Miracle-dz/UniFAR-FTUs huggingface dataset:
Perceived Mental Stress Among Employed And Unemployed Women: A Comparative Cross Sectional Study During COVID-19 Pandemic

Background: Perceived Mental Stress (PMS) is an inevitable component of life. During COVID-19 pandemic, it’s ongoing and unpredictable situation has been increasing PMS among women. This present study was designed to compare the PMS level between employed and unemployed women. Methods: This comparative cross sectional study was conducted among purposively selected 240 women; of them 120 employed women are bankers, teachers and other sectors employees and 120 unemployed women are housewives. Data were collected from these participants by using a pre tested semi structured questionnaire and PMS was assessed by using Perceived Stress Scale (PSS) Bangla version. The collected data were analyzed by using SPSS software (Version 20) and p < 0.05 considered as statistical significant. Results: In this comparative study, the mean (±SD) score of PMS between employed and unemployed women found 20.0 (±5.48) and 20.5(±5.16) respectively, which was not statistically significant (p>0.05). The majority (81.7%) of employed women and (80.8%) of unemployed women suffered from moderate stress which was not statistically significant (p>0.05). There exist significant association between PMS and socio-demographic characteristics i.e. educational qualification (p=0.04), complete recovery from COVID-19 (p=0.02) in employed women; where as in unemployed women monthly family income (p=0.03), knowledge on specific treatment of COVID-19 (p=0.02) were significantly associated with PMS. Conclusion: The study revealed no significant difference in PMS between employed and unemployed women and but some associated factors lead them to stressful situation. So, equal emphasis should be given on both employed and unemployed women to prevent perceived mental stress. JOPSOM 2021; 40(2): 52-57
Analysis of epistemic uncertainty for the friction‐induced vibration

The phenomenon of brake squeal, which is a type of friction‐induced vibration, is analyzed using a pin‐on‐disc system. For this purpose, a finite element model is derived and its parameters are updated on the basis of experiments. The FEM analysis includes the complex eigenvalue analysis and the transient analysis. As the brake‐squeal phenomenon is very sensitive with respect to parametric uncertainty, the two numerical analyses are combined with an uncertainty analysis, which in this study is based on fuzzy arithmetic. The uncertainty analysis enables the determination of both the overall uncertainty of the considered output quantity and the influence of each individual uncertain model parameter on the overall uncertainty of the output. With this information about propagation and influence of parametric uncertainty in the system, the methods of complex eigenvalue analysis and transient analysis can be compared with respect to their appropriateness for predicting the tendency of the brake to squeal.
Estimation of variance of mean using known coefficient of variation

An optimum unbiased estimator of the variance of mean is given It is defined as a function of the mean and itscustomary unbiased variance estimator, utilizing known coefficient of variation, skewness and kurtosis of the underlying distributions. Exact results are obtained. Normal and large sample cases receive particular treatment. The proposed variance estimator is generally more efficient than the customary variance estimator; its relative efficiency becomes appreciably higher for smaller coefficient of variation, smaller sample (in the normal case at least), higher negative skewness, or higher positive skewness with sufficiently large kurtosis. The empirical findings are reassuring and supportive.
Application of Electrospun Water-Soluble Synthetic Polymers for Multifunctional Air Filters and Face Masks

The worsening of air quality is an urgent human health issue of modern society. The outbreak of COVID-19 has made the improvement of air quality even more imperative, both for the general achievement of major health gains and to reduce the critical factors in the transmission of airborne diseases. Thus, the development of solutions for the filtration of airborne pollutants is pivotal. Electrospinning has gained wide attention as an effective fabrication technique for preparing ultrafine fibers which are specifically tailored for air filtration. Nevertheless, the utilization of harmful organic solvents is the major barrier for the large-scale applicability of electrospinning. The use of water-soluble synthetic polymers has attracted increasing attention as a ‘green’ solution in electrospinning. We reported an overview of the last five years of the scientific literature on the use of water-soluble synthetic polymers for the fabrication of multifunctional air filters layers. Most of recent studies have focused on polyvinyl alcohol (PVA). Various modifications of electrospun polymers have been also described. The use of water-soluble synthetic polymers can contribute to the scalability of electrospinning and pave the way to innovative applications. Further studies will be required to fully harness the potentiality of these ‘greener’ electrospinning processes.
Supplementation of Methyl-Donor Nutrients to a High-Fat, High-Sucrose Diet during Pregnancy and Lactation Normalizes Circulating 25-Dihydroxycholecalciferol Levels and Alleviates Inflammation in Offspring

A Western-style diet that is high in fat and sucrose has been shown to alter DNA methylation and epigenetically modify genes related to health risk in offspring. Here, we investigated the effect of a methyl-donor nutrient (MS) supplemented to a high-fat, high-sucrose (HFS) diet during pregnancy and lactation on vitamin D (VD) status and inflammatory response in offspring. After mating, 10-week-old female Sprague-Dawley (SD) rats (n = 10/group) were randomly assigned to one of the four dietary groups during pregnancy and lactation: (1) control diet (CON), (2) CON with MS (CON-MS), (3) HFS, and (4) HFS with MS (HFS-MS). Weanling offspring (three weeks old) were euthanized and sacrificed (n = 8–10/sex/group). The remaining offspring (n = 10/sex/group) were randomly assigned to either a CON or an HFS diet for 12 weeks and sacrificed at 15 weeks of age. Our results indicated that prenatal MS supplementation, but not postnatal diet, restored low vitamin D status and suppressed elevation of proinflammatory cytokine induced by maternal HFS in the offspring. Furthermore, both prenatal and postnatal diets modulated the abundance of Lactobacillus spp. and Bacteroides spp. in the offspring, a shift that was independent of vitamin D status. Collectively, our data support a role for MS in restoring the perturbation of VD status and normalizing maternal HFS-induced inflammation in the offspring. Further investigation is warranted to elucidate the methylation status of VD metabolism-related pathways in the offspring, as well as the immunomodulatory role of vitamin D during the progression of obesity.
A Global Indicator for Measuring the Efficiency of Machine Learning Classifier Based on Multi-Criteria Approach

DOI: 10.9734/BJMCS/2015/16358 Editor(s): (1) Anonymous. (2) Tian-Xiao He, Department of Mathematics and Computer Science, Illinois Wesleyan University, USA. Reviewers: (1) Hiram Ponce, Faculty Engineering, Universidad Panamericana, Mexico. (2) Anonymous, India. (3) Scheila de Avila e Silva, Universidade de Caxias do Sul, Brazil. (4) Li, Xing, Department of Health Sciences Research, Mayo Clinic College, USA. Complete Peer review History: http://www.sciencedomain. org/review-history.php? iid=1034&id=6&aid=8841
Moving Object Detection Algorithm Based on Adaptive Clustering

A multi-moving target detection technique based on adaptive clustering and alpha-beta filtering is proposed and applied to the detection and tracking of moving targets. The main feature of this algorithm is the adaptive selection of initial cluster centers. Track initiation can be performed for multiple targets at the same time, which reduces the blindness of target search and improves the reliability and efficiency of radar track initiation. Experiments have proved the effectiveness and reliability of the algorithm.
Healing through helping: an experimental investigation of kindness, social activities, and reappraisal as well-being interventions

ABSTRACT Social connection is vital to well-being and is often impaired among individuals with anxiety or depressive disorders, yet CBT techniques may be ineffective at improving social connection (Hofmann et al., 2014). Acts of kindness may more effectively improve social connection and related dimensions of well-being than prevailing CBT techniques. In this study, we randomly assigned individuals with elevated anxiety or depression symptoms (N = 122) to engage in acts of kindness (AK), social activities (SA), or thought records, i.e., cognitive reappraisal (CR). Multilevel modeling revealed that improvement was greater in the AK group than the CR and SA groups for social connection, and improvement was greater in the AK group than the CR group for depression/anxiety symptoms and life satisfaction. Time-lagged analyses indicated that public self-absorption mediated the effects of AK. These results converge with prior experiments to demonstrate the advantages of acts of kindness over prevailing CBT techniques.
The Role of Relative Deprivation and Attribution Style in the Relationship between Organizational Fairness and Employees’ Service Innovation Behavior

The basis of organizational innovation is employee innovation, which is of great significance for organizations to gain a competitive advantage. At present, the research on the influencing factors of employee service innovation behavior is increasing. This study, based on the social cognitive theory, with relative deprivation as the mediator and attribution style as the moderator, explores the mechanism of the effect of organizational fairness on employee service innovation behavior. Taking 342 employees of service-oriented enterprises as the subjects of investigation, this paper empirically tests the theoretical model by using Amos and SPSS. The results indicated the following, organizational fairness was positively related to employees’ service innovation behavior. Relative deprivation partially mediated the relationship between organizational fairness and service innovation behavior. An external attribution style positively moderated the relationship between relative deprivation and employee service innovation behavior. An external attribution style also positively moderated the mediation effect of the relationship between organizational fairness and service innovation behavior. The internal attribution style negatively moderated the relationship between relative deprivation and employee service innovation behavior. The internal attribution style also negatively moderated the mediation effect of the relationship between organizational fairness and service innovation behavior. The conclusion of this study has managerial implications on how to promote employee service innovation behavior in service-oriented enterprises.
Turbulence and Random Processes in Fluid Mechanics

This book aims to give students the background to understand current research books on turbulence. To achieve this, it mixes a specialized review of advanced developments with elementary derivations of basic concepts or calculations. There is no complete theory of turbulence in fluid mechanics. The scope of this subject involves a wide spectrum of topics: fluid motion equations, statistical tools, stability theory, transition to turbulence, turbulence modeling, and so on. In few pages, this book presents a panorama of distinct approaches, in the manner of a handbook. A large number of items are at least mentioned, if not treated in depth.
In-Plane and Out-Of-Plane Thermal Conductivity of Silicon Thin Films Predicted by Molecular Dynamics

The thermal conductivity of silicon thin films is predicted in the directions parallel and perpendicular to the film surfaces (in-plane and out-of-plane, respectively) using equilibrium molecular dynamics, the Green-Kubo relation, and the Stillinger-Weber interatomic potential. Three different boundary conditions are considered along the film surfaces: frozen atoms, surface potential, and free boundaries. Film thicknesses range from 2 to 217 nm and temperatures from 300 to 1000 K. The relation between the bulk pho. -non mean free path (A) and the film thickness (d s ) spans from the ballistic regime (A ≥ d s ) at 300 K to the diffusive, bulk-like regime (Λ «d s ) at 1000 K. When the film is thin enough, the in-plane and out-of-plane thermal conductivity differ from each other and decrease with decreasing film thickness, as a consequence of the scattering of phonons with the film boundaries. The in-plane thermal conductivity follows the trend observed experimentally at 300 K. In the ballistic limit, in accordance with the kinetic and phonon radiative transfer theories, the predicted out-of-plane thermal conductivity varies linearly with the film thickness, and is temperature-independent for temperatures near or above the Debye's temperature.
Audio Capture Using Structural Sensors on Vibrating Panel Surfaces

The microphones and loudspeakers of modern compact electronic devices such as smartphones and tablets typically require case penetrations that leave the device vulnerable to environmental damage. To address this, the authors propose a surface-based audio interface that employs force actuators for reproduction and structural vibration sensors to record the vibrations of the display panel induced by incident acoustic waves. This paper reports experimental results showing that recorded speech signals are of sufficient quality to enable high-reliability automatic speech recognition despite degradation by the panel’s resonant properties. The authors report the results of experiments in which acoustic waves containing speech were directed to several panels, and the subsequent vibrations of the panels’ surfaces were recorded using structural sensors. The recording quality was characterized by measuring the speech transmission index, and the recordings were transcribed to text using an automatic speech recognition system from which the resulting word error rate was determined. Experiments showed that the word error rate (10%–13%) achieved for the audio signals recorded by the method described in this paper was comparable to that for audio captured by a high-quality studio microphone (10%). The authors also demonstrated a crosstalk cancellation method that enables the system to simultaneously record and play audio signals.
Inpatient clinician workload: a scoping review protocol to understand the definition, measurement and impact of non-procedural clinician workloads

Introduction Clinicians that care for hospitalised patients face unprecedented work conditions with exposure to highly infectious disease, exceedingly high patient numbers, and unpredictable work demands, all of which have resulted in increases in stress and burnout. Preliminary studies suggest that increasing workloads negatively affect inpatient clinician well-being and may negatively affect job performance; yet high workloads may be prioritised secondary to financial drivers or from workforce shortages. Despite this, the correlation between workload and these negative outcomes has not been fully quantified. Additionally, there are no clear measures for inpatient clinician workload and no standards to define ideal workloads. Using the protocol described here, we will perform a scoping review of the literature to generate a comprehensive understanding of how clinician workload of medical patients is currently defined, measured in clinical settings and its impact on the workforce, patients and institutional outcomes. Methods and analysis We will follow the methodology outlined by Joanna Briggs Institute and Arksey and O’Malley to conduct a comprehensive search of major electronic databases including Ovid Medline (PubMed), Embase (Embase.com), PsycINFO, ProQuest Dissertations and Google Scholar. All relevant published peer-reviewed and dissertaion grey literature will be included. Data will be extracted using a standardised form to capture key article information. Results will be presented in a descriptive narrative format. Ethics and dissemination This review does not require ethics approval though all included studies will be screened to ensure appropriate approval. The synthesis of this literature will provide a better understanding of the current state of work for inpatient clinicians, associated outcomes, and will identify gaps in the literature. These findings will be used in conjunction with an expert Delphi panel to identify measures of inpatient clinician workload to then guide the development of a novel workforce mobile application to actively track clinician work. We aim to lay the groundwork for future workforce studies to understand the optimal workloads that drive key outcomes for clinicians, patients and institutions.
Generalized Gaussian beams in free space

A new solution of the paraxially approximated wave equation in free space is presented. It has the form of a Hermite-Gaussian function, where the argument of the Hermite polynomial is generally complex. The usual Gaussian beams where such argument is real and those recently described by Siegman where it is complex but coinciding with that of the Gaussian function are particular cases of the general solution presented here. The application of these generalized Gaussian beams to the analysis of the beam emerging from a complex graded-index medium is discussed in detail.
Light Weight RL Based Run Time Power Management Methodology for Edge Devices

Run time power management has been a major problem in modern-day edge computing devices. Most of the built-in run-time power managers are not adaptable across a variety of workloads. A similar problem in the domain of High-Performance Computing (HPC) is resolved using Reinforcement learning (RL) approaches like Q-learning which can continuously learn from new workload scenarios. The main bottleneck of implementing Q-learning on edge compute platforms is the large Q-table size and the compute load as the algorithm continuously runs in the background. Compute load by RL continuously running in the background adds a significant amount of overhead on power which needs to be addressed to meet the power constraints for edge devices. As a part of our work, we propose a lightweight Q-learning methodology with intelligent memory management and algorithmic workload management policy. These policies make the algorithm lightweight and fit on edge computing devices. This lightweight Run Time Manager (RTM) eventually helps to bring down the power in run time. Our model has been implemented on the A57 processor of the Jetson Tx2 board which is widely used in a number of edge devices. Our proposed lightweight methodology brought run-time average power saving of 16.63% and the Q-table size decreased by 60% compared to the state-of-the-art edge computation Q-learning approach.
CBD Oil as a Miracle Drug: A Thematic Analysis of Caregivers’ Attitudes and Practices Towards Cannabidiol in Dementia Treatment

The aim of this study was to understand caregivers of individuals with dementia attitudes toward CBD oil. Thematic analysis was conducted with 67 posts (570 comments) about CBD oil selected from a Polish online support forum for caregivers. We identified caregivers’ expectations, motivations, and practices of using CBD oil. Caregivers expected CBD to improve the behavior, cognition, communication, and daily activities of their loved ones. They motivated each other by sharing experiences about the positive effects of CBD oil and claimed to be administering CBD oil without medical advice, which led to dangerous practices such as an overnight withdrawal of all drugs or experimenting with CBD oil dosage. Caregivers perceive CBD oil as a safer and more effective treatment for those with dementia than the conventional methods. We recommend healthcare professionals inquire about possible CBD oil usage during follow-up visits and thoroughly explain what to expect from prescribed medications.
Exploiting the Combined GRACE/GRACE-FO Solutions to Determine Gravimetric Excitations of Polar Motion

Observations from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions can be used to estimate gravimetric excitation of polar motion (PM), which reflects the contribution of mass changes in continental hydrosphere and cryosphere to PM variation. Many solutions for Earth’s gravity field variations have been developed by institutes around the world based on GRACE/GRACE-FO data; however, it remains inconclusive which of them is the most reliable for the determination of PM excitation. In this study, we present a combined series of GRACE/GRACE-FO-based gravimetric excitation of PM computed using the three-cornered-hat (TCH) method, wherein the internal noise level in a combined solution is reduced to a minimum. We compare the combined series with results obtained from the combined GRACE/GRACE-FO solution provided by COST-G (International Combination Service for Time-variable Gravity Fields) and from the single solution elaborated by the Center for Space Research (CSR). All the gravimetric excitation series are evaluated by comparison with the sum of hydrological and cryospheric signals in geodetically observed PM excitation (called GAO). The results show that by minimizing the internal noise level in the combined excitation series using the TCH method, we can receive higher consistency with GAO than in the case of COST-G and CSR solutions, especially for the non-seasonal oscillations. For this spectral band, we obtained correlations between GAO and the best-combined series as high as 0.65 and 0.72 for the χ1 and χ2 equatorial components of PM excitation, respectively. The corresponding values for seasonal oscillation were 0.91 for χ1 and 0.89 for χ2. The combined series developed in this study explain up to 68% and 60% of overall GAO variability for χ1 and χ2, respectively.
Voters, issues, and party loyalty: the 2022 Italian election under the magnifying glass

The 2022 Italian election marked a historic victory for the centre-right coalition. This camp was spearheaded by Giorgia Meloni’s Brothers of Italy (FDI), with a solid performance of this radical right party across the country. However, considerable nuance emerges by looking at different aspects of the vote, which we do by leveraging original data from the pre-electoral wave of the 2022 CISE/ICCP survey. After recapping both the build-up to and results of the election, we employ this data on these specific fronts. First, we analyse vote flows between the 2018 and 2022 elections in three big cities in Northern, Central, and Southern Italy: Turin, Florence, and Naples. This analysis shows that FDI becomes more competitive in these traditionally unfavourable contexts, although less so in Naples. Second, we analyse data on the configuration of Italian voters’ preferences, which reveals an increasingly progressive electorate in an apparent contradiction with the election results. Third and final, we go deeper into the demand-side picture by assessing the role of sociodemographic characteristics over vote choice, presenting the voter profile of the five largest parties: the three main centre-right parties, the Democratic Party, and the Five Star Movement. Overall, the findings that emerge from our article enhance a more fine-grained understanding of this crucial election in Italy.