Design Fatigue Lives of Polypropylene Fibre Reinforced Polymer Concrete Composites

Flexural fatigue behavior of Poly-propylene fibre reinforced polymer concrete composites (PFRPCC) has been investigated at various stress levels and the statistical analysis of the data thus obtained has been carried out. Polymer Concrete Composite (PCC) samples without addition of any type of fibres were also tested for flexural fatigue.  Forty specimens of PCC and One hundred and Forty One specimens of PFRPCC containing 0.5%, 1.0% and 2.0% polypropylene fibres were tested in fatigue using a MTS servo controlled test system. Fatigue life distributions of PCC as well as PFRPCC are observed to approximately follow a two parameter Weibull distribution with correlation coefficient exceeding 0.9. The parameters of the Weibull distribution have been obtained by various methods. Failure probability, which is an important parameter in the fatigue design of materials, has been used to obtain the design fatigue lives for the material. Comparison of design fatigue life of PCC and PFRPCC has been carried out and it is observed that addition of fibres enhances the design fatigue life of PCC

Nuclear deformation and the two neutrino double-\beta decay in ^{124,126}Xe,^{128,130}Te, ^{130,132}Ba and ^{150}Nd isotopes

The two neutrino double beta decay of $^{124,126}$Xe,$^{128,130}$Te, $^{130,132}$Ba and $^{150}$Nd isotopes is studied in the Projected Hartree-Fock-Bogoliubov (PHFB) model. Theoretical 2$\nu$ $\beta^{-}\beta ^{-}$ half-lives of $^{128,130}$Te, and $^{150}$Nd isotopes, and 2$\nu \beta^{+}\beta^{+}$, 2$\nu$ $\beta^{+}EC$ and 2$\nu$ $ECEC$ for $^{124,126}$Xe and $^{130,132}$Ba nuclei are presented. Calculated quadrupolar transition probabilities B(E2: $0^+\to 2^+$), static quadrupole moments and $g$ factors in the parent and daughter nuclei reproduce the experimental information, validating the reliability of the model wave functions. The anticorrelation between nuclear deformation and the nuclear transition matrix element $M_{2\nu}$ is confirmed.Comment: 19 page

Metabolome Based Reaction Graphs of M. tuberculosis and M. leprae: A Comparative Network Analysis

BACKGROUND: Several types of networks, such as transcriptional, metabolic or protein-protein interaction networks of various organisms have been constructed, that have provided a variety of insights into metabolism and regulation. Here, we seek to exploit the reaction-based networks of three organisms for comparative genomics. We use concepts from spectral graph theory to systematically determine how differences in basic metabolism of organisms are reflected at the systems level and in the overall topological structures of their metabolic networks. METHODOLOGY/PRINCIPAL FINDINGS: Metabolome-based reaction networks of Mycobacterium tuberculosis, Mycobacterium leprae and Escherichia coli have been constructed based on the KEGG LIGAND database, followed by graph spectral analysis of the network to identify hubs as well as the sub-clustering of reactions. The shortest and alternate paths in the reaction networks have also been examined. Sub-cluster profiling demonstrates that reactions of the mycolic acid pathway in mycobacteria form a tightly connected sub-cluster. Identification of hubs reveals reactions involving glutamate to be central to mycobacterial metabolism, and pyruvate to be at the centre of the E. coli metabolome. The analysis of shortest paths between reactions has revealed several paths that are shorter than well established pathways. CONCLUSIONS: We conclude that severe downsizing of the leprae genome has not significantly altered the global structure of its reaction network but has reduced the total number of alternate paths between its reactions while keeping the shortest paths between them intact. The hubs in the mycobacterial networks that are absent in the human metabolome can be explored as potential drug targets. This work demonstrates the usefulness of constructing metabolome based networks of organisms and the feasibility of their analyses through graph spectral methods. The insights obtained from such studies provide a broad overview of the similarities and differences between organisms, taking comparative genomics studies to a higher dimension

Effect of Muscle Length on Cross-Bridge Kinetics in Intact Cardiac Trabeculae at Body Temperature

Dynamic force generation in cardiac muscle, which determines cardiac pumping activity, depends on both the number of sarcomeric cross-bridges and on their cycling kinetics. The Frank–Starling mechanism dictates that cardiac force development increases with increasing cardiac muscle length (corresponding to increased ventricular volume). It is, however, unclear to what extent this increase in cardiac muscle length affects the rate of cross-bridge cycling. Previous studies using permeabilized cardiac preparations, sub-physiological temperatures, or both have obtained conflicting results. Here, we developed a protocol that allowed us to reliably and reproducibly measure the rate of tension redevelopment (ktr; which depends on the rate of cross-bridge cycling) in intact trabeculae at body temperature. Using K+ contractures to induce a tonic level of force, we showed the ktr was slower in rabbit muscle (which contains predominantly β myosin) than in rat muscle (which contains predominantly α myosin). Analyses of ktr in rat muscle at optimal length (Lopt) and 90% of optimal length (L90) revealed that ktr was significantly slower at Lopt (27.7 ± 3.3 and 27.8 ± 3.0 s−1 in duplicate analyses) than at L90 (45.1 ± 7.6 and 47.5 ± 9.2 s−1). We therefore show that ktr can be measured in intact rat and rabbit cardiac trabeculae, and that the ktr decreases when muscles are stretched to their optimal length under near-physiological conditions, indicating that the Frank–Starling mechanism not only increases force but also affects cross-bridge cycling kinetics

Acceptance and Perception of Artificial Intelligence Usability in Eye Care (APPRAISE) for Ophthalmologists: A Multinational Perspective

Background: Many artificial intelligence (AI) studies have focused on development of AI models, novel techniques, and reporting guidelines. However, little is understood about clinicians' perspectives of AI applications in medical fields including ophthalmology, particularly in light of recent regulatory guidelines. The aim for this study was to evaluate the perspectives of ophthalmologists regarding AI in 4 major eye conditions: diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD) and cataract. Methods: This was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated via the major global ophthalmology societies. The survey was designed based on microsystem, mesosystem and macrosystem questions, and the software as a medical device (SaMD) regulatory framework chaired by the Food and Drug Administration (FDA). Factors associated with AI adoption for ophthalmology analyzed with multivariable logistic regression random forest machine learning. Results: One thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, n = 890/1,010) especially those with over 20 years' experience (OR 3.70, 95% CI: 1.10–12.5, p = 0.035), as compared to clinical decision support tools (78.8%, n = 796/1,010) or diagnostic tools (64.5%, n = 651). A majority of Ophthalmologists felt that AI is most relevant to DR (78.2%), followed by glaucoma (70.7%), AMD (66.8%), and cataract (51.4%) detection. Many participants were confident their roles will not be replaced (68.2%, n = 632/927), and felt COVID-19 catalyzed willingness to adopt AI (80.9%, n = 750/927). Common barriers to implementation include medical liability from errors (72.5%, n = 672/927) whereas enablers include improving access (94.5%, n = 876/927). Machine learning modeling predicted acceptance from participant demographics with moderate to high accuracy, and area under the receiver operating curves of 0.63–0.83. Conclusion: Ophthalmologists are receptive to adopting AI as assistive tools for DR, glaucoma, and AMD. Furthermore, ML is a useful method that can be applied to evaluate predictive factors on clinical qualitative questionnaires. This study outlines actionable insights for future research and facilitation interventions to drive adoption and operationalization of AI tools for Ophthalmology

Basic Atomic Physics

Contains reports on five research projects.National Science Foundation Grant PHY 96-024740National Science Foundation Grant PHY 92-21489U.S. Navy - Office of Naval Research Contract N00014-96-1-0484Joint Services Electronics Program Grant DAAHO4-95-1-0038National Science Foundation Grant PHY95-14795U.S. Army Research Office Contract DAAHO4-94-G-0170U.S. Army Research Office Contract DAAG55-97-1-0236U.S. Army Research Office Contract DAAH04-95-1-0533U.S. Navy - Office of Naval Research Contract N00014-96-1-0432National Science Foundation Contract PHY92-22768David and Lucile Packard Foundation Grant 96-5158National Science Foundation Grant PHY 95-01984U.S. Army Research OfficeU.S. Navy - Office of Naval Research Contract N00014-96-1-0485AASERT N00014-94-1-080

A Genome Wide Association Scan of Bovine Tuberculosis Susceptibility in Holstein-Friesian Dairy Cattle

peer-reviewedBackground: Bovine tuberculosis is a significant veterinary and financial problem in many parts of the world. Although many factors influence infection and progression of the disease, there is a host genetic component and dissection of this may enlighten on the wider biology of host response to tuberculosis. However, a binary phenotype of presence/absence of infection presents a noisy signal for genomewide association study. Methodology/Principal Findings: We calculated a composite phenotype of genetic merit for TB susceptibility based on disease incidence in daughters of elite sires used for artificial insemination in the Irish dairy herd. This robust measure was compared with 44,426 SNP genotypes in the most informative 307 subjects in a genome wide association analysis. Three SNPs in a 65 kb genomic region on BTA 22 were associated (i.e. p,1025, peaking at position 59588069, p = 4.0261026) with tuberculosis susceptibility. Conclusions/Significance: A genomic region on BTA 22 was suggestively associated with tuberculosis susceptibility; it contains the taurine transporter gene SLC6A6, or TauT, which is known to function in the immune system but has not previously been investigated for its role in tuberculosis infection

Climate change and COP26: Are digital technologies and information management part of the problem or the solution? An editorial reflection and call to action

The UN COP26 2021 conference on climate change offers the chance for world leaders to take action and make urgent and meaningful commitments to reducing emissions and limit global temperatures to 1.5 °C above pre-industrial levels by 2050. Whilst the political aspects and subsequent ramifications of these fundamental and critical decisions cannot be underestimated, there exists a technical perspective where digital and IS technology has a role to play in the monitoring of potential solutions, but also an integral element of climate change solutions. We explore these aspects in this editorial article, offering a comprehensive opinion based insight to a multitude of diverse viewpoints that look at the many challenges through a technology lens. It is widely recognized that technology in all its forms, is an important and integral element of the solution, but industry and wider society also view technology as being part of the problem. Increasingly, researchers are referencing the importance of responsible digitalization to eliminate the significant levels of e-waste. The reality is that technology is an integral component of the global efforts to get to net zero, however, its adoption requires pragmatic tradeoffs as we transition from current behaviors to a more climate friendly society

Comprehensive molecular characterization of gastric adenocarcinoma

Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also knownasPD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies