Displacement Based Design of Retaining Walls

A relatively simple rigid plastic model to study deformation behavior of rigid retaining wall is outlined. Both sliding and tilting modes of deformation are included. The study clearly reveals that wall movement caused by tilting can be substantial. But for high values of foundation soil friction angle, the tilting component of deformation can be omitted. Since the wall movement is affected by the characteristics (strength and frequency) of the excitation history, a number of excitation histories should be considered in retaining wall designs

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Variations in killer-cell immunoglobulin-like receptor and human leukocyte antigen genes and immunity to malaria

Malaria is one of the deadliest infectious diseases in the world. Immune responses to Plasmodium falciparum malaria vary among individuals and between populations. Human genetic variation in immune system genes is likely to play a role in this heterogeneity. Natural killer (NK) cells produce inflammatory cytokines in response to malaria infection, kill intraerythrocytic Plasmodium falciparum parasites by cytolysis, and participate in the initiation and development of adaptive immune responses to plasmodial infection. These functions are modulated by interactions between killer-cell immunoglobulin-like receptors (KIR) and human leukocyte antigens (HLA). Therefore, variations in KIR and HLA genes can have a direct impact on NK cell functions. Understanding the role of KIR and HLA in immunity to malaria can help to better characterize antimalarial immune responses. In this review, we summarize the different KIR and HLA so far associated with immunity to malaria.This work was supported through the DELTAS Africa Initiative (Grant no. 107743), that funded Stephen Tukwasibwe through PhD fellowship award, and Annettee Nakimuli through group leader award. The DELTAS Africa Initiative is an independent funding scheme of the African Academy of Science (AAS), Alliance for Accelerating Excellence in Science in Africa (AESA) and supported by the New Partnership for Africa’s Development Planning and Coordinating Agency (NEPAD Agency) with funding from the Wellcome Trust (Grant no. 107743) and the UK government. Francesco Colucci is funded by Wellcome Trust grant 200841/Z/16/Z. The project received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement No. 695551) for James Traherne and John Trowsdale. Jyothi Jayaraman is a recipient of fellowship from the Centre for Trophoblast Research

Symbolic agglomerative clustering for quantitative analysis of remotely sensed data

An efficient nonparametric, hierarchical, symbolic agglomerative clustering procedure based on the mutual nearest neighbourhood concept is proposed for classifying remotely sensed multispectral data. The procedure utilized a data reduction technique and an innovative symbolic concept to minimize the memory and computational time requirements. A new non-metric similarity measure and a novel method of formulation of composite symbolic objects are proposed to enrich the performance of the algorithm. A Mean Difference Index ( MDI) concept for identifying the optimal number of classes was used. Experiments were conducted on IRS (Indian Remote Sensing) satellite data to authenticate the efficacy of the procedure

Detection of genetically modified soya and maize: impact of heat processing

The analysis of processed foods entails a number of complications, which negatively affect the performance of DNA based detection methods. Heat-processing methods viz. autoclaving and micro-waving, that mimic processing and manufacturing, as model unit operation systems were used to study their effect on the detection of genetically modified organisms (GMOs). This study confirms the premise that high temperature and/or pressure significantly reduce the level of detectable DNA. PCR methods were developed and adapted to target varying amplicon sizes of the trait, construct and event specific gene sequences that occur in MON-810 maize and Roundup Ready® soybean. Integrity of DNA, recovery and PCR amplicon size (<200 bp) are major factors that direct the successful detection of GMOs in processed foods. The model systems used provide a platform to devise better strategies in developing detection protocols, especially for processed foods containing GMOs

Crystal structure of <i>N</i>[(2'-hydroxy)benzylidene]-3-chloro-4-fluoroaniline

2428-2431<span style="font-size:12.0pt;line-height:115%; font-family:" times="" new="" roman";mso-fareast-font-family:"times="" roman";="" mso-ansi-language:en-in;mso-fareast-language:en-in;mso-bidi-language:hi"="">The crystal structure of N[(2'-hydroxy)benzylidene]-3-chloro-4-fluoroaniline has been de termined by X-ray methods. The compound crystallizes under monoclinic system with cell parameters a = 3.878(2)Å, b = 10.809(1)Å, c = 26.262(2)Å and β= <span style="font-size:12.0pt;line-height: 115%;font-family:" times="" new="" roman";mso-fareast-font-family:"times="" roman";="" mso-ansi-language:en-in;mso-fareast-language:en-in;mso-bidi-language:hi"="">94.17(7)o. The entire molecule is planar. The torsional angle of C1-N-C7-C1' is 178° which indicates an anti periplanar arrangement. In view of the importance of weak interactions like Cl....Cl, H....Cl and F... H stabilizing the crystal structure it is pertinent to note some of such observations during the present study.</span

A review on laboratory liver function tests

Laboratory liver tests are broadly defined as tests useful in the evaluation and treatment of patients with hepatic dysfunction. The liver carries out metabolism of carbohydrate, protein and fats. Some of the enzymes and the end products of the metabolic pathway which are very sensitive for the abnormality occurred may be considered as biochemical marker of liver dysfunction. Some of the biochemical markers such as serum bilirubin, alanine amino transferase, aspartate amino transferase, ratio of aminotransferases, alkaline phosphatase, gamma glutamyl transferase, 5 ’ nucleotidase, ceruloplasmin, α-fetoprotein are considered in this article. An isolated or conjugated alteration of biochemical markers of liver damage in patients can challenge the clinicians during the diagnosis of disease related to liver directly or with some other organs. The term “liver chemistry tests ” is a frequently used but poorly defined phrase that encompasses the numerous serum chemistries that can be assayed to assess hepatic function and/or injury. Key words: Laboratory liver test, bilirubin, alanine amino transferase, aspartate amino transferase, ratio of aminotransferases, alkaline phosphatase, gamma glutamyl transferase, 5 ’ nucleotidase, ceruloplasmin, α-fetoprotein 1 Page numbers not for citation purposesLaboratory Liver Test