MOVING WALL JET FLOW NEAR CHANNEL EXIT AT MODERATE REYNOLDS NUMBER

The two-dimensional jet flow of a Newtonian fluid at moderate Reynolds number, emerging from a channel and flowing along one moving plate, while the other plate is stationary, is examined theoretically in this study. In this case, the equations of motion are reduced by expanding the flow field about the basic Couette flow. Inertia is assumed to be large enough, allowing asymptotic development in terms of the inverse Reynolds number. A boundary layer forms adjacent to the free surface, and a classical boundary- layer analysis is applied to find the flow at the free surface and elsewhere. The influence of this boundary layer is investigated by the aid of the method of matched asymptotic expansions. The flow velocity is obtained as composite expansion by matching the flow between the core region and the inner and outer layers. The influence of wall velocity on the shape of the free surface is emphasized. The formulation allows the determination of the steady state flow and free surface profiles analytically, which can serve as boundary condition for computational jet flow further downstrea

Spirituality, moral conviction, and prosocial rule-breaking in healthcare

This study investigated the effect of healthcare professionals’ workplace spirituality (WPS) on moral conviction and prosocial rule-breaking (PSRB). The data were collected from 315 healthcare professionals from three main districts of South Punjab, Pakistan. We determined the measures’ validity using confirmatory factor analysis. We investigated the hypothesized relationships using structural regression modeling. The results demonstrated a significant effect of WPS on PSRB and moral conviction. However, the mediating effect of moral conviction between WPS and PSRB was insignificant. Healthcare professionals may regulate PSRB by screening and promoting individuals with high WPS to positions requiring a high level of PSRB rather than considering health service providers’ personal moral beliefs

Incidence of Depression and Anxiety among Patients with Acute Myocardial Infarction during COVID-19 Pandemic

Objective:  This study aimed to assess the incidence of anxiety and depression among AMI patients during COVID-19 pandemic in Pakistan. Material & Method:  This cross-sectional study was conducted from February 27 to June 2, 2020, at the Cardiology ward of Dera Ghazi Khan Teaching Hospital.  Total 611 patients selected through convenience sampling. The patients were requested to respond to Hospital Anxiety and Depression Scale (HADS) and demographic information. An independent samples t test was applied for comparisons. Results:  Patients’ age was ranging from 41 to 79 years, with a mean age of 52.35 ± 5.12. There was a high frequency of anxiety (51.72%) and depression (34.86%) among AMI patients. A significant difference was observed in the level of anxiety (p = 0.001) and depression (p = 0.000) among male and female patients. Conclusion:  The present study findings affirmed that increased level of anxiety and depression are prevalent in AMI patients. Additionally, both anxiety and depressive symptoms were more common in female patients. Keywords:  COVID-19, Anxiety, Depression, Acute Myocardial Infarction (AMI)

Decision fusion in healthcare and medicine : a narrative review

Objective: To provide an overview of the decision fusion (DF) technique and describe the applications of the technique in healthcare and medicine at prevention, diagnosis, treatment and administrative levels. Background: The rapid development of technology over the past 20 years has led to an explosion in data growth in various industries, like healthcare. Big data analysis within the healthcare systems is essential for arriving to a value-based decision over a period of time. Diversity and uncertainty in big data analytics have made it impossible to analyze data by using conventional data mining techniques and thus alternative solutions are required. DF is a form of data fusion techniques that could increase the accuracy of diagnosis and facilitate interpretation, summarization and sharing of information. Methods: We conducted a review of articles published between January 1980 and December 2020 from various databases such as Google Scholar, IEEE, PubMed, Science Direct, Scopus and web of science using the keywords decision fusion (DF), information fusion, healthcare, medicine and big data. A total of 141 articles were included in this narrative review. Conclusions: Given the importance of big data analysis in reducing costs and improving the quality of healthcare; along with the potential role of DF in big data analysis, it is recommended to know the full potential of this technique including the advantages, challenges and applications of the technique before its use. Future studies should focus on describing the methodology and types of data used for its applications within the healthcare sector

Developing a Test of Mathematical Literacy based on STEM-PjBL using ADDIE Model

Mathematical literacy is one of the eminent skills in the learning process in the 21st century. However, the mathematical skills of Junior High School students in Indonesia need some improvement. This study aims to develop a test of mathematical literacy based on the integration of Science, Technology, Engineering, and Mathematics (STEM) and Project-based Learning (PjBL). The study involved research and development using the Analysis, Design, Development, Implementation and Evaluation model (ADDIE). The results showed that the developed mathematical literacy test based on STEM-PjBL is valid and practical to be implemented by the expert validator. Moreover, the construct validity through implementation in the classroom obtained the result that the instrument is valid and reliable. This instrument is expected to be disseminated to the wider population to accustom the students to the problem embedded in project-based learning and STEM activities. Keywords: Mathematical Literacy; Instrument Test; STEM-PjBL; ADDIE Mode

Stress and worry in the 2020 coronavirus pandemic: relationships to trust and compliance with preventive measures across 48 countries in the COVIDiSTRESS global survey

The COVIDiSTRESS global survey collects data on early human responses to the 2020 COVID-19 pandemic from 173 429 respondents in 48 countries. The open science study was co-designed by an international consortium of researchers to investigate how psychological responses differ across countries and cultures, and how this has impacted behaviour, coping and trust in government efforts to slow the spread of the virus. Starting in March 2020, COVIDiSTRESS leveraged the convenience of unpaid online recruitment to generate public data. The objective of the present analysis is to understand relationships between psychological responses in the early months of global coronavirus restrictions and help understand how different government measures succeed or fail in changing public behaviour. There were variations between and within countries. Although Western Europeans registered as more concerned over COVID-19, more stressed, and having slightly more trust in the governments' efforts, there was no clear geographical pattern in compliance with behavioural measures. Detailed plots illustrating between-countries differences are provided. Using both traditional and Bayesian analyses, we found that individuals who worried about getting sick worked harder to protect themselves and others. However, concern about the coronavirus itself did not account for all of the variances in experienced stress during the early months of COVID-19 restrictions. More alarmingly, such stress was associated with less compliance. Further, those most concerned over the coronavirus trusted in government measures primarily where policies were strict. While concern over a disease is a source of mental distress, other factors including strictness of protective measures, social support and personal lockdown conditions must also be taken into consideration to fully appreciate the psychological impact of COVID-19 and to understand why some people fail to follow behavioural guidelines intended to protect themselves and others from infection. The Stage 1 manuscript associated with this submission received in-principle acceptance (IPA) on 18 May 2020. Following IPA, the accepted Stage 1 version of the manuscript was preregistered on the Open Science Framework at https://osf.io/ytbcs. This preregistration was performed prior to data analysis

COVIDiSTRESS diverse dataset on psychological and behavioural outcomes one year into the COVID-19 pandemic

During the onset of the COVID-19 pandemic, the COVIDiSTRESS Consortium launched an open-access global survey to understand and improve individuals’ experiences related to the crisis. A year later, we extended this line of research by launching a new survey to address the dynamic landscape of the pandemic. This survey was released with the goal of addressing diversity, equity, and inclusion by working with over 150 researchers across the globe who collected data in 48 languages and dialects across 137 countries. The resulting cleaned dataset described here includes 15,740 of over 20,000 responses. The dataset allows cross-cultural study of psychological wellbeing and behaviours a year into the pandemic. It includes measures of stress, resilience, vaccine attitudes, trust in government and scientists, compliance, and information acquisition and misperceptions regarding COVID-19. Open-access raw and cleaned datasets with computed scores are available. Just as our initial COVIDiSTRESS dataset has facilitated government policy decisions regarding health crises, this dataset can be used by researchers and policy makers to inform research, decisions, and policy

COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak

This N = 173,426 social science dataset was collected through the collaborative COVIDiSTRESS Global Survey – an open science effort to improve understanding of the human experiences of the 2020 COVID-19 pandemic between 30th March and 30th May, 2020. The dataset allows a cross-cultural study of psychological and behavioural responses to the Coronavirus pandemic and associated government measures like cancellation of public functions and stay at home orders implemented in many countries. The dataset contains demographic background variables as well as measures of Asian Disease Problem, perceived stress (PSS-10), availability of social provisions (SPS-10), trust in various authorities, trust in governmental measures to contain the virus (OECD trust), personality traits (BFF-15), information behaviours, agreement with the level of government intervention, and compliance with preventive measures, along with a rich pool of exploratory variables and written experiences. A global consortium from 39 countries and regions worked together to build and translate a survey with variables of shared interests, and recruited participants in 47 languages and dialects. Raw plus cleaned data and dynamic visualizations are available

Validation of the Short Version (TLS-15) of the Triangular Love Scale (TLS-45) Across 37 Languages

Love is a phenomenon that occurs across the world and affects many aspects of human life, including the choice of, and process of bonding with, a romantic partner. Thus, developing a reliable and valid measure of love experiences is crucial. One of the most popular tools to quantify love is Sternberg’s 45-item Triangular Love Scale (TLS-45), which measures three love components: intimacy, passion, and commitment. However, our literature review reveals that most studies (64%) use a broad variety of shortened versions of the TLS-45. Here, aiming to achieve scientific consensus and improve the reliability, comparability, and generalizability of results across studies, we developed a short version of the scale—the TLS-15—comprised of 15 items with 5-point, rather than 9-point, response scales. In Study 1 (N = 7,332), we re-analyzed secondary data from a large-scale multinational study that validated the original TLS-45 to establish whether the scale could be truncated. In Study 2 (N = 307), we provided evidence for the three-factor structure of the TLS-15 and its reliability. Study 3 (N = 413) confirmed convergent validity and test–retest stability of the TLS-15. Study 4 (N = 60,311) presented a large-scale validation across 37 linguistic versions of the TLS-15 on a cross-cultural sample spanning every continent of the globe. The overall results provide support for the reliability, validity, and cross-cultural invariance of the TLS-15, which can be used as a measure of love components—either separately or jointly as a three-factor measure