兴山龙门河地区的植物群落与物种多样性研究

龙门河地区地处湖北省的西部，神农架的南坡，处于中亚热带向北亚热带过渡的地带。对其植物与植物群落的研究得到如下结果： 龙门河地区共有维管植物160科724属1737种，其中种了植物140科692属共1686种。其植物区系有显著的温带性，温带分布属共380属，占总属数的54.9%，这可能和该地区的地理位置，海拔及人为活动的影响有关，该地区的植物区系还具有古老性，特有属丰富特点，且有较多的珍稀濒危植物分布。 龙门河地区的植被共划分三个自然植被型共16个群系。在高海拔地区保存有较原始的落叶阔叶林，低海拔地区多为人为破坏后的次生类型。这些植被类型随环境条件的变化呈现较有规律的分布，依照其垂直分布的情况，可以将该地区植被划为三个带，即常绿阔叶林带低于海拔900(-1300)m;常绿落叶阔叶混交林位于海拔900(-1300)-600m之间;落叶阔叶林带在海拔1600(-1300)-2200m之间，无针叶林带在龙门河地区分布。应用TWINSPAN和DCA程序对各调查样地进行数量分类和排序结果说明，植物群落的分布与环境因子明显相关，但排序轴不能用海拔等单个的因子来解释。对各群落乔木层的Gleason丰富度指数，Shannon-Wiener指数及Pielou均匀度指数对比后发现，各种指数在不同的群落之间及不同海拔高度上没有明显的规律，这可能是由于人类活动混淆了群落成分及结构的结果。 锐齿槲栎林是神农架地区一种重要的落叶阔叶林，其分布广泛，保存较好。通过对锐齿槲栎种群大小结构的研究发现，中等大小的锐齿槲栎个体数量较多，幼苗与幼树的数量在不同样地间变化很大，其大小结构分布图中多有一定程度的缺失。锐齿槲栎种群多呈现聚集分布，不同的尺度下其聚集程序不同。在大多数尺度下，幼苗幼树的聚集程度比相同尺度下成体的聚集程序高。幼苗更新是锐齿槲栎更新的一种主要形式，其幼苗的出现与林窗的形成有密切的关系。在锐齿槲栎幼苗成长为幼树的过程中，同于种内与种间竞争的影响。导致了许多幼树的死亡。正是由于林窗形成等干扰因素的影响才使锐齿槲栎幼树得以进入群落上层。

鄂尔多斯高原油蒿种群分布格局与群落数量特征对降水梯度的反应

近年来，种群空间分布格局日益为生态学家所重视，已成为生态学发展最快的领域和生态学理论发展的核心之一，群落的植被盖度和生物多样性是生态学研究的常用指标。植物种群分布格局及群落特征是种群和群落对环境条件长期适应和选择的结果，一方面决定于植物自身的生物学特性，另一方面与种群和群落分布的生境密切相关，对于揭示植被对环境的适应规律及它们之间的相互关系具有十分重要的意义。 本文以油蒿种群为研究对象，沿着鄂尔多斯高原从东至西的降水梯度(336～249mm)，应用传统的分布格局检验法以及点格局方法进行油蒿种群分布格局的研究；采用Gleason 指数、Shannon-Wiener 指数、Pielou 指数和Simpson 指数分析比较油蒿群落的生物多样性。从格局分析的尺度问题、严密性以及聚集程度变化趋势等几个方面，对本文采用的种群分布格局分析方法进行比较，为种群分布格局分析方法的选择提供参考。 种群分布格局分析结果表明沿着降水递减的梯度，在小尺度上油蒿种群分布格局表现为由均匀分布向随机分布转变的趋势；在大尺度上则表现为由随机分布向聚集分布转变的趋势。沿降水逐渐减弱的梯度上，油蒿种群的聚集程度逐渐增强。降水梯度对油蒿种群分布格局的影响一方面由油蒿本身的生物学特性决定，在降雨量小的地区，油蒿母株周围幼苗的存活率高，呈现聚集分布格局，而降雨量大的地区，油蒿幼苗存活概率比较平均，形成随机分布格局；其次，降雨量较大的地区，土壤水分资源较充足，油蒿个体较大，个体之间以竞争关系为主，聚集程度较低，降雨量少的地区，油蒿个体较矮小，个体之间为共同抵御恶劣生境，呈现聚集分布的格局。 群落FPC 和生物多样性指数与年平均降水量的回归分析结果显示，降水量越大，植被盖度越高，物种丰富度越大，群落物种分布均匀程度和优势度越低。充足的降雨促进油蒿群落的发育，草本层植物长势更好，生物量增加，群落的结构趋于复杂。 传统的分布格局检验方法和点格局方法在油蒿种群分布格局分析应用中得到的结果具有高度一致性，然而在实际工作中，这些方法之间具有各自的优劣和适应性。 建议在选取种群分布格局的分析方法时，要充分考虑研究目的，根据具体的物种和实验环境确定采用的方法。需在各细微尺度上做种群分布格局分析时，点格局方法优于传统的分析方法；在大范围取样及对工作效率要求较高时，方差均值比率法和聚集强度指数法更适合。由于聚集强度指数法在进行结果判定时比较模糊，建议优先选择方差均值比率法，将聚集强度指数法作为参考。降雨的减少显著改变了植物种群的空间分布格局和群落结构及物种组成，在进行生态恢复时可以参照本文的分析结果进行恢复植被的合理配置。

丙烯酰胺水溶液辐射聚合 Ⅰ聚合过程中聚合物交联反应机制的探讨 Ⅱ聚丙烯酰胺的溶解 Ⅲ合成在水中易溶或速溶的丙烯酰胺聚合物和共聚物

Ⅰ. 聚合过程中聚合物交联反应机制的探讨 聚丙烯酰胺是水溶性聚合物，但一般工业生产的聚丙烯酰胺在水中很难溶解。一个重要因素是由于在聚合过程中聚合物发生了交联。Minsk (1949)认为聚丙烯酰胺大分子上的-CoNH_2的亚胺化，导致聚合物在水中难溶或不溶：Gleason (1959)和Suen (1960)分别指出活性链的链转移和在丙烯酰胺聚合过程中产生末端双键是聚合物交联的起因：AδkuH (1973)认为丙烯酰胺在浓水溶液中聚合是通过水离子作用生成网状聚合物。由于交联是一个伴随聚合的付反应，少量的交联就导致聚合物不溶，加之缺乏有效的分析手段，所以难于定量研究这一过程。一些科学工作者对交联的性质提出了各种设想，但有关交联方面的系统讨论加交联机制问题至今未见报导。本工作估算了聚丙烯酰胺的内聚能和分子间力（主要－CoNH_2间氢键作用力），说明了丙烯酰胺浓度越大，它的聚合产物越易交联；研究了聚合体系PH值对聚合交联的影响，丙烯酰胺在酸性或中性介质中用r射线引发聚合，很快出现凝胶，只有在碱性(PH > 13)介质中r射线幅照可得到水溶性聚丙烯酰胺。用酰胺基的亲核反应能力解释了原子效应，幅照生成聚合物自由基和双键是聚合物交联的潜在因素，在聚合体系加入链转移剂抗坏血酸，可有效地抑制聚合过程中聚合物的迅速交联；从红外光谱观察到交联聚丙烯酰胺的酰胺特征吸收峰从1650 cm~(-1)向亚胺特征吸收峰方向位移，聚丙烯酰胺的含N量低于理论值，交联聚丙烯酰胺含N量偏离理论值更大，以及不溶聚丙烯酰胺的交联键可以羟高温水解完全破坏，由此肯定聚合过程中聚合物交联具有亚胺结构。根据酰胺基结构特点加亲核取代反应原理，提出丙烯酰胺水溶液辐射聚合过程中聚合物的交联机制如下：1.聚合物自由基的生成。2.自由基促使－CoNH_2活化，导致-CoNH_2间亲核取代反应。3.当R_2 = -CH=CH_2即单体参与亚胺化则导致在分子链上产生悬挂双键，将引起聚合物交联。这一反应机制可以阐明丙烯酰胺水溶液辐射聚合过程中聚合交联起因和历程，可以解释键材剂。质子效应和亚胺之间联系，为制备水溶性聚丙烯酰胺提供了线索。Ⅱ. 聚丙烯酰胺的溶解 关于聚合物溶解理论前人曾从两方面进行探讨。一是Hidebrand (1949)提出以内聚能密度的平方根作为溶度参数δ来鉴别两种物互溶的可能性。Burrel (1955)把这一方法来研究聚合物的溶解。内聚能依赖于色散力、极性力和氢／键，它由三部分组成E = E_d + E_p + E_h，对应的溶度参数方程为δ~2 = δ_d~2 + δ_p~2 + δ_h~2，因此只有两种物质的溶度参数的各个分量相近时，才有可能互溶。这一方面的研究仅涉及溶解过程的热力学。另一是Ueberreiter (1968)提出溶解是一个相互扩散过程。聚合物在溶解过程中，溶解速度S和溶胀层厚度δ处于稳态。它们和溶剂在聚合物中平均扩散系数D-bar_s的关系为2S = D-bar_s/δ，比式直接反映了溶解的动力学过程。聚丙烯酰胺有极强的极性和形成氢键的能力，它只溶于水，对溶度参数的研究存在一定困难。采用扩散原理研究聚丙烯酰按的溶解速度和规律比较有利。为此目地，我们设计制作了专门溶解实验装置，借助聚丙烯酰胺存在电离基因，利用电导测定溶解速度S，并借助针入法则定溶胀层厚度δ和溶胀速度W，发现极性聚丙烯酰胺的溶解不同于Ueberreiter所研究的非极性聚合物聚苯乙烯的溶解。它是一个非稳态过程，不存在诱导期，溶解和溶胀同时进行，根据这事实和理论分析得到2S + W = （D-bar）_s/δ这一关系式与实验数据相符。此关系式可还原Ueberreinter的稳态溶解得到的关系式，并适用于交联聚合物的溶胀。聚丙烯酰胺的-CoNH_2强吸水性导致它在溶解时溶胀形成凝胶层是一个快步骤，而-CoNH_2强的形成氢键能A是溶解的主要障碍，因此溶解是一个慢过程。聚丙烯酰胺的溶解活化能E_s和水在聚合物中扩散活化能E_D都是6干卡／克分子左右；处于氢键离解能范围之内，所以聚丙烯酰胺溶解主要克服分子间氢键作用力。研究了影响聚丙烯酰胺的溶解因素：（1）聚丙烯酰胺单位时间溶解量与它们的颗粒直径2.5次方成反比。（2）聚丙烯酰胺溶解速度与分子量0.5 - 0.7次方成反比。（3）聚丙烯酰胺溶解速度对湿度的依赖关系为S = 0.278 exp[-627o/RT]（4）聚丙烯酰胺大分子中引进-CooNa，吸水性增强，溶解过程双电层形成，产生剪切应力和静电斥力，促使键移动，降低了溶解活化能，加速溶解。（5）聚合物中添加亲水性强的表面活活性剂有利于聚丙烯酰胺的溶解。Ⅲ. 合成在水中易溶或速溶丙烯酰胺聚合物和共聚物 本文强调了在丙烯酰胺水溶液辐射聚合过程中，避免聚合物交联是合成水溶性聚合物的先决条件。加NaOH的丙烯酰胺水溶液聚合和加链转移剂抗坏血酸的丙烯酰胺水溶液聚合物都可得到转化率和分子量都较高，而且不交联的丙烯酰胺的聚合物和共聚物。在单体水溶液中添加尿素对聚合物有助溶效果；添加亲水性强的表面活性剂JFC可改善聚合物颗粒的粘结和抱团。提出了两个聚合体系，合成出在水中速溶的聚丙烯酰胺和羰钠基不同含量的阴离子型 聚丙烯酰胺，聚合物颗粒小于40目，可在10分钟内完成溶解。

The benefit of context for facial composite construction.

Purpose - The aim of this study was to investigate whether the presence of a whole-face context during facial composite production facilitates construction of facial composite images. Design/Methodology - In Experiment 1, constructors viewed a celebrity face and then developed a facial composite using PRO-fit in one of two conditions: either the full-face was visible while facial features were selected, or only the feature currently being selected was visible. The composites were named by different participants. We then replicated the study using a more forensically-valid procedure: In Experiment 2 non-football fans viewed an image of a premiership footballer and 24 hours later constructed a composite of the face with a trained software operator. The resulting composites were named by football fans. Findings - In both studies we found that presence of the facial context promoted more identifiable facial composite images. Research limitations/implications – Though this study uses current software in an unconventional way, this was necessary to avoid error arising from between-system differences. Practical implications - Results confirm that composite software should have the whole-face context visible to witnesses throughout construction. Though some software systems do this, there remain others that present features in isolation and these findings show that these systems are unlikely to be optimal. Originality/value - This is the first study to demonstrate the importance of a full-face context for the construction of facial composite images. Results are valuable to police forces and developers of composite software.

Rodent models for resolving extremes of exercise and health

The extremes of exercise capacity and health are considered a complex interplay between genes and the environment. In general, the study of animal models has proven critical for deep mechanistic exploration that provides guidance for focused and hypothesis driven discovery in humans. Hypotheses underlying molecular mechanisms of disease, and gene/tissue function can be tested in rodents in order to generate sufficient evidence to resolve and progress our understanding of human biology. Here we provide examples of three alternative uses of rodent models that have been applied successfully to advance knowledge that bridges our understanding of the connection between exercise capacity and health status. Firstly we review the strong association between exercise capacity and all-cause morbidity and mortality in humans through artificial selection on low and high exercise performance in the rat and the consequent generation of the "energy transfer hypothesis". Secondly we review specific transgenic and knock-out mouse models that replicate the human disease condition and performance. This includes human glycogen storage diseases (McArdle and Pompe) and α-actinin-3 deficiency. Together these rodent models provide an overview of the advancements of molecular knowledge required for clinical translation. Continued study of these models in conjunction with human association studies will be critical to resolving the complex gene-environment interplay linking exercise capacity, health, and disease.

Student use of electronic information services in further education

Urquhart,C., Thomas, R., Spink, S., Fenton, R., Yeoman, A., Lonsdale, R., Armstrong, C., Banwell, L., Ray, K., Coulson, G. & Rowley, J. (2005). Student use of electronic information services in further education. International Journal of Information Management, 25(4), 347-362. Sponsorship: JISC

Allochthonous and autochthonous mire deposits, slope instability and palaeoenvironmental investigations in the Borve Valley, Barra, Outer Hebrides, Scotland

Ashmore, P. Brayshay, B.A Edwards, K.J Gilbertson, D. Grattan, J. Kent, M. Pratt, K. Weaver, R. 'Allochthonous and autochthonous mire deposits, slope instability and palaeoenvironmental investigations in the Borve Valley, Barra, Outer Hebrides, Scotland' The Holocene 2000 10, 1 pp.97-108

Genome-wide association with bone mass and geometry in the Framingham Heart Study

BACKGROUND:Osteoporosis is characterized by low bone mass and compromised bone structure, heritable traits that contribute to fracture risk. There have been no genome-wide association and linkage studies for these traits using high-density genotyping platforms.METHODS:We used the Affymetrix 100K SNP GeneChip marker set in the Framingham Heart Study (FHS) to examine genetic associations with ten primary quantitative traits: bone mineral density (BMD), calcaneal ultrasound, and geometric indices of the hip. To test associations with multivariable-adjusted residual trait values, we used additive generalized estimating equation (GEE) and family-based association tests (FBAT) models within each sex as well as sexes combined. We evaluated 70,987 autosomal SNPs with genotypic call rates [greater than or equal to]80%, HWE p [greater than or equal to] 0.001, and MAF [greater than or equal to]10% in up to 1141 phenotyped individuals (495 men and 646 women, mean age 62.5 yrs). Variance component linkage analysis was performed using 11,200 markers.RESULTS:Heritability estimates for all bone phenotypes were 30-66%. LOD scores [greater than or equal to]3.0 were found on chromosomes 15 (1.5 LOD confidence interval: 51,336,679-58,934,236 bp) and 22 (35,890,398-48,603,847 bp) for femoral shaft section modulus. The ten primary phenotypes had 12 associations with 100K SNPs in GEE models at p < 0.000001 and 2 associations in FBAT models at p < 0.000001. The 25 most significant p-values for GEE and FBAT were all less than 3.5 x 10-6 and 2.5 x 10-5, respectively. Of the 40 top SNPs with the greatest numbers of significantly associated BMD traits (including femoral neck, trochanter, and lumbar spine), one half to two-thirds were in or near genes that have not previously been studied for osteoporosis. Notably, pleiotropic associations between BMD and bone geometric traits were uncommon. Evidence for association (FBAT or GEE p < 0.05) was observed for several SNPs in candidate genes for osteoporosis, such as rs1801133 in MTHFR; rs1884052 and rs3778099 in ESR1; rs4988300 in LRP5; rs2189480 in VDR; rs2075555 in COLIA1; rs10519297 and rs2008691 in CYP19, as well as SNPs in PPARG (rs10510418 and rs2938392) and ANKH (rs2454873 and rs379016). All GEE, FBAT and linkage results are provided as an open-access results resource at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007.CONCLUSION:The FHS 100K SNP project offers an unbiased genome-wide strategy to identify new candidate loci and to replicate previously suggested candidate genes for osteoporosis.

Genetic correlates of longevity and selected age-related phenotypes: a genome-wide association study in the Framingham Study

BACKGROUND: Family studies and heritability estimates provide evidence for a genetic contribution to variation in the human life span. METHODS:We conducted a genome wide association study (Affymetrix 100K SNP GeneChip) for longevity-related traits in a community-based sample. We report on 5 longevity and aging traits in up to 1345 Framingham Study participants from 330 families. Multivariable-adjusted residuals were computed using appropriate models (Cox proportional hazards, logistic, or linear regression) and the residuals from these models were used to test for association with qualifying SNPs (70, 987 autosomal SNPs with genotypic call rate [greater than or equal to]80%, minor allele frequency [greater than or equal to]10%, Hardy-Weinberg test p [greater than or equal to] 0.001).RESULTS:In family-based association test (FBAT) models, 8 SNPs in two regions approximately 500 kb apart on chromosome 1 (physical positions 73,091,610 and 73, 527,652) were associated with age at death (p-value < 10-5). The two sets of SNPs were in high linkage disequilibrium (minimum r2 = 0.58). The top 30 SNPs for generalized estimating equation (GEE) tests of association with age at death included rs10507486 (p = 0.0001) and rs4943794 (p = 0.0002), SNPs intronic to FOXO1A, a gene implicated in lifespan extension in animal models. FBAT models identified 7 SNPs and GEE models identified 9 SNPs associated with both age at death and morbidity-free survival at age 65 including rs2374983 near PON1. In the analysis of selected candidate genes, SNP associations (FBAT or GEE p-value < 0.01) were identified for age at death in or near the following genes: FOXO1A, GAPDH, KL, LEPR, PON1, PSEN1, SOD2, and WRN. Top ranked SNP associations in the GEE model for age at natural menopause included rs6910534 (p = 0.00003) near FOXO3a and rs3751591 (p = 0.00006) in CYP19A1. Results of all longevity phenotype-genotype associations for all autosomal SNPs are web posted at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007. CONCLUSION: Longevity and aging traits are associated with SNPs on the Affymetrix 100K GeneChip. None of the associations achieved genome-wide significance. These data generate hypotheses and serve as a resource for replication as more genes and biologic pathways are proposed as contributing to longevity and healthy aging.

Optimized approach to decision fusion of heterogeneous data for breast cancer diagnosis.

As more diagnostic testing options become available to physicians, it becomes more difficult to combine various types of medical information together in order to optimize the overall diagnosis. To improve diagnostic performance, here we introduce an approach to optimize a decision-fusion technique to combine heterogeneous information, such as from different modalities, feature categories, or institutions. For classifier comparison we used two performance metrics: The receiving operator characteristic (ROC) area under the curve [area under the ROC curve (AUC)] and the normalized partial area under the curve (pAUC). This study used four classifiers: Linear discriminant analysis (LDA), artificial neural network (ANN), and two variants of our decision-fusion technique, AUC-optimized (DF-A) and pAUC-optimized (DF-P) decision fusion. We applied each of these classifiers with 100-fold cross-validation to two heterogeneous breast cancer data sets: One of mass lesion features and a much more challenging one of microcalcification lesion features. For the calcification data set, DF-A outperformed the other classifiers in terms of AUC (p < 0.02) and achieved AUC=0.85 +/- 0.01. The DF-P surpassed the other classifiers in terms of pAUC (p < 0.01) and reached pAUC=0.38 +/- 0.02. For the mass data set, DF-A outperformed both the ANN and the LDA (p < 0.04) and achieved AUC=0.94 +/- 0.01. Although for this data set there were no statistically significant differences among the classifiers' pAUC values (pAUC=0.57 +/- 0.07 to 0.67 +/- 0.05, p > 0.10), the DF-P did significantly improve specificity versus the LDA at both 98% and 100% sensitivity (p < 0.04). In conclusion, decision fusion directly optimized clinically significant performance measures, such as AUC and pAUC, and sometimes outperformed two well-known machine-learning techniques when applied to two different breast cancer data sets.