Artificial Neural Network Model for Low Strength RC Beam Shear Capacity

This research was to investigate how the shear strength prediction of low strength reinforced concrete beams will improve under an ANN model. An existing database of 310 reinforced concrete beams without web reinforcement was divided into three sets of training, validation and testing. A total of 224 different architectural networks were tried, considering networks with one hidden layer as well as two hidden layers. Error measures of strength ratios were used to select the best ANN model which was then compared with 3 conventional design code equations in predicting the shear strength of 26 low strength RC beams. Even though the ANN was the most accurate, it was less conservative compared with the design code equations. A model reduction factor based on the characteristic strength concept is derived in this research and used to modify the ANN output. The modified ANN model is conservative in terms of safety and economy but not overly conservative as the conventional design equations. The procedure has been automated such that when new experimental sets are added to the database, the model can be updated and a new model could be developed

Maternal and Infant Lipid-Based Nutritional Supplementation Increases Height of Ghanaian Children at 4–6 Years Only if the Mother Was Not Overweight Before Conception

Background Few studies have evaluated the long-term effects of nutritional supplementation during the first 1000 d of life. We previously reported that maternal and child lipid-based nutrient supplements (LNS) increased child length by 18 mo. Objective The aim of this study was to examine the effects of LNS on later growth and body composition at 4–6 y of age. Design This was a follow-up of children in the International Lipid-based Nutrient Supplements (iLiNS)-DYAD trial in Ghana. Women (n = 1320) at ≤20 weeks of gestation were randomly assigned to: 1) iron and folic acid during pregnancy and 200 mg calcium/d for 6 mo postpartum, 2) multiple micronutrients (1–2 RDA of 18 vitamins and minerals) during both periods, or 3) maternal LNS during both periods plus child LNS from 6 to 18 mo. At 4–6 y, we compared height, height-for-age z score (HAZ), and % body fat (deuterium dilution method) between the LNS group and the 2 non-LNS groups combined. Results Data were available for 961 children (76.5% of live births). There were no significant differences between LNS compared with non-LNS groups in height [106.7 compared with 106.3 cm (mean difference, MD, 0.36; P = 0.226)], HAZ [−0.49 compared with −0.57 (MD = 0.08; P = 0.226)], stunting (\u3c -2 SD) [6.5 compared with 6.3% (OR = 1.00; P = 0.993)], or % body fat [15.5 compared with 15.3% (MD = 0.16; P = 0.630)]. However, there was an interaction with maternal prepregnancy BMI (kg/m2) (P-interaction = 0.046 before correction for multiple testing): among children of women with BMI \u3c 25 , LNS children were taller than non-LNS children (+1.1 cm, P = 0.017), whereas there was no difference among children of women with BMI ≥ 25 (+0.1 cm; P = 0.874). Conclusions There was no overall effect of LNS on height at 4–6 y in this cohort, which had a low stunting rate, but height was greater in the LNS group among children of nonoverweight/obese women. There was no adverse impact of LNS on body composition. This trial was registered at clinicaltrials.gov as NCT00970866

Biophysics of Lower Back Pain

Lower back pain is one of the most predominant problems in the general public. It has been traditionally regarded as a mechanical problem by both orthodox and complementary practitioners. This study was conducted to evaluate the lumbosacral angle which is an inherent cause of lower back pain and also investigate the shearing and compressing forces on the lumbar spine. The study was carried out at in a Hospital within the …. Metropolis. A total of 210 patients’ data consisting of 72 males and 138 females was considered. The lumbosacral angle was measured using Ferguson’s method with the MicroDicom software. Patients were grouped into ages; 0 – 20, 21 – 30, 31 – 40, 41 – 50, 51 – 60, 61 – 70, 71 – 80 and 81 – 100. The number of patients in each age group was; 7, 12, 26, 28, 56, 27, 11 and 7 respectively. The average lumbosacral angle evaluated, according to age group was; 36.3º, 39º, 35.81º, 36.23º, 36.55º, 37.5º, 35.89 º and 34.92º. The overall lumbosacral mean was determined to be 36.50º. The lumbosacral angle evaluated was used to determine the corresponding compressive and shear forces at the lumbar region which are the principal predictors of the lower back pain

A Genome Wide Association Study of arabinoxylan content in 2-row spring barley grain

In barley endosperm arabinoxylan (AX) is the second most abundant cell wall polysaccharide and in wheat it is the most abundant polysaccharide in the starchy endosperm walls of the grain. AX is one of the main contributors to grain dietary fibre content providing several health benefits including cholesterol and glucose lowering effects, and antioxidant activities. Due to its complex structural features, AX might also affect the downstream applications of barley grain in malting and brewing. Using a high pressure liquid chromatography (HPLC) method we quantified AX amounts in mature grain in 128 spring 2-row barley accessions. Amounts ranged from ~ 5.2 μg/g to ~ 9 μg/g. We used this data for a Genome Wide Association Study (GWAS) that revealed three significant quantitative trait loci (QTL) associated with grain AX levels which passed a false discovery threshold (FDR) and are located on two of the seven barley chromosomes. Regions underlying the QTLs were scanned for genes likely to be involved in AX biosynthesis or turnover, and strong candidates, including glycosyltransferases from the GT43 and GT61 families and glycoside hydrolases from the GH10 family, were identified. Phylogenetic trees of selected gene families were built based on protein translations and were used to examine the relationship of the barley candidate genes to those in other species. Our data reaffirms the roles of existing genes thought to contribute to AX content, and identifies novel QTL (and candidate genes associated with them) potentially influencing the AX content of barley grain. One potential outcome of this work is the deployment of highly associated single nucleotide polymorphisms markers in breeding programs to guide the modification of AX abundance in barley grain

ICOSL+ plasmacytoid dendritic cells as inducer of graft-versus-host disease, responsive to a dual ICOS/CD28 antagonist

Acute graft-versus-host disease (aGVHD) remains a major complication of allogeneic hematopoietic cell transplantation (HCT). CD146 and CCR5 are proteins that mark activated T helper 17 (Th17) cells. The Th17 cell phenotype is promoted by the interaction of the receptor ICOS on T cells with ICOS ligand (ICOSL) on dendritic cells (DCs). We performed multiparametric flow cytometry in a cohort of 156 HCT recipients and conducted experiments with aGVHD murine models to understand the role of ICOSL+ DCs. We observed an increased frequency of ICOSL+ plasmacytoid DCs, correlating with CD146+CCR5+ T cell frequencies, in the 64 HCT recipients with gastrointestinal aGVHD. In murine models, donor bone marrow cells from ICOSL-deficient mice compared to those from wild-type mice reduced aGVHD-related mortality. Reduced aGVHD resulted from lower intestinal infiltration of pDCs and pathogenic Th17 cells. We transplanted activated human ICOSL+ pDCs along with human peripheral blood mononuclear cells into immunocompromised mice and observed infiltration of intestinal CD146+CCR5+ T cells. We found that prophylactic administration of a dual human ICOS/CD28 antagonist (ALPN-101) prevented aGVHD in this model better than did the clinically approved belatacept (CTLA-4-Fc), which binds CD80 (B7-1) and CD86 (B7-2) and interferes with the CD28 T cell costimulatory pathway. When started at onset of aGVHD signs, ALPN-101 treatment alleviated symptoms of ongoing aGVHD and improved survival while preserving antitumoral cytotoxicity. Our data identified ICOSL+-pDCs as an aGVHD biomarker and suggest that coinhibition of the ICOSL/ICOS and B7/CD28 axes with one biologic drug may represent a therapeutic opportunity to prevent or treat aGVHD

Renewable, ethical? Assessing the energy justice potential of renewable electricity

Energy justice is increasingly being used as a framework to conceptualize the impacts of energy decision making in more holistic ways and to consider the social implications in terms of existing ethical values. Similarly, renewable energy technologies are increasingly being promoted for their environmental and social benefits. However, little work has been done to systematically examine the extent to which, in what ways and in what contexts, renewable energy technologies can contribute to achieving energy justice. This paper assesses the potential of renewable electricity technologies to address energy justice in various global contexts via a systematic review of existing studies analyzed in terms of the principles and dimensions of energy justice. Based on publications including peer reviewed academic literature, books, and in some cases reports by government or international organizations, we assess renewable electricity technologies in both grid integrated and off-grid use contexts. We conduct our investigation through the rubric of the affirmative and prohibitive principles of energy justice and in terms of its temporal, geographic, socio-political, economic, and technological dimensions. Renewable electricity technology development has and continue to have different impacts in different social contexts, and by considering the different impacts explicitly across global contexts, including differences between rural and urban contexts, this paper contributes to identifying and understanding how, in what ways, and in what particular conditions and circumstances renewable electricity technologies may correspond with or work to promote energy justice

Evaluation of deep learning models for classification of asphalt pavement distresses

Transfer learning (TL) offers a convenient methodology for exploiting the capability of deep convolutional neural networks (DCNNs) for many image classification tasks including the classification of pavement distresses. Seven state-of-the-art DCNNs were retrained to classify asphalt pavement distresses grouped into eight classes using TL techniques. The aim was to evaluate the predictive performances of the selected DCNNs in order to provide some guidelines on selection of DCNNs for pavement application. The results show some existing DCNN’s are better than others for developing pavement distress classification models using the specific TL approach adopted in the study. The predictive ability of each model varied depending on distress class as some models with very low overall accuracy showed excellent results for individual distress class(s). Based on a combination of various performance metrics including F1-score, area under ROC curve, optimal operating threshold, training time, and model size, the best performing network had a relative score that was found to be significantly higher than the next two top-performing models. The best-performing networks were characterised by lower proportions of false negative values, low ambiguity scores, and well-defined t-SNE clusters that showed clear separation between the eight different pavement distress classes considered