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.     

Does performance in progressive assessment influence the outcome in final examination? An Australian experience

This paper investigates whether performance in progressive assessment necessarily influences the outcome in the end-of-semester final examination using the experience of an introductory postgraduate statistics course at a large Australian university. The average score on progressive assessments was higher than that of the final examination. Students attaining a higher distinction (HD) at the progressive assessment had a 37% chance of securing the same grade in the final examination, while students securing just a pass grade at the progressive assessment had 54 percent chance of failure in the final examination. Multiple regression analysis revealed that students’ performance in progressive assessments had a significant positive impact on final examination, so has the impact of learning diary. Mid-semester tests based exclusively on multiple choice questions (MCQs), more weights in progressive assessment and class-size appeared to have significant negative impact on the performance in the final examination. Focus group discussions suggest that (a) the final examination under timed conditions; (b) competing demands on time for final examination in other courses due contemporaneously; and (c) weaker motivation to sustain the momentum due to pass or near pass based on progressive assessments were the main hurdles in achieving better performance in the final examination.     

Performance improvement of complementary feeders using static transfer switch system

The performance of complementary feeders, running in parallel, can be significantly improved by installing static transfer switches （STSs） at critical locations. We develop the STS control logic, which transfers the critical load from the preferred feeder to the alternate feeder when a voltage sag or a fault occurs on the preferred feeder. A forced commutation technique is proposed and implemented to turn off the preferred feeders＇ thyristor, thus avoiding cross current to flow and minimizing the transfer time. Simulation results show that the forced commutation technique is more effective as compared to the recently proposed time delay technique for STS operation. Two different feeders, namely New Exchange, the preferred feeder, and Sector 1-10/2, the alternate feeder of Islamabad Electric Supply COmpany （IESCO）, Pakistan, have been selected for case studies. The software PSCAD/EMTDC professional package has been used for simulation.     

A new fabrication technique to form complex polymethylmethacrylate microchannel for bioseparation

Recent studies show that reduction in cross-sectional area can be used to improve the concentration factor in microscale bioseparations. Due to simplicity in fabrication process, a step reduction in cross-sectional area is generally implemented in microchip to increase the concentration factor. But the sudden change in cross-sectional area can introduce significant band dispersion and distortion. This paper reports a new fabrication technique to form a gradual reduction in cross-sectional area in polymethylmethacrylate (PMMA) microchannel for both anionic and cationic isotachophoresis (ITP). The fabrication technique is based on hot embossing and surface modification assisted bonding method. Both one-dimensional and two-dimensional gradual reduction in cross-sectional area microchannels were formed on PMMA with high fidelity using proposed techniques. ITP experiments were conducted to separate and preconcentrate fluorescent proteins in these microchips. Thousand fold and ten thousand fold increase in concentrations were obtained when 10 × and 100 × gradual reduction in cross-sectional area microchannels were used for ITP.     

Prior knowledge and information-seeking behavior of PhD and MA students

Information seeking and its dimensions have been analyzed and measured in different disciplines and contexts and the relationships to other variables, such as gender, task, knowledge, personality, experience, and expertise, have been measured by researchers and have yielded helpful results. In this study, the relationships between information-seeking behavior and prior knowledge of graduate (MA and PhD) students at Tehran University were tested and analyzed. Results show positive and strong relationships between these two variables. Moreover, some dimensions of information-seeking behavior and some aspects of prior knowledge (expertise, familiarity, and past experience) had positive and significant relationships.