Numerical simulation of water impact of solid bodies with vertical and oblique entries

The flow problem of hydrodynamic impact during water entry of solid objects of various shapes and configurations is simulated by a two-fluid free surface code based on the solution of the Navier-Stokes equations (NSE) on a fixed Cartesian grid. In the numerical model the free surface is captured by the level set function, and the partial cell method combined with a local relative velocity approach is applied to the simulation of moving bodies. The code is firstly validated using experimental data and other numerical results in terms of the impact forces and surface pressure distributions for the vertical entry of a semi-circular cylinder and a symmetric wedge. Then configurations of oblique water entry of a wedge are simulated and the predicted free surface profiles during impact are compared with experimental results showing a good agreement. Finally, a series of tests involving vertical and oblique water entry of wedges with different heel angles are simulated and the results compared with published numerical results. It is found that the surface pressure distributions and forces predicted by the present model generally agree very well with other numerical results based on the potential flow theory. However, as the current model is based on the solution of the NSE, it is more robust and can therefore predict, for example, the formation and separation of the thin flow jets (spray) from surface of the wedge and associated ventilation phenomena for the cases of oblique water entry when the horizontal velocity is dominant. It is also noted that the potential flow theory can result in over-estimated negative pressures at the tip of the wedge due to its inherent restriction to nonseparated flows. © 2013 Elsevier Ltd. All rights reserved

A GPU based compressible multiphase hydrocode for modelling violent hydrodynamic impact problems

This paper presents a GPU based compressible multiphase hydrocode for modelling violent hydrodynamic impacts under harsh conditions such as slamming and underwater explosion. An effort is made to extend a one-dimensional five-equation reduced model (Kapila et al., 2001) to compute three-dimensional hydrodynamic impact problems on modern graphics hardware. In order to deal with free-surface problems such as water waves, gravitational terms, which are initially absent from the original model, are now considered and included in the governing equations. A third-order finite volume based MUSCL scheme is applied to discretise the integral form of the governing equations. The numerical flux across a mesh cell face is estimated by means of the HLLC approximate Riemann solver. The serial CPU program is firstly parallelised on multi-core CPUs with the OpenMP programming model and then further accelerated on many-core graphics processing units (GPUs) using the CUDA C programming language. To balance memory usage, computing efficiency and accuracy on multi- and many-core processors, a mixture of single and double precision floating-point operations is implemented. The most important data like conservative flow variables are handled with double-precision dynamic arrays, whilst all the other variables/arrays like fluxes, residual and source terms are treated in single precision. Several benchmark test cases including water-air shock tubes, one-dimensional liquid cavitation tube, dam break, 2D cylindrical underwater explosion near a planar rigid wall, 3D spherical explosion in a rigid cylindrical container and water entry of a 3D rigid flat plate have been calculated using the present approach. The obtained results agree well with experiments, exact solutions and other independent numerical computations. This demonstrates the capability of the present approach to deal with not only violent free-surface impact problems but also hull cavitation associated with underwater explosions. Performance analysis reveals that the running time cost of numerical simulations is dramatically reduced by use of GPUs with much less consumption of electrical energy than on the CPU

Accumulation capacity of ions in cabbage (Brassica oleracea L.) supplied with sea water

Cabbage seedlings were grown hydroponically to study the effects of different concentrations of seawater on the seedling growth, ion content under one-fourth strength Hoagland's nutrient solution in the greenhouse. The biomass of various organs of cabbage seedlings as well as the whole plants was significantly higher in the treatments with 1 g and 2 g sea salt/L than the no-salt control, but the treatments with 4, 5 or 6 g sea salt/L caused a decrease in growth. Root/shoot ratio remained at the level of control regardless of the sea salt treatment. Na+ and Cl- concentration in different parts of cabbage seedlings increased significantly, whereas K+ and Ca2+ concentration generally increased at low concentrations of sea salt and then decreased with increasing seawater concentration. Sodium and K+ concentrations were significantly higher in the stems than roots and leaves regardless of the sea salt treatment. The sea salt treatment increased Mg2+ concentration in stems and leaves of cabbage seedlings. An increase in Na+ and Cl- concentration in roots, stems and leaves of cabbage seedlings was the main contributor to declining ratios of K+/Na+, Ca2+/Na+ and Mg2+/Na+. The obtained data suggest that cabbage seedlings have strong ability to sustain seawater stress by the regulation of transport and distribution of ions

Counter-current chromatography for the separation of terpenoids: A comprehensive review with respect to the solvent systems employed

Copyright @ 2014 The Authors.This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.Natural products extracts are commonly highly complex mixtures of active compounds and consequently their purification becomes a particularly challenging task. The development of a purification protocol to extract a single active component from the many hundreds that are often present in the mixture is something that can take months or even years to achieve, thus it is important for the natural product chemist to have, at their disposal, a broad range of diverse purification techniques. Counter-current chromatography (CCC) is one such separation technique utilising two immiscible phases, one as the stationary phase (retained in a spinning coil by centrifugal forces) and the second as the mobile phase. The method benefits from a number of advantages when compared with the more traditional liquid-solid separation methods, such as no irreversible adsorption, total recovery of the injected sample, minimal tailing of peaks, low risk of sample denaturation, the ability to accept particulates, and a low solvent consumption. The selection of an appropriate two-phase solvent system is critical to the running of CCC since this is both the mobile and the stationary phase of the system. However, this is also by far the most time consuming aspect of the technique and the one that most inhibits its general take-up. In recent years, numerous natural product purifications have been published using CCC from almost every country across the globe. Many of these papers are devoted to terpenoids-one of the most diverse groups. Naturally occurring terpenoids provide opportunities to discover new drugs but many of them are available at very low levels in nature and a huge number of them still remain unexplored. The collective knowledge on performing successful CCC separations of terpenoids has been gathered and reviewed by the authors, in order to create a comprehensive document that will be of great assistance in performing future purifications. © 2014 The Author(s)

Study of psi(2S) decays to X J/psi

Using J/psi -> mu^+ mu^- decays from a sample of approximately 4 million psi(2S) events collected with the BESI detector, the branching fractions of psi(2S) -> eta J/psi, pi^0 pi^0 J/psi, and anything J/psi normalized to that of psi(2S) -> pi^+ pi^- J/psi are measured. The results are B(psi(2S) -> eta J/psi)/B(psi(2S) -> pi^+ pi^- J/psi) = 0.098 \pm 0.005 \pm 0.010, B(psi(2S) -> pi^0 pi^0 J/psi)/B(psi(2S) -> pi^+ pi^- J/psi) = 0.570 \pm 0.009 \pm 0.026, and B(psi(2S) -> anything J/psi)/B(psi(2S) -> pi^+ pi^- J/psi) = 1.867 \pm 0.026 \pm 0.055.Comment: 13 pages, 8 figure

Inflammatory cytokines and biofilm production sustain Staphylococcus aureus outgrowth and persistence: A pivotal interplay in the pathogenesis of Atopic Dermatitis

Individuals with Atopic dermatitis (AD) are highly susceptible to Staphylococcus aureus colonization. However, the mechanisms driving this process as well as the impact of S. aureus in AD pathogenesis are still incompletely understood. In this study, we analysed the role of biofilm in sustaining S. aureus chronic persistence and its impact on AD severity. Further we explored whether key inflammatory cytokines overexpressed in AD might provide a selective advantage to S. aureus. Results show that the strength of biofilm production by S. aureus correlated with the severity of the skin lesion, being significantly higher (P < 0.01) in patients with a more severe form of the disease as compared to those individuals with mild AD. Additionally, interleukin (IL)-β and interferon γ (IFN-γ), but not interleukin (IL)-6, induced a concentration-dependent increase of S. aureus growth. This effect was not observed with coagulase-negative staphylococci isolated from the skin of AD patients. These findings indicate that inflammatory cytokines such as IL1-β and IFN-γ, can selectively promote S. aureus outgrowth, thus subverting the composition of the healthy skin microbiome. Moreover, biofilm production by S. aureus plays a relevant role in further supporting chronic colonization and disease severity, while providing an increased tolerance to antimicrobials

Gene ontology based transfer learning for protein subcellular localization

<p>Abstract</p> <p>Background</p> <p>Prediction of protein subcellular localization generally involves many complex factors, and using only one or two aspects of data information may not tell the true story. For this reason, some recent predictive models are deliberately designed to integrate multiple heterogeneous data sources for exploiting multi-aspect protein feature information. Gene ontology, hereinafter referred to as <it>GO</it>, uses a controlled vocabulary to depict biological molecules or gene products in terms of biological process, molecular function and cellular component. With the rapid expansion of annotated protein sequences, gene ontology has become a general protein feature that can be used to construct predictive models in computational biology. Existing models generally either concatenated the <it>GO </it>terms into a flat binary vector or applied majority-vote based ensemble learning for protein subcellular localization, both of which can not estimate the individual discriminative abilities of the three aspects of gene ontology.</p> <p>Results</p> <p>In this paper, we propose a Gene Ontology Based Transfer Learning Model (<it>GO-TLM</it>) for large-scale protein subcellular localization. The model transfers the signature-based homologous <it>GO </it>terms to the target proteins, and further constructs a reliable learning system to reduce the adverse affect of the potential false <it>GO </it>terms that are resulted from evolutionary divergence. We derive three <it>GO </it>kernels from the three aspects of gene ontology to measure the <it>GO </it>similarity of two proteins, and derive two other spectrum kernels to measure the similarity of two protein sequences. We use simple non-parametric cross validation to explicitly weigh the discriminative abilities of the five kernels, such that the time & space computational complexities are greatly reduced when compared to the complicated semi-definite programming and semi-indefinite linear programming. The five kernels are then linearly merged into one single kernel for protein subcellular localization. We evaluate <it>GO-TLM </it>performance against three baseline models: <it>MultiLoc, MultiLoc-GO </it>and <it>Euk-mPLoc </it>on the benchmark datasets the baseline models adopted. 5-fold cross validation experiments show that <it>GO-TLM </it>achieves substantial accuracy improvement against the baseline models: 80.38% against model <it>Euk-mPLoc </it>67.40% with <it>12.98% </it>substantial increase; 96.65% and 96.27% against model <it>MultiLoc-GO </it>89.60% and 89.60%, with <it>7.05% </it>and <it>6.67% </it>accuracy increase on dataset <it>MultiLoc plant </it>and dataset <it>MultiLoc animal</it>, respectively; 97.14%, 95.90% and 96.85% against model <it>MultiLoc-GO </it>83.70%, 90.10% and 85.70%, with accuracy increase <it>13.44%</it>, <it>5.8% </it>and <it>11.15% </it>on dataset <it>BaCelLoc plant</it>, dataset <it>BaCelLoc fungi </it>and dataset <it>BaCelLoc animal </it>respectively. For <it>BaCelLoc </it>independent sets, <it>GO-TLM </it>achieves 81.25%, 80.45% and 79.46% on dataset <it>BaCelLoc plant holdout</it>, dataset <it>BaCelLoc plant holdout </it>and dataset <it>BaCelLoc animal holdout</it>, respectively, as compared against baseline model <it>MultiLoc-GO </it>76%, 60.00% and 73.00%, with accuracy increase <it>5.25%</it>, <it>20.45% </it>and <it>6.46%</it>, respectively.</p> <p>Conclusions</p> <p>Since direct homology-based <it>GO </it>term transfer may be prone to introducing noise and outliers to the target protein, we design an explicitly weighted kernel learning system (called Gene Ontology Based Transfer Learning Model, <it>GO-TLM</it>) to transfer to the target protein the known knowledge about related homologous proteins, which can reduce the risk of outliers and share knowledge between homologous proteins, and thus achieve better predictive performance for protein subcellular localization. Cross validation and independent test experimental results show that the homology-based <it>GO </it>term transfer and explicitly weighing the <it>GO </it>kernels substantially improve the prediction performance.</p

A Multi-Label Predictor for Identifying the Subcellular Locations of Singleplex and Multiplex Eukaryotic Proteins

Subcellular locations of proteins are important functional attributes. An effective and efficient subcellular localization predictor is necessary for rapidly and reliably annotating subcellular locations of proteins. Most of existing subcellular localization methods are only used to deal with single-location proteins. Actually, proteins may simultaneously exist at, or move between, two or more different subcellular locations. To better reflect characteristics of multiplex proteins, it is highly desired to develop new methods for dealing with them. In this paper, a new predictor, called Euk-ECC-mPLoc, by introducing a powerful multi-label learning approach which exploits correlations between subcellular locations and hybridizing gene ontology with dipeptide composition information, has been developed that can be used to deal with systems containing both singleplex and multiplex eukaryotic proteins. It can be utilized to identify eukaryotic proteins among the following 22 locations: (1) acrosome, (2) cell membrane, (3) cell wall, (4) centrosome, (5) chloroplast, (6) cyanelle, (7) cytoplasm, (8) cytoskeleton, (9) endoplasmic reticulum, (10) endosome, (11) extracellular, (12) Golgi apparatus, (13) hydrogenosome, (14) lysosome, (15) melanosome, (16) microsome, (17) mitochondrion, (18) nucleus, (19) peroxisome, (20) spindle pole body, (21) synapse, and (22) vacuole. Experimental results on a stringent benchmark dataset of eukaryotic proteins by jackknife cross validation test show that the average success rate and overall success rate obtained by Euk-ECC-mPLoc were 69.70% and 81.54%, respectively, indicating that our approach is quite promising. Particularly, the success rates achieved by Euk-ECC-mPLoc for small subsets were remarkably improved, indicating that it holds a high potential for simulating the development of the area. As a user-friendly web-server, Euk-ECC-mPLoc is freely accessible to the public at the website http://levis.tongji.edu.cn:8080/bioinfo/Euk-ECC-mPLoc/. We believe that Euk-ECC-mPLoc may become a useful high-throughput tool, or at least play a complementary role to the existing predictors in identifying subcellular locations of eukaryotic proteins

The counseling african americans to control hypertension (caatch) trial: baseline demographic, clinical, psychosocial, and behavioral characteristics

<p>Abstract</p> <p>Background</p> <p>Effectiveness of combined physician and patient-level interventions for blood pressure (BP) control in low-income, hypertensive African Americans with multiple co-morbid conditions remains largely untested in community-based primary care practices. Demographic, clinical, psychosocial, and behavioral characteristics of participants in the Counseling African American to Control Hypertension (CAATCH) Trial are described. CAATCH evaluates the effectiveness of a multi-level, multi-component, evidence-based intervention compared with usual care (UC) in improving BP control among poorly controlled hypertensive African Americans who receive primary care in Community Health Centers (CHCs).</p> <p>Methods</p> <p>Participants included 1,039 hypertensive African Americans receiving care in 30 CHCs in the New York Metropolitan area. Baseline data on participant demographic, clinical (<it>e.g</it>., BP, anti-hypertensive medications), psychosocial (<it>e.g</it>., depression, medication adherence, self-efficacy), and behavioral (<it>e.g</it>., exercise, diet) characteristics were gathered through direct observation, chart review, and interview.</p> <p>Results</p> <p>The sample was primarily female (71.6%), middle-aged (mean age = 56.9 ± 12.1 years), high school educated (62.4%), low-income (72.4% reporting less than $20,000/year income), and received Medicaid (35.9%) or Medicare (12.6%). Mean systolic and diastolic BP were 150.7 ± 16.7 mm Hg and 91.0 ± 10.6 mm Hg, respectively. Participants were prescribed an average of 2.5 ± 1.9 antihypertensive medications; 54.8% were on a diuretic; 33.8% were on a beta blocker; 41.9% were on calcium channel blockers; 64.8% were on angiotensin converting enzyme (ACE) inhibitors/angiotensin receptor blockers (ARBs). One-quarter (25.6%) of the sample had resistant hypertension; one-half (55.7%) reported medication non-adherence. Most (79.7%) reported one or more co-morbid medical conditions. The majority of the patients had a Charlson Co-morbidity score ≥ 2. Diabetes mellitus was common (35.8%), and moderate/severe depression was present in 16% of participants. Participants were sedentary (835.3 ± 1,644.2 Kcal burned per week), obese (59.7%), and had poor global physical health, poor eating habits, high health literacy, and good overall mental health.</p> <p>Conclusions</p> <p>A majority of patients in the CAATCH trial exhibited adverse lifestyle behaviors, and had significant medical and psychosocial barriers to adequate BP control. Trial outcomes will shed light on the effectiveness of evidence-based interventions for BP control when implemented in real-world medical settings that serve high numbers of low-income hypertensive African-Americans with multiple co-morbidity and significant barriers to behavior change.</p

Star Formation Rates of Massive Molecular Clouds in the Central Molecular Zone

We investigate star formation at very early evolutionary phases in five massive clouds in the inner 500 pc of the Galaxy, the Central Molecular Zone. Using interferometer observations of H$_2$O masers and ultra-compact H II regions, we find evidence of ongoing star formation embedded in cores of 0.2 pc scales and $\gtrsim$10$^5$ cm$^{-3}$ densities. Among the five clouds, Sgr C possesses a high (9%) fraction of gas mass in gravitationally bound and/or protostellar cores, and follows the dense ($\gtrsim$10$^4$ cm$^{-3}$) gas star formation relation that is extrapolated from nearby clouds. The other four clouds have less than 1% of their cloud masses in gravitationally bound and/or protostellar cores, and star formation rates 10 times lower than predicted by the dense gas star formation relation. At the spatial scale of these cores, the star formation efficiency is comparable to that in Galactic disk sources. We suggest that the overall inactive star formation in these Central Molecular Zone clouds could be because there is much less gas confined in gravitationally bound cores, which may be a result of the strong turbulence in this region and/or the very early evolutionary stage of the clouds when collapse has only recently started