Miracle-dz/UniFAR-FTUs huggingface dataset:
Predictors of Knowledge-Sharing Behavior for Teams in Extreme Environments

Knowledge-sharing behavior seems to be important for team functioning and performance. A theoretical model explaining antecedents that impact knowledge-sharing behavior and its interplay with shared knowledge within teams was investigated. In the present study, we examined the effect of the individual’s intention and five organizational antecedents (team communication, perceived appraisal, organizational communication, organizational support, and social ties) on knowledge-sharing behavior. Five production and five maintenance teams (123 participants altogether) working in a steel mill took part in the study to investigate the assumed relationships. The results indicate that knowledge-sharing behavior is positively affected by intention, organizational communication, and social ties. in turn, knowledge-sharing behavior had a significant impact on the shared knowledge corresponding to the four types of shared mental models (task, equipment, interaction, team), and as a trend, teams with a higher knowledge-sharing behavior seem to have greater shared mental model similarity. The implications of the findings are discussed in terms of further research in production settings and with regard to developing a knowledge-sharing intervention.
Morphometric analysis and genetic diversity in Pistacia species populations using sequence related amplified polymorphism

The Anacardiaceae family includes 11 or more species, including the genus Pistacia. Pistacia vera L. is the most commercially developed of them all, thanks to its tasty nut seeds. Pistacia khinjuk Stocks, Pistacia atlantica Dsef, Pistacia vera, Pistacia eurycarpa Yalt. (Pistacia atlantica subsp. Kurdica Zoh.) and all have their origins in Iran. The present study aimed to investigate the SRAP (Sequence-related amplified polymorphism) markers in 13 wild pistachio accessions, which comprised three different species: Pistacia khinjuk, Pistacia vera, and Pistacia atlantica. Through polymerase chain reaction amplifications (PCR) of three Pistacia species, a total of 170 (Number of total loci) (NTL) DNA bands were obtained. Ten different selective primers were combined to generate these bands. The number of amplified pieces ranged from nine to twenty-six. The projected impartial gene diversity (UHe) ranged from 0.053 (Pistacia khinjuk) to 0.417 (Pistacia khinjuk) (Pistacia atlantica subsp. Kurdica). The genetic similarity of three species is estimated to be between 0.61 to 0.90. Two significant groupings emerged from the clustering findings: Pistacia khinjuk and Pistacia atlantica subsp. Kurdica exhibited the least similarity in the SRAP markers study. Our findings revealed excellent molecular recognition of all genotypes tested, indicating that a significant amount of genetic variety exists among pistachio accessions. This discovery might be useful in breeding management techniques for genetic preservation and cultivar improvement.
Detecting Diabetic Retinopathy in Fundus Images using Combined Enhanced Green and Value Planes (CEGVP) with k-NN

Diabetic Retinopathy (DR) is a disease that causes damage to the blood vessels of the retina, especially in patients having high uncontrolled blood sugar levels, which may lead to complications in the eyes or loss of vision. Thus, early detection of DR is essential to avoid complete blindness. The automatic screenings through computational techniques would eventually help in diagnosing the disease more accurately. The traditional DR detection techniques identify the abnormalities such as microaneurysms, hemorrhages, hard exudates, and soft exudates from the diabetic retinopathy images individually. When these abnormalities occur in combination, it becomes difficult to predict them and the individual detection (traditional 4 class classification) accuracy decreases. Hence, there is a need to have separate combinational classes (16 class classification) that help to classify these abnormalities in a group or one by one. The objective of our work is to develop an automated DR prediction scheme that classifies the abnormalities either individually or in combination in retinal fundus images. The proposed system uses Combined Enhanced Green and Value Planes (CEGVP) for processing the fundus images, Principal Component Analysis (PCA) for feature extraction, and k-nearest neighbor (k-NN) for classification of DR. The suggested technique yields an average accuracy of 97.11 percent using a k-NN classifier. This is the first time that a 16-class classification is initiated that precisely gives the ability and flexibility to map the combinational complexity in a single step. The proposed method can assist ophthalmologists in efficiently detecting the abnormalities and starting the diagnosis on time. Keywords—Combined enhanced green and value plane; diabetic retinopathy; fundus image; image processing; k-NN; principal component analysis
Hybrid Energy to Drive Renewable Energy Diversity in Bibliometric Analysis

Hybrid energy is a combination of two or more energy sources, some of which can be sourced from several renewable energies combined, or combined with fossil energy. Renewable energy diversity is implemented through the development of hybrid energy in order to obtain new energy sources that are more effective and efficient. Bibliometric analysis is directed to analyze topics that have novelty according to the time period of publication based on qualitative methods. Analysis of scientific literature sourced from scientific journals published in the last ten years with the topic of hybrid energy. The results of study stated that several topics that had novelty were obtained to be used in the development of further knowledge and technology, especially in the development of hybrid energy including energy density, renewable energy system, supercapacitor, storage system, algorithm, electric vehicle, and energy system. The development of hybrid energy is very important to be followed up in order to get more comprehensive source of energy diversity and has full support for development of green technology that has relevance in sustainable development.
ASM-ROBOT: A Cyber-Physical Home Automation Controller with Memristive Reconfigurable State Machine

In the next 5 to 10 years, digital Artificial Intelligence with Machine Circuit Learning Algorithms (MCLA) will become the mainstream in complex automated robots. Its power concerns, ethical perspectives, including the issues of digital sensing, actuation, mobility, efficient processcomputation, and wireless communication will require advanced neuromorphic process variable controls. Existing home automated robots lack memristic associative memory. This work presents Cyber-Physical Home Automation System (CPHAS) using Memristive Reconfigurable Algorithmic State Machine (MRASM) chart. A process control architecture that supports Concurrent Wireless Data Streams and Power-Transfer (CWDSPT) is developed. Unlike legacy systems with powersplitting (PS) and time-switching (TS) controls, the MRASMROBOT explores granular wireless signal controls through unmodulated high-power continuous wave (CW). This transmits infinite process variables using Orthogonal Space-Time Block Code (OSTBC) for interference reduction. The CWDSPT transmitter and receiver circuit design for signal processing are implemented with complexity noise-error reduction during telemetry data decoding. Received signals are error-buffered while gathering control variables' status. Transceiver Memristive neuromorphic circuits are introduced for computational acceleration in the design. Hardware circuit design is tested for system reliability considering the derived schematic models for all process variables. Under small range space diversity, the system demonstrated significant memory stabilization at the synchronous iteration of the synaptic circuitry. Keywords—Cloud computing; cyber-physical systems; complex robot; computational science; IoT; machine learning
Prevalence and Predictors of Overweight and Obesity Among Adolescents in Seremban, Negeri Sembilan, Malaysia

Introduction: Obesity is recognized as a serious public health threat. Recent evidence has warned of the alarming rise in the prevalence of childhood overweight and obesity throughout the world. This study aimed to determine the prevalence of overweight and obesity, and its associations with socio-demographic, behavioral, and psychosocial factors among school-going adolescents in Seremban, Negeri Sembilan. Methods: Cross-sectional study was conducted. A total of 2,221 adolescents were randomly selected from eight secondary schools. A questionnaire was administered to assess socio-demographic profiles, meal patterns, physical activity level, self-efficacy, self-esteem, body size satisfaction, perception of body weight status, depression, anxiety, stress, and nutrition knowledge. Bodyweight and height were measured and BMI-for-age z scores were computed to determine the body weight status. Bivariate analysis and multivariate logistic regression were used for the data analysis. Results: The prevalence of overweight among the participants in this study was 17.0%, while the prevalence of obesity was 14.9%. The significant predictors of overweight and obesity in this study were breakfast skipping, low physical activity level, low self-efficacy scores in terms of healthy eating, weight and physical activity, body dissatisfaction, and perception of large body size. Conclusion: The results emphasize the need to broaden the scope of nutrition guidelines, public health policies, and programs to address overweight and obesity among adolescents in Malaysia. The findings also suggest that health education programs should cover practical advice for modifying healthy eating behaviors, increasing physical activity, as well as matters on body image and body satisfaction.
Intra Pleural Streptokinase in Management of Empyema, Is It Beneficial?

Background: Around 15-20 % of patients suffering from parapneumonic effusion their condition is complicated by empyema. Despite treatment using aggressive antibiotics, it is associated with significant morbidity and mortality. Drainage of the collection in early stage by intercostal tube with administration of proper antibiotics according to the culture and sensitivity is considered the cornerstone of treatment. Intrapleural fibrinolytics as streptokinase is gaining more popularity. Objective: This study aimed to show the advantages of adding streptokinase to the protocol of conservative management of empyema by studying its effectiveness and safety. Patients and Methods: Our study was conducted on 58 patients on retrospective analytical manner through the period from December 2017 to March 2021 at Kasr Alainy Hospitals. All patients in this study were complaining of empyema following pneumonia. The diagnosis was based on frank pus aspiration from the pleural collection appeared on chest radiography (X-ray, ultrasonography or CT), confirmed by the results of bacteriological culture and gram staining of retrieved samples. Those patients received intrapleural instillation of streptokinase. Results: Mean age of patients was 49. 2 years. The majority of them were males (n=42, 72. 4 %) and females were 16(27. 6 %). According to the causative organisms, Staphylococcus aureus was the commonest (n=31), kleibsiella (n=6), E. coli (n=5), pseudomonas (n=3), mixed (n=2) and others (n=2). Successful treatment occurred in 43 patients (74.1%), partial success in 13 patients (22.4%) and failure of treatment in 2 patients (3.5 %). Conclusion: In our study, intrapleural instillation of fibrinolytics was a safe and effective procedure in management of empyema with decreased incidence of surgical referral.
SAFETY MANAGEMENT

The design of complex systems, as in the case of autonomous vehicles, requires a specialized systems engineering methodology and an adapted modelling framework. In particular, the integration of non-functional requirements, as important as the Safety, requires from this methodological framework the well-adapted semantic expression of constraints as well as their traceability during all phases of analysis, design and implementation. This paper focuses on the study of model-based autonomous system design and investigates the design flows and initiatives grasping with this complex computational model. The specialization of the ARCADIA methodology will be illustrated in a real industrial case.
Semantic and Stylistic Problems Encountered in Translating Qur'anic Digression “Iltifât” into English: A Contrastive Linguistic Study

This research paper aims to explore the digression ''Iltifât'' as one of the effective rhetorical devices used generally in the language of the Holy Quran. The purposive sample of the study was selected randomly from Qur’anic verses containing Iltifāt or digression and their renditions by three translators, namely, Abdel Haleem, Khan Hilali, and Pickthall. The study's findings revealed that the translations of the three translators adopted several translation strategies such as literal translation, couplet translation to render the Qur'anic digression, or shifting (Iltifat) expressions into English. Moreover, the study also indicated that both literal translation and couplet translation are not always adequate for translating the Qur’anic digression or shifting (Iltifat) expressions because they have not successfully maintained the meaning of the Qur’anic Arabic digression ''Iltifât'' (ST) into the Qur’anic digression ''Iltifât'' English version (TT).
Suppression of acoustic reflection artifact in endoscopic photoacoustic tomographic images based on approximation of ideal signals

BACKGROUND: In endoscopic photoacoustic tomography (EPAT), the photoacoustically induced ultrasonic wave reflects at tissue boundaries due to the acoustic inhomogeneity of the imaged tissue, resulting in reflection artifacts (RAs) in the reconstructed images. OBJECTIVE: To suppress RAs in EPAT image reconstruction for improving the image quality. METHODS: A method was presented to render the cross-sectional images of the optical absorption with reduced RAs from acoustic measurements. The ideal photoacoustic signal was recovered from acoustic signals collected by the detector through solving a least square problem. Then, high-quality images of the optical absorption distribution were reconstructed from the ideal signal. RESULTS: The results demonstrated the improvement in the quality of the images rendered by this method in comparison with the conventional back-projection (BP) reconstructions. Compared with the short lag spatial coherence (SLSC) method, the peak signal-to-noise ratio (PSNR), normalized mean square absolute distance (NMSAD), and structural similarity (SSIM) were improved by up to 8%, 20%, and 5%, respectively. CONCLUSIONS: This method was capable of rendering images displaying the complex tissue types with reduced RAs and lower computational burden in comparison with previously developed methods.
Transient stability studies of power system with shared transmission of wind power and thermal power

In this paper, transient stability of power system with shared transmission of wind power and thermal power (PSWT) is studied. First, the wind disturbance models are built. And the wind turbine generator models are established, which include wind turbine with squirrel-cage induction generator (IG) and wind turbine with doubly fed induction generator (DFIG). Second, the influence of various types of wind farms with various types of wind disturbance on the system transient stability is studied in details. Especially the impact of wind disturbance accompany with the fault on the system is focused on. The mechanism of simulation results is discussed.Third, based on the Gansu power grid, the simulation and the Prony analysis results show that wind speed variation during system transient process should be considered for getting more accurate and correct results of transient stability analysis. And IG wind farms with gust wind disturbance can have the worst impact on the transient stability of PSWT.
Multimodality Imaging in Ischemic Chronic Cardiomyopathy

Ischemic chronic cardiomyopathy (ICC) is still one of the most common cardiac diseases leading to the development of myocardial ischemia, infarction, or heart failure. The application of several imaging modalities can provide information regarding coronary anatomy, coronary artery disease, myocardial ischemia and tissue characterization. In particular, coronary computed tomography angiography (CCTA) can provide information regarding coronary plaque stenosis, its composition, and the possible evaluation of myocardial ischemia using fractional flow reserve CT or CT perfusion. Cardiac magnetic resonance (CMR) can be used to evaluate cardiac function as well as the presence of ischemia. In addition, CMR can be used to characterize the myocardial tissue of hibernated or infarcted myocardium. Echocardiography is the most widely used technique to achieve information regarding function and myocardial wall motion abnormalities during myocardial ischemia. Nuclear medicine can be used to evaluate perfusion in both qualitative and quantitative assessment. In this review we aim to provide an overview regarding the different noninvasive imaging techniques for the evaluation of ICC, providing information ranging from the anatomical assessment of coronary artery arteries to the assessment of ischemic myocardium and myocardial infarction. In particular this review is going to show the different noninvasive approaches based on the specific clinical history of patients with ICC.
Comparison of Unnoticed Glove Perforations during Minimally Invasive versus Open Surgeries: A Systematic Review and Meta-Analysis

Objective: Various studies have depicted the incidence of glove perforations during open (OS) and minimally invasive surgeries (MIS). The aim of this meta-analysis was to compare the incidence of macroscopic and microscopic glove perforations during MIS and OS. Methods: The review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Scientific databases (PubMed, Web of Science, Scopus, and EMBASE) were systematically searched for comparative studies depicting the glove perforation rates during MIS and OS. Risk ratios (RR) were calculated for both the outcomes (dichotomous) and the Mantel–Haenszel method was utilized for the estimation of pooled RR. The methodological quality assessment was performed by two independent investigators using the Downs and Black scale. The main outcomes of the study were the proportion of gloves with gross (macroscopic) perforations and the proportion of gloves with microscopic perforations. Results: Four comparative studies including a total of 1428 gloves (435 from the MIS group) were included. Pooling the data demonstrated no difference in the incidence of macroscopic glove perforations among the MIS and OS groups (RR 0.57, 95% CI 0.21 to 1.54, p = 0.27). On the other hand, the incidence of microscopic perforations was significantly higher in the OS group versus the MIS group (RR 0.72, 95% CI 0.55 to 0.95, p = 0.02). However, all the studies had a moderate risk of bias. Conclusions: When compared to OS, the macroscopic glove perforation rate during MIS showed no significant difference. The incidence of microscopic glove perforations was significantly higher during OS as compared to MIS. However, due to the moderate risk of bias of the available comparative studies, the level of evidence of these studies is limited.
Barriers and Facilitators for Population Genetic Screening in Healthy Populations: A Systematic Review

Studies suggest that 1–3% of the general population in the United States unknowingly carry a genetic risk factor for a common hereditary disease. Population genetic screening is the process of offering otherwise healthy patients in the general population testing for genomic variants that predispose them to diseases that are clinically actionable, meaning that they can be prevented or mitigated if they are detected early. Population genetic screening may significantly reduce morbidity and mortality from these diseases by informing risk-specific prevention or treatment strategies and facilitating appropriate participation in early detection. To better understand current barriers, facilitators, perceptions, and outcomes related to the implementation of population genetic screening, we conducted a systematic review and searched PubMed, Embase, and Scopus for articles published from date of database inception to May 2020. We included articles that 1) detailed the perspectives of participants in population genetic screening programs and 2) described the barriers, facilitators, perceptions, and outcomes related to population genetic screening programs among patients, healthcare providers, and the public. We excluded articles that 1) focused on direct-to-consumer or risk-based genetic testing and 2) were published before January 2000. Thirty articles met these criteria. Barriers and facilitators to population genetic screening were organized by the Social Ecological Model and further categorized by themes. We found that research in population genetic screening has focused on stakeholder attitudes with all included studies designed to elucidate individuals’ perceptions. Additionally, inadequate knowledge and perceived limited clinical utility presented a barrier for healthcare provider uptake. There were very few studies that conducted long-term follow-up and evaluation of population genetic screening. Our findings suggest that these and other factors, such as prescreen counseling and education, may play a role in the adoption and implementation of population genetic screening. Future studies to investigate macro-level determinants, strategies to increase provider buy-in and knowledge, delivery models for prescreen counseling, and long-term outcomes of population genetic screening are needed for the effective design and implementation of such programs. Systematic Review Registration: https://www.crd. york.ac. uk/prospero/display_record. php? ID=CRD42020198198
A Bayesian networks approach for event tree time-dependency analysis on phased-mission system

[1, 4, 13, 23]. PMS reliability attracts substantial attentions, and various techniques have been developed to deal with the phase-dependency. The analytical techniques for the PMS can be classified into two categories: combinatorial models (e.g., mini-components, sum of disjoint phase products, BDD) and state-space transition models (e.g., Markov models, Petri nets) [19, 21]. The combinatorial method is based on the
CovSeg-Unet: End-to-End Method-based Computer-Aided Decision Support System in Lung COVID-19 Detection on CT Images

COVID-19 epidemic continues to threaten public health with the appearance of new, more severe mutations, and given the delay in the vaccination process, the situation becomes more complex. Thus, the implementation of rapid solutions for the early detection of this virus is an immediate priority. To this end, we provide a deep learning method called CovSeg-Unet to diagnose COVID-19 from chest CT images. The CovSeg-Unet method consists in the first time of preprocessing the CT images to eliminate the noise and make all images in the same standard. Then, CovSeg-Unet uses an end-to-end architecture to form the network. Since CT images are not balanced, we propose a loss function to balance the pixel distribution of infected/uninfected regions. CovSeg-Unet achieved high performances in localizing COVID-19 lung infections compared to others methods. We performed qualitative and quantitative assessments on two public datasets (Dataset-1 and Dataset-2) annotated by expert radiologists. The experimental results prove that our method is a real solution that can better help in the COVID-19 diagnosis process © 2022,International Journal of Advanced Computer Science and Applications.All Rights Reserved