Convolutional network based animal recognition using YOLO and darknet.

In general, the manual detection of animals with their names is a very tedious task. To overcome this challenge, this research work has developed a YOLOV3 model to identify the animal present in the image given by user. The algorithm used in YOLOV3 model is darknet, which has a pre-trained dataset. The overall performance of the model is based on different training images and testing images of the dataset. The main goal of this research work is to build an animal recognition methodology using YOLOV3 model. The image of animal will be given as input, then it will display the name of the animal as output by using YOLOV3 model. The detection is done by using a pre-trained coco dataset from darknet

Stock price prognosticator using machine learning techniques.

Stock market price prediction is one of the favourite research topics under consideration for professionals from various fields like mathematics, statistics, history, finance, computer science engineering etc., as it requires a set of skills to predict variation of price of shares in a very volatile and challenging share market scenario. Share market trading is mostly dependent on sentiments of investors and other factors like economic policies, political changes, natural disasters etc., Many theories were forwarded, mathematical and statistical applications in conjunction with probability, to simplify the complex process. After the advent of computers, it got further simplified but still challenging due to various external influential factors ruling the volatility of the market prices. Thus, AI and ML algorithms were being developed, but for only for next day using Linear Regression procedures.Our project aims to predict the prices of shares more precisely and accurately using special algorithms using RNN by improvising the back propagation, feedback routines to overcome the short-term memory loss involved in RNN thus providing efficiency in LSTM applications.Our project emphasizes how the LSTM applications perform with datasets of extreme, larger and minimal fluctuating data

Types of Social Capital and Mental Disorder in Deprived Urban Areas: A Multilevel Study of 40 Disadvantaged London Neighbourhoods

Objectives To examine the extent to which individual and ecological-level cognitive and structural social capital are associated with common mental disorder (CMD), the role played by physical characteristics of the neighbourhood in moderating this association, and the longitudinal change of the association between ecological level cognitive and structural social capital and CMD. Design Cross-sectional and longitudinal study of 40 disadvantaged London neighbourhoods. We used a contextual measure of the physical characteristics of each neighbourhood to examine how the neighbourhood moderates the association between types of social capital and mental disorder. We analysed the association between ecological-level measures of social capital and CMD longitudinally. Participants 4,214 adults aged 16-97 (44.4% men) were randomly selected from 40 disadvantaged London neighbourhoods. Main Outcome Measures General Health Questionnaire (GHQ-12). Results Structural rather than cognitive social capital was significantly associated with CMD after controlling for socio-demographic variables. However, the two measures of structural social capital used, social networks and civic participation, were negatively and positively associated with CMD respectively. ‘Social networks’ was negatively associated with CMD at both the individual and ecological levels. This result was maintained when contextual aspects of the physical environment (neighbourhood incivilities) were introduced into the model, suggesting that ‘social networks’ was independent from characteristics of the physical environment. When ecological-level longitudinal analysis was conducted, ‘social networks’ was not statistically significant after controlling for individual-level social capital at follow up. Conclusions If we conceptually distinguish between cognitive and structural components as the quality and quantity of social capital respectively, the conclusion of this study is that the quantity rather than quality of social capital is important in relation to CMD at both the individual and ecological levels in disadvantaged urban areas. Thus, policy should support interventions that create and sustain social networks. One of these is explored in this article

Lactate signalling regulates fungal β-glucan masking and immune evasion

AJPB: This work was supported by the European Research Council (STRIFE, ERC- 2009-AdG-249793), The UK Medical Research Council (MR/M026663/1), the UK Biotechnology and Biological Research Council (BB/K017365/1), the Wellcome Trust (080088; 097377). ERB: This work was supported by the UK Biotechnology and Biological Research Council (BB/M014525/1). GMA: Supported by the CNPq-Brazil (Science without Borders fellowship 202976/2014-9). GDB: Wellcome Trust (102705). CAM: This work was supported by the UK Medical Research Council (G0400284). DMM: This work was supported by UK National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC/K000306/1). NARG/JW: Wellcome Trust (086827, 075470,101873) and Wellcome Trust Strategic Award in Medical Mycology and Fungal Immunology (097377). ALL: This work was supported by the MRC Centre for Medical Mycology and the University of Aberdeen (MR/N006364/1).Peer reviewedPostprin

Genetic variation in stromal proteins decorin and lumican with breast cancer: investigations in two case-control studies.

INTRODUCTION: The stroma is the supportive framework of biologic tissue in the breast, consisting of various proteins such as the proteoglycans, decorin and lumican. Altered expression of decorin and lumican is associated with breast tumors. We hypothesized that genetic variation in the decorin (DCN) and lumican (LUM) genes may contribute to breast cancer. METHODS: We investigated associations of 14 common polymorphisms in the DCN and LUM genes with 798 breast cancer cases and 843 controls from Mayo Clinic, MN, USA. One polymorphism per gene with the strongest risk association in the Mayo Clinic sample was genotyped in 4,470 breast cancer cases and 4,560 controls from East Anglia, England (Studies of Epidemiology and Risk Factors in Cancer Heredity (SEARCH)). RESULTS: In the Mayo Clinic sample, six polymorphisms were associated with breast cancer risk (P trend <or= 0.05). The association with LUM rs2268578, evaluated further in SEARCH, was positive, although the odds ratios (OR) were weaker and not statistically significant. ORs were 1.4 (95% confidence interval [CI], 1.1 to 1.8) for heterozygotes and 2.2 (95% CI, 1.1 to 4.3; P2 df = 0.002) for homozygotes in the Mayo Clinic sample, and were 1.1 (95% CI, 0.9 to 1.2) for heterozygotes and 1.4 (95% CI, 1.0 to 2.1; P2 df = 0.13) for homozygotes in the SEARCH sample. In combined analyses, the ORs were 1.1 (95% CI, 1.0 to 1.2) for heterozygotes and 1.6 (95% CI, 1.2 to 2.3; P2 df = 0.005) for homozygotes. Positive associations for this polymorphism were observed for estrogen receptor-positive tumors in both the Mayo Clinic sample (OR for heterozygotes = 1.5, 1.1 to 1.9 and OR for homozygotes = 2.5, 1.2 to 5.3;P2 df = 0.001) and the SEARCH sample (OR for heterozygotes = 1.0, 0.9 to 1.1 and OR for homozygotes = 1.6, 1.0 to 2.5; P2 df = 0.10). In combined analyses, the ORs were 1.1 (95% CI, 0.9 to 1.2) for heterozygotes and 1.9 (95% CI, 1.3 to 2.8; P2 df = 0.001) for homozygotes. CONCLUSIONS: Although LUM rs2268578 was associated with breast cancer in the Mayo Clinic study, particularly estrogen receptor-positive breast cancer, weaker and modest associations were observed in the SEARCH sample. These modest associations will require larger samples to adequately assess the importance of this polymorphism in breast cancer

Mycobacterial F420H2-dependent reductases promiscuously reduce diverse compounds through a common mechanism

An unusual aspect of actinobacterial metabolism is the use of the redox cofactor F420. Studies have shown that actinobacterial F420H2-dependent reductases promiscuously hydrogenate diverse organic compounds in biodegradative and biosynthetic processes. These enzymes therefore represent promising candidates for next-generation industrial biocatalysts. In this work, we undertook the first broad survey of these enzymes as potential industrial biocatalysts by exploring the extent, as well as mechanistic and structural bases, of their substrate promiscuity. We expressed and purified 11 enzymes from seven subgroups of the flavin/deazaflavin oxidoreductase (FDOR) superfamily (A1, A2, A3, B1, B2, B3, B4) from the model soil actinobacterium Mycobacterium smegmatis. These enzymes reduced compounds from six chemical classes, including fundamental monocycles such as a cyclohexenone, a dihydropyran, and pyrones, as well as more complex quinone, coumarin, and arylmethane compounds. Substrate range and reduction rates varied between the enzymes, with the A1, A3, and B1 groups exhibiting greatest promiscuity. Molecular docking studies suggested that structurally diverse compounds are accommodated in the large substrate-binding pocket of the most promiscuous FDOR through hydrophobic interactions with conserved aromatic residues and the isoalloxazine headgroup of F420H2. Liquid chromatography-mass spectrometry (LC/MS) and gas chromatography-mass spectrometry (GC/MS) analysis of derivatized reaction products showed reduction occurred through a common mechanism involving hydride transfer from F420H- to the electron-deficient alkene groups of substrates. Reduction occurs when the hydride donor (C5 of F420H-) is proximal to the acceptor (electrophilic alkene of the substrate). These findings suggest that engineered actinobacterial F420H2-dependent reductases are promising novel biocatalysts for the facile transformation of a wide range of α,β-unsaturated compounds.This work was supported by a CSIRO Office of the Chief Executive Postdoctoral Fellowship and an ARC DECRA DE120102673

Measures of exposure to the Well London Phase-1 intervention and their association with health well-being and social outcomes

In this paper, we describe the measures of intervention exposure used in the cluster randomised trial of the Well London programme, a public health intervention using community engagement and community-based projects to increase physical activity, healthy eating and mental health and well-being in 20 of the most deprived neighbourhoods in London.10 No earmarked resources to support the development of these measures and associated data collection were provided to either the research team or to those delivering the interventions on the ground. Instead, these were derived from contractually specified performance management information reported quarterly by partners and by inclusion of questions seeking information about participation in the follow-up questionnaires used to measure the main trial outcomes. The exposure measures are consequently considerably less sophisticated than those used in the US studies, where earmarked funding was available

Fine-mapping of the HNF1B multicancer locus identifies candidate variants that mediate endometrial cancer risk.

Common variants in the hepatocyte nuclear factor 1 homeobox B (HNF1B) gene are associated with the risk of Type II diabetes and multiple cancers. Evidence to date indicates that cancer risk may be mediated via genetic or epigenetic effects on HNF1B gene expression. We previously found single-nucleotide polymorphisms (SNPs) at the HNF1B locus to be associated with endometrial cancer, and now report extensive fine-mapping and in silico and laboratory analyses of this locus. Analysis of 1184 genotyped and imputed SNPs in 6608 Caucasian cases and 37 925 controls, and 895 Asian cases and 1968 controls, revealed the best signal of association for SNP rs11263763 (P = 8.4 × 10(-14), odds ratio = 0.86, 95% confidence interval = 0.82-0.89), located within HNF1B intron 1. Haplotype analysis and conditional analyses provide no evidence of further independent endometrial cancer risk variants at this locus. SNP rs11263763 genotype was associated with HNF1B mRNA expression but not with HNF1B methylation in endometrial tumor samples from The Cancer Genome Atlas. Genetic analyses prioritized rs11263763 and four other SNPs in high-to-moderate linkage disequilibrium as the most likely causal SNPs. Three of these SNPs map to the extended HNF1B promoter based on chromatin marks extending from the minimal promoter region. Reporter assays demonstrated that this extended region reduces activity in combination with the minimal HNF1B promoter, and that the minor alleles of rs11263763 or rs8064454 are associated with decreased HNF1B promoter activity. Our findings provide evidence for a single signal associated with endometrial cancer risk at the HNF1B locus, and that risk is likely mediated via altered HNF1B gene expression