Morphological variability between wild populations and inbred stocks of a Chinese minnow, Gobiocypris rarus

Gobiocypris rarus, a small, native cyprinid fish, is currently widely used in research on fish pathology, genetics, toxicology, embryology, and physiology in China. To develop this species as a model laboratory animal, inbred strains have been successfully created. In this study, to explore a method to discriminate inbred strains and evaluate inbreeding effects, morphological variation among three wild populations and three inbred stocks of G. rarus was investigated by the multivariate analysis of eight meristic and 30 morphometric characters. Tiny intraspecific variations in meristic characters were found, but these were not effective for population distinction. Stepwise discriminant analysis and cluster analysis of conventional measures and truss network data showed considerabe divergence among populations, especially between wild populations and inbred stocks. The average discriminant accuracy for all populations was 82.1% based on conventional measures and 86.4% based on truss data, whereas the discriminant accuracy for inbred strains was much higher. These results suggested that multivariate analyses of morphometric characters are an effective method for discriminating inbred strains of G. rarus. Morphological differences between wild populations and inbred strains appear to result from both genetic differences and environmental factors. Thirteen characters, extracted from stepwise discriminant analysis, played important roles in morphological differentiation. These characters were mainly measures related to body depth and head size.

一种宏观网络数据挖掘网格系统

研究宏观网络安全数据挖掘系统的目的是保护大型网络中关键网络基础设施的可用性、机密性和完整性。为此,首先提出了一种宏观网络数据挖掘的系统框架;然后分析了宏观网络挖掘子系统和态势分析子系统;最后利用网格计算技术实现了该平台,并给出了其运行环境。该系统具有可扩展性,能有效进行宏观网络的数据挖掘和实时势态感知.

同事关系质量及其作用机制

Although the research into coworker relationship quality has been recognized one of key factors related to organization performance, and has been thought a new trend in organization behavior research with the flatting of organization structure and complication of task assignment, there is relatively little empirical research on the mechanism between coworkers’ interaction, contraring to the fruitful results on member exchange research based on social network theory, say nothing of the influence of cultural differences such as GUANXI. This research developed the scale for the assessment of Coworker Relationship Quality by literature review, deep interview, and questionnaires, compared the predictable ability of Coworker Relationship Quality (CRQ) scale and Coworker Exchange (CWX) scale on employees’ work attitudes and behaviors. Finally, the mediating effect of Coworker Relationship Quality between employees’ similarities on personality and their work attitudes and behaviors was investigated. Following are main results. Firstly, we found that the interpersonal communication, trust, and mutual support are the key factors of coworker relationship quality, which is similar to the result getting from western samples. But Chinese people are more GUANXI ORIENTATION, means they want to build longtime relationship with others, not only when they are coworkers, but also when one of them left the organization. Secondly, though the core meaning of CRQ and CWX are same, their predictable ability on organization outcomes is different. CRQ is more powerful than CWX, especially on turnover intention. The result showed that after controlling the effect of demographic variables and CRQ, CWX cannot predict turnover intention significantly, but CRQ can still predict turnover intention significantly after controlling demographic variables and CWX. Thirdly, the partial mediating effect of CRQ between positive affectivity similarity and organizational citizenship behavior, coworker satisfaction, organizational commitment and turnover intention are validated, but we did not find the mediating effect of CRQ between demographic variable similarity and workers’ attitudes and behaviors. The Similarity Attraction Paradigm, Social Identity Theory, and Self Category Theory were supported.

社会形势预警的几种建模方法比较

Based on social survey data conducted by local research group in some counties executed in the nearly past five years in China, the author proposed and solved two kernel problems in the field of social situation forecasting: i) How can the attitudes’ data on individual level be integrated with social situation data on macrolevel; ii) How can the powers of forecasting models’ constructed by different statistic methods be compared? Five integrative statistics were applied to the research: 1) algorithm average (MEAN); 2) standard deviation (SD); 3) coefficient variability (CV); 4) mixed secondary moment (M2); 5) Tendency (TD). To solve the former problem, the five statistics were taken to synthesize the individual and mocrolevel data of social situations on the levels of counties’ regions, and form novel integrative datasets, from the basis of which, the latter problem was accomplished by the author: modeling methods such as Multiple Regression Analysis (MRA), Discriminant Analysis (DA) and Support Vector Machine (SVM) were used to construct several forecasting models. Meanwhile, on the dimensions of stepwise vs. enter, short-term vs. long-term forecasting and different integrative (statistic) models, meta-analysis and power analysis were taken to compare the predicting power of each model within and among modeling methods. Finally, it can be concluded from the research of the dissertation: 1) Exactly significant difference exists among different integrative (statistic) models, in which, tendency (TD) integrative models have the highest power, but coefficient variability (CV) ones have the lowest; 2) There is no significant difference of the power between stepwise and enter models as well as short-term and long-term forecasting models; 3) There is significant difference among models constructed by different methods, of which, support vector machine (SVM) has the highest statistic power. This research founded basis in all facets for exploring the optimal forecasting models of social situation’s more deeply, further more, it is the first time methods of meta-analysis and power analysis were immersed into the assessments of such forecasting models.