Miracle-dz/UniFAR-FTUs huggingface dataset:
THE EFFECT OF ORGANIZATIONAL COMMITMENT AND PROFESSIONAL COMMITMENT ON EMPLOYEE WORK MOTIVATION AND ITS IMPACT ON PERFORMANCE OF CUT NYAK DHIEN HOSPITAL EMPLOYEES

This study intends to examine the effect of organizational commitment and professional commitment on work motivation and their impact on employee performance at the Cut NyakDhien General Hospital in Aceh Barat District, Indonesia. The population of this study was all medical and non-medical employees at Cut NyakDhien Hospital, totaling 1773 people. The sampling technique used in this research was proportional stratified random sampling accompanied by the use of the Slovin formula so as to produce a total sample of 326 people. Data were collected using a questionnaire and analyzed using the Structural Equation Modeling (SEM) method. The test results prove that organizational commitment and professional commitment can significantly affect work motivation and employee performance, work motivation can significantly affect the performance of Cut NyakDhien Hospital employees, and work motivation can be a partial mediator on the model of the influence of organizational commitment and professional commitment on the performance of Cut NyakDienHospital employees. The interesting thing is that it is proven that the model of improving employee performance at Cut NyakDhien Hospital can be done by strengthening organizational commitment and professional commitment so that it will be able to directly affect the increase in work motivation, and influence both directly and indirectly the increase in employee performance with work motivation as a mediator. The findings can be used as academic references and future researchers are expected to be able to develop this tested model by adding other moderating variables such as job satisfaction, knowledge management, and knowledge sharing. Keyword: Organizational Commitment, Professional Commitment, Work Motivation, and Employee Performance.
Observer-Based Bipartite Formation Control for MASs With External Disturbances Under Event-Triggered Scheme

This brief investigates the bipartite time-varying formation tracking control for multi-agent systems with cooperative-antagonistic interactions and external disturbances under event-triggered scheme. To deal with the external disturbances, an extended state observer is employed to illustrate the control protocol. Then, a time-varying formation control protocol is developed under event-triggered scheme to eliminate continuous communication, further reducing unnecessary computational cost successfully. Besides, Zeno behavior is verified to be excluded and convergence analysis of proposed protocol is demonstrated by the lights of Lyapunov stability theory. Finally, the effectiveness of the proposed protocol is indicated by a numerical simulation, where the agents realize two time-varying antagonistic sub-formations with disturbance rejection under event-triggered scheme.
COVID-19: pathogenic mechanism, detection, and treatment

COVID-19, which broke out in 2019 in China, is caused by SARS-CoV-2. According to the latest WHO real-time statistics, as of 1:19 p.m. BST on April 22, there were 142557268 cumulative new confirmed cases of coronavirus pneumonia and 3033798 cumulative deaths worldwide. Therefore, it is significant to understand the structure and the pathogenic mechanism of SARS-CoV-2, which is helpful to understand the diagnosis and treatment of sars-cov-2. We primarily investigate related sources on Pubmed and related scholar websites. We found some antiviral drugs such as lopinavir, chloroquine, and its derivative hydroxychloroquine, remdesivir, and arbidol have great potential in the treatment of COVID-19. However, some of them have a serious adverse reaction, reminding us to use them with caution.
The association between food diversity and serum antioxidant indices in cataract patients compared to healthy subjects

Background: Cataract is a chronic disorder that is related to antioxidant–oxidant imbalance situation. We aimed to investigate the association between food diversity and serum antioxidant and oxidant indices in cataract patients compared to healthy subjects. Materials and Methods: In this case–control study, ninety volunteers (aged > 50 years) were divided into the cataract (n = 45) and healthy control (n = 45) groups. Anthropometric variables, physical activity and stress levels, food diversity score, serum total oxidant capacity (TOC), and total antioxidant capacity (TAC) measurements were done for all participants. Results: Serum TAC, even after adjustment for stress level, was significantly higher in healthy people compared to cataract patients (P < 0.001). In addition, serum TOC was significantly lower in healthy controls compared to cataract patients (P < 0.002). In healthy group, there was a weak significant positive association between serum TAC and meats group diversity (r = 0.149, P = 0.047). In addition, there was a moderate negative association between meats group diversity and TOC in the healthy controls (r = −0.712, P = 0.041). In the cataract group, there was a significant negative association between serum TOC and diversity score of fruits (r = −0.811, P = 0.017) and meats group (r = −0.926, P = 0.046) as well as total score of food diversity (r = −0.466, P = 0.003). Conclusion: It seems that increase in total dietary diversity and food groups' diversity can have a beneficial effect on oxidant situation among cataract patients.
Improving End-to-end Throughput in Multi-Hop Wireless Networks With Cut-Through Capability

Wireless cut-through transmission, based on in-band full-duplex (FD) technique, has a great potential to improve the end-to-end throughput of a multi-hop wireless network via enabling simultaneous multi-hop relaying transmissions in the same frequency band. Different from single-hop relaying transmission in traditional half-duplex multi-hop network, cut-through transmission has multiple relaying transmission modes, which makes it more difficult to achieve the maximum end-to-end throughput via improving the spatial reuse in a multi-hop wireless network. The goal of this paper is to improve the end-to-end throughput in multi-hop wireless networks with cut-through capability. In particular, we first establish an effective analytical model and find that the achievable end-to-end throughput is mainly determined by the cut-through mode, the spatial reuse factor, the protocol overhead, and the channel rate. Then, we give a comprehensive analysis for these factors in a string-topology multi-hop wireless network. In order to improve the end-to-end throughput in a practical distributed multi-hop wireless network, we design a low-overhead distributed medium access control (MAC) protocol, and propose a transmit-delay mechanism to improve spatial reuse and link scheduling. Furthermore, we design an algorithm to adaptively select the transmission parameters, including the cut-through mode, the spatial reuse factor, and the channel rate. Extensive simulations show that the proposed MAC design can effectively improve the end-to-end throughput by more than 55 percent, compared with the state-of-the-art protocol.
A Combined DFT/Machine Learning Framework for Materials Discovery: Application to Spinels and Assessment of Search Completeness and Efficiency

It is challenging to evaluate machine learning approaches developed for accelerating materials search and discovery in a realistic way. Machine learning approaches to materials stability prediction are typically assessed by their ability to reproduce results from direct physical modeling, whereas ideally both machine learning and direct physical modeling should be assessed by their ability to reproduce reality. Additionally, traditional evaluation metrics do not directly reflect the experience of an experimental search for unknown compounds in a large candidate phase space, and often result in overly optimistic assessments. Here, we (i) present a framework that combines density functional theory and traditional supervised machine learning methods (ML/DFT), and (ii) introduce the concepts of search completeness – the fraction of discoverable compounds found relative to the fraction of search space explored – and search efficiency – the rate of discovery relative to the fraction of search space explored – to evaluate it. The ML/DFT framework is an iterative approach to predict stable chemistries of a fixed crystal structure (here, spinels) that uses DFT to generate a training set of unstable compounds. The training set of stable compounds is given by experimentally known spinels. The method is carried out using random forest, LASSO, and ridge regression to predict as-of-yet undiscovered spinel chemistries. TreeSHAP analysis is used to determine features that most contribute to stability/instability classification. While no single feature dominates, several emerge that align with chemical intuition. To estimate the efficacy of ML/DFT compared to pure DFT, we introduce a Bayesian description of DFT distribution of energies for stable and unstable spinels. The Bayesian model enables quantifying the search completeness and search efficiency of DFT, which is then compared to that of ML/DFT. ML/DFT achieves search completeness and efficiency on par with pure DFT, despite requiring fewer DFT simulations (∼300 vs. 14,200). More importantly, by quantitatively assessing ML approaches in ways that better reflect how they would be used in materials discovery experiments, we obtain key insights into the challenges that need to be overcome by such methods: that the small number of stable compounds to be found in a search space orders of magnitude larger places stringent demands on model accuracy to achieve good search efficiency. Finally, we report the top candidates of our spinel search, which may be of interest for synthesis experiments
The Effect and Compensation of Phase Angle Deviation Along the Winding for the Online Stator Insulation Condition Monitoring

The insulation impedance monitoring methods such as capacitance/dissipation factor monitoring methods have been proposed for the online stator insulation condition monitoring. By measuring the insulation leakage currents and the phase-to-ground voltages, the groundwall and phase-to-phase insulation impedances can be calculated in frequency domain. In the existing methods, the calculation is based on the assumption that the differential mode phase-to-ground voltage decreases linearly along the stator winding and no phase angle deviation is considered. However, the phase angles of the induced electromagnetic forces in stator winding in different slots depend on the slot positions. The assumption in the existing methods neglects this phase deviation and causes errors in the monitoring results. In order to eliminate this effect, the effect of the phase angle deviation on monitoring results is analyzed in this article. Its dependency on the turn number, the winding configuration and the frequency of the selected monitoring signals is studied. A compensation method is proposed and the compensation coefficients are calculated for different winding cases for the demonstration purpose. The online experimental results prove that the accuracy of the online monitoring results is improved after the compensation.
Laboratory model to evaluate efficacy of an experimental titanium oxide nanofibers bleaching agent

Objectives This study aimed to use a laboratory model to evaluate the efficacy of an experimental bleaching agent. Materials and Methods The model used human extracted molars that were treated and measured for bleaching efficacy. Teeth (n = 50) were distributed into 5 groups: Negative control (NC): immersion in water for 8 hours; Nanofibers (NFs): Experimental titanium dioxide nanofibers with stirring and light activation for 8 hours; Whitestrips (WS): Crest 3D White Glamorous White Whitestrips, 2 applications daily for 30 minutes, 14 days; 1% hydrogen peroxide (HP) standard: 1% hydrogen peroxide for 8 hours; and 30% HP standard: 30% hydrogen peroxide for 8 hours. Instrumental measurements were performed using a spectrophotometer. Results were recorded at baseline, 1-day post-bleaching, and 1-week post-bleaching. Kruskal-Wallis procedure was used to determine differences in color change. Pearson correlation was used to evaluate the relationship between visual and instrumental measurements. Tests of hypotheses were 2-sided with alpha = 0.05. Results There was no significant difference in color parameters (L1, a1, b1, and shade guide units [SGU]) at baseline (p > 0.05). There was a significant difference among the groups for overall color change (ΔE*ab) and change in shade guide units (ΔSGU) at 1-day and 1-week post-bleaching (p < 0.05). The higher the HP concentration, the higher the color change as expressed in ΔSGU and ΔE*ab. The negative control exceeded the perceptibility threshold of ΔE* = 1.2 regardless of time point. NFs showed a decrease in chroma, but were not statistically different compared to the negative control. Conclusions The laboratory model was successful in screening an experimental bleaching agent.
Experimental Investigate on Pre-combustion Characteristic and Flame Shape of an Adjustable Axial Swirl Burner for Pulverized Coal Combustion

The 14 MW pilot–scale pulverized coal experiment system was built, pre-combustion characteristic and flame shape of adjustable axial swirl burner was investigation, and influence of swirl number also was discussed. The temperature and species concentration distribution in pre-combustion chamber showed that a high temperature oxygen-free and high CO concentration zone appeared around central pulverized coal, which enhanced burnout and inhibiting or reduction NOx. The pre-combustion characteristic belonged to high temperature preheating combustion technology. The captured flame image showed that flame shape beyond pre-combustion chamber outlet belonged to turbulent diffusion flame. Then flame shape scales were obtained. For different swirl numbers, ignition, wall temperature, mean maximum temperature, oxygen-free boundary and CO concentration was discussed, the results indicated that S=1.67 had advantaged for burnout and reduction NOx emission on the basis of stable ignition and avoiding high temperature corrosion. Mean flame length and diameter and divergence angle also were analyzed, the results showed that S=1.67 case had moderate flame length and best diameter and divergence. It was favorable for flame stability and high temperature region in furnace part, and increasing burnout and deceasing NOx emission. Therefor the optimal selection was S=1.67 case under experimental condition.
Usefulness of Management Accounting Information in Decision Making Among SMEs: The Moderating Role of Cloud Computing

Small and medium sized enterprises (SMEs) are the biggest contributors to the Malaysian economy with more than a third of total gross domestic product (GDP) delivered by these industries. In a competitive business environment, SMEs need to utilize information and technology in making decisions. This study aimed to see the relationship between management accounting information (MAI), decision-making, and cloud computing among SMEs in Malaysia. A quantitative research design utilizing survey questionnaires were used to collect the data. The survey was conducted on 384 Malaysian small and medium-sized enterprises in various sectors. The study obtained 105 useable responses which were analysed using Smart PLS 3.0 (Partial Least Square). The study found all the dimensions of MAI; namely broad scope, timeliness, aggregation and integration, positively related to decision-making. The findings also indicated that cloud computing moderated the relationship between MAI and decision-making. The results provided evidence for organizations to realize the importance of MAI, and strategize how to relate to information characteristics in decision-making. Moreover, it enhances the understanding of SMEs on the role of cloud computing, in light of competitive business environments. Future studies have the opportunity to expand the scope to include samples from other geograpical areas and enhance data collection through case studies and interviews to understand the issue in-depth. Keywords: management accounting information (MAI), cloud computing, decision-making, SMEs
Assessment of Nurses knowledge toward Postoperative Wound Care at Al-Diwaniya Teaching Hospital

Objective: The study aims to assess nurse’s knowledge toward postoperative wound care also the discoverany link between sociodemographic characteristics concerning the knowledge nurses.Methodology: This cross – sectional descriptive design study was carried out with 1st of March 2020 to the1st of September - 2020. (70) staff nurses in surgical ward of Al Diwaniya Teaching Hospital. In order toassess the nurses’ knowledge about post-operative wound care. This staff who agreement to participate andwere recruited on giving oral consent . knowledge about postoperative wound care through (38) items thatdeals with . data was collected by distribution structure a self-administered questionnaire , these questionnairealso distribution on (11) experts . while finalized on the basis of the Test- retest reliability was determinedthrough a uses of Pearson Correlations. (r= 0.931**). Results: The outcomes of the search reveals, more than half nurses (54 %) at the age between 20 -28 yearsold. Concerning to gender results of study showed half of the study sample (50%) were female and (50%)of study sample were male. Most of them (60%) were single and reminder was married. Regarding to theireducational status, majority (50%) of the nurses was secondary nursing school degree holders, (28%) ofthe nurses had up to diploma nursing holder and( 22%) of the nurses were BSc degree holders. As regardtheir years of experience it was found that nearly three quarter of the nurses (72%) were5 to 10 years. Themajority of studied nurses (86%) had participated in training course. Twenty six (52%) of the nurses hadhigh level of knowledge regarding postoperative wound care, following by (30%) of total participants hadmoderate knowledge, finally few number of study participants (18%) were had poor knowledge. The findingof study demonstrated no relationship between awareness for nurse with sociodemographic variables.
Analysing a novel multi-objective prioritization model using improved fuzzy c mean clustering

ABSTRACT Consistent regression testing (RT) is an abstract class, that considered indispensable for assuring the quality of software systems but it is too expensive. To minimize the computational cost of RT, test case prioritization (TCP) is the most adopted methodology in literature. The implementation of TCP process, performed using various hard clustering techniques but fuzzy clustering, one of the most sought clustering technique for selecting appropriate test cases had not been discover at a wider platform. Therefore, the proposed work discusses a novel density based fuzzy c- mean (NDB-FCM) algorithm with newly derived initialize membership function for prioritizing the test cases. It first, generates optimal number of cluster (Copt) using a density based algorithm, which in turn minimizes the search criteria to find the ‘Copt’, especially in cases where a given data set does not follow the empirical rule. Then, creates an initial fuzzy partition matrix based upon newly suggested initial membership method. In addition, a novel multi-objective prioritization model (NDS-FCMPM) proposed to achieve the performance goal of enhanced fault recognition. Initially, feature extraction carried out by exploiting the dependencies between test cases, and then test cases are clustered using proposed fuzzy clustering approach, which finally, prioritized using a newly developed prioritization algorithm. To validate the performance of suggested fuzzy clustering algorithm two-performance measure namely “Fuzzy Rand Index” and “Run Time” exercised and for prioritization algorithm “APFD” metrics is analysed. The proposed model is assessed using eclipse data extracted from Github Repository. Inferences generated depict that NDB-FCM clustering provide more stable results in terms of classification accuracy, run time and quick convergence when compared with other state-of-the-art techniques. Also, it is verified that NDS-FCMPM observes an improved rate of fault identification at early stage.
Oxygenation and Membrane Oxygenators: Emergence, Evolution and Progress in Material Development and Process Enhancement for Biomedical Applications

Ever-increasing demands for high performance blood oxygenators have led to continuous advancements in this field. Despite the progresses made since their emergence, there still exist challenges that intimidate the reliability of membrane oxygenators. A promising approach for addressing these challenges and enhancing the overall process performance relates to the selection, development, and modification of materials with desirable characteristics. The main impetus for the present review is to bring forward important and yet less explored subjects by shedding light on the technological, design, and engineering aspects of oxygenators and the oxygenation process. Special attention is paid to membrane oxygenators and their essential characteristics such as gas transport, plasma leakage, and biocompatibility. Also, various practical configurations of membrane oxygenators are illustrated with their merits and limitations. From the materials perspective, a comprehensive range of polymeric materials with track records for applications as membrane oxygenators are surveyed and analyzed considering their physicochemical and biocompatibility properties in order to gain insights into the features of an optimal material. In addition to elaborations on the methods for fabrication of membrane oxygenators, various effective techniques that could be used for altering the microstructure and surface properties of the membranes are presented. Also, an in-depth overview is provided about the transport phenomena in membrane oxygenators aiming to provide a better understanding of the molecular and process aspects of the process. An overview of the state of the art is summarized along with points about the trends of future developments are provided at the end.
Stabilizing effect of elasticity on the motion of viscoelastic/elastic fluids

It is well-known that viscoelasticity is a material property that exhibits both viscous and elastic characteristics with deformation. In particular, an elastic fluid strains when it is stretched and quickly returns to its original state once the stress is removed. In this review, we first introduce some mathematical results, which exhibit the stabilizing effect of elasticity on the motion of viscoelastic fluids. Then we further briefly introduce similar stabilizing effect in the elastic fluids.
Large-area growth of SnS2 nanosheets by chemical vapor deposition for high-performance photodetectors

Two-dimensional tin disulfide (SnS2) is very popular in electronic, optoelectronic, energy storage, and conversion applications. However, the uncontrollable large-area growth of SnS2 nanosheets and unsatisfactory performance of the photodetectors based on SnS2 have hindered its applications. Here, we propose a chemical vapor deposition (CVD) method using SnCl2 as a precursor to grow SnS2 nanosheets. We found that the as-grown SnS2 nanosheets were high-quality crystal structures. Then, photodetectors based on the as-grown SnS2 were fabricated and, exhibited a high responsivity (1400 A W−1), fast response rate (a response time of 7 ms and a recovery time of 6 ms), perfect external quantum efficiency (EQE) (2.6 × 105%), and remarkable detectivity (D*) (3.1 × 1013 Jones). Our work provides a new CVD method to grow high-quality SnS2 nanosheets.