994 resultados para investment models
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Monthly Public Assistance Statistical Report Family Investment Program
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A-1 Monthly Public Assistance Statistical Report Family Investment Program
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The use of cannabis sativa preparations as recreational drugs can be traced back to the earliest civilizations. However, animal models of cannabinoid addiction allowing the exploration of neural correlates of cannabinoid abuse have been developed only recently. We review these models and the role of the CB1 cannabinoid receptor, the main target of natural cannabinoids, and its interaction with opioid and dopamine transmission in reward circuits. Extensive reviews on the molecular basis of cannabinoid action are available elsewhere (Piomelli et al., 2000;Schlicker and Kathmann, 2001).
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Monthly Public Assistance Statistical Report Family Investment Program
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The recent wave of upheavals and revolts in Northern Africa and the Middle East goes back to an old question often raised by theories of collective action: does repression act as a negative or positive incentive for further mobilization? Through a review of the vast literature devoted to this question, this article aims to go beyond theoretical and methodological dead-ends. The article moves on to non-Western settings in order to better understand, via a macro-sociological and dynamic approach, the causal effects between mobilizations and repression. It pleads for a meso- and micro-level approach to this issue: an approach that puts analytical emphasis both on protest organizations and on individual activists' careers.
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Confronting a recently mated female with a strange male can induce a pregnancy block ('Bruce effect'). The physiology of this effect is well studied, but its functional significance is still not fully understood. The 'anticipated infanticide hypothesis' suggests that the pregnancy block serves to avoid the cost of embryogenesis and giving birth to offspring that are likely to be killed by a new territory holder. Some 'compatible-genes sexual selection hypotheses' suggest that the likelihood of a pregnancy block is also dependent on the female's perception of the stud's and the stimulus male's genetic quality. We used two inbred strains of mice (C57BL/6 and BALB/c) to test all possible combinations of female strain, stud strain, and stimulus strain under experimental conditions (N(total) = 241 mated females). As predicted from previous studies, we found increased rates of pregnancy blocks if stud and stimulus strains differed, and we found evidence for hybrid vigour in offspring of between-strain mating. Despite the observed heterosis, pregnancies of within-strain matings were not more likely to be blocked than pregnancies of between-strain matings. A power analysis revealed that if we missed an existing effect (type-II error), the effect must be very small. If a female gave birth, the number and weight of newborns were not significantly influenced by the stimulus males. In conclusion, we found no support for the 'compatible-genes sexual selection hypotheses'.
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Monthly Public Assistance Statistical Report Family Investment Program
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Background: Single nucleotide polymorphisms (SNPs) are the most frequent type of sequence variation between individuals, and represent a promising tool for finding genetic determinants of complex diseases and understanding the differences in drug response. In this regard, it is of particular interest to study the effect of non-synonymous SNPs in the context of biological networks such as cell signalling pathways. UniProt provides curated information about the functional and phenotypic effects of sequence variation, including SNPs, as well as on mutations of protein sequences. However, no strategy has been developed to integrate this information with biological networks, with the ultimate goal of studying the impact of the functional effect of SNPs in the structure and dynamics of biological networks. Results: First, we identified the different challenges posed by the integration of the phenotypic effect of sequence variants and mutations with biological networks. Second, we developed a strategy for the combination of data extracted from public resources, such as UniProt, NCBI dbSNP, Reactome and BioModels. We generated attribute files containing phenotypic and genotypic annotations to the nodes of biological networks, which can be imported into network visualization tools such as Cytoscape. These resources allow the mapping and visualization of mutations and natural variations of human proteins and their phenotypic effect on biological networks (e.g. signalling pathways, protein-protein interaction networks, dynamic models). Finally, an example on the use of the sequence variation data in the dynamics of a network model is presented. Conclusion: In this paper we present a general strategy for the integration of pathway and sequence variation data for visualization, analysis and modelling purposes, including the study of the functional impact of protein sequence variations on the dynamics of signalling pathways. This is of particular interest when the SNP or mutation is known to be associated to disease. We expect that this approach will help in the study of the functional impact of disease-associated SNPs on the behaviour of cell signalling pathways, which ultimately will lead to a better understanding of the mechanisms underlying complex diseases.
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Three-dimensional models of organ biogenesis have recently flourished. They promote a balance between stem/progenitor cell expansion and differentiation without the constraints of flat tissue culture vessels, allowing for autonomous self-organization of cells. Such models allow the formation of miniature organs in a dish and are emerging for the pancreas, starting from embryonic progenitors and adult cells. This review focuses on the currently available systems and how these allow new types of questions to be addressed. We discuss the expected advancements including their potential to study human pancreas development and function as well as to develop diabetes models and therapeutic cells.
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The development of the field-scale Erosion Productivity Impact Calculator (EPIC) model was initiated in 1981 to support assessments of soil erosion impacts on soil productivity for soil, climate, and cropping conditions representative of a broad spectrum of U.S. agricultural production regions. The first major application of EPIC was a national analysis performed in support of the 1985 Resources Conservation Act (RCA) assessment. The model has continuously evolved since that time and has been applied for a wide range of field, regional, and national studies both in the U.S. and in other countries. The range of EPIC applications has also expanded greatly over that time, including studies of (1) surface runoff and leaching estimates of nitrogen and phosphorus losses from fertilizer and manure applications, (2) leaching and runoff from simulated pesticide applications, (3) soil erosion losses from wind erosion, (4) climate change impacts on crop yield and erosion, and (5) soil carbon sequestration assessments. The EPIC acronym now stands for Erosion Policy Impact Climate, to reflect the greater diversity of problems to which the model is currently applied. The Agricultural Policy EXtender (APEX) model is essentially a multi-field version of EPIC that was developed in the late 1990s to address environmental problems associated with livestock and other agricultural production systems on a whole-farm or small watershed basis. The APEX model also continues to evolve and to be utilized for a wide variety of environmental assessments. The historical development for both models will be presented, as well as example applications on several different scales.
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In this work we describe the usage of bilinear statistical models as a means of factoring the shape variability into two components attributed to inter-subject variation and to the intrinsic dynamics of the human heart. We show that it is feasible to reconstruct the shape of the heart at discrete points in the cardiac cycle. Provided we are given a small number of shape instances representing the same heart atdifferent points in the same cycle, we can use the bilinearmodel to establish this. Using a temporal and a spatial alignment step in the preprocessing of the shapes, around half of the reconstruction errors were on the order of the axial image resolution of 2 mm, and over 90% was within 3.5 mm. From this, weconclude that the dynamics were indeed separated from theinter-subject variability in our dataset.
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A-1 Monthly Public Assistance Statistical Report Family Investment Program, June 2005
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A-1 Monthly Public Assistance Statistical Report Family Investment Program, July 2005
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A-1 Monthly Public Assistance Statistical Report Family Investment Program, August 2005