Miracle-dz/UniFAR-FTUs huggingface dataset:
Contemporary digital qualitative research in sport, exercise and health: introduction

ABSTRACT This paper provides an introduction to the Special Issue on Digital Qualitative Research in Sport, Exercise and Health. The aim is to spur qualitative researchers to new ways of thinking, new ways of doing, and new ways of representing with the ultimate goal of supporting new ways of knowing, through the lens of digital technologies. First, digital qualitative research is defined and articulated as research that engages in qualitative inquiry and meaning making through digital content, digital contexts and/or digital practices. In using this definition, an analysis of the articles published in sport, exercise and health reveal that most research to date has primarily focused on technology as method, the impacts of technologies on participants, technology as an empirical finding, and/or technology as a medium to represent research findings. Accordingly, and with the intent of advancing digital qualitative research in sport, exercise and health, the concept of practice architectures is used as a heuristic device to articulate the cultural, social and material conditions that potentially support or constrain current and potential future research. Embedded in this discussion, is an overview of the papers in this Special Issue. Overall, these papers showcase the most innovative and world-leading digital qualitative research in sport, exercise and health to date, and provide inspiration and direction for moving forward. The papers use established qualitative concepts, theories and methodologies, offer challenges to existing frameworks, and illustrate contemporary understandings of sport, exercise and health through digital mediums.
Suppressive effects of valproic acid on caudal fin regeneration in adult zebrafish

ABSTRACT Zebrafish can regenerate fins following injury through an epimorphic process that includes the formation of new tissues and reconstruction of the original morphology. In this study, the effects of valproic acid (VPA), a widely used anti-epileptic drug, on fin regeneration were studied after the caudal fin amputation of adult zebrafish. In the control group, zebrafish formed new tissues and reconstructed the original rays 14 days after amputation (dpa). Meanwhile, VPA treatments between 20 and 200 µM following amputation suppressed fin regeneration in a dose-dependent manner and altered morphological characteristics, such as bifurcation and segmentation, in the rays. Compared to the control, VPA also delayed blastema formation and decreased cell proliferation in the mesenchymal area of the regenerated fin. The mRNA expression of lef1, a downstream signaling gene in the Wnt pathway, was transiently increased in the regenerated fin of the control at 2 dpa; the same increase was not observed in the VPA-treated zebrafish. Sodium butyrate (SB), an histone deacetylase activity (HDAC) inhibitor, suppressed the fin regeneration without affecting the morphological characteristics of the regenerated ray. Furthermore, the transient increase of lef1 mRNA was not suppressed in the SB-treated zebrafish. These results suggested that VPA's suppressive effects on fin regeneration are partly mediated through decreased cell proliferation and lef1 mRNA expression.
Essential Oil Composition of Leaf and Rhizome Oil of Alpinia nigra (Gaertner) B.L.Burtt. from Northeast India

Abstract The essential oils of the leaves and rhizomes of Alpinia nigra (Gaertner) B.L. Burtt. , family Zingiberaceae, were obtained by hydrodistillation and yielded 0.02% and 0.4%, respectively. The oils were analyzed for their chemical composition by capillary GC and GC/MS. A total of 18 compounds were identified representing about 96.4% of leaf and 97.8% of rhizome oils, respectively. 1,8-cineole was the major component in both leaf (25.4%) and rhizome (34%) oils. In addition, β-pinene (15.1%), camphor (15.3%), carotol (7.3%), α-pinene (7.8%) and camphene (7.0%) were also present in leaf oil, whereas in the rhizome oil α-fenchyl acetate (13.1%), α-terpineol (9.6%), β-pinene (8.1%) and camphene (7.0%) were the other main constituents.
A topological approach of multiple correspondence analysis

ABSTRACT Topological multiple correspondence analysis (TMCA) studies a group of categorical variables defined on the same set of individuals. It is a topological method of data analysis that consists of exploring, analyzing, and representing the associations between several qualitative variables in the context of multiple correspondence analysis (MCA). It compares and classifies proximity measures to select the best one according to the data under consideration, then analyzes, interprets, and visualizes with graphic representations, the possible associations between several categorical variables relating to the known problem of MCA. Based on the notion of neighborhood graphs, some of these proximity measures are more-or-less equivalent. A topological equivalence index between two measures is defined and statistically tested according to the degree of description of the associations between the modalities of these qualitative variables. We compare proximity measures and propose a topological criterion for choosing the best association measure, adapted to the data considered, from among some of the most widely used proximity measures for categorical data. The principle of the proposed approach is illustrated using a real dataset with conventional proximity measures for binary variables from the literature. The first step is to find the proximity measure that can best be adapted to the data; the second step is to use this measure to perform the TMCA.
Burnout and Anxiety Among Trauma Nursing Specialties in a Rural Level I Trauma Center

Supplemental Digital Content is Available in the Text. Background: Burnout and anxiety compromise physical and mental well-being of nurses and jeopardize patient safety. Personal, professional, and workplace characteristics have been associated with burnout and anxiety across diverse practice settings, yet none in rural, community trauma centers. We sought to identify the severity and predictors of burnout and anxiety in the trauma nursing staff of a rural Level I trauma center. Methods: A convenience sample of trauma nurses from the emergency department (ED), intensive care unit (ICU), and trauma ward was voluntarily surveyed using a demographic questionnaire, the Maslach Burnout Inventory (MBI) subscales: depersonalization (DP), emotional exhaustion (EE), and reduced personal accomplishment, as well as the Generalized Anxiety Disorder seven-item (GAD-7) scale. Multivariable linear regression identified the significant predictors of burnout and anxiety. Results: Ninety-six nurses completed surveys (response rate: 83.5%). Married or divorced status, and ICU or trauma ward job assignments were associated with significantly lower adjusted DP scores. Thus, the model-predicted score for a single ED nurse was 15 versus a predicted score of 7 for a divorced ICU or trauma ward nurse, p < . 001 for each group. The GAD-7 model demonstrated that race/ethnicity (Asian compared with White, coefficient: −5.06, p = .03), number of children (2 compared with 0, coefficient: −2.54, p = .02), and job tenure (5–10 years vs. <2, coefficient: −3.18, p = .01) were each associated with fewer GAD-7 points. Conclusion: Depersonalization and anxiety vary across the trauma nursing workforce based on identifiable personal and work-related risk factors. Group-specific, targeted interventions are needed to effectively reduce burnout and anxiety in trauma nursing staff.
Improved Efficiency of Desorption of Oxygenated Solvents from Activated Charcoal Using a New Polar Additive to Carbon Disulfide

Abstract In industrial operations where workers may be exposed to a mixture of polar and nonpolar organic vapors, such as in spray painting, the use of carbon disulfide as the desorption liquid for charcoal tubes or diffusion badges is inadequate. Desorption efficiencies for some polar analytes may be low, and a loading dependency of the desorption efficiency may be present, making quantitation difficult. Many researchers have added polar substances to carbon disulfide or used alternative polar desorption solvents or schemes; however, often the polar additive or solvent may be a compound of interest or interfere in some way with the analysis. Numerous polar and nonpolar solvents were found on charcoal tube and diffusion badge samples collected during automobile assembly spray painting operations. Methanol in carbon disulfide was tried as a desorption solvent but was found to be inadequate. Considerable improvement in desorption efficiencies for the polar analytes was obtained when 2-(2-butoxyethoxy) ethan.
Prevalence of Disease-Related Undernutrition on Hospital Admission and Its Association With Functionality and Length of Hospital Stay in Multiethnic Suriname

Our aim was to describe the prevalence of disease-related undernutrition (DRU) on admission to a department of surgery in Suriname and to explore its association with ethnicity and adverse outcomes. All patients 18 years or older who were not pregnant were invited to participate. Data were collected on weight (history), length, fat-free mass index (FFMI) using bioimpedance analysis, and ethnicity. Age, sex, and diagnosis data were extracted from the medical files. Associations between DRU and ethnicity, functionality, and length of hospital stay were assessed using logistic and Cox regression analyses adjusting for age, sex, diagnosis, and disease severity. The study population of 351 participants revealed 46% were undernourished, 31% had unintended weight loss (UWL), and 27% had a low FFMI. DRU and low FFMI were associated with low handgrip strength, but UWL was not. DRU, UWL, and low FFMI were associated with length of stay. Determinants of DRU seemed to vary between ethnic groups. The prevalence of DRU was high, and nutrition protocols should be implemented to increase awareness and limit adverse outcomes. Further research is needed to reveal whether ethnicity should be part of the DRU risk assessment.
Detecting Kernel Memory Leaks in Specialized Modules with Ownership Reasoning

develop a new ownership reasoning mechanism that employs enhanced escape analysis and consumer-function analysis to infer expected release locations. By applying K-M E LD to the Linux kernel, we confirm its effectiveness: it finds 2 18 n ew b ugs, w ith 4 1 C VEs assigned. Out of those 218 bugs, 115 are in specialized modules.
Variational Prototype Inference for Few-Shot Semantic Segmentation

In this paper, we propose variational prototype inference to address few-shot semantic segmentation in a probabilistic framework. A probabilistic latent variable model infers the distribution of the prototype that is treated as the latent variable. We formulate the optimization as a variational inference problem, which is established with an amortized inference network based on an auto-encoder architecture. The probabilistic modeling of the prototype enhances its generalization ability to handle the inherent uncertainty caused by limited data and the huge intra-class variations of objects. Moreover, it offers a principled way to incorporate the prototype extracted from support images into the prediction of the segmentation maps for query images. We conduct extensive experimental evaluations on three benchmark datasets. Ablation studies show the effectiveness of variational prototype inference for few-shot semantic segmentation by probabilistic modeling. On all three benchmarks, our proposal achieves high segmentation accuracy and surpasses previous methods by considerable margins.
Financial Systems Theory and Control of Finances: The Mediating Role of Psychological Empowerment in the Relationship between Transformational Leadership and Employee Engagement: An Evidence from Vietnam

Employee engagement has been closely linked to work attitudes (e.g., job satisfaction, intentions to quit, withdrawal), employees' innovation, organizational success and financial performance (e.g., profits, shareholder return) and, therefore, getting much attention from academia and practitioner communities. Additionally, to have a full insight in employees, organizations have to take care of psychological side of employees, which manifests in psychological empowerment. This study investigates the mediating role of psychological empowerment in the relationship between transformational leadership and employee engagement in the context of Vietnam. Data were collected through a survey conducted in Vietnam using 254 respondents who are employees and managers. A researcher-administered questionnaire survey method was used for data collection. The findings reveal that Psychological Empowerment is significantly related with Transformational leadership and Employee Engagement; there is a direct effect of Psychological Empowerment and Employee Engagement; and Transformational leadership not only has a direct impact on Employee Engagement, but also has indirect effect through Psychological Empowerment as a mediating variable. These findings have several implications also for human resource practices in organizations. It is expected that this study provides valuable information to consider in business practice for the development of interventions aimed at mitigating turnover behavior and maximizing organizational performances through an engaged workforce.
Impact Of Parallelism And Virtualization On Task Scheduling In Cloud Environment

-Today’s, cloud computing has placed itself in every field of the IT industry. It provides infrastructure, platform, and software as an amenity to users which are effortlessly available via the internet. It has a large number of users and has to deal with a large number of task executions which needs a suitable task scheduling algorithm. Virtualization and parallelism are the core components of cloud computing for optimization of resource utilization and to increase system performance. Virtualization is used to provide IT infrastructure on demand. To take more advantages of virtualization, parallel processing plays an important role to improve the system performance. But it is important to understand the mutual effect of parallel processing and virtualization on system performance. This research helps to better understand the effect of virtualization and parallel processing. In this paper, we studied the effect of parallelization and virtualization for the scheduling of tasks to optimize the time and cost. We found that virtualization along with parallelization boosts the system performance. The experimental study has been done using the CloudSim simulator.
UTILIZING WASTE MATERIALS PROCUREMENT FOR ADSORPTION OF CHROMIUM ONTO BIO-MATRIX FROM RICE HUSK TO MINIMIZE WATER CONTAMINATION

Agricultural waste has been explored as a productive adsorbent for efficient metal removal due to their lower cost. The presence of various chemical functional groups in agricultural wastes especially phenolic, amino, carbonyl, alcoholic and sulfhydryl group etc. facilitates the removal of heavy metals as they tend to form metal complexes or chelates by reacting with them. Biosorption is a process of removing metal ions using biological agents and it includes processes like chemisorption, complexation, adsorption on the surface, diffusion through pores and ion exchange etc. To enhance the adsorption ability of these adsorbents, chemical modification is required. Specific chemicals such as mineral and organic acids, bases, oxidising agents or polymeric acids are used for modification of adsorbents. The purpose of this article is to show the removal efficiency of rice husk based hydrogel as a bio-adsorbent to remove Cr ions. Characterisation of the bio-adsorbent is done using FTIR and SEM before and after adsorption in order to explore number and position of the functional groups present on the adsorbent surface for Cr(VI) binding and changes in adsorbent surface morphology.
Users’ Guides to the Medical Literature XVIII. How to Use an Article Evaluating the Clinical Impact of a Computer-Based Clinical Decision Support System

CLINICAL SCENARIO It is 7 AM, and medical rounds are starting on university hospital ward 3B. In the past 24 hours of your residency, you have transferred 2 critically ill patients to the intensive care unit; accepted 11 patients to your medical service; examined and revised medication orders for 22 patients; placed 9 intravascular catheters; written 35 notes; and reviewed, categorized, and acted on more than 300 new pieces of laboratory and radiology data. You were planning to ask the infectious disease specialist about a patient, but he seems very busy, and the broad-spectrum antibiotic regimen you prescribed should suffice. You were just told that you ordered total parenteral nutrition for the wrong patient. While deciding which patient should receive parenteral nutrition, you realize that the calculations for the amino acid concentration are erroneous. After the first 5 minutes of your first patient presentation, the senior physician asks you details from the patient’s past medical history. You wish you could refer to your admission note, but you couldn’t access it before your rounds because a utilization review clerk had the chart. The chair of medicine keeps promising to install computers to help manage all of this information, but she is limited by the budget squeeze. She needs proof that computerization will improve patient care to justify such a major expense. She asks you to help. You remember reading, in one of the many journals piled up at home, about how computers can be used to provide decision support leading to improved patient outcomes. If you can show that computers improve patient care, maybe the hospital administration will see the expense as an investment that could reduce costs.
Effects of Robot-Aided Rehabilitation on Improving Ankle and Balance Performance of Stroke Survivors: A Randomized Controlled Trial

Background: Stroke survivors with impaired ankle control due to stiff plantar flexors often experience abnormal posture control, which affects balance and locomotion. Forceful and safe stretching under intelligent control may decrease ankle stiffness and improve balance. The purpose of this study was to investigate the effects of robot-aided ankle rehabilitation on stroke survivors with ankle spasticity and the correlations between biomechanical properties and balance in these participants. Methods: Twenty patients poststroke with ankle spasticity received 20 minutes of stretching treatment daily over 2 weeks. The study group used a robot-aided ankle rehabilitation and the control group received manual stretching. Outcome measures included biomechanical, clinical evaluations, and the Pro-Kin balance test.Results: The study group significantly improved in joint stiffness and range of motion of dorsiflexion, Modified Ashworth Scale (MAS), trajectory lengths, elliptical trajectory, standard deviation medial/lateral, average speed forward/backward with eyes closed, and standard deviation forward/backward with eyes open in the Pro-Kin test (P<.05), but no significant changes were found in the control group in above indexes; significant decreases were found in the control group in trajectory length with eyes open (P<.05); dorsiflexion stiffness was positively correlated with the Pro-Kin test outcomes with eyes open and the MAS; no between-group significant changes were found except the activities of daily living after training (P<.05). Conclusions: Ankle stiffness may affect balance poststroke significantly. The robot-aided ankle rehabilitation improved biomechanical properties of the spastic ankle including stiffness, and it may help improve balance post-stroke.Trial registration: www.chictr. org.cn ChiCTR2000030108. Registered 23 February 2020. Retrospectively registered.
Optimizing Training Data Selection for Decision Trees using Genetic Algorithms

Summary Genetic algorithms (GAs) have recently been used as a search method for training set selection in supervised machine learning. The assumption is made that not all the data are equally useful in training supervised algorithms. In this paper, we empirically study the performance of classical GA for selecting a ‘good’ training set for decision tree classifiers. We also discuss different fitness functions and their influence on the results. A set of widely used classification datasets from Kaggle and UCI machine learning repository are used. Empirical results show that improved generalization can indeed be obtained using this approach.
Molecular dynamics simulation of gaseous–liquid phase transitions of soluble and insoluble surfactants at a fluid interface

Molecular dynamics simulations are used to study the formation of gaseous and liquid expanded phases of surfactants on a liquid/vapor interface. Both insoluble and soluble surfactants are considered, modeled as freely jointed chains in a monatomic solvent with appropriate Lennard–Jones interactions. For both insoluble and soluble cases our results indicate that the surface tension as a function of coverage shows a plateau close to the clean interface value until a critical surface concentration, beyond which the surface tension lowers steeply. For the soluble case, we also detail a complete Gibbs construction for the surface excess and report an adsorption isotherm. Snapshots of the positions of the molecules, together with analysis of correlation functions, show that these model surfactants assemble from solution and exhibit coexistence in the plateau of isolated surfactants and liquid aggregates. We have identified this coexistence as a gas–liquid phase transition, in agreement with recent experimental .