Relationships Between Mental Workload, Burnout, and Job Performance

Mental workload is a popular topic for ergonomics, psychology, and organizational behavior-related studies. Difficulties and differences in defining and measurement of mental workload engage the attention of scholars to the concept. Furthermore, the importance of mental workload on performance and burn out increases attention to the topic for empirical studies. In this chapter, the authors reveal the relations between mental workload, burnout, and job performance. Data were obtained from 144 academicians in Turkey. Results demonstrated that mental workload has a 1) positive impact on burn out and 2) negative impact on job performance of academicians. Moreover, it was found that burn out and job performance are negatively correlated. Finally, findings reported that there are differences among some demographic variables in accordance with mental workload, burn out, and job performance.

Critical Thinking in Research and Analysis

This chapter reviews the need for critical thinking and analysis and the art of reasoning and looks at quantitative and qualitative research methodologies and the situations where they are appropriate. The chapter reviews the question of why the analysis required for business development is so critical. Why is gathering the information needed for business development more difficult than gathering information for information systems development? To understand these questions, it is necessary to review the range and complexity of the information required for business research and analysis. The internal performance data must be evaluated and the actual economic position of the organisation established. The critical value elements of the organisation's resources need to be identified and the competencies established. The competitive environment must be researched together with the external factors that impact the organization, and all the interactions that result must be evaluated.

Multicenter Technical Validation of 30 Rapid Antigen Tests for the Detection of SARS-CoV-2 (VALIDATE)

During COVID19 pandemic, SARS-CoV-2 rapid antigen tests (RATs) were marketed with minimal or no performance data. We aimed at closing this gap by determining technical sensitivities and specificities of 30 RATs prior to market release. We developed a standardized technical validation protocol and assessed 30 RATs across four diagnostic laboratories. RATs were tested in parallel using the Standard Q® (SD Biosensor/Roche) assay as internal reference. We used left-over universal transport/optimum media from nasopharyngeal swabs of 200 SARS-CoV-2 PCR-negative and 100 PCR-positive tested patients. Transport media was mixed with assay buffer and applied to RATs according to manufacturer instructions. Sensitivities were determined according to viral loads. Specificity of at least 99% and sensitivity of 95%, 90%, and 80% had to be reached for 107, 106, 105 virus copies/mL, respectively. Sensitivities ranged from 43.5% to 98.6%, 62.3% to 100%, and 66.7% to 100% at 105, 106, 107 copies/mL, respectively. Automated assay readers such as ExDia or LumiraDx showed higher performances. Specificities ranged from 88.8% to 100%. Only 15 of 30 (50%) RATs passed our technical validation. Due to the high failure rate of 50%, mainly caused by lack of sensitivity, we recommend a thorough validation of RATs prior to market release.

The Interpersonal Entrainment in Music Performance Data Collection

The Interpersonal Entrainment in Music Performance Data Collection (IEMPDC) comprises six related corpora of music research materials: Cuban Son & Salsa (CSS), European String Quartet (ESQ), Malian Jembe (MJ), North Indian Raga (NIR), Tunisian Stambeli (TS), and Uruguayan Candombe (UC). The core data for each corpus comprises media files and computationally extracted event onset timing data. Annotation of metrical structure and code used in the preparation of the collection is also shared. The collection is unprecedented in size and level of detail and represents a significant new resource for empirical and computational research in music. In this article we introduce the main features of the data collection and the methods used in its preparation. Details of technical validation procedures and notes on data visualization are available as Appendices. We also contextualize the collection in relation to developments in Open Science and Open Data, discussing important distinctions between the two related concepts.

Dried blood spot specimens for SARS-CoV-2 antibody testing: A multi-site, multi-assay comparison

The true severity of infection due to COVID-19 is under-represented because it is based on only those who are tested. Although nucleic acid amplifications tests (NAAT) are the gold standard for COVID-19 diagnostic testing, serological assays provide better population-level SARS-CoV-2 prevalence estimates. Implementing large sero-surveys present several logistical challenges within Canada due its unique geography including rural and remote communities. Dried blood spot (DBS) sampling is a practical solution but comparative performance data on SARS-CoV-2 serological tests using DBS is currently lacking. Here we present test performance data from a well-characterized SARS-CoV-2 DBS panel sent to laboratories across Canada representing 10 commercial and 2 in-house developed tests for SARS-CoV-2 antibodies. Three commercial assays identified all positive and negative DBS correctly corresponding to a sensitivity, specificity, positive predictive value, and negative predictive value of 100% (95% CI = 72.2, 100). Two in-house assays also performed equally well. In contrast, several commercial assays could not achieve a sensitivity greater than 40% or a negative predictive value greater than 60%. Our findings represent the foundation for future validation studies on DBS specimens that will play a central role in strengthening Canada’s public health policy in response to COVID-19.

Effect of Turbulence Models in Performance Characterization of a Low Reynolds Number UAV Propeller

The advancement of computer technology has given the necessary impetus to perform numerical modelling and simulation in engineering. Turbulence modelling in Computational Fluid Dynamics is characterized by non-physics based modelling and there are several developments in this area that also has contributed to the growing rise in empiricism. Typically, turbulence models are chosen based on expert knowledge and experience. In this paper, the problem of selecting a turbulence closure is addressed for a small Unmanned Aerial Vehicle propeller rotating at a low Reynolds number. Using scientific approaches, verification and validation of performance data against experimental results have been performed for a selected number of turbulence model candidates available in the well-known finite-volume solver Fluent. Modified bivariate plots of performance data error reveal a few numbers of strong candidates of turbulence closures for this problem. After performing a series of checks for consistency, accuracy and computational cost, the two-equation standard k-ω is selected as the preferred model for further propeller simulations.

The impact of pragmalinguistic support on video-conferenced collaborative suggestion-giving task

This study explored the impact of pragmalinguistic support on L2 users’ suggestion-giving task performance. Data came from 12 pairs of L2 users in a Zoom-mediated university course. They collaboratively wrote suggestions for improvement in their peers’ lesson plans using Office 365. Six pairs received pragmalinguistic support, while the others wrote their suggestions on their own. Audio-recorded pair discussions were coded qualitatively, and the written suggestions were analyzed in terms of linguistic and pragmatic characteristics. The results showed that pragmalinguistic support encouraged the participants to engage more in language-related and task-related episodes. Also, their suggestions contained more diverse lexical downgraders and conventional suggestion-giving expressions. By contrast, those who wrote suggestions without pragmalinguistic support engaged more in pragmatic-related episodes, relying extensively on epistemic modal verbs (e.g., would). The findings indicate that pragmalinguistic support may help L2 users to better attend to task content and language, producing lexically and pragmatically richer output.