The influence of joints and composite floor slabs on effective tying of steel structures in preventing progressive collapse

The event of the terrorist attack at 11th September 2001 in the USA has attracted increasing attention of researchers and engineers on progressive collapse of structures. It has gradually become a general practice for engineers to consider progressive collapse resistance in their design. In this paper, progressive collapse of steel frames with composite floor slabs is simulated by the finite element method. The numerical results are compared with test results. The influence of the joints and the concrete slabs on the effective tying of steel beams is investigated through parametric studies. From the analysis, methods of preventing progressive collapse that can be considered in design and when retrofitting existing structures are proposed. The results show that retrofitting a structure with pre-stressed steel cables and an increase of crack resistance in the concrete near joints can effectively improve effective tying of a structure, which results in an enhanced structural capacity in preventing progressive collapse

Evaluation of antibacterial activity and phytochemical analysis of root extracts of Boscia angustifolia

The aqueous and organic solvents extracts of Boscia angustifolia were screened for antibacterial and phytochemical properties. Alkaloids and saponins were detected in aqueous and chloroform extracts.These extract fractions were significantly (

Human preferences for sexually dimorphic faces may be evolutionarily novel

This article has been made available through the Brunel Open Access Publishing Fund.A large literature proposes that preferences for exaggerated sex typicality in human faces (masculinity/femininity) reflect a long evolutionary history of sexual and social selection. This proposal implies that dimorphism was important to judgments of attractiveness and personality in ancestral environments. It is difficult to evaluate, however, because most available data come from largescale, industrialized, urban populations. Here, we report the results for 12 populations with very diverse levels of economic development. Surprisingly, preferences for exaggerated sex-specific traits are only found in the novel, highly developed environments. Similarly, perceptions that masculine males look aggressive increase strongly with development, specifically, urbanization. These data challenge the hypothesis that facial dimorphism was an important ancestral signal of heritable mate value. One possibility is that highly developed environments provide novel opportunities to discern relationships between facial traits and behavior by exposing individuals to large numbers of unfamiliar faces, revealing patterns too subtle to detect with smaller samples

On the Existence of Global Weak Solutions for a Weakly Dissipative Hyperelastic Rod Wave Equation

Assuming that the initial value v0(x) belongs to the space H1(R), we prove the existence of global weak solutions for a weakly dissipative hyperelastic rod wave equation in the space C([0,∞)×R)⋂‍L∞([0,∞);H1(R)). The limit of the viscous approximation for the equation is used to establish the existence

Electronic Properties of Boron and Nitrogen doped graphene: A first principles study

Effect of doping of graphene either by Boron (B), Nitrogen (N) or co-doped by B and N is studied using density functional theory. Our extensive band structure and density of states calculations indicate that upon doping by N (electron doping), the Dirac point in the graphene band structure shifts below the Fermi level and an energy gap appears at the high symmetric K-point. On the other hand, by B (hole doping), the Dirac point shifts above the Fermi level and a gap appears. Upon co-doping of graphene by B and N, the energy gap between valence and conduction bands appears at Fermi level and the system behaves as narrow gap semiconductor. Obtained results are found to be in well agreement with available experimental findings.Comment: 11 pages, 4 figures, 1 table, submitted to J. Nanopart. Re

Self-rated health in middle-aged and elderly Chinese : distribution, determinants and associations with cardio-metabolic risk factors

Background: Self-rated health (SRH) has been demonstrated to be an accurate reflection of a person's health and a valid predictor of incident mortality and chronic morbidity. We aimed to evaluate the distribution and factors associated with SRH and its association with biomarkers of cardio-metabolic diseases among middle-aged and elderly Chinese. Methods: Survey of 1,458 men and 1,831 women aged 50 to 70 years, conducted in one urban and two rural areas of Beijing and Shanghai in 2005. SRH status was measured and categorized as good (very good and good) vs. not good (fair, poor and very poor). Determinants of SRH and associations with biomarkers of cardio-metabolic diseases were evaluated using logistic regression. Results: Thirty two percent of participants reported good SRH. Males and rural residents tended to report good SRH. After adjusting for potential confounders, residence, physical activity, employment status, sleep quality and presence of diabetes, cardiovascular disease, and depression were the main determinants of SRH. Those free from cardiovascular disease (OR 3.68; 95%CI 2.39; 5.66), rural residents (OR 1.89; 95% CI 1.47; 2.43), non-depressed participants (OR 2.50; 95% CI 1.67; 3.73) and those with good sleep quality (OR 2.95; 95% CI 2.22; 3.91) had almost twice or over the chance of reporting good SRH compared to their counterparts. There were significant associations -and trend- between SRH and levels of inflammatory markers, insulin levels and insulin resistance. Conclusion: Only one third of middle-aged and elderly Chinese assessed their health status as good or very good. Although further longitudinal studies are required to confirm our findings, interventions targeting social inequalities, lifestyle patterns might not only contribute to prevent chronic morbidity but as well to improve populations' perceived health

Full Counting Statistics of Superconductor--Normal-Metal Heterostructures

The article develops a powerful theoretical tool to obtain the full counting statistics. By a slight extension of the standard Keldysh method we can access immediately all correlation functions of the current operator. Embedded in a quantum generalization of the circuit theory of electronic transport, we are able to study the full counting statistics of a large class of two-terminal contacts and multi-terminal structures, containing superconductors and normal metals as elements. The practical use of the method is demonstrated in many examples.Comment: 35 pages, contribution to "Quantum Noise", ed. by Yu.V. Nazarov and Ya.M. Blanter, minor changes in text, references adde

Detecting topological currents in graphene superlattices

This is the author accepted manuscript. The final version is available from AAAS via the DOI in this record.Topological materials may exhibit Hall-like currents flowing transversely to the applied electric field even in the absence of a magnetic field. In graphene superlattices, which have broken inversion symmetry, topological currents originating from graphene's two valleys are predicted to flow in opposite directions and combine to produce long-range charge neutral flow. We observed this effect as a nonlocal voltage at zero magnetic field in a narrow energy range near Dirac points at distances as large as several micrometers away from the nominal current path. Locally, topological currents are comparable in strength with the applied current, indicating large valley-Hall angles. The long-range character of topological currents and their transistor-like control by means of gate voltage can be exploited for information processing based on valley degrees of freedom.This work was supported by the European Research Council, the Royal Society, the National Science Foundation (STC Center for Integrated Quantum Materials, grant DMR‐1231319), Engineering & Physical Research Council (UK), the Office of Naval Research and the Air Force Office of Scientific Research

Estimating true evolutionary distances under rearrangements, duplications, and losses

Background: The rapidly increasing availability of whole-genome sequences has enabled the study of whole-genome evolution. Evolutionary mechanisms based on genome rearrangements have attracted much attention and given rise to many models; somewhat independently, the mechanisms of gene duplication and loss have seen much work. However, the two are not independent and thus require a unified treatment, which remains missing to date. Moreover, existing rearrangement models do not fit the dichotomy between most prokaryotic genomes (one circular chromosome) and most eukaryotic genomes (multiple linear chromosomes). Results: To handle rearrangements, gene duplications and losses, we propose a new evolutionary model and the corresponding method for estimating true evolutionary distance. Our model, inspired from the DCJ model, is simple and the first to respect the prokaryotic/eukaryotic structural dichotomy. Experimental results on a wide variety of genome structures demonstrate the very high accuracy and robustness of our distance estimator. Conclusions: We give the first robust, statistically based, estimate of genomic pairwise distances based on rearrangements, duplications and losses, under a model that respects the structural dichotomy between prokaryotic and eukaryotic genomes. Accurate and robust estimates in true evolutionary distances should translate into much better phylogenetic reconstructions as well as more accurate genomic alignments, while our new model of genome rearrangements provides another refinement in simplicity and verisimilitude

ABCD Neurocognitive Prediction Challenge 2019: Predicting individual residual fluid intelligence scores from cortical grey matter morphology

We predicted residual fluid intelligence scores from T1-weighted MRI data available as part of the ABCD NP Challenge 2019, using morphological similarity of grey-matter regions across the cortex. Individual structural covariance networks (SCN) were abstracted into graph-theory metrics averaged over nodes across the brain and in data-driven communities/modules. Metrics included degree, path length, clustering coefficient, centrality, rich club coefficient, and small-worldness. These features derived from the training set were used to build various regression models for predicting residual fluid intelligence scores, with performance evaluated both using cross-validation within the training set and using the held-out validation set. Our predictions on the test set were generated with a support vector regression model trained on the training set. We found minimal improvement over predicting a zero residual fluid intelligence score across the sample population, implying that structural covariance networks calculated from T1-weighted MR imaging data provide little information about residual fluid intelligence.Comment: 8 pages plus references, 3 figures, 2 tables. Submission to the ABCD Neurocognitive Prediction Challenge at MICCAI 201