Cotton Statistics for Texas.

68 p

Approaching human 3D shape perception with neurally mappable models

Humans effortlessly infer the 3D shape of objects. What computations underlie this ability? Although various computational models have been proposed, none of them capture the human ability to match object shape across viewpoints. Here, we ask whether and how this gap might be closed. We begin with a relatively novel class of computational models, 3D neural fields, which encapsulate the basic principles of classic analysis-by-synthesis in a deep neural network (DNN). First, we find that a 3D Light Field Network (3D-LFN) supports 3D matching judgments well aligned to humans for within-category comparisons, adversarially-defined comparisons that accentuate the 3D failure cases of standard DNN models, and adversarially-defined comparisons for algorithmically generated shapes with no category structure. We then investigate the source of the 3D-LFN's ability to achieve human-aligned performance through a series of computational experiments. Exposure to multiple viewpoints of objects during training and a multi-view learning objective are the primary factors behind model-human alignment; even conventional DNN architectures come much closer to human behavior when trained with multi-view objectives. Finally, we find that while the models trained with multi-view learning objectives are able to partially generalize to new object categories, they fall short of human alignment. This work provides a foundation for understanding human shape inferences within neurally mappable computational architectures and highlights important questions for future work

Information Basic to Farm Adjustments in the Rolling Plains Area of Texas.

108 p

Planning the Ranch for Greater Profit: A Study of Physical and Economic Factors Affecting Organization and Management of Ranches in the Edwards Plateau Grazing Area.

45 p

Conceptualising the technical relationship of animal disease surveillance to intervention and mitigation as a basis for economic analysis

<p>Abstract</p> <p>Background</p> <p>Surveillance and intervention are resource-using activities of strategies to mitigate the unwanted effects of disease. Resources are scarce, and allocating them to disease mitigation instead of other uses necessarily involves the loss of alternative sources of benefit to people. For society to obtain the maximum benefits from using resources, the gains from disease mitigation must be compared to the resource costs, guiding decisions made with the objective of achieving the optimal net outcome.</p> <p>Discussion</p> <p>Economics provides criteria to guide decisions aimed at optimising the net benefits from the use of scarce resources. Assessing the benefits of disease mitigation is no exception. However, the technical complexity of mitigation means that economic evaluation is not straightforward because of the technical relationship of surveillance to intervention. We argue that analysis of the magnitudes and distribution of benefits and costs for any given strategy, and hence the outcome in net terms, requires that mitigation is considered in three conceptually distinct stages. In Stage I, 'sustainment', the mitigation objective is to sustain a free or acceptable status by preventing an increase of a pathogen or eliminating it when it occurs. The role of surveillance is to document that the pathogen remains below a defined threshold, giving early warning of an increase in incidence or other significant changes in risk, and enabling early response. If a pathogen is not contained, the situation needs to be assessed as Stage II, 'investigation'. Here, surveillance obtains critical epidemiological information to decide on the appropriate intervention strategy to reduce or eradicate a disease in Stage III, 'implementation'. Stage III surveillance informs the choice, timing, and scale of interventions and documents the progress of interventions directed at prevalence reduction in the population.</p> <p>Summary</p> <p>This article originates from a research project to develop a conceptual framework and practical tool for the economic evaluation of surveillance. Exploring the technical relationship between mitigation as a source of economic value and surveillance and intervention as sources of economic cost is crucial. A framework linking the key technical relationships is proposed. Three conceptually distinct stages of mitigation are identified. Avian influenza, salmonella, and foot and mouth disease are presented to illustrate the framework.</p

Mutations in ELAC2 associated with hypertrophic cardiomyopathy impair mitochondrial tRNA 3&apos;-end processing

Mutations in either the mitochondrial or nuclear genomes are associated with a diverse group of human disorders characterized by impaired mitochondrial respiration. Within this group, an increasing number of mutations have been identified in nuclear genes involved in mitochondrial RNA metabolism, including ELAC2. The ELAC2 gene codes for the mitochondrial RNase Z, responsible for endonucleolytic cleavage of the 3' ends of mitochondrial pre-tRNAs. Here, we report the identification of sixteen novel ELAC2 variants in individuals presenting with mitochondrial respiratory chain deficiency, hypertrophic cardiomyopathy and lactic acidosis. We provide evidence for the pathogenicity of the novel missense variants by studying the RNase Z activity in an in vitro system. We also modelled the residues affected by missense mutation in solved RNase Z structures, providing insight into enzyme structure and function. Finally, we show that primary fibroblasts from the affected individuals have elevated levels of unprocessed mitochondrial RNA precursors. Our study thus broadly confirms the correlation of ELAC2 variants with severe infantile-onset forms of hypertrophic cardiomyopathy and mitochondrial respiratory chain dysfunction. One rare missense variant associated with the occurrence of prostate cancer (p.Arg781His) impairs the mitochondrial RNase Z activity of ELAC2, suggesting a functional link between tumorigenesis and mitochondrial RNA metabolism

Common ataxia telangiectasia mutated haplotypes and risk of breast cancer: a nested case–control study

INTRODUCTION: The ataxia telangiectasia mutated (ATM) gene is a tumor suppressor gene with functions in cell cycle arrest, apoptosis, and repair of DNA double-strand breaks. Based on family studies, women heterozygous for mutations in the ATM gene are reported to have a fourfold to fivefold increased risk of breast cancer compared with noncarriers of the mutations, although not all studies have confirmed this association. Haplotype analysis has been suggested as an efficient method for investigating the role of common variation in the ATM gene and breast cancer. Five biallelic haplotype tagging single nucleotide polymorphisms are estimated to capture 99% of the haplotype diversity in Caucasian populations. METHODS: We conducted a nested case–control study of breast cancer within the Nurses' Health Study cohort to address the role of common ATM haplotypes and breast cancer. Cases and controls were genotyped for five haplotype tagging single nucleotide polymorphisms. Haplotypes were predicted for 1309 cases and 1761 controls for which genotype information was available. RESULTS: Six unique haplotypes were predicted in this study, five of which occur at a frequency of 5% or greater. The overall distribution of haplotypes was not significantly different between cases and controls (χ(2 )= 3.43, five degrees of freedom, P = 0.63). CONCLUSION: There was no evidence that common haplotypes of ATM are associated with breast cancer risk. Extensive single nucleotide polymorphism detection using the entire genomic sequence of ATM will be necessary to rule out less common variation in ATM and sporadic breast cancer risk

Neuromatch Academy: Teaching Computational Neuroscience with Global Accessibility

Neuromatch Academy (NMA) designed and ran a fully online 3-week Computational Neuroscience Summer School for 1757 students with 191 teaching assistants (TAs) working in virtual inverted (or flipped) classrooms and on small group projects. Fourteen languages, active community management, and low cost allowed for an unprecedented level of inclusivity and universal accessibility

Fatigue behaviour of SiC p -reinforced aluminium composites in the very high cycle regime using ultrasonic fatigue

The fatigue behaviour of a 2009/SiC/15p-T4 DRA composite has been examined in the very high cycle fatigue (VHCF) regime where 10 7 ≤ N f ≤ 10 9 cycles. Ultrasonic fatigue was used to achieve the very high cycle counts. Careful processing yielded a composite with a very homogeneous particle distribution with minimal clustering. Fatigue crack initiation was observed almost exclusively at AlCuFe inclusions with no crack initiation observed at SiC particle clusters. Fatigue lives at a given stress level exhibited minimal scatter and subsurface crack initiation was observed in all cases. This behaviour is consistent with the presence of a low number density of critical inclusions that are responsible for crack initiation very early in fatigue life.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73177/1/j.1460-2695.2006.00998.x.pd