Miracle-dz/UniFAR-FTUs huggingface dataset:
PERSPECTIVES OF PHARMACOVIGILANCE OF AYUSH DRUGS AMONG HEALTH CARE PROFESSIONALS-A CROSS-SECTIONAL SURVEY

Objective: To assess the knowledge of Pharmacovigilance of AYUSH drugs and recommendations for improving adverse drug reporting of AYUSH drugs among the healthcare professionals working in various disciplines. Methods: This study was a crosssectional questionnaire based survey conducted during a one day national seminar on “Pharmacovigilance of AYUSH drugs” conducted by Faculty of Pharmacy, Sri Ramachandra University. A structured questionnaire was designed and distributed among 500 delegates working in different districts of the state of Tamilnadu. The colleceted data were analysed using Epi Info software and expressed in percentage (%). Results: Analysis of the data revealed that 36% were aware of the existence of the National Pharmacovigilance Program for AYUSH drugs in India, 24% knew that the National Pharmacovigilance Centre is located at Indian Pharmacopoeia Commission (IPC), Ghaziabad, 12% were aware that the International Centre of Pharmacovigilance is located at UPSALA, Sweden, 14% were familiar with a standardized form for Reporting ADRs of AYUSH drugs and 12% knew that most commonly used causality assessment scale is Naranjo’s scale. Conclusion: The present study revealed the lack of knowledge of pharmacovigilance of AYUSH drugs among the study population. There is a need for a regular training and the reinforcement for the ADR reporting among the health care personnel for the better clinical management of the patients in general.
Effect of Palm Oil Fiber (POF) to Strength Properties and Fracture Energy of Green Concrete

The lack of research on concrete which utilizes Palm Oil Fuel Ash (POFA), Rice Husk Ash (RHA), Recycled Concrete Aggregate (RCA) and Palm Oil Fiber (POF) simultaneously in concrete was globally observed. To meet this gap, a study on green concrete consisting of POFA, RHA and RCA with added untreated POF as binders was conducted. The study focusses on the effect of varying percentages of untreated POF, ranging from 0%, 0.25%, 0.50% and 0.75%, to the strength properties and fracture energy of green concrete. The strength properties of green concrete were investigated by conducting the compression strength test and tensile strength test on forty-eight (48) cubes and cylinders at the curing age of 7 and 28 days. The tests show that the strength of green concrete decreases, as the percentage of POF increases. This was preceded by the establishment of an optimum percentage of POF at 0.25%. The fracture energy of the green concrete was determined by testing twelve numbers of notched beams with dimensions of 100mm x 100mm x 500mm under the three-point bending test. From the threepoint bending test, the load-deflection profile for each specimen with different percentages of untreated POF was obtained. Three existing theoretical models, namely Hillerborg, Bazant and CEB models were used to measure the fracture energy of the green concrete with varying percentage of fiber. Results range from 37.94 N/m to 153.81 N/m was observed. The study also successfully established the reliability of Hillerborg’s model to fracture energy when models by Bazant and CEB surprisingly shows a decrease in fracture energy measurements with increase in fiber content.
Entrepreneurial Intention and Motivation to Learn Among Accountancy Students

Objective: To analyze the relationship between entrepreneurial intention and motivation to learn among Accountancy students at the Federal University of Santa Maria, Brazil. Method: Grounded on the Theory of Planned Behavior, considering the theoretical framework addressing entrepreneurial intention proposed by Liñán and Chen (2009) and motivation to learn by Tho (2017). Therefore, this is a quantitative, descriptive survey. Data were obtained using the Entrepreneurial Intention Questionnaire (Liñán & Chen, 2009) and the Motivation to Learn Questionnaire (Tho, 2017). A total of 219 students were addressed. Data were tabulated and statistically analyzed. Results: The results showed that the students’ motivation to learn, behavioral perception, and entrepreneurial intention were moderate, while high ratios were found for personal attitude and subjective norm. Additionally, no significant correlation was found between the constructs of motivation to learn and entrepreneurial intention. In-depth analyses were performed using regression models, which revealed that entrepreneurial intention influences motivation to learn. Contributions: This study contributes to a greater understanding of the behavioral aspects of Accountancy students, enabling and encouraging the development of behaviors driven to learn and perform entrepreneurial activities.
The Utility of Google Rating as a Tool for Evaluating Nursing Homes Performance

The study aims to validate the utility of Google rating in evaluating nursing homes’ performance. The researchers used a correlational design to determine if the average Google rating was associated with CMS's NHCompare 5-star ratings, the researchers compared Google consumer-reported ratings of nursing homes to the Centers of Medicare and Medicaid Services (CMS) Nursing Home Compare (NHCompare) 5-star ratings. Three hundred and forty-five out of 363 nursing homes in New Jersey were included in the study. The average Google rating was 3.74, and the average NHCompare overall star rating was 3.64. Analysis revealed a statistically significant and weak positive correlation between the average Google rating and the NHCompare overall star rating (r=0.12, p < 0.05), health inspection rating (r=0.11, p < 0.05), and quality of resident care rating (r=0.15, p < 0.01). Although Google rating was correlated with NHCompare 5-star ratings, the correlation coefficients were too weak to be meaningful and insufficient to validate the utility of using Google rating as a standalone measure of nursing home quality. Using Google rating as a standalone measure for evaluating nursing homes’ performance should be done with caution.
Effect of Psychological Capital and Emotional Intelligence on Employee’s Job Performance

Employee’s job performance is considered to be very key variable effecting organizational performance. In today’s hypercompetitive world global economy business need to try identifying the factors that has effect on employee’s performance, and psychological capital and emotional intelligence are amongst them. Consequently the main aim of the study was to find out the relationship of psychological capital and emotional intelligence on employee’s job performance in Public sector Universities of Peshawar. In order to obtain the required objectives, a sample of 170 respondents was selected randomly through proportional allocation method. Well-structured questionnaire was used to collect the data. For checking the reliability of data, Cronbach’s alpha coefficient was used. The results quantified that the collected data is reliable as coefficient of Cronbach’s alpha is greater than 0.70 for psychological capital and emotional intelligence. For employee performance the reliability measures was less than 70%. MAS were greater than 3 for most of studied attributes showing that employees are in favor of effect of psychological capital and emotional intelligence on employee’s performance. The results of Chi-square showed a significant (P < 0.05) association between psychological capital and employee performance and also emotional intelligence and employee performance. Grounded on the results, it is determined that psychological capital and emotional intelligence are significantly associated with employee’s performance.
Understanding supply chain security strategy

In the post-9/11 environment, organizations are acutely aware of the need to secure their supply chains from risks of being a target of, or an unwilling participant in, a terror attack. However, supply chain security (SCS) comes at a cost and increasing levels of protection have increasing levels of costs to the firm. So some firms engage in strategic initiatives to secure the supply chain (SC) while others do not; and each firm engages in varying degrees of activities to ensure SCS. Therefore, in this study, the researchers sought to explore what types of SCS strategies exist. The researchers analyze 162 responses to a SCS survey completed by executives from a broad range of firms and industries and identify three general SCS strategies: Advanced, Laggards, and Compliant. Implications for researchers and practitioners are presented. INTRODUCTION The events of September 11, 2001 were a catalyst for change in many supply chain operations. Supply chain security issues and initiatives have affected numerous firms (Yang and Wei, 2013). At a minimum, firms want to protect their property and investments. From a larger perspective, firms want to protect society. Clearly, no firm wants its name permanently linked to the next 9/11-like attack. However, Supply Chain Security (SCS) can be difficult to understand and ultimately implement. SCS is unique because if it is working well, it remains virtually invisible. As a result, little is known about SCS strategies. Understanding strategy is at the core of supply chain research (Christopher et al. 2006; Tokman et al. 2007) and it is through firm strategy formulation that cost/benefit considerations are weighed (Tang, 2006). But supply chains, particularly those that are multimodal, are vastly complex (Scholliers et al. 2012), where a multitude of firms in any given network will employ a myriad of strategies. As a result, academicians have dedicated efforts to understanding them, and in some cases guiding them. Research on supply chain strategies has examined the relationship between corporate strategy and SCM (Hofman 2010); logistics strategies (Autry et al. 2008) and logistics activities in relation to firm performance (Lynch et al. 2000); postponement versus speculation (Pagh and Cooper 1998); and changes to strategy based on environmental factors (Atwater et al. 2010).
Quantitation of SARS-CoV-2 neutralizing antibodies with a virus-free, authentic test

Neutralizing antibodies (NAbs), and their concentration in sera of convalescents and vaccinees are a solid correlate of protection from COVID-19. The antibody concentrations in clinical samples that neutralize SARS-CoV-2 are difficult and very cumbersome to assess with conventional virus neutralization tests (cVNTs), which require work with the infectious virus and biosafety level 3 containment precautions. Alternative virus neutralization tests currently in use are mostly surrogate tests based on direct or competitive ELISA formats or use viral vectors with the spike protein as the single structural component of SARS-CoV-2. To overcome these obstacles, we developed a virus-free, safe and very fast (4.5 h) in vitro diagnostic test based on engineered yet authentic SARS-CoV-2 virus-like-particles (VLPs). They share all features of the original SARS-CoV-2 but lack the viral RNA genome and thus are non-infectious. NAbs induced by infection or vaccination, but also potentially neutralizing monoclonal antibodies can be reliably quantified and assessed with ease and within hours with our test, because they interfere and block the ACE2-mediated uptake of VLPs by recipient cells. Results from the VLP neutralization test (VLPNT) show excellent correlation to a cVNT with fully infectious SARS-CoV-2 and allow to estimate the reduced neutralization capacity of COVID-19 vaccinee sera with variants of concern of SARS-CoV-2.
Effective Connectivity of LSD-induced Ego Dissolution

Classic psychedelic-induced ego dissolution involves a shift in the sense of self and blurring of boundary between the self and the world. A similar phenomenon is identified in psychopathology and is associated to the balance of anticorrelated activity between the default mode network (DMN), which directs attention inwards, and the salience network (SN), which recruits the dorsal attention network (DAN) to direct attention outward. To test whether change in anticorrelated networks underlie the peak effects of LSD, we applied dynamic causal modeling to infer (directed) effective connectivity of resting state functional MRI scans from a double-blind, randomised, placebo-controlled cross-over study where 100mg of LSD, or placebo, was administered to 25 healthy adults. Under the peak effects of LSD, the hierarchical organisation of the resting state brain networks was altered. Inhibitory effective connectivity from the SN to DMN decreased and became excitatory, and inhibitory effective connectivity from DMN to DAN decreased when compared to the placebo. These changes in connectivity reflect diminution of the anticorrelation between the resting state networks which may be a key neural mechanism of LSD-induced ego dissolution. Our findings suggest the hierarchically organised balance of resting state networks is a central feature in the construct of self.
COVID-19 vaccine effectiveness among immunocompromised populations: a targeted literature review of real-world studies

ABSTRACT Introduction From July through October of 2021, several countries issued recommendations for increased COVID-19 vaccine protection for individuals with one or more immunocompromised (IC) conditions. It is critically important to understand the vaccine effectiveness (VE) of COVID-19 vaccines among IC populations as recommendations are updated over time in response to the evolving COVID-19 pandemic. Areas covered A targeted literature review was conducted to identify real-world studies that assessed COVID-19 VE in IC populations between December 2020 and September 2021. A total of 10 studies from four countries were identified and summarized in this review. Expert opinion VE of the widely available COVID-19 vaccines, including BNT162b2 (Pfizer/BioNTech), mRNA-1273 (Moderna), Ad26.COV2. S (Janssen), and ChAdOx1 nCoV-19 (Oxford/AstraZeneca), ranged from 64% to 90% against SARS-CoV-2 infection, 73% to 84% against symptomatic illness, 70% to 100% against severe illness, and 63% to 100% against COVID-19-related hospitalization among the fully vaccinated IC populations included in the studies. COVID-19 VE for most outcomes in the IC populations included in these studies were lower than in the general populations. These findings provide preliminary evidence that the IC population requires greater protective measures to prevent COVID-19 infection and associated illness, hence should be prioritized while implementing recommendations of additional COVID-19 vaccine doses.
Fabrication of Wear Resistance Ni/SiC nano composite Coating by Electro co-deposition

In this paper, we succeeded in obtaining a Ni/SiC nano composite coating using conventional electro deposition by adding different amount of SiC nanoparticles to a nickel-watt bath to be co-deposited. The effect of electro deposition conditions was studied by changing the amount of SiC nanoparticles in the nano composite, and the deposition current density which affects on the participation of SiC nanoparticles in the coating. The morphology and mechanical properties of the electrodeposited nano-composite were studied. The wear behavior of the nano-composite coatings was evaluated on a ball-on-disk test. It was found that the increased micro hardness and wear resistance of the nano-composite coatings increased with increasing content of the SiC nano-particulate in bath.
Determining photosensor settings for optimum energy saving of suspended lighting systems in a small double‐skinned office

A photoelectric dimming control system applied to a suspended direct/indirect and indirect lighting system was analyzed to determine effective control options in a small office with double‐skin envelope. Computer simulations were performed for photosensors positioned at three different locations with three specific configurations under three Commission Internationale de l'Élairage standard sky types. Optimum ideal dimming level was determined for each combination of room orientation, photosensor configurations and positions.
Measuring of radioactive contamination by Gamma-ray Spectroscopy for many water projects in Baghdad City

The study aims to provide the effective monitoring of radioactive contents in refining water stations. Attempts were made to measure the radionuclide’s concentrations level which indicates to radioactive contamination in the samples of raw water taken from the Tigris River and samples of river sediments. The radionuclides contents have been obtained using the gamma-ray spectroscopy technique. Analysis system (HPGe) has been applied to measure the radioactivity concentration of Uranium, Radium, and Thorium in water and sediment samples. For solid samples (sediments), results have shown that the activity for238U the range was from (52±5.31Bq/kg)In S4 to(120±8)in S3, for 232Th the range was from(26±2.4Bq/kg)in S1to (48±3.1Bq/kg) in S3, for 40K, the range was from (247±17Bq/kg) in s4 to (453±18Bq/kg) in S3, for 137Cs the range was from(1.28±0.1Bq/kg) in S3 to (7.8±0.67) in S2. For liquid samples (water), the activity for 238U was from (10±1 Bq/l) in Kh1to(38±4.2Bq/l) in D1, for 232Th was from (1±0.35Bq/l) in kD1 to (1.8±0.60Bq/l) in D1, for 40K was from (10±0.3 Bq/l), in ka1to(48±5.7Bq/l) in KD1. In the final step (drinking water) showed only 40K isotope appeared at range(18±0.03 - 55±0.06Bq/l).
Simulation and Numerical Modelling of CIGSSe-Based Solar Cells by AFORS-HET

A general equation to determine properties of penternary solar cell based on Cu (In, Ga) (Se, S) 2 (CIGSSe) with a double buffer layer ZnS/Zn0.8Mg0. 2O(ZMO) were derived. Numerical analysis of a (CIGSSe) solar cell with a double buffer layer ZnS/ZMO, CdS free absorber layer, were investigated using the AFORS-HET software simulation. Taking into consideration the effect of thickness and doping concentration for the CIGSSe absorption layer, ZnS buffer layer and ZnO:B(BZO) window layer on the electron transport, short circuit current density (Jsc) and open circuit voltage (Voc); numerical simulation demonstrated that the changes in band structure characteristics occurred. The solar energy conversion efficiency is 28.34%, the filling factor is 85.59%, the open circuit voltage is 782.3 mV, the short circuit current is 42.32 mA. then we take the range of the gradient between the ratio of x and y for the absorption layer, and the best result of Voc, Jsc, FF, Eff equal (838.7 mV, 40.94 mA/cm2, 86.23%, 29.61%) respectively at x= 0, y= 0.26.
Inlet fogging of gas turbine engines. Part II: Fog droplet sizing analysis, nozzle types, measurement, and testing

The inlet fogging of gas turbine engines for power augmentation has seen increasing application over the past decade yet not a single technical paper treating the physics and engineering of the fogging process, droplet size measurement, droplet kinetics, or the duct behavior of droplets, from a gas turbine perspective, is available. This paper provides the results of extensive experimental and theoretical studies conducted over several years, coupled with practical aspects learned in the implementation of nearly 500 inlet fogging systems on gas turbines ranging in power from 5 to 250 MW. Part B of the paper treats the practical aspects of fog nozzle droplet sizing, measurement and testing presenting the information from a gas turbine fogging perspective. This paper describes the different measurement techniques available, covers design aspects of nozzles, provides experimental data on different nozzles and provides recommendations for a standardized nozzle testing method for gas turbine inlet air fogging.
Control of a batch-processing machine: A computational approach

Batch processing machines, where a number of jobs are processed simultaneously as a batch, occur frequently in semiconductor manufacturing environments, particularly at diffusion in wafer fabrication and at burn-in in final test. In this paper we consider a batch-processing machine subject to uncertain (Poisson) job arrivals. Two different cases are studied: (1) the processing times of batches are independent and identically distributed (IID), corresponding to a diffusion tube; and (2) the processing time of each batch is the maximum of the processing times of its constituent jobs, where the processing times of jobs are IID, modelling a burn-in oven. We develop computational procedures to minimize the expected long-run-average number of jobs in the system under a particular family of control policies. The control policies considered are threshold policies, where processing of a batch is initiated once a certain number of jobs have accumulated in the system. We present numerical examples of our methods and.
NEW RELATIVISTIC APPROACH TO COMPUTING SPECTRAL PARAMETERS OF MULTICHARGED IONS IN PLASMAS

It is presented a new relativistic approach to computing the spectral parameters of multicharged ions in plasmas for different values of the plasmas screening (Debye) parameter (respectively, electron density, temperature). The approach used is based on the generalized relativistic energy approach combined with the optimized relativistic many-body perturbation theory (RMBPT) with the Dirac-Debye shielding model as zeroth approximation, adapted for application to study the spectral parameters of ions in plasmas. An electronic Hamiltonian for N-electron ion in plasmas is added by the Yukawa-type electron-electron and nuclear interaction potential. The special exchange potential as well as the electron density with dependence upon the temperature are used.
Systemwide Optimization of Safety Improvements for Resurfacing, Restoration, or Rehabilitation Projects

Highway agencies face a dilemma in determining the appropriate balance of resurfacing and safety improvements in their programs to maintain the structural integrity and ride quality of highway pavements. Highway agencies currently lack a tool that would allow them to determine which sites should be resurfaced without accompanying safety improvements and which sites should be resurfaced and improved in other ways that would enhance safety. A resource allocation process that maximizes the benefits from resurfacing and safety improvements within a specified improvement budget can provide such a tool. A resource allocation process that accomplishes this goal has been developed and implemented in a software tool known as the Resurfacing Safety Resource Allocation Program (RSRAP). RSRAP uses an optimization process based on integer programming to determine which improvement alternatives (or combinations of alternatives) would optimize the benefits for a specified set of improvement projects. RSRAP incorporates the best available estimates of the safety effectiveness of specific geometric and safety improvements. RSRAP also gives consideration to the potential effects of resurfacing on vehicle speeds and on safety. The goal of the optimization process is not to optimize safety at any particular site but to optimize systemwide safety for a given set of resurfacing projects while not exceeding a user-specified improvement budget.