippo-campal involvement.Here we used model-based fMRI,analyses of functional coupling,and extensive behavioral procedures to investigate how episodic future thinking affects delay discounting.In Exper-iment 1,subjects performed a classical delay discounting task(Kable and Glimcher,2007;Peters and Bu¨chel,2009)that involved a series of choices between smaller immediate and larger delayed rewards,while brain activity was measured using fMRI.Critically,we introduced a novel episodic condition that involved the presentation of episodic cue words (tags )obtained during an extensive prescan interview,referring to real,subject-specific future events planned for the respective day of reward delivery.This design allowed us to assess individual discount rates separately for the two experimental conditions,allowing us to investigate neural mechanisms mediating changes in delay discounting associated with episodic thinking.In a second behavioral study,we replicated the behavioral effects of Exper-iment 1and addressed a number of alternative explanations for the observed effects of episodic tags on discount rates.RESULTSExperiment 1:Prescan InterviewOn day 1,healthy young volunteers (n =30,mean age =25,15male)completed a computer-based delay discounting proce-dure to estimate their individual discount rate (Peters and Bu ¨-chel,2009).This discount rate was used solely for the purpose of constructing subject-specific trials for the fMRI session (see Experimental Procedures ).Furthermore,participants compiled a list of events that they had planned in the next 7months (e.g.,vacations,weddings,parties,courses,and so forth)andrated them on scales from 1to 6with respect to personal rele-vance,arousal,and valence.For each participant,seven subject-specific events were selected such that the spacing between events increased with increasing delay to the episode,and that events were roughly matched based on personal rele-vance,arousal,and valence.Multiple regression analysis of these ratings across the different delays showed no linear effects (relevance:p =0.867,arousal:p =0.120,valence:p =0.977,see Figure S1available online).For each subject,a separate set of seven delays was computed that was later used as delays in the control condition.Median and range for the delays used in each condition are listed in Table S1(available online).For each event,a label was selected that would serve as a verbal tag for the fMRI session.Experiment 1:fMRI Behavioral ResultsOn day 2,volunteers performed two sessions of a delay dis-counting procedure while fMRI was measured using a 3T Siemens Scanner with a 32-channel head-coil.In each session,subjects made a total of 118choices between 20V available immediately and larger but delayed amounts.Subjects were told that one of their choices would be randomly selected and paid out following scanning,with the respective delay.Critically,in half the trials,an additional subject-specific episodic tag (see above,e.g.,‘‘vacation paris’’or ‘‘birthday john’’)was displayed based on the prescan interview (see Figure 1)indicating which event they had planned on the particular day (episodic condi-tion),whereas in the remaining trials,no episodic tag was pre-sented (control condition).Amount and waiting time were thus displayed in both conditions,but only the episodic condition involved the presentation of an additional subject-specific event tag.Importantly,nonoverlapping sets of delays were used in the two conditions.Following scanning,subjects rated for each episodic tag how often it evoked episodic associations during scanning (frequency of associations:1,never;to 6,always)and how vivid these associations were (vividness of associa-tions:1,not vivid at all;to 6,highly vivid;see Figure S1).Addition-ally,written reports were obtained (see Supplemental Informa-tion ).Multiple regression revealed no significant linear effects of delay on postscan ratings (frequency:p =0.224,vividness:p =0.770).We averaged the postscan ratings acrosseventsFigure 1.Behavioral TaskDuring fMRI,subjects made repeated choices between a fixed immediate reward of 20V and larger but delayed amounts.In the control condi-tion,amounts were paired with a waiting time only,whereas in the episodic condition,amounts were paired with a waiting time and a subject-specific verbal episodic tag indicating to the subjects which event they had planned at the respective day of reward delivery.Events were real and collected in a separate testing session prior to the day of scanning.NeuronEpisodic Modulation of Delay DiscountingNeuron 66,138–148,April 15,2010ª2010Elsevier Inc.139and the frequency/vividness dimensions,yielding an‘‘imagery score’’for each subject.Individual participants’choice data from the fMRI session were then analyzed byfitting hyperbolic discount functions to subject-specific indifference points to obtain discount rates (k-parameters),separately for the episodic and control condi-tions(see Experimental Procedures).Subjective preferences were well-characterized by hyperbolic functions(median R2 episodic condition=0.81,control condition=0.85).Discount functions of four exemplary subjects are shown in Figure2A. For both conditions,considerable variability in the discount rate was observed(median[range]of discount rates:control condition=0.014[0.003–0.19],episodic condition=0.013 [0.002–0.18]).To account for the skewed distribution of discount rates,all further analyses were conducted on the log-trans-formed k-parameters.Across subjects,log-transformed discount rates were significantly lower in the episodic condition compared with the control condition(t(29)=2.27,p=0.016),indi-cating that participants’choice behavior was less impulsive in the episodic condition.The difference in log-discount rates between conditions is henceforth referred to as the episodic tag effect.Fitting hyperbolic functions to the median indifference points across subjects also showed reduced discounting in the episodic condition(discount rate control condition=0.0099, episodic condition=0.0077).The size of the tag effect was not related to the discount rate in the control condition(p=0.56). We next hypothesized that the tag effect would be positively correlated with postscan ratings of episodic thought(imagery scores,see above).Robust regression revealed an increase in the size of the tag effect with increasing imagery scores (t=2.08,p=0.023,see Figure2B),suggesting that the effect of the tags on preferences was stronger the more vividly subjects imagined the episodes.Examples of written postscan reports are provided in the Supplemental Results for participants from the entire range of imagination ratings.We also correlated the tag effect with standard neuropsychological measures,the Sensation Seeking Scale(SSS)V(Beauducel et al.,2003;Zuck-erman,1996)and the Behavioral Inhibition Scale/Behavioral Approach Scale(BIS/BAS)(Carver and White,1994).The tag effect was positively correlated with the experience-seeking subscale of the SSS(p=0.026)and inversely correlated with the reward-responsiveness subscale of the BIS/BAS scales (p<0.005).Repeated-measures ANOVA of reaction times(RTs)as a func-tion of option value(lower,similar,or higher relative to the refer-ence option;see Experimental Procedures and Figure2C)did not show a main effect of condition(p=0.712)or a condition 3value interaction(p=0.220),but revealed a main effect of value(F(1.8,53.9)=16.740,p<0.001).Post hoc comparisons revealed faster RTs for higher-valued options relative to similarly (p=0.002)or lower valued options(p<0.001)but no difference between lower and similarly valued options(p=0.081).FMRI DataFMRI data were modeled using the general linear model(GLM) as implemented in SPM5.Subjective value of each decision option was calculated by multiplying the objective amount of each delayed reward with the discount fraction estimated behaviorally based on the choices during scanning,and included as a parametric regressor in the GLM.Note that discount rates were estimated separately for the control and episodic conditions(see above and Figure2),and we thus used condition-specific k-parameters for calculation of the subjective value regressor.Additional parametric regressors for inverse delay-to-reward and absolute reward magnitude, orthogonalized with respect to subjective value,were included in theGLM.Figure2.Behavioral Data from Experiment1Shown are experimentally derived discount func-tions from the fMRI session for four exemplaryparticipants(A),correlation with imagery scores(B),and reaction times(RTs)(C).(A)Hyperbolicfunctions werefit to the indifference points sepa-rately for the control(dashed lines)and episodic(solid lines,filled circles)conditions,and thebest-fitting k-parameters(discount rates)and R2values are shown for each subject.The log-trans-formed difference between discount rates wastaken as a measure of the effect of the episodictags on choice preferences.(B)Robust regressionrevealed an association between log-differences indiscount rates and imagery scores obtained frompostscan ratings(see text).(C)RTs were signifi-cantly modulated by option value(main effectvalue p<0.001)with faster responses in trialswith a value of the delayed reward higher thanthe20V reference amount.Note that althoughseven delays were used for each condition,somedata points are missing,e.g.,onlyfive delay indif-ference points for the episodic condition areplotted for sub20.This indicates that,for the twolongest delays,this subject never chose the de-layed reward.***p<0.005.Error bars=SEM.Neuron Episodic Modulation of Delay Discounting140Neuron66,138–148,April15,2010ª2010Elsevier Inc.Episodic Tags Activate the Future Thinking NetworkWe first analyzed differences in the condition regressors without parametric pared to those of the control condi-tion,BOLD responses to the presentation of the delayed reward in the episodic condition yielded highly significant activations (corrected for whole-brain volume)in an extensive network of brain regions previously implicated in episodic future thinking (Addis et al.,2007;Schacter et al.,2007;Szpunar et al.,2007)(see Figure 3and Table S2),including retrosplenial cortex (RSC)/PCC (peak MNI coordinates:À6,À54,14,peak z value =6.26),left lateral parietal cortex (LPC,À44,À66,32,z value =5.35),and vmPFC (À8,34,À12,z value =5.50).Distributed Neural Coding of Subjective ValueWe then replicated previous findings (Kable and Glimcher,2007;Kable and Glimcher,2010;Peters and Bu¨chel,2009)using a conjunction analysis (Nichols et al.,2005)searching for regions showing a positive correlation between the height of the BOLD response and subjective value in the control and episodic condi-tions in a parametric analysis (Figure 4A and Table S3).Note that this is a conservative analysis that requires that a given voxel exceed the statistical threshold in both contrasts separately.This analysis revealed clusters in the lateral orbitofrontal cortex (OFC,À36,50,À10,z value =4.50)and central OFC (À18,12,À14,z value =4.05),bilateral VS (right:10,8,0,z value =4.22;left:À10,8,À6,z value =3.51),mPFC (6,26,16,z value =3.72),and PCC (À2,À28,24,z value =4.09),representing subjective (discounted)value in both conditions.We next analyzed the neural tag effect,i.e.,regions in which the subjective value correlation was greater for the episodic condi-tion as compared with the control condition (Figure 4B and Table S4).This analysis revealed clusters in the left LPC (À66,À42,32,z value =4.96,),ACC (À2,16,36,z value =4.76),left dorsolateral prefrontal cortex (DLPFC,À38,36,36,z value =4.81),and right amygdala (24,2,À24,z value =3.75).Finally,we performed a triple-conjunction analysis,testing for regions that were correlated with subjective value in both conditions,but in which the value correlation increased in the episodic condition.Only left LPC showed this pattern (À66,À42,30,z value =3.55,see Figure 4C and Table S5),the same region that we previously identified as delay-specific in valuation (Petersand Bu¨chel,2009).There were no regions in which the subjective value correlation was greater in the control condition when compared with the episodic condition at p <0.001uncorrected.ACC Valuation Signals and Functional Connectivity Predict Interindividual Differences in Discount Function ShiftsWe next correlated differences in the neural tag effect with inter-individual differences in the size of the behavioral tag effect.To this end,we performed a simple regression analysis in SPM5on the single-subject contrast images of the neural tag effect (i.e.,subjective value correlation episodic >control)using the behavioral tag effect [log(k control )–log(k episodic )]as an explana-tory variable.This analysis revealed clusters in the bilateral ACC (right:18,34,18,z value =3.95,p =0.021corrected,left:À20,34,20,z value =3.52,Figure 5,see Table S6for a complete list).Coronal sections (Figure 5C)clearly show that both ACC clusters are located in gray matter of the cingulate sulcus.Because ACC-limbic interactions have previously been impli-cated in the control of choice behavior (Floresco and Ghods-Sharifi,2007;Roiser et al.,2009),we next analyzed functional coupling with the right ACC from the above regression contrast (coordinates 18,34,18,see Figure 6A)using a psychophysiolog-ical interaction analysis (PPI)(Friston et al.,1997).Note that this analysis was conducted on a separate first-level GLM in which control and episodic trials were modeled as 10s miniblocks (see Experimental Procedures for details).We first identified regions in which coupling with the ACC changed in the episodic condition compared with the control condition (see Table S7)and then performed a simple regression analysis on these coupling parameters using the behavioral tag effect as an explanatory variable.The tag effect was associated with increased coupling between ACC and hippocampus (À32,À18,À16,z value =3.18,p =0.031corrected,Figure 6B)and ACC and left amygdala (À26,À4,À26,z value =2.95,p =0.051corrected,Figure 6B,see Table S8for a complete list of activa-tions).The same regression analysis in a second PPI with the seed voxel placed in the contralateral ACC region from the same regression contrast (À20,34,22,see above)yielded qual-itatively similar,though subthreshold,results in these same structures (hippocampus:À28,À32,À6,z value =1.96,amyg-dala:À28,À6,À16,z value =1.97).Experiment 2We conducted an additional behavioral experiment to address a number of alternative explanations for the observed effects of tags on choice behavior.First,it could be argued thatepisodicFigure 3.Categorical Effect of Episodic Tags on Brain ActivityGreater activity in lateral parietal cortex (left)and posterior cingulate/retrosplenial and ventro-medial prefrontal cortex (right)was observed in the episodic condition compared with the control condition.p <0.05,FWE-corrected for whole-brain volume.NeuronEpisodic Modulation of Delay DiscountingNeuron 66,138–148,April 15,2010ª2010Elsevier Inc.141tags increase subjective certainty that a reward would be forth-coming.In Experiment 2,we therefore collected postscan ratings of reward confidence.Second,it could be argued that events,always being associated with a particular date,may have shifted temporal focus from delay-based to more date-based processing.This would represent a potential confound,because date-associated rewards are discounted less than delay-associated rewards (Read et al.,2005).We therefore now collected postscan ratings of temporal focus (date-based versus delay-based).Finally,Experiment 1left open the question of whether the tag effect depends on the temporal specificity of the episodic cues.We therefore introduced an additional exper-imental condition that involved the presentation of subject-specific temporally unspecific future event cues.These tags (henceforth referred to as unspecific tags)were obtained by asking subjects to imagine events that could realistically happen to them in the next couple of months,but that were not directly tied to a particular point in time (see Experimental Procedures ).Episodic Imagery,Not Temporal Specificity,Reward Confidence,or Temporal Focus,Predicts the Size of the Tag EffectIn total,data from 16participants (9female)are included.Anal-ysis of pretest ratings confirmed that temporally unspecific and specific tags were matched in terms of personal relevance,arousal,valence,and preexisting associations (all p >0.15).Choice preferences were again well described by hyperbolic functions (median R 2control =0.84,unspecific =0.81,specific =0.80).We replicated the parametric tag effect (i.e.,increasing effect of tags on discount rates with increasing posttest imagery scores)in this independent sample for both temporally specific (p =0.047,Figure 7A)and temporally unspecific (p =0.022,Figure 7A)tags,showing that the effect depends on future thinking,rather than being specifically tied to the temporal spec-ificity of the event cues.Following testing,subjects rated how certain they were that a particular reward would actually be forth-coming.Overall,confidence in the payment procedure washighFigure 4.Neural Representation of Subjective Value (Parametric Analysis)(A)Regions in which the correlation with subjective value (parametric analysis)was significant in both the control and the episodic conditions (conjunction analysis)included central and lateral orbitofrontal cortex (OFC),bilateral ventral striatum (VS),medial prefrontal cortex (mPFC),and posterior cingulate cortex(PCC),replicating previous studies (Kable and Glimcher,2007;Peters and Bu¨chel,2009).(B)Regions in which the subjective value correlation was greater for the episodic compared with the control condition included lateral parietal cortex (LPC),ante-rior cingulate cortex (ACC),dorsolateral prefrontal cortex (DLPFC),and the right amygdala (Amy).(C)A conjunction analysis revealed that only LPC activity was positively correlated with subjective value in both conditions,but showed a greater regression slope in the episodic condition.No regions showed a better correlation with subjective value in the control condition.Error bars =SEM.All peaks are significant at p <0.001,uncorrected;(A)and (B)are thresholded at p <0.001uncorrected and (C)is thresholded at p <0.005,uncorrected for display purposes.NeuronEpisodic Modulation of Delay Discounting142Neuron 66,138–148,April 15,2010ª2010Elsevier Inc.(Figure 7B),and neither unspecific nor specific tags altered these subjective certainty estimates (one-way ANOVA:F (2,45)=0.113,p =0.894).Subjects also rated their temporal focus as either delay-based or date-based (see Experimental Procedures ),i.e.,whether they based their decisions on the delay-to-reward that was actually displayed,or whether they attempted to convert delays into the corresponding dates and then made their choices based on these dates.There was no overall significant effect of condition on temporal focus (one-way ANOVA:F (2,45)=1.485,p =0.237,Figure 7C),but a direct comparison between the control and the temporally specific condition showed a significant difference (t (15)=3.18,p =0.006).We there-fore correlated the differences in temporal focus ratings between conditions (control:unspecific and control:specific)with the respective tag effects (Figure 7D).There were no correlations (unspecific:p =0.71,specific:p =0.94),suggesting that the observed differences in discounting cannot be attributed to differences in temporal focus.High-Imagery,but Not Low-Imagery,Subjects Adjust Their Discount Function in an Episodic ContextFor a final analysis,we pooled the samples of Experiments 1and 2(n =46subjects in total),using only the temporally specific tag data from Experiment 2.We performed a median split into low-and high-imagery participants according to posttest imagery scores (low-imagery subjects:n =23[15/8Exp1/Exp2],imagery range =1.5–3.4,high-imagery subjects:n =23[15/8Exp1/Exp2],imagery range =3.5–5).The tag effect was significantly greater than 0in the high-imagery group (t (22)=2.6,p =0.0085,see Figure 7D),where subjects reduced their discount rate by onaverage 16%in the presence of episodic tags.In the low-imagery group,on the other hand,the tag effect was not different from zero (t (22)=0.573,p =0.286),yielding a significant group difference (t (44)=2.40,p =0.011).DISCUSSIONWe investigated the interactions between episodic future thought and intertemporal decision-making using behavioral testing and fMRI.Experiment 1shows that reward delay dis-counting is modulated by episodic future event cues,and the extent of this modulation is predicted by the degree of sponta-neous episodic imagery during decision-making,an effect that we replicated in Experiment 2(episodic tag effect).The neuroi-maging data (Experiment 1)highlight two mechanisms that support this effect:(1)valuation signals in the lateral ACC and (2)neural coupling between ACC and hippocampus/amygdala,both predicting the size of the tag effect.The size of the tag effect was directly related to posttest imagery scores,strongly suggesting that future thinking signifi-cantly contributed to this effect.Pooling subjects across both experiments revealed that high-imagery subjects reduced their discount rate by on average 16%in the episodic condition,whereas low-imagery subjects did not.Experiment 2addressed a number of alternative accounts for this effect.First,reward confidence was comparable for all conditions,arguing against the possibility that the tags may have somehow altered subjec-tive certainty that a reward would be forthcoming.Second,differences in temporal focus between conditions(date-basedFigure 5.Correlation between the Neural and Behavioral Tag Effect(A)Glass brain and (B and C)anatomical projection of the correlation between the neural tag effect (subjective value correlation episodic >control)and the behav-ioral tag effect (log difference between discount rates)in the bilateral ACC (p =0.021,FWE-corrected across an anatomical mask of bilateral ACC).(C)Coronal sections of the same contrast at a liberal threshold of p <0.01show that both left and right ACC clusters encompass gray matter of the cingulate gyrus.(D)Scatter-plot depicting the linear relationship between the neural and the behavioral tag effect in the right ACC.(A)and (B)are thresholded at p <0.001with 10contiguous voxels,whereas (C)is thresholded at p <0.01with 10contiguousvoxels.Figure 6.Results of the Psychophysiolog-ical Interaction Analysis(A)The seed for the psychophysiological interac-tion (PPI)analysis was placed in the right ACC (18,34,18).(B)The tag effect was associated with increased ACC-hippocampal coupling (p =0.031,corrected across bilateral hippocampus)and ACC-amyg-dala coupling (p =0.051,corrected across bilateral amygdala).Maps are thresholded at p <0.005,uncorrected for display purposes and projected onto the mean structural scan of all participants;HC,hippocampus;Amy,Amygdala;rACC,right anterior cingulate cortex.NeuronEpisodic Modulation of Delay DiscountingNeuron 66,138–148,April 15,2010ª2010Elsevier Inc.143。
爱思唯尔期刊出版流程介绍
pamphlet #10Produced byLibrary Connect in collaboration with the Global Academic & Customer Relations DepartmentCONTENTSIntroduction PrepublicationProduction and Publication Dissemination and Use AppendicesRecommended Resources, USA , USAWhat’s journal publishing really about? Certainly it’s about a process, a well-established formalized system for communicating research results. But it’s not just about systems and technology. Most importantly, it’s about people and relationships.Journal publishing has stood the test of time since at least the mid-17th century when Denis de Sallo founded the Journal des Sçavans and Henry Oldenburg founded the journal PhilosophicalTransactions . What has made journal publishing truly valuable and enduring is human communication,the comments and ideas exchanged between authors, editors, reviewers and publishers.Ultimately, journal publishing cannot be a purely mechanical exercise. To ensure research articlesdeliver high-quality information and serve as building blocks for intellectual advancement and scientificdiscovery, researchers must submit their work to trusted and reputable journals which bring together experts – editors, advisory boards and reviewers – to see and comment on the work. To ensure we collectively achieve excellence and advancement, authors, reviewers and editors must deliberate and communicate regarding submitted papers and so improve their final versions, and publishers must ensure that high-quality literature is published and preserved for the future.As we publish journals, Elsevier provides the following valuable functions – unchanged since the days of Sallo and Oldenburg:■Registration: Date-stamping the research of a particular author to establish precedence ■Peer review: Employing a wholly independent peer-review process ■Dissemination: Broadcasting authors’ claims to peers and the media ■Archival record: Establishing a permanent record of authors’ findingsWhile providing the four core services traditionally associated with scholarly publishing, Elsevier also offers value-adding services – especially relating to our electronic products. Today these services include helping define new disciplines and providing forums for their debate and discourse; establishing and actively managing editorial boards; and investing in new technologies and partnerships that make new and archived research more accessible to a broad range of users.Whether we’re discussing the core functions or the value-adding services of journal publishing, we can see that people and relationships are at the heart of the enterprise. Through dialog and collaboration, authors, editors and reviewers working with Elsevier help us ensure the integrity of content we publish, encourage and introduce innovation, and guard our collective intellectual heritage.In this fast-changing world, no one can rest on what has been accomplished thus far. Elsevier will continue to listen, learn, test and adapt to meet the changing needs of our customers and the scholarly and scientific communities we serve.If you’re considering publishing with Elsevier, I hope this pamphlet provides useful information. If you’re already among librarians,authors, reviewers and editors working with Elsevier, I thank you for your confidence in our company and invite your input on how we can serve you better.My appreciation to all colleagues who've contributed to this pamphlet.Kind regards,Mayur Amin, Senior Vice President, Global Academic & Customer Relations Department, Elsevier, Oxford, UKMayur AminIntroductory Comments■■■EXPERIMENTCONDUCT RESEARCHASSESS IMPACTSBUILD FAMEIDENTIFY NEW AREASREPORT NEW FINDINGSPEER REVIEWResearchWorkflowconjecture.minds of the public.An independent charitable trust, Sense About Science promotes good science and evidence in public debates. Sense About Science works with scientists to:safe transactions.■■■Through partnerships with Book Aid International and the Sabre4321Archiving PolicyInternal ArchiveDe Facto ArchivesNational ArchivesOfficial ArchivesOfficial Archives。
alzheimer's and dementia under editor review
alzheimer's and dementia under editor reviewAlzheimer's disease and dementia are complex neurological conditions that affect millions of people worldwide. These disorders are often characterized by progressive cognitive decline, leading to difficulties with daily tasks and eventually resulting in severe cognitive impairment.While Alzheimer's disease is the most common cause of dementia in older adults, there are several other types of dementia, each with its own underlying pathology and clinical manifestations. Some of the most common types of dementia include:1. Vascular dementia: Caused by impaired blood flow to the brain, leading to cell death and cognitive decline.2. Lewy body dementia: Characterized by the presence of Lewy bodies (abnormal protein deposits) in the brain, which affect neurotransmission and cause cognitive fluctuations.3. Frontotemporal dementia: Resulting from the degeneration of cells in the fronto-temporal regions of the brain, leading to behavioral and language changes.4. Progressive supranuclear palsy: A rare disorder caused by the degeneration of neurons in the brainstem and basal ganglia, resulting in difficulty with eye movements, balance, and speech.5. Corticobasal degeneration: A progressive disease characterized by the loss of neurons in the cerebral cortex and basal ganglia, causing movement and cognitive impairments.6. Normal pressure hydrocephalus: Caused by increased fluid pressure in the brain, leading to cognitive decline, difficulty with gait, and urinary incontinence.7. Dementia due to HIV or other infectious diseases: HIV-related dementia occurs when the virus infects and damages the brain, leading to cognitive decline. Similarly, dementia can result from other infectious diseases that affect the central nervous system.8. Dementia associated with Parkinson's disease: Some individuals with Parkinson's disease develop cognitive impairments, which can progress to dementia.9. Dementia with lewy bodies: This type of dementia is characterized by the presence of Lewy bodies in the brain and typically presents with cognitive fluctuations, visual hallucinations, and parkinsonism.10. Autosomal dominant Alzheimer's disease: A rare genetic form of Alzheimer's disease that typically presents in individuals under 65 years of age.The diagnosis and management of Alzheimer's disease and other dementias involve a comprehensive evaluation by a healthcare professional, including a medical history, physical examination, and cognitive testing. Treatment strategies aim to alleviate symptoms, slow down disease progression, and improve the quality of life for patients and their caregivers.Currently, there is no cure for Alzheimer's disease or most other dementias. However, researchers are making significant strides in understanding the underlying mechanisms of these disorders and developing new treatments. Some experimental therapies target amyloid plaques and tau tangles, while others aim to boost neurogenesis or protect neurons from damage.As our understanding of Alzheimer's and dementia continues to evolve, scientists hope to develop more effective treatments and ultimately find a cure for these devastating diseases.。
新核心综合学术英语教程第二册Unit6解析
the Healthpartners Research Foundation
• HealthPartners is an integrated, nonprofit health care provider located in Bloomington, Minnesota offering care, coverage, research and education to its members, patients and the community. HealthPartners was founded in 1957 as Group Health, a consumergoverned nonprofit health plan with a board of directors made up of its own members and patients. In 1992, Group Health merged with MedCenters Health Plan, and together they formed HealthPartners. In late 2012 it was announced that HealthPartners would merge with Park Nicollet Health Services of St. Louis Park on January 1, 2013 following federal approval
— Samuel Johnson • The function of education, therefore, is to teach one to think
intensively and to think critically. But education which stops with efficiency may prove the greatest menace to society. The most dangerous criminal may be the man gifted with reason, but with no morals… We must remember that intelligence is not enough. Intelligence plus character—that is the goal of true education.
JESD22标准
C:\Users\ ATC6100\ Desktop\ JEDEC标准\ JESD22-A100D.pdfC:\Users\ATC6100\ Desktop\JESD22-A101D.pdfC:\Users\ATC6100\Desktop\JEDEC标准\JESD22-A102E.pdf C:\Users\ ATC6100\ Desktop\JESD22-1D标准解读.docxC:\Users\ATC6100\Desktop\JESD22-A103E.pdfC:\Users\ATC6100\Desktop\JESD22-A104E.pdfC:\Users\ATC6100\Desktop\JESD22\JEDEC标准\JESD22-A105C_0.pdfC:\Users\ATC6100\Desktop\JESD22\JEDEC标准\JESD22-A106B-01.pdfC:\Users\ATC6100\Desktop\JEDEC标准\JESD22-A107C.pdfC:\Users\ATC6100\Desktop\JEDEC标准\JESD22-A108D.pdfC:\Users\ATC6100\Desktop\JESD22\JEDEC标准\JESD22-A109B.pdf C:\Users\ATC6100\Desktop\JESD22\JEDEC标准\JESD22-A110E.pdf C:\Users\ATC6100\Desktop\JEDEC标准\JESD22-A111B.pdf C:\Users\ATC6100\Desktop\JESD22\JEDEC标准\J-STD-020E.pdf C:\Users\ATC6100\Desktop\JESD22\JEDEC标准\JESD22-A113H.pdf C:\Users\ATC6100\Desktop\C:\Users\ATC6100\Desktop\JEDEC标准\JESD22-A117D.pdf C:\Users\ATC6100\Desktop\JEDEC标准\JESD22-A118B.pdf C:\Users\ATC6100\Desktop\JEDEC标准\JESD22-A119A.pdf C:\Users\ATC6100\Desktop\JESD22-A120B.pdfC:\Users\ATC6100\Desktop\JEDEC标准\JESD22-A121A_R.pdf C:\Users\ATC6100\Desktop\JESD22\JEDEC标准\JESD22-A122A.pdf C:\Users\ATC6100\Desktop\JESD22\JEDEC标准\JESD22-B100B.pdf C:\Users\ATC6100\Desktop\JESD22\JEDEC标准\JESD22-B101C.pdf C:\Users\ATC6100\Desktop\JESD22\JEDEC标准\JESD22-A120B.pdf C:\Users\ATC6100\Desktop\JESD22\JEDEC标准\JESD22-B103B-01.pdf C:\Users\ATC6100\Desktop\JESD22-B110B.pdf C:\Users\ATC6100\Desktop\JESD22-B105E.pdf C:\Users\ATC6100\Desktop\JESD22\JEDEC标准\JESD22-B106E.pdf C:\Users\ATC6100\Desktop\JESD22\JEDEC标准\JESD22-B107D_R.pdf C:\Users\ATC6100\Desktop\JEDEC标准\JESD22-B108B.pdfC:\Users\ ATC6100\ Desktop\ JEDEC标准\JESD22-B109B.pdf C:\Users\ ATC6100\ Desktop\JESD22-B110B.pdfC:\Users\ ATC6100\ Desktop\ JEDEC标准\ JESD22-B111A.pdf C:\Users\ ATC6100\ Desktop\ JEDEC标准\JESD22-B112B.pdfC:\Users\ATC6100\Desktop\ JEDEC标准\JESD22-B113A.pdfC:\Users\ATC6100\Desktop\JEDEC标准\JESD22-B114A.pdfC:\Users\ATC6100\Desktop\C:\Users\ATC6100\Desktop\JESD22-B117B.pdfC:\Users\ ATC6100\ Desktop\C:\Users\ ATC6100\ Desktop\C:\Users\ ATC6100\ Desktop\。
一种便捷方法制备表面氨基化的超顺磁Fe3O4纳米粒子
一种便捷方法制备表面氨基化的超顺磁Fe 3O 4纳米粒子刘星辰党永强吴玉清*(吉林大学超分子结构与材料国家重点实验室,长春130012)摘要:提出了一种简便易行的对磁性纳米粒子表面进行氨基化的方法.首先使用化学共沉淀法合成了粒径为10nm 左右的Fe 3O 4纳米粒子,然后用阿仑膦酸钠对其表面进行修饰,使其表面具有了功能化的氨基.利用透射电子显微镜(TEM)、X 射线衍射(XRD)、振动样品磁强计(VSM)、动态光散射(DLS)仪、热重分析(TGA)仪、傅里叶变换红外(FT ⁃IR)光谱仪、X 射线光电子能谱(XPS)仪等对其进行表征.结果显示磁性纳米粒子表面被成功地修饰了一层双膦酸分子.所制备的纳米粒子可在pH=6.3稳定存在4周以上.关键词:磁性纳米粒子;氨基化;阿仑膦酸钠中图分类号:O647;O648A Convenient Method to Synthesize Surface Amino 鄄Coated Superparamagnetic Fe 3O 4NanoparticlesLIU Xing ⁃Chen DANG Yong ⁃Qiang WU Yu ⁃Qing *(State Key Laboratory of Supramolecular Structure and Material,Jilin University,Changchun130012,P.R.China )Abstract :We propose a convenient method to synthesize surface amino ⁃coated magnetic nanoparticles.Fe 3O 4nanoparticles with a grain diameter of about 10nm were synthesized by the chemical co ⁃precipitation of ferrous chloride and ferric chloride.The obtained superparamagnetic nanoparticles were surface ⁃modified with alendronate to introduce an amino group onto their surfaces.The particles were characterized by transmission electron microscopy (TEM),X ⁃ray diffraction (XRD),vibrating sample magnetometry (VSM),dynamic light scattering (DLS),thermogra ⁃vimetric analysis (TGA),Fourier transform infrared (FT ⁃IR)spectroscopy,and X ⁃ray photoelectron spectroscopy (XPS).The data showed that alendronate was successfully linked to the SPM nanoparticles.These particles are stable for more than 4weeks without precipitation at pH=6.3.Key Words :Magnetic nanoparticles;Amino ⁃coated;Alendronate[Article]物理化学学报(Wuli Huaxue Xuebao )Acta Phys.鄄Chim.Sin .,2010,26(3):789-794磁性纳米粒子是一类重要的纳米材料,它除了具有纳米效应,还会呈现异常的磁学性质,如超顺磁性、高矫顽力、低居里温度与高磁化率等特点.目前磁性纳米粒子已在许多领域得到广泛的应用,如磁性记录[1]、生物传感[2]、医学磁共振成像(MRI)[3]、蛋白质分离[4]、靶向药物输送[5]等领域.其中Fe 3O 4纳米粒子磁流体是应用最广泛的铁氧体类磁性纳米材料之一.然而磁性纳米粒子自身极易团聚,且表面缺乏容易和功能分子偶联的基团,因此在制备时必须加以修饰.所以采取合适的物理化学方法将磁性纳米粒子修饰衍生或表面功能化,是实现生物分子与磁性纳米粒子结合、负载及生物传感的必要前提和关键[6].用有机小分子来修饰磁性纳米粒子是一类重要的制备功能化磁性纳米粒子的方法.这类纳米粒子通常具有水溶性好,生物相容性好等特点.此外,作为MRI 对比剂,小分子修饰的纳米粒子相比高分子March Received:August 27,2009;Revised:November 16,2009;Published on Web:January 12,2010.∗Corresponding author.Email:yqwu@;Tel :+86⁃431⁃85168730.The project was supported by the National Natural Science Foundation of China (20773051),Natural Science Foundation of Jilin Province,China (20070926⁃01)and the 111Project,China (B06009).国家自然科学基金(20773051),吉林省自然科学基金(20070926⁃01)和111项目(B06009)资助ⒸEditorial office of Acta Physico ⁃Chimica Sinica789Acta Phys.鄄Chim.Sin.,2010Vol.26包裹的纳米粒子[7]具有尺寸小,易于在组织之间穿透的优点,而且小分子修饰可以比高分子修饰更好地保持纳米粒子的磁性能[8].通常所用的小分子有:氨基酸[9]、柠檬酸[10]、磷酰维生素B 、环糊精[11]等.采用氨基酸等上述小分子进行表面修饰所得到的纳米粒子虽然具有良好的生物相容性,但其表面的修饰性小分子很容易在体内被代谢分解,造成纳米粒子的聚集沉淀,因此不适于在生物体内使用.双膦酸分子由于其特殊的P —C —P 骨架结构,在体内不易被代谢分解,因而具有比其他常用小分子更优良的性质,适于进行生物相容性纳米粒子的表面修饰.此外,双膦酸基团与金属的强配位能力可以使其较为牢固地结合在纳米粒子表面,具有非毒性,生物兼容性好等优点,也使双膦酸成为生物医学领域磁性纳米粒子的良好修饰物.Portet 等[12]于2001年首次报导了利用双膦酸化合物修饰氧化铁纳米粒子,并用作医学磁共振成像对比剂.其研究表明,双膦酸与纳米粒子表面的结合能力要远远强于其他一些常用的配位基团,如羧基、磺酸基、单膦酸基等;这种纳米粒子的稳定性可达到4周以上.Lalatonne 等[8]利用尾部为羧基的双膦酸修饰Fe 2O 3纳米粒子,得到了高稳定性、超顺磁性以及生物相容性的纳米材料.MRI 测试表明,这种材料可以作为对比剂.利用其尾部的羧基基团顺利连接了荧光素分子,证明双膦酸与纳米粒子结合较为牢固,不受尾部基团进一步化学偶联的影响.本文介绍了一种基于双膦酸修饰的表面氨基化磁性纳米粒子,首先采用化学共沉淀法制备Fe 3O 4纳米粒子,然后将具有强配位能力的阿仑膦酸钠(如图1所示)修饰到纳米粒子表面,并对其形态、组成、磁性等性质进行了表征.1实验部分1.1原料与试剂FeCl 3·6H 2O(99%),分析纯;FeCl 2·4H 2O(99%),分析纯;氨水(28%),分析纯,以上试剂均购自北京化学试剂公司.阿仑膦酸钠(98%,w ),分析纯,购自山东中科泰斗试剂公司.实验用水为二次去离子水.1.2Fe 3O 4纳米粒子的制备及其表面氨基化取去离子水200mL,通氮气除氧1h,密封备用.精密称取FeCl 3·6H 2O 1.08g 与FeCl 2·4H 2O 0.49g,在氮气保护的环境下溶于30mL 除氧的去离子水中.机械搅拌使固体全部溶解后,调转速为700r ·min -1,升温至45℃,迅速加入1.5mol ·L -1氨水10mL,然后继续加入氨水,调节pH 到10-11.反应30min 后,加热到60℃陈化30min,反应过程中持续通氮气保护,最后得到黑色溶胶状物质.利用外加磁场将所得到的沉淀从反应体系中分离出来,并用除氧的去离子水洗涤5次以除去杂质离子,直到pH=7.然后在真空烘箱中30℃下干燥,研磨后得到未修饰的四氧化三铁纳米粒子.用于修饰的Fe 3O 4纳米粒子则是在反应结束且洗涤完后,直接用去离子水将粒子分散在250mL 锥形瓶中,超声30min.另配制等体积的25mmol ·L -1的阿仑膦酸钠水溶液,调pH 到6.2后,加入到纳米粒子胶体中,用1mol ·L -1的NaOH 和HCl 控制体系pH=6.3,在室温下搅拌2h.反应结束后在4℃、15000r ·min -1下离心10min,用蒸馏水洗涤后再离心分离,重复3次以除去未修饰上的阿仑膦酸钠和少量的杂质离子.最后置于真空烘箱中干燥.1.3测试与表征仪器H ⁃8100IV 透射电镜(日本日立公司);Vertex 80V 型傅里叶变换红外光谱仪(德国BRUKER 公司);Q500型TGA 热重分析仪(德国耐驰仪器制造有限公司);D/MAX 2550diffractometer X 射线衍射仪(日本Rigaku 公司);VSM ⁃300型振动样品磁强计(英普技术公司);ESCALAB 250X 射线光电子能谱仪(英国VG 公司);Zetasizer nanoseries 纳米粒度分析仪(英国Malvern 仪器公司).2结果与讨论2.1Fe 3O 4纳米粒子的表面氨基化原理吸附可分为物理吸附和化学吸附.前者主要通过分子间作用力如静电相互作用、氢键、范德华力;后者主要通过共价键等化学键吸附.实际吸附过程常是两种过程共同起作用,先物理吸附,再化学吸附[13].Fe 2+、Fe 3+的价电子结构分别为3d 64s 0、3d 54s 0,而图1双膦酸和阿仑膦酸钠的结构Fig.1Structures of bisphosphonic acid andalendronate790No.3刘星辰等:一种便捷方法制备表面氨基化的超顺磁Fe 3O 4纳米粒子4s 和4p 为空轨道处于不饱和状态,因此易于接受电子形成配位键.四氧化三铁纳米粒子的等电点是6.5-7.0[14],而阿仑膦酸的p K a 分别为0.8、2.2、6.3、10.9和12.2[15],阿仑膦酸钠(单钠盐)的等电点为2.2.当pH>6.5时,阿仑膦酸钠带负电荷,纳米粒子表面也带负电荷,静电排斥作用不利于阿仑膦酸钠的磷酸端基以静电吸附的方式吸附在Fe 3O 4纳米粒子表面;当6.5>pH>2.2时,阿仑膦酸钠带负电荷,纳米粒子表面带正电荷,阿仑膦酸钠将以磷酸端基吸附于Fe 3O 4纳米粒子表面;当pH<2.2时,两者都带正电荷,阿仑膦酸钠也无法通过静电作用吸附于Fe 3O 4纳米粒子上.因此,理论上修饰的pH 范围应为2.2-6.5.但在实验中发现,当体系的pH 值小于6.0时,Fe 3O 4纳米粒子会被溶解.所以实际操作时,综合考虑各个因素后选择pH=6.3.2.2形貌分析图2为阿仑膦酸钠修饰前后Fe 3O 4纳米粒子的TEM 图.从TEM 可知,所制备的纳米粒子直径在10nm 左右.修饰前的纳米粒子分散性很差,极易团聚.这是因为在反应结束后,在磁分离的过程中,外加磁场的作用导致粒子部分磁化,因而容易造成团聚.此外,修饰前纳米粒子间的静电排斥力较小,也易于导致团聚.修饰后,Fe 3O 4纳米粒子团聚程度较轻,分散性大大提高.从粒径上看,修饰前后纳米粒子的粒径改变很小,这体现了小分子修饰的优点.从图片中可以看到一些颜色较深的粒子,这说明反应过程中结晶不完全.2.3动态光散射图3为阿仑膦酸钠修饰前后Fe 3O 4纳米粒子的粒度分布曲线.从图3可以看出,修饰前Fe 3O 4纳米粒子聚集严重,即使经过长时间的超声,DLS 测得的粒径依然在100nm 左右(图3(a)).而修饰后,同样浓度的纳米粒子,其分散度得到了很大程度的改善,DLS 粒径为24.3nm 左右(图3(b)).2.4物相分析图4中a 为未修饰的磁性纳米粒子的XRD 谱图.和标准谱图对比可知,离子物相为反式尖晶石结构的Fe 3O 4,峰形窄且尖锐,说明晶体完整.23°左右的无定形峰可能是Fe 3O 4纳米粒子在生成过程中结晶不完全导致的.根据Scherrer 公式:D =k λ/(βcos θ)其中k 为Scherrer 常数,取0.89,λ为X 射线波长,β为半峰宽,θ为布拉格角,取(311)晶面计算得D =8.4nm,和TEM 数据较好地吻合.图4中b 为阿仑膦酸钠修饰的磁性纳米粒子的XRD 谱图,和曲线a 比较可知,修饰前后,纳米粒子的晶体结构基本上未发生变化.但是23°左右的无定形峰增强,表明修饰后纳米粒子上有大量的无定图2阿仑膦酸钠修饰前后Fe 3O 4纳米粒子的TEM 图Fig.2TEM images of Fe 3O 4nanoparticles before andafter modification with alendronate(a)Fe 3O 4,(b)Fe 3O 4⁃alendronate;Inset in Fig.2a is the selected areaelectron diffraction.图3阿仑膦酸钠修饰前后Fe 3O 4纳米粒子的粒度分布曲线Fig.3Size distribution curves of Fe 3O 4nanoparticles before and after modification with alendronate(a)Fe 3O 4,(b)Fe 3O 4⁃alendronate791Acta Phys.鄄Chim.Sin.,2010Vol.26形物存在,这说明阿仑膦酸钠以无定形的形式被大量地吸附到了Fe 3O 4纳米粒子的表面.2.5磁性能分析根据文献[16],在无外磁场存在下,当Fe 3O 4粒子的尺寸小于31.8nm 时,将表现出超顺磁性.为了考察所制得的纳米粒子的磁性能,利用振动样品磁强计(VSM)在磁场强度(H )为-796000-796000A ·m -1的范围内,于室温(25℃)测定了纳米粒子的磁性.图5分别为修饰前后的Fe 3O 4纳米粒子的磁滞回线.从图中可以看出,制备样品的磁滞回线是两条重合的磁化曲线,这正体现了磁性材料的一个重要特征,即超顺磁性[17].比饱和磁化强度是指单位质量样品的饱和磁化强度,通常用比饱和磁化强度(M )值来评价材料的磁性能.由图5可知,随着外加磁场的增强,样品的磁化强度也随之变强.当外加磁场达到±796000A ·m -1时,Fe 3O 4纳米粒子的磁化强度达到饱和,为61.7A ·m 2·kg -1.经阿仑膦酸钠修饰后,纳米粒子的比饱和磁化强度(M )略有下降(55.2A ·m 2·kg -1),但仍明显优于高分子材料修饰的Fe 3O 4纳米粒子[7].比饱和磁化强度的略微改变是由于纳米粒子表面吸附了大量的阿仑膦酸钠后,导致样品中Fe 3O 4的相对含量有所下降,因此其比饱和磁化强度值有所下降.此外,由于在修饰及干燥过程中,可能有部分二价铁被氧化为三价铁,亦可导致粒子磁性能的微小下降.2.6热重分析为了进一步研究阿仑膦酸钠在Fe 3O 4表面的吸附情况,我们还采用热重分析的方法检测其在空气中受热的质量变化情况(图6).从图6可以看出,低温下裸Fe 3O 4粒子的质量随温度升高而减少,在120℃左右失重量达1.5%左右,这归属于表面吸附水的脱去,随着温度的上升,Fe 3O 4有部分被氧化成Fe 2O 3,其质量会略有增加;而当温度高于150℃时,纳米粒子间的吸附水开始挥发,导致失重,这主要是图5阿仑膦酸钠修饰前后Fe 3O 4纳米粒子的磁滞回线Fig.5Magnetic hysteresis loop of Fe 3O 4nanoparticlesbefore and after modification withalendronate图6阿仑膦酸钠修饰前后Fe 3O 4纳米粒子(a)以及阿仑膦酸钠(b)的热重曲线Fig.6Thermogravimetry curves of Fe 3O 4nanoparticles before and after modification withalendronate (a)and alendronate(b)图4阿仑膦酸钠修饰前后Fe 3O 4纳米粒子的XRD 图Fig.4XRD patterns of Fe 3O 4nanoparticles beforeand after modification with alendronate(a)Fe 3O 4,(b)Fe 3O 4⁃alendronate792No.3刘星辰等:一种便捷方法制备表面氨基化的超顺磁Fe 3O 4纳米粒子由于真空干燥并不能除去粒子之间存在的吸附水,于是在空隙中形成大量的弯月液面,当毛细收缩作用将颗粒压向一起后,水分被保留在聚集的颗粒之间;只有在高温(>150℃)时,这些水分才开始被逐渐蒸发出来[18].这两个因素共同作用的结果使裸Fe 3O 4纳米粒子在高温过程中质量变化较小,最终失重在2%-3%的范围内.阿仑膦酸钠修饰后的Fe 3O 4纳米粒子从200℃开始有一个明显的失重峰,这是表面阿仑膦酸钠分解所造成的失重和Fe 3O 4的氧化增重共同作用的结果,二者最终的失重量为2.9%,经过计算,若Fe 3O 4完全被氧化,其增重量约为3.2%,从而得出阿仑膦酸钠在纳米粒子上的吸附量大约为6.1%.此外,我们还测量了相同条件下阿伦膦酸钠单独存在时的热重曲线,结果如图6(b)所示,阿仑膦酸钠在110-140℃之间失去结晶水,而在250℃左右开始分解,一直持续到450℃.这与阿仑膦酸钠修饰Fe 3O 4的情形基本相符,说明纳米粒子表面的修饰物是阿仑膦酸钠.2.7傅里叶变换红外光谱图7为阿仑膦酸钠修饰前后,Fe 3O 4纳米粒子以及阿仑膦酸钠的红外光谱.在红外光谱图上,P —O 伸缩振动对应的区域一般在900-1200cm -1之间[8].阿仑膦酸钠固体在这个区域除了P —OH 、P ‗O 以及PO 3基团的特征峰外,由于膦酸基团与结晶水的结合,还产生了多组复杂的红外吸收峰,如图7所示.而结合到纳米粒子上的阿仑膦酸钠在该区域发生了较大的变化,包括峰的消失和P —OH 、P ‗O 、PO 3基团特征峰的位移,说明这些基团周围的环境发生了很大的变化.这表明阿仑膦酸钠上的磷酸基团和纳米粒子上的铁离子发生了配位作用.2.8光电子能谱图8、图9是修饰前后Fe 3O 4纳米粒子的Fe 2p 、N 1s 、P 2p 的XPS 谱.从图8可以看出,其E B (2p 3/2)=710.8eV,说明纳米粒子的成分确实为Fe 3O 4[19].另图9阿仑膦酸钠修饰前后Fe 3O 4纳米粒子的N 1s (a)和P 2p (b)的XPS 谱Fig.9N 1s (a)and P 2p (b)XPS spectra for Fe 3O 4nanoparticles before and after modification with alendronate图7阿仑膦酸钠修饰前后Fe 3O 纳米粒子以及阿仑膦酸钠的傅里叶变换红外光谱Fig.7FTIR spetra of of Fe 3O 4nanoparticles beforeand after modification with alendronate andalendronate图8阿仑膦酸钠修饰前后Fe 3O 4纳米粒子的Fe 2p 的XPS 谱Fig.8Fe 2p XPS spectra for Fe 3O 4nanoparticles before and after modification withalendronate793Acta Phys.⁃Chim.Sin.,2010Vol.26外,修饰前后纳米粒子的Fe2p谱均有震激伴峰,即shake⁃up卫星峰存在,而且伴峰与主峰的能量差(ΔE)为13.7eV,明显符合文献[20]报道的Fe3O4的ΔE>8.80eV的判别标准,也证明纳米粒子的成分确实为Fe3O4.修饰前后峰位基本不变,说明修饰过程不改变纳米粒子的主体成分Fe3O4的结构.从图9可知,修饰后的纳米粒子与修饰前相比,出现了明显的N(401eV)和P(132.5eV)的谱峰,且二者以单峰出现,说明其各自只有一种价态,符合阿仑膦酸钠中N、P的化学环境.这些结果进一步验证了阿仑膦酸钠已经被修饰到了纳米粒子表面,同时也说明纳米粒子表面具有了功能化的基团———氨基.根据文献[9],我们提出了阿仑膦酸钠结合纳米粒子的模型,如图10所示.2.9稳定性分析本实验制备的经阿仑膦酸钠修饰的纳米粒子,在pH=6.3的条件下,存放4周时间不产生任何聚集;调整pH到9以上时,会产生少量的聚集.这是由于氨基的等电点在pH=9左右,当溶液碱性过强时,会中和掉氨基所带的正电荷;改变pH到5以下时,由于纳米粒子本身由碱性氧化物组成,放置2d以后纳米粒子会被溶解.因此,使用Fe3O4⁃阿仑膦酸钠修饰的纳米粒子的最佳使用pH范围是6-9,比较适合于在生物体系中应用.3结论提出了一种简便易行的对磁性纳米粒子表面进行氨基化修饰的方法.首先使用共沉淀法合成了粒径为10nm左右的Fe3O4纳米粒子,然后使用阿仑膦酸钠对其表面进行了修饰,使其表面具有了功能化的氨基.并对其进行了一系列物理性质表征.结果显示磁性纳米粒子表面被成功地修饰上了一层双膦酸分子.修饰后纳米粒子的比饱和磁化强度为55.2 A·m2·kg-1.这种纳米粒子可在pH=6.3稳定存在4周以上,为其进一步的生物学应用奠定了基础. References1Sun,S.;Murray,C.B.;Weller,D.;Folks,L.;Moser,A.Science,2000,287:19892Miller,M.M.;Prinz,G.A.;Cheng,S.F.;Bounnak,S.Appl.Phys.Lett.,2002,81:22113Burtea,C.;Laurent,S.;Roch,A.;Vander Elst,L.;Muller,R.N.J.Inorg.Biochem.,2005,99(5):11354Frenzel,A.;Bergemann,C.;Köhl,G.;Reinard,T.J.Chromatogr.B,2003,793(2):3255Jain,T.K.;Morales,M.A.;Sahoo,S.K.;Leslie⁃Pelecky,D.L.;Labhasetwar,V.Mol.Pharm.,2005,2(3):1946Rosi,N.L.;Mirkin,C.A.Chem.Rev.,2005,105:15477Chen,Z.J.;Peng,K.;Fang,S.M.;Tian,J.F.;Li,D.D.;Jia,L.J.;Mao,X.F.Acta Phys.⁃Chim.Sin.,2007,23(3):349[陈志军,彭凯,方少明,田俊峰,李丁丁,贾陆军,冒小峰.物理化学学报,2007,23(3):349]8Lalatonne,Y.;Paris,C.;Serfaty,J.M.;Weinmann,P.;Lecouvey,M.;Motte,mun.,2008:25539Souna,M.H.;Rubim,J.C.;Sobrinho,P.G.J.Magn.Magn.Mater.,2001,225:6710Domingo,J.C.;Mercadal,M.;Petriz,J.;Madariaga,M.D.J.Microencapsulation,2001,18(1):4111Bonacchi,D.;Caneschi,A.;Dorignac,D.;Falqui,A.;Gatteschi,D.;Rovai,D.;Sangregorio,C.;Sessoli,R.Chem.Mater.,2004,16:201612Portet,D.;Denizot,B.;Rump,E.;Lejeune,J.J.;Jallet,P.J.Colloid Interface Sci.,2001,238:3713Liu,B.;Wang,D.P.;Huang,W.H.J.Func.Mater.,2007,38(7): 1074[刘冰,王德平,黄文。
SCI期刊缩写汇总
SCI期刊缩写汇总以下是一些SCI期刊的缩写,以及它们所代表的领域:1. Nature - 自然2. Science - 科学3. Cell - 细胞4. PNAS - 国家科学院院报(Proceedings of the National Academy of Sciences)5. Brain - 大脑6. Neuron - 神经元8. EMBO J - 欧洲分子生物学组织期刊(European Molecular Biology Organization Journal)9. PLoS ONE - 公共科学图书馆(Public Library of Science One)10. PLoS Biology - 公共科学图书馆生物学版(Public Library of Science Biology)11. JAMA - 美国医学会杂志(Journal of the American Medical Association)12. Lancet - 《柳叶刀》13. BMJ - 英国医学杂志(British Medical Journal)14. Ann Intern Med - 美国内科医学年鉴(Annals of Internal Medicine)15. Cell Reports - 细胞报告16. J Biol Chem - 生物化学杂志(Journal of Biological Chemistry)17. Immunity - 免疫18. J Immunol - 免疫学杂志(Journal of Immunology)19. Genes Dev - 基因发展(Genes & Development)20. Oncogene - 癌基因21. Nat Genet - 自然遗传学(Nature Genetics)22. Cancer Res - 癌症研究(Cancer Research)23. Nat Med - 自然医学(Nature Medicine)24. J Clin Invest - 临床医学杂志(Journal of Clinical Investigation)25. Mol Cell - 分子细胞(Molecular Cell)26. Cell Stem Cell - 细胞干细胞27. Dev Cell - 发展细胞(Developmental Cell)28. Nat Cell Biol - 自然细胞生物学(Nature Cell Biology)29. Nat Immunol - 自然免疫学(Nature Immunology)30. J Exp Med - 实验医学杂志(Journal of Experimental Medicine)31. Cell Metab - 细胞新陈代谢(Cell Metabolism)32. Nat Neurosci - 自然神经科学(Nature Neuroscience)33. J Neurosci - 神经科学杂志(Journal of Neuroscience)34. Genome Res - 基因组研究 (Genome Research)35. Nat Biotechnol - 自然生物技术(Nature Biotechnology)36. Cell Host Microbe - 细胞寄生菌宿主37. Nat Rev Mol Cell Biol - 自然分子细胞生物学评论(Nature Reviews Molecular Cell Biology)38. JAMA Intern Med - JAMA内科杂志(JAMA Internal Medicine)39. JAMA Pediatrics - JAMA儿科杂志40. JAMA Psychiatry - JAMA精神病学杂志41. JAMA Neurol - JAMA神经学杂志42. JAMA Dermatol - JAMA皮肤病学杂志43. JAMA Surg - JAMA外科杂志44. JAMA Otolaryngol Head Neck Surg - JAMA耳鼻喉头颈外科杂志45. JAMA Ophthalmol - JAMA眼科学杂志46. JAMA Cardiol - JAMA心脏病学杂志47. JAMA Oncol - JAMA肿瘤杂志48. JAMA Health Forum - JAMA健康论坛49. Sci Transl Med - 科学转化医学(Science Translational Medicine)50. J Exp Biol - 实验生物学杂志(Journal of Experimental Biology)这只是众多SCI期刊中的一小部分。
网络信息检索
• 4、网络信息检索的原理是什么?检索的流程(步骤)有哪些?
• 按照一定方式组织存贮信息,并根据用户需求查找出有关信息的过程。 又称信息存贮与检索、情报检索。信息的查找萌芽于图书馆的参考工作。 “信息检索”一词出现于20世纪50年代 。
•
信息检索包括3个主要环节 :①信息内容分析与编码,产生信息记录及 检索标识。②组织存贮,将全部记录按文件、数据库等形式组成有序的信息 集合。③用户提问处理和检索输出。它按对象分为文献检索、数据检索和事 实检索;按设备分为手工检索、机械检索和计算机检索。由一定的设备和信 息集合构成的服务设施称为信息检索系统,如穿孔卡片系统、联机检索系统、 光盘检索系统、多媒体检索系统等。信息检索最初应用于图书馆和科技信息 机构,后来逐渐扩大到其他领域,并与各种管理信息系统结合在一起。与信 息检索有关的理论、技术和服务构成了一个相对独立的知识领域,是信息学 的一个重要分支,并与计算机应用技术相互交叉。
• 4、检索国内自己所学专业相对领先的学校,并列举出2个学校图书馆 OPAC系统。
• 5、书目数据库(OPAC)检索实习。
分别利用本校图书馆OPAC和前一题列举的1个学校OPAC及CALIS公共
OPAC检索与本专业相关的书目信息(题目自拟),并以截屏的形式显 示检索过程及结果,要求尽量使用高级检索或组合检索)
• 6、书附光盘数据库检索实习。 在本校图书馆借书的时候,如果需要书附光盘的内容,应如何获取, 请举例说明(题目自拟),并以截屏的形式显示检索过程及结果。
• •
•
③外文数据库: a.Frontiers in China期刊数据库 , Frontiers 系列教育部主管、高等教育 出版社出版、德国施普林格公司负责海外发行的大型英文学术期刊项目。自 2006 年正式创刊以来,以网络版和印刷版形式出版了25 种刊物,是目前国 内覆盖学科最广的系列英文学术期刊,现由CALIS文理中心与高等教育出版社 共同负责国内数字化内容服务工作。Frontiers 系列期刊数据库共含25种全 英文学术期刊(期刊列表),其中自然科学类18种(包括基础科学、生命科 学、工程技术类),人文社会科学类7种,可提供分类浏览和检索查询。文献 类型为期刊论文。 b. EI工程索引 。《工程索引》(The Engineering Index,简称EI)创刊于 1884年,是美国工程信息公司(Engineering information Inc.)出版的著名 工程技术类综合性检索工具。EI Compendex是目前全球最全面的工程领域二 次文献数据库,侧重提供应用科学和工程领域的文摘索引信息。 C.Springer Link数据库,德国施普林格(Springer-Verlag)是世界上著名的 科技出版集团,Springer出版社与Kluwer Academic Pub.合并后,成立了新 的Springer集团。该数据库通过Springer LINK系统提供学术期刊及电子图书 的在线服务。 Springer Link包含图书、期刊/会议论文,其中期刊及图书等 所有资源划分为12个 学科,并包含了很多跨学科内容
橡胶树优良品种大丰95在云南的生产适应性试验研究
!""#$%&'()*+,!"#$%&&'&()!"!#$%&'()*+,-./$%&'0)*,1$%&234'(2C +D!"#$%&'())'*"%&+(!+"'()),&%-.&-))/))!-&0.1(1*297:>/#"75../#热带农业科技云南省热带作物科学研究所云南省热带作物学会1977年创刊,季刊2022年第45卷第2期2022年4月出版目◇次主办Redai Nongye Keji[期刊基本参数]CN53-1181/S*1977*q*A4*64*zh*P*¥10.00*1200*12*2022-04主管单位:云南省农垦局地址:云南省景洪市宣慰大道99号国内统一刊号:CN 53-1181/S编辑出版:《热带农业科技》编辑部邮编:666100国际标准刊号:ISSN 1672-450X 主编:倪书邦电话:(0691)2124140发行范围:国内外公开发行副主编:李维锐,林有兴电子信箱:***************国内定价:10元/册责任编辑:黄雪莲,曾雁网址:https://印刷:云南博多彩印包装有限公司◇◇天然橡胶橡胶树优良品种大丰95在云南的生产适应性试验研究.................................................刘忠亮,何素民,和丽岗[1]橡胶树炭疽病生防链霉菌DL5C 发酵培养基筛选及发酵条件优化研究.......................................................................................................................................................................................李岚岚,施玉萍,刘一贤,戴利铭,蔡志英[6]◇热带亚热带果蔬基于转录组测序分析澳洲坚果脂肪酸的合成.......................................刘紫艳,郑诚,牛迎凤,毛常丽,柳觐[12]西双版纳10个菠萝品种的品质分析......................................................刘世红,倪书邦,管艳,殷振华,张阳梅[19]攀西干热河谷气候区油梨大田嫁接技术...................................吴健华,李进红,李丽,李所清,杨菊华,彭洪恩[24]‘满天星’百香果不同基质种子育苗探索...................................................................................................胡方剑[28]◇药用与功能植物不同成熟度诺丽果主要活性成分分析.......................................徐荣,许木果,姜士宽,杨焱,付鎵榕,岩利[31]不同种子处理方式对珠芽黄魔芋生长的影响.......................................李金威,岩香甩,周会平,原慧芳,田耀华[36]高寒区百合鳞茎营养成分及安全性评价............................和继泉,陈玉芹,知史,克叁英,施罗丽,斯那七皮[41]◇专题论述乡村振兴背景下粤北地区无花果产业的SWOT 分析...........................何少波,冯慧敏,张敏,曹秋艳,李海渤[47]临沧市山茶花嫁接苗培育技术规程编制...................................李秀君,万晓丽,杨建荣,黄绍琨,王红颜,何家梅[51]◇学会工作云南省热带作物学会2021年度工作总结及2022年工作计划 (56)云南省热带作物学会在昆明召开2022年度工作会暨学会九届四次常务理事会.........................................................[62]云南省热带作物学会在昆明召开团体标准技术审查会. (46)Tropical Agricultural Science &TechnologySponsored by :Yunnan Institute of Tropical CropsYunnan Tropical Crops Academic AssociationEdited &Published by :Editorial Office of Tropical Agricultural Science &Technology Editor-in-Chief :Professor NI Shubang Address :99Xuanwei Road ,Jinghong ,Yunnan 666100,ChinaResearch on Production Adaptability Test of Rubber Tree Excellent Variety Dafeng 95in Yunnan ......................................................................................................................................................LIU Zhongliang,HE Suming,HE Ligang (1)Screening of Biocontrol Streptomyces DL5C Fermentation Medium and Optimization of Fermentation Conditionsfor Anthracnose of Rubber Tree ...............................LI Lanlan,SHI Yuping,LIU Yixian,DAI Liming,CAI Zhiying (6)Analysis of Fatty Acid Biosynthesis in Macadamia Nut by Transcriptome Sequencing ......................................................................................................................................LIU Ziyan,ZHENG Cheng,NIUYingfeng,MAO Changli,LIU Jin (12)Quality Analysis of 10Pineapple Varieties in Xishuangbanna .................................................................................................................................................................LIU Shihong,NI Shubang,GUAN Yan,YIN Zhenhua,ZHANG Yangmei (19)Grafting Techniques of Avocado in Field under Dry and Hot Valley Condition in Panxi Area ..............................................................................................................WU Jianhua,LI Jinhong,LI Li,LI Suoqing,YANG Juhua,PENG Hongen (24)Breeding of 'Mantianxing'Passiflora edulis under Different Treatments .......................................................HU Fangjian (28)The Main Active Ingredients in Morinda citrigolia at Different Maturity Stages .......................................................................................................................................X U Rong,XU Muguo,JIANG Shikuan,YANG Yan,FU Jiarong,YAN Li (31)Effects of Different Seed Treatments on the Growth of Bulbil-Yellow Konjac ....................................................................................................................................LI Jinwei,YAN Xiangshuai,ZHOU Huiping,YUAN Huifang,TIAN Yaohua (36)The Evaluation of Nutritional Components and Safety in the Lily of Alpine Area .......................................................................................................................................HE Jiquan,CHEN Yuqin,ZHI Shi,KE Sanying,SHI Luoli,SINA Qipi (41)SWOT Analysis of Ficus carica Industry under Background of Rural Revitalization in Northern Guangdong Province .............................................................................................HE Shaobo,FENG Huimin,ZHANG Min,CAO Qiuyan,LI Haibo(47)The Technical Specification on Grafting Seedling of Camellia in Lincang City ...............................................................................................................LI Xiujun,WAN Xiaoli,YANG Jianrong,HUANG Shaokun,WANG Hongyan,HE Jiamei(51)热带农业科技2022,45(2)Tropical Agricultural Science &Technology橡胶树优良品种大丰95在云南的生产适应性试验研究刘忠亮1,何素民2,和丽岗1*(1.云南省热带作物科学研究所,云南景洪666100;2,云南农业大学热带作物学院,云南普洱665099)摘要摘要::1986年引进海南大丰农场培育的橡胶树优良品种大丰95,在云南建立生产性适应系比试验区,通过29年的生长量、产量、副性状、抗性观测结果表明:大丰95幼树生长快,可提早开割,产量中等,抗寒能力与对照GT1相当,抗白粉病能力与对照RRIM600相当,干胶含量较对照RRIM600高,死皮发病指数较对照RRIM600低,刺激效应差,但耐刺激,为二类刺激品种。
会议 presenting author bio简介
会议 presenting author bio简介The presenting author is a renowned expert in their field, with extensive experience in research and academia. They have published numerous papers and articles in prestigious journals, and their work has made significant contributions to their respective field.Having obtained a Ph.D. in their area of expertise, the presenting author has a deep understanding of the research topic and is well-versed in the latest developments and advancements.They have also presented their research at various national and international conferences, gaining recognition for their insightful findings and innovative approach.In addition to their research accomplishments, the presenting author is also actively involved in teaching and mentoring students. They have supervised several graduate and undergraduate students in their research projects and have received positive feedback for their dedication and guidance.With their excellent communication skills and ability to deliver complex concepts in a clear and concise manner, the presenting author is highly regarded as an engaging speaker. Their presentations are known for being informative, thought-provoking, and inspiring.Overall, the presenting author brings a wealth of knowledge and expertise to the conference, making their session a highly anticipated and valuable contribution to the event.。
基于转录组探究外源水杨酸对条锈菌侵染小麦幼苗的缓解效应及差异表达基因分析
作物学报 ACTA AGRONOMICA SINICA 2024, 50(4): 1080-1090 / ISSN 0496-3490; CN 11-1809/S; CODEN TSHPA9 E-mail:***************本研究由财政部和农业农村部国家现代农业产业技术体系建设专项(小麦, CARS-3-7)和河南省农业科学院自主创新项目(2022ZC03)资助。
This study was supported by the China Agriculture Research System of MOF and MARA (Wheat, CARS-3-7) and Independent Innovation Project of HAAS (2022ZC03).*通信作者(Corresponding authors): 张建周,E-mail:*********************** **同等贡献(Contributed equally to this work)第一作者联系方式: 齐学礼,E-mail:******************;李莹,E-mail:******************Received (收稿日期): 2023-09-17; Accepted (接受日期): 2024-01-12; Published online (网络出版日期): 2024-02-23. URL: https:///urlid/11.1809.S.20240222.1514.002This is an open access article under the CC BY-NC-ND license (/licenses/by-nc-nd/4.0/).DOI: 10.3724/SP.J.1006.2024.31053基于转录组探究外源水杨酸对条锈菌侵染小麦幼苗的缓解效应及差异表达基因分析齐学礼1,** 李 莹2,** 李春盈3 韩留鹏1 赵明忠1 张建周3,*1河南省作物分子育种研究院, 河南郑州450002; 2 河南农业大学学报编辑部, 河南郑州450002; 3 河南省农业科学院小麦研究所, 河南郑州450002摘 要: 为探究外源水杨酸提高小麦条锈病抗性的作用机制, 本文将周麦18分为未处理的小麦幼苗(对照)、条锈菌侵染的小麦幼苗(SR)和水杨酸处理条锈菌侵染的小麦幼苗(SA-SR), 对处理15 d 后的小麦幼苗进行抗病性鉴定、氨基酸含量检测、转录组测序及荧光定量分析鉴定。
Water Resources Research in 2013
Water Resources Research in 2013Alberto Montanari(1)(1)Department of Civil, Chemical, Environmental and Materials Engineering (DICAM),University of Bologna, Bologna, Italy.IntroductionThe year 2013 marked important changes for Water Resources Research (WRR). On the one hand some of them can be considered part of the usual development of the journal, that is co-evolving with the international hydrological community. On the other hand, some changes that occurred in 2013 marked a major and perhaps irreversible shift for WRR. It is well known that change, in all human expressions and even in Nature, is typically inducing difficult transition periods. However, change is necessary to adapt to shifting external and internal conditions and its actual impact and implications can be evaluated in the long term only. This editorial presents a summary and a personal assessment of the development of WRR in 2013, including an overview of submission statistics as well as emerging and dominant thematic areas. Reviewing the status of WRR in 2013 is an opportunity to elaborate a perspective on the current patterns in water resources research.The major changes that WRR experienced in 2013 are summarized by the following events: (1) The production of WRR has been transferred from AGU to Wiley-Blackwell. As a consequence, the web site of WRR has been renewed and the layout for published papers was radically revised. (2) The Editorial Board of WRR underwent the planned transition to a new set of editors, that began their term in April 2013. (3) The number of submissions and published papers increased, according to the trend that WRR has experienced in the recentyears. These three events are discussed in the following sections of this editorial, which also includes an overview of the emerging research areas and some concluding personal remarks.Transition to Wiley-BlackwellIn 2012, the Board of Directors of the American Geophysical Union (AGU) took the relevant decision to outsource to Wiley-Blackwell the production, sales, distribution, and subscription of AGU journals starting from January 2013, while keeping in house their control and ownership and the scientific aspects of publishing including editorial control and oversight by AGU governance. The decision was motivated by the will to keep the pace of a publishing marketplace that is tremendously evolving, by adopting a business model for journal production that is widely used by scientific associations. In fact, the primary scope of these associations is to promote the advance and dissemination of science while journal production, sales, and distribution may take advantage of the experience and resources of publishers for whom these functions constitute the main mission. A commercial publisher is expected to bring additional capabilities and expertise in publication strategy, processes and global visibility, therefore benefiting AGU and the scientific community as a whole [McEntee, 2012].On the other hand, we are all aware of the potential drawbacks that the shift from the AGU management to commercial production implies. In fact, the scientific community raised several concerns during 2013, while continuing to support WRR with an increasing number of submissions.In my opinion, the above motivations for the transition to a commercial publisher are justified. However, it is strictly necessary that a tight link is maintained between AGU and the research community while taking the important decisions that the transition implies. At the same time, it is necessary that the Editorial Board and the community itself make sure that the scientific legacy of WRR is preserved, by improving the quality of the articles, the quality ofthe service to authors and the impact and visibility of the journal.The transition to Wiley initially implied some delay in the production process. At present I am pleased to note that the timeliness in the production phase is excellent. On average, papers are available on-line, and are citable, within 6 days from acceptance and are published as early view, in their final form, within 38 days from acceptance.New layouts for articles and web siteDuring 2013 the cooperation with Wiley-Blackwell led to the design of new layouts for journal articles and web sites. A one column format was adopted for articles in view of its flexibility to adapt to several visualization platforms and will be used for all AGU journals from early 2014. The new layout implies an increase of the length of papers by 20% on average, according to statistics that have been estimated on a sample size that is still limited. To keep the publication fees unchanged, the page charges have been adjusted by AGU by adopting an algorithm that is still being optimized. I am in favor of adapting the look of the journal to modern communication means, for the sake of increasing the impact of scientific publishing. Therefore, when the journal editors were involved by AGU in the design of the new layout, in September 2013, I supported its quick adoption. However, I underestimated the time required to deliver an efficient communication of this important change to the authors and therefore I personally take the responsibility for any mismatch that may have arisen between the expectation of the community and the final look of papers. Change always brings adaptation problems, which in this case stimulated constructive reviews of the new layout which is still being tested.The new web site for WRR was launched at the end of 2013, with the aim to reach full compatibility with the most used web platforms. The web site is still in provisional mode. In my opinion it represents an improvement for the web look of the journal. Still, even in this case, the transition phase is taking longer than expected: I believe it is necessary to achievethe full functionality of the web site as soon as possible.Transition to the new Editorial BoardThe new Editorial Board of WRR began the term on April 1st, 2013. The transition phase between the former and new boards, during which former editors concluded the review process for their pending papers, was concluded in December 2013. The vision of the current Board was presented in Montanari et al.[2014] and is basically centered around further improving the visibility and quality of hydrological and water resources publishing. This target will be achieved by pursuing the open access publication mode for WRR, by promoting the dialogue with society and the quality of papers as well as the review process [Van der Hilst and Hanson, 2013; Bloeschl et al., 2014].The transition phase between editorial boards is always a matter of concern for potential authors, for the risk that lack of continuity occurs in the management of the review process. I am pleased to note that such risk is very limited for WRR, as the Editorial Board includes more than 100 associate editors that ensure a tight connection with the community and are rotated with a different timing with respect to editors. Associate editors are the ambassadors of WRR. Their tireless effort (WRR is a demanding journal; see Figure 1) is essential for preserving the quality and the legacy of the journal. Managing the editorial process through associate editors implies longer times to deliver the decision to authors, but significantly reduces the risk of discontinuities in the journal management therefore ensuring a more robust treatment of papers. I believe this is an important issue that marks a clear distinction between involving or not associate editors in the review process.Being an associate editor of WRR is a time demanding task. Figure 1 reports the frequency density of the number of newly submitted papers managed by WRR associate editors in 2013. The actual workload included the management of papers that are resubmitted after revision.Submission statistics in 2013 and timelinessThe number of submission to WRR from 2010 is reported in Table 1. A markedly increasing trend is clearly visible. Table 1 also shows the number of published items and provides an estimate of the rejection rate. The latter is computed by dividing the number of rejected items by the number of submissions in each year and therefore the resulting rejection rates, for the presence of the above mentioned increasing trend, are slightly overestimated. In 2013 about 22% of the papers were rejected without review.Table 1 shows that WRR is keeping its traditional behavior of rigorous journal. The new Editorial Board is continuing the policy of accepting for publication the contributions presenting innovative findings for the international community of water scientists. Case studies are usually not accepted, unless they present research results that have general validity.Table 2 provides statistics on the timing from submission to first decision in 2013, not considering rejections without review. Figure 2 shows the frequency density of the number of days required to reach the first decision for all 2013 submissions. The distribution is bimodal because of the presence of the above mentioned significant number (about 22%) of rejections without review, that are quickly handled. The average time to the selection of the first referee is 12 days after submission (including the initial quality control).The above statistics show that WRR is efficient, especially if one considers that any step of the editorial process is double checked. The initial quality control is overseen by a AGU staff member, who also monitors the timeliness of the process. Late referees are chased in consultation with the relevant editor, and decision letters are also reviewed by the AGU staff before sending them out. Statistics are computed on the performances of each editorial board member and referee, and timeliness is continuously pursued. Nevertheless, some late handling of few papers may still occur.Thematic areasIt is interesting to look at the subdivision in thematic areas of WRR papers that were published in 2013. Figure 3 presents the relative frequency of the primary and secondary index terms (pooled in macro groups) and therefore depicts a first classification that was operated by the authors. Apart from the dominating role of the index term “Hydrology”, which one would of course expect, it is interesting to note that the second most used term is “Natural hazards”, followed by “Informatics”. The significant role played by “Biogeosciences” highlights the emerging role of that area. “Global change” and “Atmospheric processes” display comparable relevance, as well as “Mathematical geophysics”. “Oceanography” and “Cryosphere” are also important and it is interesting to note the relevant role played by “Policy sciences”, therefore highlighting another emerging area.A second classification was operated by the editors, by associating each published paper to a single thematic area. Accordingly, we found that about 118 and 72 published papers were dealing with groundwater and soil science, respectively, while 69 papers (about 21% of the published items) referred to river processes (river hydraulics, river temperature, sediment transport, river morphology, etc.). Ecohydrology and atmospheric processes counted 41 and 34 papers, respectively, while floods and drought were dealt with by 33 contributions. Water quality, cryospheric sciences and climate processes counted about 20 contributions each, while approximately 15 papers focused on each of the areas of uncertainty, hyporheic exchange and water policy.The above distribution of subjects is markedly different with respect to 30 years ago, when catchment modeling, system theory and applied water resources management were more relevant. What is surprising, in comparison with the past pictures, is the striking dominance of modeling studies and the index term “Informatics”. It is well known that the massive increase of computing power that occurred in the 1990s radically changed theresearch activity in water resources. While one may say that our predictive capabilities and understanding did not increase as much, it can be recognized that significant progress has been made. There is no doubt that hydrological models are increasingly applied in the operational practice.By comparing the past and present publication showcases there is another relevant difference that immediately emerges, namely, the globalization of hydrology that has been favored by the much more powerful communication means that are available today. International cooperation has risen significantly and, as a result, the number of authors per paper is increased as well.Figure 3, whose data are confirmed by the present submission trends, seems to put in evidence that aqueous biogeochemistry, ecohydrology and water policy, in connection with social sciences, are the emerging research fields.CitationsSome WRR papers that were published in early 2013 already got a significant number of citations. According to ISI, the most cited 2013 WRR paper, up to February 20, 2014, is Revil [2013] which was published in the January issue and has already received 10 citations. The following most cited papers are Lutz et al. [2013] and van Dijk et al. [2013], both of which were published in the February issue and have received 8 citations. Voss et al. [2013], that was again published in the February Issue, follows with 6 citations. For the sake of comparison, it is interesting to note that the most cited WRR papers published in 2012 are Revil[2012], Schöniger et al. [2012], Landerer and Swenson [2012] and Gupta et al. [2012], with 29, 25, 19 and 18 citations to date, respectively.WRR papers published in 2013 already received a total number of 270 citations (up to February 20, 2014), while the total amount of WRR papers published since 1965, for a total of more than 13,800 items, received approximately 22,000 citations in 2013. This number isimpressive and testifies the massive volume and interest of WRR contributions. By considering that the total count of citations to WRR contributions since 1965 is about 380,000, one notices that WRR received in 2013 more than 5% of its total citations!The above perspective highlights the marked increase of the number of citations in recent times. In fact, it is well known that the number of published items in science is tremendously increasing and therefore the rise in the number of citations is to be expected. However, the impact factor of WRR (that reached the value of 3.149 in 2012) still does not reflect the pivotal role that water plays for society. A more timely communication of recent research results, by giving due reference to recent works, is needed in order to increase the public awareness of research in hydrology. I call on all authors to make their and their colleague’s research quickly known, by involving the most recent work in discussions.Featured papers and press releases.During 2013, twenty-six papers were categorized by the editors as featured contributions in WRR, which correspond to about 5% of the published items. These contributions provide another detailed perspective on emerging areas in WRR. It is interesting to note that the topics covered by featured papers are diverse and complementary. Precipitation was the focus of the contributions by Paschalis et al. [2013], who proposed a new stochastic model for space-time simulation of rainfall fields, and Mengqian et al.[2013], who focused on large scale precipitation predictability by analyzing global and regional atmospheric circulation. The aim of the latter research was to verify whether the study of global atmospheric moisture pathways may provide information to predict large scale flood events, like the one that persisted over western Europe in 1995.Synoptic weather events were also considered by Farlin et al.[2013], who studied their impact on isotopic composition of atmospheric moisture. Their study is relevant for constraining isotope-enabled GCMs in future investigation of atmospheric water cycle.Downscaling of climate model simulations and remote sensing images was the subject of the paper by Jha et al.[2013], who presented an approach based on multiple-point geostatistics. The impact of a changing climate on freshwater withdrawals was investigated by Brown et al.[2013]. Interestingly, they conclude that increasing water use efficiency and decreasing water demands for domestic, public and industrial use will nearly compensate the planned increase in freshwater withdrawals due to growing population in the USA for the next 50 years. Allen et al.[2013] analyzed a tree-ring reconstruction of the Logan River streamflows from 1605 to 1921 and found that the inherent uncertainty in contemporary water management and planning in the considered region is due to hydroclimatic variability that has persisted for at least the last four centuries. The two above conclusions are somehow in agreement in showing that recent climate change interacts with several other drivers that are significantly impacting water resources planning and management.Beck et al.[2013] presented an analysis of recession curves in 3394 catchments all over the world and indentified links between significant physiographic characteristics, the base flow index (BFI) and the base flow recession constant k. Global maps of the estimated BFI and k values were produced and made publicly available. A large-scale study was also performed by Sutanudjaja et al. [2013] by exploring the possibility of using remotely sensed soil moisture data and in situ discharge observations to calibrate a large-extent hydrological model.Parameterisation of hydrological models, at regional scale, was considered by Kumar et al. [2013] who presented a framework to reduce the computational expense that is required for hydrologic prediction over new domains, by using parameter transfer. Again Kumar et al. [2013] focused on parameterization methods for distributed hydrologic models at local scale. Tiedeman and Green[2013] analyzed the effect of correlated observation errors on model parameterization and simulation uncertainty.Floods were the subject of the aforementioned paper by Mengqian et al. [2013] andthe contributions by Viglione et al. [2013] and Dottori et al. [2013]. The former dealt with the role of complementary information, besides past flood records, for inferring the flood frequency distribution, while the latter analyzed the role of new information in flood inundation mapping.Snow modeling was the subject of three papers. Ouellette et al. [2013] focused on the estimation of snow water equivalent from GPS vertical site-position observations. Soil moisture data that were included in the analysis led to a significant improvement of the estimates. Lundquist et al. [2013] proved that lower forest density enhances snow retention in regions with warmer winters. Gaume et al. [2013] focused on mapping extreme snowfalls in the French Alps by using max-stable processes, which allowed a consistent improvement of the estimates for 40 meteorological stations.River hydraulics and morphology was the subject of 2 contributions. Bennett et al. [2013] developed a probabilistic sediment cascade model to simulate sediment transfer in a mountain basin located in Switzerland, which may provide support to better understand the generation of debris flow. Matthew et al. [2013] used data from the Surface Water and Ocean Topography (SWOT) radar interferometer satellite mission to estimate river flow depth.Soltani and Cvetkovic [2013] proposed an analytical model for assessing the water age distribution under arbitrary transient flow along one-dimensional hydrological pathways, while Beven and Germann [2013] presented an interesting review of macropores and water flow in soils. A similar review was presented by the same authors 30 years ago and therefore the Beven and Germann[2013] paper provides an attempt to review the progress in observations and theoretical reasoning about preferential soil water flows over the intervening period.Lutz et al.[2013] proposed an assessment, with counterintuitive results, of the generation, transport, and disposal of wastewater associated with Marcellus Shale gas development. The Marcellus Shale is by far the largest shale gas resource in the United States.Gas and wastewater production was evaluated by using data from 2189 wells located throughout Pennsylvania. The results show that Marcellus wells produce significantly less wastewater per unit gas recovered (approximately 35%) compared to conventional natural gas wells. Kunz et al. [2013] referred to the Itezhi-Tezhi Reservoir (Zambia) as a model system to optimize turbine withdrawal to prevent hypoxia and to relieve low-nutrient conditions in the downstream ecosystems. Van Loon and Van Lanen [2013] proposed an observation-modeling framework to distinguish between water scarcity and droughts, therefore obtaining supporting information for the mitigation of the related societal impacts.A paper that received a considerable attention from the media, and was lately commented in WRR, was authored by Voss et al. [2013] who used observations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission to evaluate freshwater storage trends in the north-central Middle East, including portions of the Tigris and Euphrates River Basins and western Iran, from January 2003 to December 2009. The results showed a decreasing rate in total water storage of approximately 143.6 km3 of water during the course of the study period.Finally, the identification and assessment of model structure was the subject of two contributions: Hartmann et al. [2013] developed and tested four hydrological model structures, based on different hypotheses about subsurface flow and storage behavior, to identify the functioning of a large Mediterranean karst system, while Pande [2013] focused on quantile hydrologic model selection and structure deficiency assessment by referring to three case studies.Two press releases were issued by the American Geophysical Union to provide media visibility to papers that dealt with issues interesting for the wide public. The first press release referred to the paper by Kibler and Tullos [2013], which investigated the environmental impacts of dams on an ecologically diverse and partially protected river in China. The second press release highlighted the aforementioned paper by Voss et al. [2013].ConclusionsThe above overview highlights the evolving context in which scientific journals today operate which is dominated by a tremendously increasing number of submissions, publications and citations. The management of Water Resources Research needs to quickly adapt to a situation that is markedly changing and will change even more radically in the future. Managing a scientific journal by ensuring a rigorous scrutiny is requiring more and more time and personal commitment. The question then arises whether the current model for peer review is sustainable in the long term. More generally, I think that another relevant question is whether the current methods for assessing scientific research are still providing a meaningful perspective. Is peer review still efficient? Are citations still a reliable indicator of scientific value in a context where they are tremendously increasing in number?The success of scientific activity of young researchers and the future of science are tightly connected to the efficiency of research assessment and publishing and therefore the above questions are extremely relevant. Assessing and communicating research should become a priority for the scientific community, including editors and journal publishers. I am convinced that leading scientific journals, like WRR, should take an active role in seeking and promoting forward looking solutions.AcknowledgementsI am very grateful to Brooks Hanson, Rebecca Knowlton, Victoria Forlini, Swapna Padhye and Maria Kheyman for providing essential information to prepare this Editorial.ReferencesAllen, E. B., T. M. Rittenour, R. J. DeRose, M. F. Bekker, R. Kjelgren, and B. M. Buckley (2013), A tree-ring based reconstruction of Logan River streamflow, northern Utah, WaterResour. Res., 49, 8579–8588, doi:10.1002/2013WR014273.Beck, H. E., A. I. J. M. van Dijk, D. G. Miralles, R. A. M. de Jeu, L. A. Bruijnzeel, T. R. McVicar, and J. Schellekens (2013), Global patterns in base flow index and recession based on streamflow observations from 3394 catchments, Water Resour. Res., 49, 7843–7863, doi:10.1002/2013WR013918.Bennett, G. L., P. Molnar, B. W. McArdell, and P. Burlando (2014), A probabilistic sediment cascade model of sediment transfer in the Illgraben, Water Resour. Res., 50, doi:10.1002/2013WR013806.Beven, K., and P. Germann (2013), Macropores and water flow in soils revisited, Water Resour. Res., 49, 3071–3092, doi:10.1002/wrcr.20156Blöschl, G., A Bárdossy, D. Koutsoyiannis, Z.W. Kundzewicz, I. Littlewood, A. Montanari, H. Savenije (2014), Joint Editorial – On the Future of Journal Publications in Hydrology, to be published on Water Resources Research, Hydrology and Earth System Sciences, Journal of Hydrology, Hydrological Sciences Journal, Hydrology Research.Brown, T. C., R. Foti, and J. A. Ramirez (2013), Projected freshwater withdrawals in the United States under a changing climate, Water Resour. Res., 49, 1259–1276,doi:10.1002/wrcr.20076.Dottori, F., G. Di Baldassarre, and E. Todini (2013), Detailed data is welcome, but with a pinch of salt: Accuracy, precision, and uncertainty in flood inundation modeling, Water Resour. Res., 49, 6079–6085, doi:10.1002/wrcr.20406.Farlin, J., C.-T. Lai, and K. Yoshimura (2013), Influence of synoptic weather events on the isotopic composition of atmospheric moisture in a coastal city of the western United States, Water Resour. Res., 49, 3685–3696, doi:10.1002/wrcr.20305.Gaume, J., N. Eckert, G. Chambon, M. Naaim, and L. Bel (2013), Mapping extreme snowfalls in the French Alps using max-stable processes, Water Resour. Res., 49,doi:10.1002/wrcr.20083.Gupta, H. V., M. P. Clark, J. A. Vrugt, G. Abramowitz, and M. Ye (2012), Towards a comprehensive assessment of model structural adequacy, Water Resour. Res., 48, W08301, doi:10.1029/2011WR011044.Hartmann, A., T. Wagener, A. Rimmer, J. Lange, H. Brielmann, and M. Weiler (2013), Testing the realism of model structures to identify karst system processes using water quality and quantity signatures, Water Resour. Res., 49, 3345–3358, doi:10.1002/wrcr.20229.Jha, S. K., G. Mariethoz, J. P. Evans, and M. F. McCabe (2013), Demonstration of a geostatistical approach to physically consistent downscaling of climate modeling simulations, Water Resour. Res., 49, doi:10.1029/2012WR012602.Kibler, K. M., and D. D. Tullos (2013), Cumulative biophysical impact of small and large hydropower development in Nu River, China, Water Resour. Res., 49, 3104–3118, doi:10.1002/wrcr.20243.Kumar, R., B. Livneh, and L. Samaniego (2013), Toward computationally efficient large-scale hydrologic predictions with a multiscale regionalization scheme, Water Resour. Res., 49, 5700–5714, doi:10.1002/wrcr.20431.Kumar, R., L. Samaniego, and S. Attinger (2013), Implications of distributed hydrologic model parameterization on water fluxes at multiple scales and locations, Water Resour. Res., 49, doi:10.1029/2012WR012195.Kunz, M. J., D. B. Senn, B. Wehrli, E. M. Mwelwa, and A. Wüest (2013), Optimizing turbine withdrawal from a tropical reservoir for improved water quality in downstream wetlands, Water Resour. Res., 49, 5570–5584, doi:10.1002/wrcr.20358.Landerer, F. W., and S. C. Swenson (2012), Accuracy of scaled GRACE terrestrial water storage estimates, Water Resour. Res., 48, W04531, doi:10.1029/2011WR011453.Lu, M., U. Lall, A. Schwartz, and H. Kwon (2013), Precipitation predictability associated with tropical moisture exports and circulation patterns for a major flood in France in 1995, Water Resour. Res., 49, 6381–6392, doi:10.1002/wrcr.20512.。
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AUTHOR AGREEMENTJournal____________________________________________________________________ ArticleTitle_________________________________________________________________The undersigned author (after reviewing criteria for authorship as defined by International Committee of Medical Journal Editors [ICJME] found at ‘http://www//’ and have participated reasonably in the intellectual content, analysis of data and writing of the article) jointly and severally, hereby transfer and assign all rights, title, and interest therein, including any and all copyrights in all forms and media now or hereafter known, to the Journal of Medical sciences. The author/s retain the nonexclusive right to use part or all of the article in future work of their own, provided proper credit is given to the Journal of Medical Sciences. In case, the submitted article is not published, the Editorial Board agrees to release its rights therein.I certify thatA) None of the material in the manuscript has been published previously/currently under consideration for publication elsewhere.B) The article has not been accepted for publication elsewhereC) I have not signed any right or interest in the article to any third partyD) I am able/willing to produce the data on which this article is based, should the Editorial Board of the Journal of Medical Sciences request such data.E) Animal Care Committee/Institutional Review Board approval was granted for this study.I (including spouse and children), disclose financial interest at the level:a) Nothing to discloseb) Financial interest to the amount of _________________________F) I/We confirm to comply fully with the suggestions/critical views of the reviewers/editor, failing which my/our article may be rejected at the sole discretion of the editor. I/we further confirm that if our article is rejected (which is the sole discretion of the editor) I/we will have no right to complain against the journal/editor/representative of the journal/printer in any forum including the court of law.G) I/we suggest the following two overseas reviewers to review our article.______________________ _______________________ _______________________________________________ _______________________ _________________________Name of reviewer Postal address Email address & Telephone No _______________________ ______________________ __________________________ _______________________ ______________________ __________________________ _______________________ ______________________ __________________________ _______________________ ______________________ __________________________ _______________________ ______________________ __________________________ Author name Author signature Author e-mail addressNote: Author agreement form must be signed by each author (one page for each) and submitted with the article.Author’s Checklist:Eliminate nonstandard abbreviation in the titlesSupply full author names (including institutional affiliation and contact information) Abstract: 200 words, Article: 2000 words (excluding references)Supply references in Vancouver style, accurately cited in the text in numerical order Cite tables in the text in numerical orderSend 03 Hard copies and on an R/W CD (in MS Word), in a protective envelop, do not use clipsCite figures in the text in numerical orderAuthor agreement is signed by all authorsBank draft for Rs. 3000/- (Pak Rupees) in the name of Journal of Medical Sciences, Peshawar, Pakistan/or deposit in cash with Managing Editor.。
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Editorial:The IEEE T RANSACTIONS ON N EURAL N ETWORKS2010and BeyondI T gives me great pleasure to write thisfirst editorial of theyear and to say“Happy New Year!”to all of you.I have great hope for2010,which is the year of the tiger according to the Chinese lunar calendar.Coincidentally,I was born in the year of the tiger,which is said to represent courage,passion, speed,and generosity.So I look forward to a wonderful year, and I wish the best for all of you.On that note,I would like to address four important topics as we move forward into2010:our new Associate Editors,a hearty“thank you”to our outgoing Editor-in-Chief,challenges in2010,and a brief self-introduction.Welcome New Associate EditorsAssociate Editors play a very critical role in maintaining the quality of a journal and in getting all submissions reviewed in a professional and timely manner.So,I would like to begin our year by introducing them.All of them are established authorities in their respectivefields and have been carefully selected based on their expertise and past publication experi-ence with the IEEE T RANSACTIONS ON N EURAL N ETWORKS (TNN).It is my great pleasure to welcome the following new Asso-ciate Editors,whose term officially starts on January1,2010(B. DasGupta,A.Hirose,and Z.Yi started on August1,2009):•Hojjat Adeli,Ohio State University,USA•Amit Bhaya,Universidade Federal do Rio de Janeiro,Rio de Janeiro,Brazil•Pau-Choo(Julia)Chung,National Cheng Kung University, Taiwan•Bhaskar DasGupta,University of Illinois at Chicago,USA •El-Sayed M.El-Alfy,King Fahd University of Petroleum and Minerals,Saudi Arabia•Haibo He,Stevens Institute of Technology,USA •Akira Hirose,University of Tokyo,Japan•Sanqing Hu,Drexel University,USA•Hossein Javaherain,General Motors R&D Center,USA •Li-Wei(Leo)Ko,National Chiao-Tung University,Taiwan •Frank L.Lewis,University of Texas at Arlington,USA •Guo-Ping Liu,University of Glamorgan,U.K.•Seiichi Ozawa,Kobe University,Japan•Stefano Squartini,Universita Politecnica delle Marche, Italy•Changyin Sun,Southeast University,China•Draguna Vrabie,University of Texas at Arlington,USA •Zhang Yi,Sichuan University,China•Zhigang Zeng,Huazhong University of Science and Tech-nology,China•Huaguang Zhang,Northeastern University,China •Nian Zhang,University of the District of Columbia,USA •Liang Zhao,Universidade de Sao Paulo,Brazil •Nanning Zheng,Xi’an Jiaotong University,China.Digital Object Identifier10.1109/TNN.2009.2038645Fig.1.TNN impact factors between2003and2008.Thank you,MariosNext,I want to offer a heartfelt“Thank you!”to my prede-cessor,Marios Polycarpou.Under the leadership of Marios,notonly has the quantity of submissions to the TNN increased,butalso the quality.In2008,the TNN received585submissions,andin2009,that number will be more than600.In addition,we haveseen a steady increase in the quality of papers submitted to ourT RANSACTIONS.Since Marios took over the T RANSACTIONS onJanuary1,2004,he has led the transition from a manual to an all-electronic submission and review system,the ScholarOne Manu-scripts system(previously,the Manuscript Central system).OurT RANSACTIONS also went from six issues per year to12issuesper year currently.Thank you,Marios,for a job well done.With the ScholarOne Manuscripts system,we have nowstreamlined all submissions and reviews in a paperless fashionwith an environment-and user-friendly process.This hasresulted in a faster procedure for paper review and handling.It also makes it easier for the Editor-in-Chief to communicatewith Associate Editors and authors.I would like to mention thatmy predecessor has exerted tireless efforts to transition throughseveral versions of the ScholarOne Manuscripts system.The most recent ISI journal citation report indicated that ourT RANSACTIONS has an impact factor of3.726(see Fig.1).Withthis,it is ranked fourth among all journals in artificial intel-ligence,ninth among all IEEE journals,and eleventh amongall journals in electrical and electronic engineering.I wouldlike to congratulate Marios for his leadership and hard work inachieving what we have today.Thank you again,Marios.ChallengesIn terms of challenges for2010,I see this year as a crucialperiod of potential growth and development.This issue marksthe beginning of the21st year of the TNN.Founded in1990,theTNN has undergone many changes.However,just as a youngperson crossing the threshold into adulthood,our T RANSACTIONSis coming of age and must continue to grow and change.I am very excited about the related challenges ahead of me.Ican imagine how difficult it was to increase the rankings of our 1045-9227/$26.00©2010IEEET RANSACTIONS in recent years.So my primary challenge will be tostartwiththecurrentrankingandtrytoimproveitfurther.Other challenges include making the TNN the number one choice for young and senior researchers in ourfield to publish their best re-search results and to search for the latest information.The TNN has been growing steadily since it was founded20years ago. We must make sure that this trend continues and that the TNN will show significant further growth in the years to come.Self-IntroductionFinally,let me say a few words about myself.I started working in neural networks after I joined the Univer-sity of Notre Dame as a Ph.D.student in electrical engineering with a Michael J.Birck Fellowship in1990.I worked with Prof. Anthony N.Michel on nonlinear dynamical systems with satura-tion nonlinearities that include several classes of recurrent neural networks.Our work included analysis and synthesis of recurrent neural networks,robust analysis and design of associative mem-ories,and synthesis algorithms for cellular neural networks.In addition to neural networks,my research interests include intelligent control with a primary focus on adaptive dynamic programming and reinforcement learning(ADPRL)and its ap-plications.Neural networks are used as a tool for functional ap-proximation to the implementation of adaptive dynamic pro-gramming,even though other functional approximation tools may be employed.I am working with my Ph.D.students and collaborators on the fundamental theoretical development of ADPRL and appli-cations with significant economic impact.I have also started working in thefield of computational neuroscience,which I view as a natural next step in the quest for understanding brain functions and brain-like intelligence.The ultimate goal of my research is to understand and mimic natural,biological neural networks,i.e.,our brain.My current study on adaptive dynamic programming is closely related to the learning functions of the putational neuroscience is an exciting interdisciplinaryfield,which is at the intersection of neuroscience,biological science,computer science,and en-gineering.It is a multidisciplinary research effort,and I am col-laborating with others in medical and psychological disciplines. In conclusion,I would like to express my sincere gratitude to the Institute of Automation,Chinese Academy of Sciences (Prof.Fei-Yue Wang,Vice-President of CASIA,and Director of the KLCSIS)and the Department of Electrical and Com-puter Engineering,University of Illinois at Chicago(Prof.Mitra Dutta,Head of UIC’s Electrical and Computer Engineering De-partment)for allowing me and the TNN staff to use the extra office space as well as the computing and networking facilities for the benefit of our T RANSACTIONS.I look forward to a wonderful new year and this exciting new opportunity with the TNN.D ERONG L IU,Editor-in-ChiefChinese Academy of Sciences,Institute of AutomationBeijing,100190,ChinaPhone:+861062557379University of Illinois,Department of Electrical andComputer EngineeringChicago,IL60607USAPhone:3123554475E-mail:ieeetnn@Derong Liu(S’91–M’94–SM’96–F’05)received the B.S.degree in mechanical engineering fromthe East China Institute of Technology(now Nanjing University of Science and Technology),Nan-jing,China,in1982,the M.S.degree in automatic control theory and applications from the Instituteof Automation,Chinese Academy of Sciences,Beijing,China,in1987,and the Ph.D.degree inelectrical engineering from the University of Notre Dame,Notre Dame,IN,in1994.He was a Product Design Engineer with China North Industries Corporation,Jilin,China,from1982to1984.He was an Instructor with the Graduate School of the Chinese Academy of Sci-ences,Beijing,China,from1987to1990.He was a Staff Fellow with General Motors Researchand Development Center,Warren,MI,from1993to1995.He was an Assistant Professor in theDepartment of Electrical and Computer Engineering,Stevens Institute of Technology,Hoboken,NJ,from1995to1999.He joined the University of Illinois at Chicago in1999,where he becamea Full Professor of Electrical and Computer Engineering and of Computer Science in2006.Hewas selected for the“100Talents Program”by the Chinese Academy of Sciences in2008.He has published nine books(five research monographs and four edited volumes).Dr.Liu is an Associate Editor of Automatica.He was General Chair for the2007International Symposium on Neural Networks, Nanjing,China.He was a member of the Conference Editorial Board of the IEEE Control Systems Society(1995–2000),an Associate Editor of the IEEE T RANSACTIONS ON C IRCUITS AND S YSTEMS—P ART I:F UNDAMENTAL T HEORY AND A PPLICATIONS (1997–1999),the IEEE T RANSACTIONS ON S IGNAL P ROCESSING(2001–2003),the IEEE C OMPUTATIONAL I NTELLIGENCE M AGAZINE(2006–2009),the IEEE C IRCUITS AND S YSTEMS M AGAZINE(2008–2009),and the IEEE T RANSACTIONS ON N EURAL N ETWORKS(2004–2009),and the Letters Editor of the IEEE T RANSACTIONS ON N EURAL N ETWORKS(2006–2008).He was the Editor of the IEEE Computational Intelligence Society’s E LECTRONIC L ETTER(2004–2009).Currently,he is the Editor-in-Chief of the IEEE T RANSACTIONS ON N EURAL N ETWORKS.He was General Chair for the2009IEEE Conference on Service Operations, Logistics,and Informatics,Chicago,IL,and the2008IEEE International Conference on Networking,Sensing and Control, Sanya,China.He was an elected AdCom member of the IEEE Computational Intelligence Society(2006–2008).He received the Michael J.Birck Fellowship from the University of Notre Dame(1990),the Harvey N.Davis Distinguished Teaching Award from Stevens Institute of Technology(1997),the Faculty Early Career Development(CAREER)award from the National Science Foundation(1999),the University Scholar Award from University of Illinois(2006–2009),and the Overseas Outstanding Young Scholar Award from the National Natural Science Foundation of China(2008).He is a member of Eta Kappa Nu.。