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Представлены результаты процесса спорадического формирования китайской диаспоры на Дальнем Востоке России. Выявлены наиболее дискуссионные элементы данного процесса: сложность определения значения понятия «китайская диаспора» и даты зарождения самой диаспоры в указанном регионе; дискуссия относительно численности китайского населения на Дальнем Востоке на рубежах XIX–XX и XX–XXI вв. Автором проведен кластерный анализ регионов Дальнего Востока России на предмет функционирования там китайской диаспоры с использованием данных относительно их площади, численности населения, величины ВРП на душу населения и количества убийств на 100 тыс. чел. Каждый из этих показателей характеризует ключевые сферы развития регионов Дальнего Востока России. По результатам построения кластерного дерева, выделения трех групп субрегионов Дальнего Востока и проведения картографического районирования региона было выявлено, что географическая близость указанных субрегионов к китайской территории значительно сильнее влияет на формирование китайской диаспоры, чем экономический фактор. Отдельно при этом можно выделить Якутию, которая концентрирует 42 % представителей китайской диаспоры Дальнего Востока.

Self-concept and self-efficacy are important constructs in educational psychology. They have frequently been the object of research in the past, mostly, however, in separate studies. Thus, little is known about their juxtaposition and incremental validity they possess for predicting academic performance. This study sheds light on the interdependence of three subject-related academic self-concepts and three corresponding subject-related self-efficacies as well as on their predictive power of the respective scholastic achievements (grades in the subjects English, History, Mathematics). The sample comprised N = 825 Chinese middle-school students (M = 14.46 years, SD = 0.79). All variables were measured on the same level of generality. Confirmatory factor analyses (CFA) revealed two "self"-factors (self-concept, self-efficacy) within each school subject and three subject-specific factors (English, History, Mathematics) within each "self"-construct. Pooled CFA confirmed six dimensions: three subject-related academic self-concept factors and three subject-related academic self-efficacy factors. Less differentiated models did not fit well. Multiple regression analyses and commonality analyses revealed that the subject-specific academic self-concepts scales were more powerful statistical predictors of scholastic achievements than the subject-specific academic self-efficacy scales. The common (indivisible) explained variances amounted to 29.9% (English), 17.0% (History), and 31.5% (Mathematics). The unique parts of the achievement variances exclusively explained by the self-concept scales versus the self-efficacy scales amounted to 5.3% vs. 3.4% (English), 8.0% vs. 0.4% (History), and 8.1% vs. 1.8% (Mathematics). The discussion underpins that academic self-concepts and academic self-efficacies are correlated, albeit different constructs. The relevance of school subjects for the distinctiveness, measurement, and validity of academic "self"-constructs is stressed. [ABSTRACT FROM AUTHOR]

Abstract Selective DNA pooling is an efficient method to identify chromosomal regions that harbor quantitative trait loci (QTL) by comparing marker allele frequencies in pooled DNA from phenotypically extreme individuals. Currently used single marker analysis methods can detect linkage of markers to a QTL but do not provide separate estimates of QTL position and effect, nor do they utilize the joint information from multiple markers. In this study, two interval mapping methods for analysis of selective DNA pooling data were developed and evaluated. One was based on least squares regression (LS-pool) and the other on approximate maximum likelihood (ML-pool). Both methods simultaneously utilize information from multiple markers and multiple families and can be applied to different family structures (half-sib, F2 cross and backcross). The results from these two interval mapping methods were compared with results from single marker analysis by simulation. The results indicate that both LS-pool and ML-pool provided greater power to detect the QTL than single marker analysis. They also provide separate estimates of QTL location and effect. With large family sizes, both LS-pool and ML-pool provided similar power and estimates of QTL location and effect as selective genotyping. With small family sizes, however, the LS-pool method resulted in severely biased estimates of QTL location for distal QTL but this bias was reduced with the ML-pool.