Tensile testing and fracture mechanism analysis of polyvinyl alcohol nanofibrous webs

A tensile properties testing study was conducted to understand the influence of thickness, cross-head speed (speed of testing), gauge length (GL; specimen test length), and sample shape on important tensile properties of polyvinyl alcohol (PVA) nanofiber webs. The effects of each testing parameter on load at break, extension at break, Young's modulus, and tensile stress–strain curve of PVA nanofiber webs are analyzed. The Welch two sample t-tests show the significant difference among tested data. Using interaction plots, two-way analysis of variance, and margin mean plots, the interaction effects among testing parameters have been analyzed. Of all the factors, cross-head speed, the interaction among GL, and sample thickness (GL: Thickness) and the interaction among GL, testing speed and sample thickness (GL: Speed: Thickness) have significant influence on the tensile properties of PVA nanofiber webs. Moreover, the hypothesized model of mechanism of tensile strain–stress curve of PVA nanofiber webs has been proposed. Based on the model, the tensile strain–stress curve can be split into three stages: linear elastic, partial break up, and complete breakage. This study will provide a better understanding of tensile testing parameters' effects and their interaction effects on the tensile properties of nanowebs.     

Analysis of multilayered dielectric waveguides: variationaltreatment

A fast and near exact modal analysis is presented to obtain the propagation constants and electric field profiles for dielectric multilayered channel (rib) waveguides. Calculations are performed for a particular channel configuration and found to be in excellent agreement with those obtained using the finite difference method     

Lipoprotein(a) as a risk predictor for cardiac mortality in patients with acute coronary syndromes

AIMS: Raised lipoprotein(a) concentrations are considered to be a risk factor for atherothrombotic diseases. We examined whether baseline concentrations were a risk factor for an adverse outcome in patients admitted with acute coronary syndromes. METHODS AND RESULTS: Five hundred and nineteen patients admitted with suspected acute coronary syndromes were studied and followed prospectively for a median of 3 years. The prognostic significance of a baseline lipoprotein(a) concentration of > or = 30 mg x dl(-1) or lower for subsequent cardiac death was assessed in patients with myocardial infarction (266) and unstable angina (197) and compared with other variables in regression models. In patients with myocardial infarction, a baseline lipoprotein(a) concentration of > or =30 mg x dl(-1) was associated with a 62% increase in subsequent cardiac death compared to the lower concentration group (29.8% vs 18.6%, Log rank P=0.04). In a multivariate regression model a baseline lipoprotein(a) concentration of > or = 30 mg x dl(-1) retained its significance as an independent predictor of cardiac death (P=0.037). In patients with unstable angina, baseline concentrations of > or = 7.9 mg x dl(-1) were found to be significant predictors of cardiac death in univariate (P=0.021) and multivariate (P=0.035) regression models. CONCLUSION: Baseline lipoprotein(a) concentrations in patients admitted with acute coronary syndromes are associated with an increased risk of cardiac death. For patients with myocardial infarction a concentration of > or = 30 mg x dl(-1) appears appropriate as a risk discriminator; for patients admitted with unstable angina, however, much lower concentrations of lipoprotein(a) appear to be prognostically important.     

Empirically supported psychological therapies.

This article introduces the special section of the Journal of Consulting and Clinical Psychology on empirically supported psychological therapies. After a discussion of the rationale for the selection of the specific terms in the label, several justifications are considered for conducting and learning from empirical evaluations of psychological therapies. Finally, the process that guided the special section is described. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Secondary Metabolic Profile as a Tool for Distinction and Characterization of Cultivars of Black Pepper (Piper nigrum L.) Cultivated in Pará State,Brazil

This study evaluated the chemical compositions of the leaves and fruits of eight black pepper cultivars cultivated in Pará State (Amazon, Brazil). Hydrodistillation and gas chromatography–mass spectrometry were employed to extract and analyze the volatile compounds, respectively. Sesquiterpene hydrocarbons were predominant (58.5–90.9%) in the cultivars “Cingapura”, “Equador”, “Guajarina”, “Iaçará”, and “Kottanadan”, and “Bragantina”, “Clonada”, and “Uthirankota” displayed oxygenated sesquiterpenoids (50.6–75.0%). The multivariate statistical analysis applied using volatile composition grouped the samples into four groups: γ-Elemene, curzerene, and δ-elemene (“Equador”/“Guajarina”, I); δ-elemene (“Iaçará”/“Kottanadan”/“Cingapura”, II); elemol (“Clonada”/“Uthirankota”, III) and α-muurolol, bicyclogermacrene, and cubebol (“Bragantina”, IV). The major compounds in all fruit samples were monoterpene hydrocarbons such as α-pinene, β-pinene, and limonene. Among the cultivar leaves, phenolics content (44.75–140.53 mg GAE·g⁻¹ FW), the enzymatic activity of phenylalanine-ammonia lyase (20.19–57.22 µU·mL⁻¹), and carotenoids (0.21–2.31 µg·mL⁻¹) displayed significant variations. Due to black pepper’s susceptibility to Fusarium infection, a molecular docking analysis was carried out on Fusarium protein targets using each cultivar’s volatile components. F. oxysporum endoglucanase was identified as the preferential protein target of the compounds. These results can be used to identify chemical markers related to the susceptibility degree of black pepper cultivars to plant diseases prevalent in Pará State.     

Aliphatic heterocyclic polymers

Aliphatic polybenzoxazoles, polybenzothiazoles, and polybenzimidazoles have been prepared by three methods: in poly(phosphoric acid), by the polyamide precursor, and by melt polymerization. The melt polymerization method was found to be the most satisfactory. All of the aliphatic heterocyclic polymers had excellent thermal stability, resistance to alkaline hydrolysis, high glass transition temperatures, and a high degree of flexibility. The only class of polymer found having any degree of solubility, however, was the polybenzimidazoles. Aliphatic polybenzimidazole films were prepared by solution casting. These films were found to be extremely flexible at ambient and cryogenic temperatures. The films were unaffected by alkaline hydrolysis, even in an oxidizing medium. A molding prepared from the aliphatic polybenzimidazole had excellent physical properties at both cryogenic and room temperature.     

On tool wear and its effect on machined surface integrity

This paper presents the results of an investigation of induced residual stress, induced strain, and induced subsurface energy in machined surfaces due to the machining process. The influence of tool wear on residual stress, strain, and energy is also reported. The exact elasticity solution for a split ring was extended and used to calculate the residual stress in the machined surface by using ring dimension changes caused by the electrochemical removal of a thin layer of residually stressed surface. The strain distribution beneath the machined surface was determined by using the grid technique. The subsurface energy stored in the machined surface was then obtained from the data of residual stress and strain. For the materials studied, this investigation showed that such energy could not be neglected when establishing the total energy needed for machining a unit volume of material. Tool coatings having different surface roughness and tools having various magnitudes of flank wear were investigated. The experimental results show that tool wear is a dominant factor affecting the values of induced residual stress, strain, subsurface energy, and the quality of the machined surface. The increase of tool wear caused an increase of residual stress and strain beneath the machined surface. It was also found that the overall energy stored in the machined subsurface increases as the tool wear increases and as the tool surface gets rougher. When the cutting tool is severely worn, the machined surface not only becomes very rough, but also contains many partially fractured laps or cracks. This makes tool wear a key factor in controlling the quality of the machined surface.     

Development of a Weather Forecasting Code: A Case Study

Computational science is increasingly supporting advances in scientific and engineering knowledge. The unique constraints of these types of projects result in a development process that differs from the process more traditional information technology projects use. This article reports the results of the sixth case study conducted under the support of the Darpa High Productivity Computing Systems Program. The case study aimed to investigate the technical challenges of code development in this environment, understand the use of development tools, and document the findings as concrete lessons learned for other developers' benefit. The project studied here is a major component of a weather forecasting system of systems. It includes complex behavior and interaction of several individual physical systems (such as the atmosphere and the ocean). This article describes the development of the code and presents important lessons learned.     

Scalable multi-variate analytics of seismic and satellite-based observational data

Over the past few years, large human populations around the world have been affected by an increase in significant seismic activities. For both conducting basic scientific research and for setting critical government policies, it is crucial to be able to explore and understand seismic and geographical information obtained through all scientific instruments. In this work, we present a visual analytics system that enables explorative visualization of seismic data together with satellite-based observational data, and introduce a suite of visual analytical tools. Seismic and satellite data are integrated temporally and spatially. Users can select temporal ;and spatial ranges to zoom in on specific seismic events, as well as to inspect changes both during and after the events. Tools for designing high dimensional transfer functions have been developed to enable efficient and intuitive comprehension of the multi-modal data. Spread-sheet style comparisons are used for data drill-down as well as presentation. Comparisons between distinct seismic events are also provided for characterizing event-wise differences. Our system has been designed for scalability in terms of data size, complexity (i.e. number of modalities), and varying form factors of display environments.     

An improved constraint satisfaction adaptive neural network for job-shop scheduling

This paper presents an improved constraint satisfaction adaptive neural network for job-shop scheduling problems. The neural network is constructed based on the constraint conditions of a job-shop scheduling problem. Its structure and neuron connections can change adaptively according to the real-time constraint satisfaction situations that arise during the solving process. Several heuristics are also integrated within the neural network to enhance its convergence, accelerate its convergence, and improve the quality of the solutions produced. An experimental study based on a set of benchmark job-shop scheduling problems shows that the improved constraint satisfaction adaptive neural network outperforms the original constraint satisfaction adaptive neural network in terms of computational time and the quality of schedules it produces. The neural network approach is also experimentally validated to outperform three classical heuristic algorithms that are widely used as the basis of many state-of-the-art scheduling systems. Hence, it may also be used to construct advanced job-shop scheduling systems.