Mechanical Performance of Injection‐Molded Poly(propylene): Characterization and Modeling

It is shown that predictions of local mechanical properties in a product can be made from the orientation only using an anisotropic viscoplastic model. Due to processing‐induced crystalline orientations, the mechanical properties of injection‐molded polymer products are anisotropic and exhibit strong variations within a product. The tensile response and the mechanical lifetime under static loading depend strongly on the direction of loading and the location. The deformation kinetics are described with an anisotropic viscoplastic model, and quantitative predictions are made based on coupling of the orientation factor in direction of loading and model parameters. A limited characterization of the morphology within a product is sufficient to determine its local mechanical performance.

     

Low-Complexity Butterfly Integration Structure for MMSE-SIC SISO Detector

In this paper, we propose a low-complexity butterfly integration structure (LCBIS) for the minimum mean square error-soft interference cancellation (MMSE-SIC) soft-in soft-out (SISO) detector, which is widely used for MIMO systems. Unlike the conventional MMSE-SIC SISO detector which performs matrix inverse operations, the LCBIS performs butterfly integration operations with low complexity. To develop the LCBIS SISO detector, we derive an integral expression for the extrinsic information of the conventional MMSE-SIC SISO detector, and then propose a butterfly integration structure to compute the integral expression efficiently. Without matrix inverse operations, LCBIS significantly reduces the complexity of the MMSE-SIC SISO detector. In addition, simulation results show that LCBIS can offer much better BER than the other SISO detectors which do not perform matrix inverse operations.     

Noniterative unfolding algorithm for neutron spectrum measurementswith Bonner spheres

The use of detectors moderated by Bonner spheres of different diameters is a relatively easy and inexpensive method of measuring the energy spectrum of neutron emission sources. Because the number of counts for each sphere diameter can be obtained by integration of the spectrum multiplied by a two-dimensional kernel, the spectrum is obtained from measurement data by means of a deconvolution or “unfolding” algorithm. Algorithms capable of solving this ill-posed “inverse” problem are based on iteration, requiring an initial spectrum estimate, extensive computation, and considerable experience on the part of the user. This paper presents a noniterative algorithm based on spectrum models with undetermined parameters. It computes the set of parameters that minimizes the error between the actual Bonner counts measured and those predicted by integration of the resulting spectrum. Examples based on ideal data show that to avoid large spectrum errors caused by small measurement errors, the number of parameters involved must be small, much less than the number of sphere diameters employed. This restriction limits resolution in the spectrum, but the limitation is believed to be inherent in the physical characteristics of the Bonner system, not a defect of the algorithm. The method appears effective, fast, and easy to use     

Determination of Autotransformer-Capacitor Phase Converter Parameters

An analytical approach is described for determining the parameters for an autotransformer-capacitor phase converter that allows matching of the converter to a specific motor for a given load. Equations are developed for the capacitor size and autotransformer turns ratio that will give balanced operation of a three-phase motor. Predicted values are compared with the experimental results.     

CPAP Influence on Readily Available Inflammatory Markers in OSA—A Pilot Study

Obstructive sleep apnea (OSA) is characterized by repetitive upper airway collapse, chronic hypoxia and a proinflammatory phenotype. The purpose of our study was to evaluate readily available inflammatory biomarkers (C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), white blood cell count (WBC), red cell distribution width (RDW), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), mean platelet volume (MPV), WBC-to-MPV ratio (WMR) and lymphocyte-to-C-reactive protein ratio (LCR)) before and after CPAP in patients with moderate–severe OSA. We performed a prospective study that included patients with newly-diagnosed moderate–severe OSA. The control groups (patients without OSA and with mild OSA) were selected from the hospital polygraphy database. All subjects underwent routine blood panel, which was repeated in moderate–severe OSA patients after 8 weeks of CPAP. Our final study group included 31 controls, 33 patients with mild, 22 patients with moderate and 37 patients with severe OSA. CRP, ESR, NLR and WMR were correlated with OSA severity. After 8-week CPAP therapy, we documented a decrease in weight status, which remained statistically significant in both CPAP-adherent and non-adherent subgroups. Readily available, inexpensive inflammatory parameters can predict the presence of moderate–severe OSA, but are not influenced by short-term CPAP.     

Anti-plane shear stress problem of two bonded dissimilar half spaces with an elliptical hole or rigid inclusion on the interface

The problem of anti-plane shear stress of two bonded dissimilar half spaces with an elliptical hole or a rigid inclusion at the interface and having interfacial cracks is presented. Uniform anti-plane shear stresses and the stress free or zero displacement boundary conditions on the elliptical hole are considered. The two cases are reduced to Riemann–Hilbert problems and closed form solutions are obtained by use of the complex stress function and the conformal mapping approaches. Stress distributions, as well as stress intensity factor, are shown. When the elliptical hole collapses, the known solutions of the interfacial crack and thin rigid fiber can be obtained. If the coordinates in the Plemelj function are changed, a debonding length can be determined.     

Development of a method for poliovirus detection in freshwater clams

Consumption of shellfish has been implicated in more than 100 viral gastroenteritis and hepatitis A outbreaks in the United States. Methods for virus detection in marine shellfish have been recently developed. However recent interest in the establishment of freshwater clam fisheries requires the development of methods capable of detecting viral contamination in these species. In this study, freshwater clam homogenates were seeded with poliovirus and detection efficiencies were determined by the adsorption-elution method. Adsorption of poliovirus to clam homogenates was >99·9% at pH 4·5. Recovery efficiency using elution conditions of pH 9·5 and 8000 mg l⁻¹ sodium chloride averaged 55%. Addition of 3% beef extract to the eluent increased overall recoveries to 83%. In summary, the recovery of seeded poliovirus from freshwater clams requires the same basic methodology used for marine species with minor modifications.     

数字视频融合大未来新一代数位电视内存频宽需求解析具有成本效益和高效能的消费性产品DRAM解决方案

数字电视(DTV)简介 美国联邦通讯委员会(FCC)规定在2009年之前,数字电视广播将会取代自1950年代初期开始使用之模拟电视格式.相对于ATV(模拟),DTV(数字)拥有较高的分辨率与更新率,以及数字压缩格式.     

Investigating Injury Occurrence in Motor Vehicle Collision Using Artificial Neural Networks

Vehicle collisions amount to a significant loss of life in America. Upward of 30,000 lives are lost each year in the United States alone. Hundreds of millions of dollars are spent each year on vehicle safety and roadway design in the United States, and many studies have been conducted on the causal factors for vehicle collisions. This study used artificial neural networks as a means to predict the occurrence of injury of a vehicle collision. The objective was to classify the levels of the “injury occurrence” in vehicle collisions, given certain input variables, including demographic and environmental factors involved in crashes. Using Neural Ware's Predict software, a back‐propagation neural network model was constructed, trained, tested, and validated using data from the 2006 and 2007 Florida Traffic Crash Database. The neural network's computational power was iteratively increased by adding hidden layers to boost its predicting power until the performance began to plateau. Classification rates as well as Kolmogorov‐Smirnov (K‐S) statistical analysis were used to validate the model. A sensitivity analysis was then applied to find the level of contribution that the input variables had on the injury occurrence. Accident severity, number of lanes, and road surface conditions were found to have the most positive impacts on the injury occurrence. The implications of the study are discussed at the end of the article.