Stress and Fracture Analyses Under Elastic-plastic and Creep Conditions: Some Basic Developments and Computational Approaches

A new hybrid-stress finite element algorith, suitable for analyses of large quasi-static deformations of inelastic solids, is presented. Principal variables in the formulation are the nominal stress-rate and spin. A such, a consistent reformulation of the constitutive equation is necessary, and is discussed. The finite element equations give rise to an initial value problem. Time integration has been accomplished by Euler and Runge-Kutta schemes and the superior accuracy of the higher order schemes is noted. In the course of integration of stress in time, it has been demonstrated that classical schemes such as Euler's and Runge-Kutta may lead to strong frame-dependence. As a remedy, modified integration schemes are proposed and the potential of the new schemes for suppressing frame dependence of numerically integrated stress is demonstrated. The topic of the development of valid creep fracture criteria is also addressed

Application and Analysis of Machine Learning Algorithms on Pima and Early Diabetes Datasets for Diabetes Prediction

Diabetes is a chronic condition that strike how your body burns food for energy. Much of the food you consume is converted by your body into sugar (glucose), which is then released into your bloodstream. Your pancreas releases insulin when your blood sugar levels rise. Over the years, several scholars have sought to create reliable diabetes prediction models. Due to a lack of adequate data sets and prediction techniques, this discipline still faces many unsolved research issues, which forces researchers to apply big data analytics and ML-based methodology. Four distinct machine learning algorithms are used in the study to analyze healthcare prediction analytics and solve the issues. In this investigation, the Pima and Early detection datasets were employed. We applied the Decision Tree, MLP, Naive Bayes, and Random Forest algorithms to these datasets and evaluated the accuracy and F-Measure. The goal of this research is to develop a system that could more precisely predict a patient's risk of developing diabetes

Sterile alpha motif and histidine/aspartic acid domain-containing protein 1 (SAMHD1)-facilitated HIV restriction in astrocytes is regulated by miRNA-181a

Background Although highly active antiretroviral therapy (HAART) has significantly reduced the morbidity and mortality in HIV patients, virus continues to reside in the central nervous system (CNS) reservoir. Hence, a complete eradication of virus remains a challenge. HIV productively infects microglia/macrophages, but astrocytes are generally restricted to HIV infection. The relative importance of the possible replication blocks in astrocytes, however, is yet to be delineated. A recently identified restriction factor, sterile alpha motif and histidine/aspartic acid domain-containing protein 1 (SAMHD1), restricts HIV infection in resting CD4+T cells and in monocyte-derived dendritic cells. However, SAMHD1 expression and HIV-1 restriction activity regulation in the CNS cells are unknown. Though, certain miRNAs have been implicated in HIV restriction in resting CD4+T cells, their role in the CNS HIV restriction and their mode of action are not established. We hypothesized that varying SAMHD1 expression would lead to restricted HIV infection and host miRNAs would regulate SAMHD1 expression in astrocytes. Results We found increased SAMHD1 expression and decreased miRNA expression (miR-181a and miR-155) in the astrocytes compared to microglia. We report for the first time that miR-155 and miR-181a regulated the SAMHD1 expression. Overexpression of these cellular miRNAs increased viral replication in the astrocytes, through SAMHD1 modulation. Reactivation of HIV replication was accompanied by decrease in SAMHD1 expression. Conclusions Here, we provide a proof of concept that increased SAMHD1 in human astrocytes is in part responsible for the HIV restriction, silencing of which relieves this restriction. At this time, this concept is of theoretical nature. Further experiments are needed to confirm if HIV replication can be reactivated in the CNS reservoir

Concordance of Treatment Effect: An Analysis of The Society of Thoracic Surgeons Intermacs Database

BACKGROUND: The Society of Thoracic Surgeons (STS) Intermacs Registry represents a real-world data source of durable, left ventricular assist devices that can address knowledge gaps not informed through randomized clinical trials. We sought to compare survival with contemporary left ventricular assist device technologies using multiple analytic approaches to assess concordance of treatment effects and to validate prior STS Intermacs observations. METHODS: Patients (aged \u3e 19 years) enrolled into STS Intermacs between August 2017 - June 2019 were stratified by device type (centrifugal device with hybrid levitation [CF-HL] or full magnetic levitation [CF-FML]). The primary outcome was 1-year survival assessed by three statistical methodologies (multivariable regression, propensity score matching, and instrumental variable analysis). RESULTS: Of 4,448 patients, 2,012 (45.2%) received CF-HL and 2,436 (54.8%) received CF-FML. One-year survival for CF-FML was 88% vs. 79% for CF-HL (overall p \u3c .001), with a hazard ratio for mortality of 3.18 for CF-HL (p\u3c0.0001) after risk adjustment. With propensity score matching (n=1400 each cohort), 1-year survival was 87% for CF-FML vs. 80% for CF-HL, with a hazard ratio of 3.20 for mortality with CF-HL (p\u3c0.0001) after risk adjustment. With an instrumental variable analysis, the probability of receiving CF-HL was associated with a hazard ratio of 3.11 (p\u3c0.0001). CONCLUSIONS: Statistical methodology using propensity score matching and instrumental variable analysis increased the robustness of observations derived from real-world data and demonstrates the feasibility of performing comparative effectiveness research using STS Intermacs. These analyses provide additional evidence supporting a survival benefit of CF-FML versus CF-HL

Pulmonary toxicity of synthetic amorphous silica–effects of porosity and copper oxide doping

Materials can be modified for improved functionality. Our aim was to test whether pulmonary toxicity of silica nanomaterials is increased by the introduction of: a) porosity; and b) surface doping with CuO; and whether c) these modifications act synergistically. Mice were exposed by intratracheal instillation and for some doses also oropharyngeal aspiration to: 1) solid silica 100 nm; 2) porous silica 100 nm; 3) porous silica 100 nm with CuO doping; 4) solid silica 300 nm; 5) porous silica 300 nm; 6) solid silica 300 nm with CuO doping; 7) porous silica 300 nm with CuO doping; 8) CuO nanoparticles 9.8 nm; or 9) carbon black Printex 90 as benchmark. Based on a pilot study, dose levels were between 0.5 and 162 µg/mouse (0.2 and 8.1 mg/kg bw). Endpoints included pulmonary inflammation (neutrophil numbers in bronchoalveolar fluid), acute phase response, histopathology, and genotoxicity assessed by the comet assay, micronucleus test, and the gamma-H2AX assay. The porous silica materials induced greater pulmonary inflammation than their solid counterparts. A similar pattern was seen for acute phase response induction and histologic changes. This could be explained by a higher specific surface area per mass unit for the most toxic particles. CuO doping further increased the acute phase response normalized according to the deposited surface area. We identified no consistent evidence of synergism between surface area and CuO doping. In conclusion, porosity and CuO doping each increased the toxicity of silica nanomaterials and there was no indication of synergy when the modifications co-occurred

Dynamic Authorisation Policies for Event-based Task Delegation

International audienceTask delegation presents one of the business process security leitmotifs. It denes a mechanism that bridges the gap between both workfow and access control systems. There are two important issues relating to delegation, namely allowing task delegation to complete, and having a secure delegation within a workfow. Delegation completion and authorisation enforcement are specied under specic constraints. Constraints are dened from the delegation context implying the presence of a xed set of delegation events to control the delegation execution. In this paper, we aim to reason about delegation events to specify delegation policies dynamically. To that end, we present an event-based task delegation model to monitor the delegation process. We then identify relevant events for authorisation enforcement to specify delegation policies. Moreover, we propose a technique that automates delegation policies using event calculus to control the delegation execution and increase the compliance of all delegation changes in the global policy

A Mathematical model for Astrocytes mediated LTP at Single Hippocampal Synapses

Many contemporary studies have shown that astrocytes play a significant role in modulating both short and long form of synaptic plasticity. There are very few experimental models which elucidate the role of astrocyte over Long-term Potentiation (LTP). Recently, Perea & Araque (2007) demonstrated a role of astrocytes in induction of LTP at single hippocampal synapses. They suggested a purely pre-synaptic basis for induction of this N-methyl-D- Aspartate (NMDA) Receptor-independent LTP. Also, the mechanisms underlying this pre-synaptic induction were not investigated. Here, in this article, we propose a mathematical model for astrocyte modulated LTP which successfully emulates the experimental findings of Perea & Araque (2007). Our study suggests the role of retrograde messengers, possibly Nitric Oxide (NO), for this pre-synaptically modulated LTP.Comment: 51 pages, 15 figures, Journal of Computational Neuroscience (to appear

Force-Bioreactor for Assessing Pharmacological Therapies for Mechanobiological Targets

Tissue fibrosis is a major health issue that impacts millions of people and is costly to treat. However, few effective anti-fibrotic treatments are available. Due to their central role in fibrotic tissue deposition, fibroblasts and myofibroblasts are the target of many therapeutic strategies centered primarily on either inducing apoptosis or blocking mechanical or biochemical stimulation that leads to excessive collagen production. Part of the development of these drugs for clinical use involves in vitro prescreening. 2D screens, however, are not ideal for discovering mechanobiologically significant compounds that impact functions like force generation and other cell activities related to tissue remodeling that are highly dependent on the conditions of the microenvironment. Thus, higher fidelity models are needed to better simulate in vivo conditions and relate drug activity to quantifiable functional outcomes. To provide guidance on effective drug dosing strategies for mechanoresponsive drugs, we describe a custom force-bioreactor that uses a fibroblast-seeded fibrin gels as a relatively simple mimic of the provisional matrix of a healing wound. As cells generate traction forces, the volume of the gel reduces, and a calibrated and embedded Nitinol wire deflects in proportion to the generated forces over the course of 6 days while overhead images of the gel are acquired hourly. This system is a useful in vitro tool for quantifying myofibroblast dose-dependent responses to candidate biomolecules, such as blebbistatin. Administration of 50 μM blebbistatin reliably reduced fibroblast force generation approximately 40% and lasted at least 40 h, which in turn resulted in qualitatively less collagen production as determined via fluorescent labeling of collagen