Farm diversification strategies, dietary diversity and farm size: results from a cross-country sample in South and Southeast Asia

South and Southeast Asia host almost half of the world's undernourished people. Food and agricultural systems in these regions are highly dependent on the production and consumption of staple cereals such as rice, maize and wheat. More diverse farming systems can potentially improve rural people's nutrition, while reducing the environmental impact of agriculture. Yet, it remains uncertain whether farm diversification is always the most suitable and viable strategy for all types of smallholder farms. We use generalised linear regression models to analyse the farm diversification strategies of 4772 rural households in Cambodia, India, Lao PDR and Vietnam. Our analysis is twofold and focuses first on drivers of farm diversification, and second, on the impacts of farm diversification and other livelihood strategies on dietary diversity. We find that (1) farm diversification is significantly influenced by environmental and climate variables, including rainfall patterns, as well as household and farm characteristics such as farm size and education level; and (2) farm diversification, market orientation and off-farm income generation are all strategies that can improve household and individual dietary diversity. However, their relative effects resulted influenced by farm size. Specifically, the positive effect of farm diversification on dietary diversity was larger for smaller farms, while it decreased for farms of larger size that may improve their diet more by increasing their engagement in off-farm activities and markets. These findings highlight that characteristics such as farm size can represent substantial determinants in production and consumption decisions, suggesting the importance of understanding and considering the type of farm and the situational context of analysis when targeting interventions for improving smallholder farm livelihoods

Meta-Profiles of Gene Expression during Aging: Limited Similarities between Mouse and Human and an Unexpectedly Decreased Inflammatory Signature

Background: Skin aging is associated with intrinsic processes that compromise the structure of the extracellular matrix while promoting loss of functional and regenerative capacity. These processes are accompanied by a large-scale shift in gene expression, but underlying mechanisms are not understood and conservation of these mechanisms between humans and mice is uncertain. Results: We used genome-wide expression profiling to investigate the aging skin transcriptome. In humans, age-related shifts in gene expression were sex-specific. In females, aging increased expression of transcripts associated with T-cells, B-cells and dendritic cells, and decreased expression of genes in regions with elevated Zeb1, AP-2 and YY1 motif density. In males, however, these effects were contrasting or absent. When age-associated gene expression patterns in human skin were compared to those in tail skin from CB6F1 mice, overall human-mouse correspondence was weak. Moreover, inflammatory gene expression patterns were not induced with aging of mouse tail skin, and well-known aging biomarkers were in fact decreased (e.g., Clec7a, Lyz1 and Lyz2). These unexpected patterns and weak human-mouse correspondence may be due to decreased abundance of antigen presenting cells in mouse tail skin with age. Conclusions: Aging is generally associated with a pro-inflammatory state, but we have identified an exception to this pattern with aging of CB6F1 mouse tail skin. Aging therefore does not uniformly heighten inflammatory status across all mouse tissues. Furthermore, we identified both intercellular and intracellular mechanisms of transcriptome aging, including those that are sex- and species-specific

Les progrès dans la réalisation de la classification quantitative de la psychopathologie

Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad "spectrum level'' dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the "problem of comorbidity'' by explicitly modeling patterns of co-occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach. (C) 2020 Published by Elsevier Masson SAS

Inference problems based on non-central distributions / by William N. Venables.

Includes bibliographical referencesvii, 146 leaves ; 30 cm.Thesis (Ph.D.)--University of Adelaide, Dept. of Statistics, 197