Kinetic study of low density lipoprotein oxidation by copper

Oxidation of Low Density Lipoprotein (LDL) is regarded as a key event in the development of atherosclerosis. The aim of this study was to investigate effect of various copper concentrations on LDL oxidation kinetic profile as a mechanism in atherosclerosis process. LDL was isolated from plasma and its oxidation with copper was investigated by monitoring the formation of conjugated dienes. Based on time course of the formation of conjugated diene was observed at concentrations of 0.5 to 10 μM copper, represented the conventional kinetics of LDL oxidation with an inhibition period followed by a propagation phase. In contrast, at concentrations of 20 to 50 μM copper, LDL oxidation proceeded after a negligibly short lag-time followed by a distinct propagation phase. At lower copper concentrations of about 0.5 μM, LDL oxidation can be combined in 4 consecutive oxidation phase. The increasing copper concentration (to 10 μM) lowered the first propagation and shortened the seconded inhibition period until they melted into one apparent kinetic phase. But in copper concentrations of about 20 to 50 μM, increasing copper concentration increased the first propagation and the second inhibition but lowered the second propagation phase. The results of this investigation on the copper dependence of the oxidation kinetics suggest that LDL contains two different copper binding sites. Copper bound to the low affinity binding sites with molar ratio of 200 to 500 of copper / LDL. These ions bound to the high affinity binding sites with molar ratio of copper / LDL of 5 to 100.     

Design of digital controllers for uncertain chaotic systems using fuzzy logic

A new and systematic method to design digital controllers for uncertain chaotic systems with structured uncertainties is presented in this paper. Takagi-Sugeno (TS) fuzzy model is used to model the chaotic dynamic system, while the uncertainties are decomposed such that the uncertain chaotic system can be rewritten as a set of local linear models with an additional disturbed input. Conventional control techniques are utilized to develop the continuous-time controllers first. Then, the digital controllers are obtained as the digital redesign of the continuous-time controllers using the state-matching approach. The performance of the proposed controller design is illustrated through numerical examples.     

MI-NLMS adaptive beamforming algorithm for smart antenna system applications

INTRODUCTION The demand for mobile communication services is increasing at a rapid pace throughout the globe. The increasing demand for mobile communication ser- vices in a limited RF spectrum motivates the need for better techniques to improve spectrum utilization. Smart antenna system was adopted by ITU for the IMT-2000 or the Third Generation (3G) wireless networks due to its capability to improve channel capacity and interference suppression. A smart an- tenna system combines mult…     

Right ventricular function in elite male athletes meeting the structural echocardiographic task force criteria for arrhythmogenic right ventricular cardiomyopathy

Athlete pre-participation screening is focused on detecting pathological conditions like arrhythmogenic right ventricular cardiomyopathy (ARVC). The diagnosis of ARVC is established by applying the revised 2010 ARVC Task Force Criteria (TFC) that assesses RV structure and function. Some athletes may meet structural TFC without having ARVC but we do not know the consequences for RV function. This study compared RV structural and functional indices in male athletes that meet the structural TFC (MTFC) for ARVC and those that do not (NMTFC). We recruited 214 male elite athletes. All participants underwent 2D, Doppler, tissue Doppler and strain (ε) echocardiography with a focused and comprehensive assessment of the right heart. Athletes were grouped on RV structural data: MTFC n = 34; NMTFC n = 180. Functional data were compared between groups. By selection, MTFC had larger absolute and scaled RV outflow tract (RVOT) diameter compared to NMTFC (P ?0.05) but these athletes did not develop a proportional increase in the RV inflow dimensions. There was no difference in global conventional RV systolic function between both groups however, there was significantly lower global RV ε in athletes that MTFC which can be explained, in part, by the RVOT dimension.     

Identification of voltera kernels of a class of nonlinear systems by walsh function techniques

This paper discusses the identification problem for a class of nonlinear systems. A member of this class may be represented by a single-valued power-law type nonlinearity preceded and succeeded by linear dyadic invariant systems. Such an arrangement allows for a Voltera functional series representation. The identification problem is then concerned with the specification of the associated Voltera kernels.Two approaches are presented for dealing with this problem. Both approaches are, however, based on Walsh function techniques. The first approach relies on direct output measurements when the input is a Walsh function. This approach is suitable for a deterministic case. The second approach assumes ergodic processes for the input. Based on measurements drawn from an input-output dyadic correlation function, determination of the Voltera kernels is made.     

Determining the SARS-CoV-2 serological immunoassay test performance indices based on the test results frequency distribution

IntroductionCoronavirus disease 2019 (COVID-19) is known to induce robust antibody response in most of the affected individuals. The objective of the study was to determine if we can harvest the test sensitivity and specificity of a commercial serologic immunoassay merely based on the frequency distribution of the SARS-CoV-2 immunoglobulin (Ig) G concentrations measured in a population-based seroprevalence study.Materials and methodsThe current study was conducted on a subset of a previously published dataset from the canton of Geneva. Data were taken from two non-consecutive weeks (774 samples from May 4-9, and 658 from June 1-6, 2020). Assuming that the frequency distribution of the measured SARS-CoV-2 IgG is binormal (an educated guess), using a non-linear regression, we decomposed the distribution into its two Gaussian components. Based on the obtained regression coefficients, we calculated the prevalence of SARS-CoV-2 infection, the sensitivity and specificity, and the most appropriate cut-off value for the test. The obtained results were compared with those obtained from a validity study and a seroprevalence population-based study.ResultsThe model could predict more than 90% of the variance observed in the SARS-CoV-2 IgG distribution. The results derived from our model were in good agreement with the results obtained from the seroprevalence and validity studies. Altogether 138 of 1432 people had SARS-CoV-2 IgG ≥ 0.90, the cut-off value which maximized the Youden’s index. This translates into a true prevalence of 7.0% (95% confidence interval 5.4% to 8.6%), which is in keeping with the estimated prevalence of 7.7% derived from our model. Our model can provide the true prevalence.ConclusionsHaving an educated guess about the distribution of test results, the test performance indices can be derived with acceptable accuracy merely based on the test results frequency distribution without the need for conducting a validity study and comparing the test results against a gold-standard test.     

Effects of arch-support orthoses on ground reaction forces and lower extremity kinematics related to running at various inclinations

ABSTRACT

While foot orthoses are commonly used in running, little is known regarding biomechanical risk potentials during uphill running. This study investigated the effects of arch-support orthoses on kinetic and kinematic variables when running at different inclinations. Sixteen male participants ran at different inclinations (0°, 3° and 6°) when wearing arch-support and flat orthoses on an instrumented treadmill. Arch-support orthoses induced longer contact time, larger initial ankle dorsiflexion, maximum ankle eversion, and knee sagittal range of motion (RoM) (p < 0.05). As incline slopes increased, vertical impact peak and loading rate, stride length, and ankle coronal RoM decreased, but contact time, stride frequency, initial ankle dorsiflexion and inversion, maximum dorsiflexion, initial knee flexion, and ankle sagittal RoM increased (p < 0.05). Furthermore, knee sagittal RoM was lowest when running at an inclination of 3°. The interaction effect indicated that in arch-support condition, participants running at 6° induced higher maximum ankle eversion than running at 0° (p < 0.05), while no differences were found in flat orthosis condition. These findings suggest that the use of arch-support orthoses would influence running biomechanics that is related to injury risks. Running at higher inclination led to more alterations to biomechanical variables than at lower inclination.     

Implicit aspect extraction in sentiment analysis: Review,taxonomy, oppportunities,and open challenges

Sentiment analysis is a text classification branch, which is defined as the process of extracting sentiment terms (i.e. feature/aspect, or opinion) and determining their opinion semantic orientation. At aspect level, aspect extraction is the core task for sentiment analysis which can either be implicit or explicit aspects. The growth of sentiment analysis has resulted in the emergence of various techniques for both explicit and implicit aspect extraction. However, majority of the research attempts targeted explicit aspect extraction, which indicates that there is a lack of research on implicit aspect extraction. This research provides a review of implicit aspect/features extraction techniques from different perspectives. The first perspective is making a comparison analysis for the techniques available for implicit term extraction with a brief summary of each technique. The second perspective is classifying and comparing the performance, datasets, language used, and shortcomings of the available techniques. In this study, over 50 articles have been reviewed, however, only 45 articles on implicit aspect extraction that span from 2005 to 2016 were analyzed and discussed. Majority of the researchers on implicit aspects extraction rely heavily on unsupervised methods in their research, which makes about 64% of the 45 articles, followed by supervised methods of about 27%, and lastly semi-supervised of 9%. In addition, 25 articles conducted the research work solely on product reviews, and 5 articles conducted their research work using product reviews jointly with other types of data, which makes product review datasets the most frequently used data type compared to other types. Furthermore, research on implicit aspect features extraction has focused on English and Chinese languages compared to other languages. Finally, this review also provides recommendations for future research directions and open problems.     

Leveraging textual properties of bug reports to localize relevant source files

Bug reports are an essential part of a software project's life cycle since resolving them improves the project's quality. When a new bug report is received, developers usually need to reproduce the bug and perform code review to locate the bug and assign it to be fixed. However, the huge number of bug reports and the increasing size of software projects make this process tedious and time-consuming. To solve this issue, bug localization techniques try to rank all the source files of a project with respect to how likely they are to contain a bug. This process reduces the search space of source files and helps developers to find relevant source files quicker. In this paper, we propose a multi-component bug localization approach that leverages different textual properties of bug reports and source files as well as the relations between previously fixed bug reports and a newly received one. Our approach uses information retrieval, textual matching, stack trace analysis, and multi-label classification to improve the performance of bug localization. We evaluate the performance of the proposed approach on three open source software projects (i.e., AspectJ, SWT, and ZXing) and the results show that it can rank appropriate source files for more than 52% of bugs by recommending only one source file and 78% by recommending ten files. It also improves the MRR and MAP values compared to several existing state-of-the-art bug localization approaches.     

Yaffa: a school of their choice?

This article is a product of in‐depth research in Yaffa, The Arab Democratic School that was carried out in 2004/05, as part of a study on alternative Arab education in Israel. Its aim, beyond telling the story of Yaffa, is to explicate the motivations that underlay this initiative, and to examine parental choice amongst the disadvantaged. We ask how the Arabs’ parental choice is affected by their (marginalised) social location, by how far they are from the dominant culture, and by their (in)capacity to make a difference. Apparently, to make a choice is a multidimensional act, reflecting the Palestinian citizens’ resistance to their marginalisation and unwillingness to be subjugated through non‐democratic educational perceptions. Their positionality resonates in Yaffa, as an act of intervention, and their search for an alternative reality where democratic education is not and cannot be separated from the Palestinian citizens’ need to imagine themselves as Arabs.