Miracle-dz/UniFAR-FTUs huggingface dataset:
You, Me, and the Organization Makes Three: The Organization’s (Adverse) Effect on Relationships among Coworkers

ABSTRACT Organizational leaders seek to cultivate close relationships among employees to positively impact employees’ workplace behaviors. However, to leaders’ detriment, they often do so without focusing on employees’ relationships with the organization itself. Grounded in social exchange theory and conservation of resources theory, we hypothesize that employees’ perceptions of their relationships with their organizations, in the forms of psychological contract breach (PCB) and perceived organizational support (POS), impact their behaviors (deviance and citizenship) toward their coworkers, even when employees have stronger relationships with their coworkers. Results from a sample of 266 employees across two time points suggest that employees who perceive a more positive relationship with their employers (i.e., lower PCB or higher POS) engage in more deviant behaviors toward their coworkers when they have stronger relationships with their coworkers. In contrast, employees engage in fewer deviant behaviors toward their coworkers when they perceive a more negative relationship with their employers (i.e., higher PCB or lower POS). We find no such effects for citizenship behaviors toward coworkers. We believe these results suggest that there may be different theoretical processes operating for interpersonal deviance and interpersonal citizenship toward coworkers.
Experimental Study of a Gurney Flap on a Pitching Wind Turbine Airfoil under Turbulent Flow Conditions

The present work aimed to investigate the aerodynamic characteristics of a pitching wind turbine airfoil with a Gurney flap under turbulent inflow. Experiments were carried out for the DTU-LN221 offshore wind turbine airfoil under different turbulence levels at Reynolds number 105 order of magnitude by replacing the grilles in the wind tunnel. The dynamic stall characteristics were analyzed by measuring surface pressure and near-wake flow field. The pressure results demonstrated that with the increase of turbulence intensity, the differences in lift hysteresis loops between baseline airfoil and flapped airfoil became smaller. With the turbulence intensity from 0.5% to 10.18%, the maximum lift increment of the Gurney flap decreased from 14.32% to 4.34% (i.e., 0–20° pitching oscillation). In a more extensive range of oscillation, the capability for the lift-improvement dropped down a bit more (i.e., 0–25°). A brief aerodynamic damping analysis indicated that the Gurney flap was more stable in turbulent conditions than the baseline airfoil. Besides, hysteresis loops of the wake were analyzed to compare the difference between the flapped airfoil and the baseline airfoil. Unlike the studies of static airfoils, the results may help better understand the dynamic characteristics of offshore wind turbines with Gurney flaps for practical situations.
Optimal pricing and core acquisition strategy for a hybrid manufacturing/remanufacturing system

Remanufacturing is one of the product recovery options where the quality of used products (cores) is upgraded to ‘as-good-as-new’ conditions. In this article, we consider a monopolist firm selling new and remanufactured products to quality-conscious primary customers and price-sensitive secondary customers, respectively, with one-way substitution, i.e. some primary customers may substitute new products by remanufactured products while secondary customers can never afford to buy new products. We develop economic models under two scenarios – when the supply of cores is unconstrained and when manufacturers have to procure cores at an acquisition price. The major observations of the article are as follows. A firm is better off when there is no constraint on the supply of cores. Even when cores have to be acquired at an acquisition price, the profitability is higher than that when the firm does not engage in remanufacturing activities. When a larger number of primary customers replace new products with remanufactured products, there is partial cannibalization of new product sales; however, the combined market share and profitability of the firm increase. When core supply is constrained and customers are less sensitive to core prices, the limited supply of cores may render remanufacturing an infeasible option for the firm. Therefore, firms should not only generate awareness among primary customers to buy remanufactured products, but also step up efforts to ensure a steady supply of cores. We conclude the article with managerial implications and directions for future research.
Molecular Genetic Diversity and Combining Ability for Some Physiological and Agronomic Traits in Rice under Well-Watered and Water-Deficit Conditions

Water deficit is a pivotal abiotic stress that detrimentally constrains rice growth and production. Thereupon, the development of high-yielding and drought-tolerant rice genotypes is imperative in order to sustain rice production and ensure global food security. The present study aimed to evaluate diverse exotic and local parental rice genotypes and their corresponding cross combinations under water-deficit versus well-watered conditions, determining general and specific combining ability effects, heterosis, and the gene action controlling important traits through half-diallel analysis. In addition, the research aimed to assess parental genetic distance (GD) employing simple sequence repeat (SSR) markers, and to determine its association with hybrid performance, heterosis, and specific combining ability (SCA) effects. Six diverse rice genotypes (exotic and local) and their 15 F1 hybrids were assessed for two years under water-deficit and well-watered conditions. The results revealed that water-deficit stress substantially declined days to heading, plant height, chlorophyll content, relative water content, grain yield, and yield attributes. Contrarily, leaf rolling and the sterility percentage were considerably increased compared to well-watered conditions. Genotypes differed significantly for all the studied characteristics under water-deficit and well-watered conditions. Both additive and non-additive gene actions were involved in governing the inheritance of all the studied traits; however, additive gene action was predominant for most traits. The parental genotypes P1 and P2 were identified as excellent combiners for earliness and the breeding of short stature genotypes. Moreover, P3, P4, and P6 were identified as excellent combiners to increase grain yield and its attributes under water-deficit conditions. The hybrid combinations; P1 × P4, P2 × P5, P3 × P4, and P4 × P6 were found to be good specific combiners for grain yield and its contributed traits under water-deficit conditions. The parental genetic distance (GD) ranged from 0.38 to 0.89, with an average of 0.70. It showed lower association with hybrid performance, heterosis, and combining ability effects for all the studied traits. Nevertheless, SCA revealed a significant association with hybrid performance and heterosis, which suggests that SCA is a good predictor for hybrid performance and heterosis under water-deficit conditions. Strong positive relationships were identified between grain yield and each of relative water content, chlorophyll content, number of panicles/plant, number of filled grains/panicle, and 1000-grain weight. This suggests that these traits could be exploited as important indirect selection criteria for improving rice grain yield under water-deficit conditions.
Modelling the impact of context in real-world highway pull-out dynamics to inform acceptable path planning of automated vehicles

Growing research attention is focusing on Automated Vehicle (AV) technologies, promising significant safety benefits. An in-depth understanding of human driving will play an important role in determining the most acceptable AV behaviour, supporting passenger comfort and thus the adoption of the technology, but also the optimal prediction of the behaviour of the surrounding traffic. The current study examined 1740 real-world motorway pull-out manoeuvres (pull-out distance, speed differential with the leading vehicle, manoeuvre duration, pull-out comfort zone) under different conditions. The results highlighted the significant impact of the surrounding traffic and the driving characteristics on or before the manoeuvre initiation point, which reflected the overtaking strategy selected. The findings can inform the design of automated overtaking systems that resemble human driving and thus encourage their uptake; in addition, they can assist the intention prediction for lane keeping assistance systems in order to optimise the system’s response to cutting in and pull-out manoeuvres.
Electrochemical Deposition of Fe–Co–Ni Samples with Different Co Contents and Characterization of Their Microstructural and Magnetic Properties

In this study, to explore the effect of Co contents on the electroplated Fe–Co–Ni samples, three different Fe–Co33–Ni62, Fe–Co43–Ni53, and Fe–Co61–Ni36 samples were electrochemically grown from Plating Solutions (PSs) containing different amounts of Co ions on indium tin oxide substrates. Compositional analysis showed that an increase in the Co ion concentration in the PS gives rise to an increment in the weight fraction of Co in the sample. In all samples, the co–deposition characteristic was described as anomalous. The samples exhibited a predominant reflection from the (111) plane of the face–centered cubic structure. However, the Fe–Co61–Ni36 sample also had a weak reflection from the (100) plane of the hexagonal close–packed structure of Co. An enhancement in the Co contents caused a strong decrement in the crystallinity, resulting in a decrease in the size of the crystallites. The Fe–Co33–Ni62 sample exhibited a more compact surface structure comprising only cauliflower–like agglomerates, while the Fe–Co43–Ni53 and Fe–Co61–Ni36 samples had a surface structure consisting of both pyramidal particles and cauliflower–like agglomerates. The results also revealed that different Co contents play an important role in the surface roughness parameters. From the magnetic analysis of the samples, it was understood that the Fe–Co61–Ni36 sample has a higher coercive field and magnetic squareness ratio than the Fe–Co43–Ni53 and Fe–Co33–Ni62 samples. The differences observed in the magnetic characteristics of the samples were attributed to the changes revealed in their phase structure and surface roughness parameters. The obtained results are the basis for the fabrication of future magnetic devices.
The Impact of the U.S. Macroeconomic Variables on the CBOE VIX Index

The purpose of this study is to find the influence of various macroeconomic factors on the volatility index, as macroeconomic factors affect stock market volatility, resulting in an impact on the VIX Index, representing the risk in the stock market. To estimate the significance and importance of the U.S. macroeconomic variables on stock market volatility and risk, classification problems from machine learning are constructed to predict the daily and weekly trends of the VIX Index. Data from May 2007 to December 2021 is considered for analysis. The selected models are trained with twenty-four daily features and twenty-four plus nine weekly features. The outcomes suggest that the decisions made by the Light GBM and XG Boost on ranking features can be significantly accepted over logistic regression. It is found from the results that economic policy uncertainty indices, gold price, the USD Index, and crude oil are signified as strong predictors. The Financial Stress Index, initial claims, M2, TED spread, Fed rate, and credit spread are also strong predictors, while various yields on fixed income securities make a little less impact on the VIX Index. The TED spread, Financial Stress Index, and Equity Market Volatility (Infectious Disease Tracker) are positively associated with the VIX.
Impact of Iterative Deuterium Annealing in Long-Channel MOSFET Performance

In contrast to conventional forming gas annealing (FGA), high-pressure deuterium annealing (HPD) shows a superior passivation of dangling bonds on the Si/SiO2 interface. However, research detailing the process optimization for HPD has been modest. In this context, this paper demonstrates the iterative impact of HPD for the better fabrication of semiconductor devices. Long-channel gate-enclosed FETs are fabricated as a test vehicle. After each cycle of the annealing, device parameters are extracted and compared depending on the number of the HPD. Based on the results, an HPD condition that maximizes on-state current (ION) but minimizes off-state current (IOFF) can be provided.
Cenobamate for treatment-resistant focal seizures: current evidence and place in therapy

Background Cenobamate is newly approved for partial-onset seizures in adults, albeit the mechanism of its action remain poorly understood. Methods This article aims to review the efficacy, safety, and tolerability of cenobamate in treating partial-onset seizures. Data Collection: The English language articles were searched in the National Institute of Health clinical trials registry, PubMed, and the Cochrane library between 2010 and June 2021 using the keywords cenobamate, YKP 3089, and seizure, and filter “trial” was applied. Results: A total of 31 articles were retrieved. Eventually, two randomized, double-blind, multicenter clinical trials involving 659 patients were analyzed. Cenobamate has shown significant reduction in seizure frequency compared to placebo. In cenobamate group, a greater number of participants showed ≥50% reduction in seizure frequency, adverse effects, and drug discontinuation compared to placebo. Multiple drug-drug interactions with other anti-seizure drugs were also observed. Conclusions Based on the findings of these trials, cenobamate seems to be an attractive option for treatment-resistant partial-onset seizures; however, multiple treatment-related adverse effects and drug-drug interactions are the areas of concern.
Precise and extensive characterization of anoptical resonator for cavity-based quantumnetworks

Dowon Lee, Myunghun Kim, Jungsoo Hong, Taegyu Ha, Junwoo Kim, Sungsam Kang, 3 Youngwoon Choi, 5 Kyungwon An, and Moonjoo Lee ∗ Department of Electrical Engineering, Pohang University of Science and Technology (POSTECH), 37673 Pohang, Korea Center for Molecular Spectroscopy and Dynamics, Institute for Basic Science (IBS), 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Korea Department of Physics, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea Department of Bioengineering, Korea University, Seoul 02841, Korea Interdisciplinary Program in Precision Public Health, Korea University, Seoul 02841, Korea Department of Physics and Astronomy & Institute of Applied Physics, Seoul National University, 08826 Seoul, Korea (Dated: March 18, 2022)
Computer vision and augmented reality for guiding assembly

An Augmented Reality (AR) system that can enhance a user's view of the surrounding scene with annotations based on the scene content, has many potential applications. We consider the problem of scene augmentation in the context of a human engaged in assembling an object from its components. In order to exploit AR's potential, two main problems need to be considered. The first key issue is designing an effective augmentation scheme for information presentation and control. The second, providing accurate and robust sensing to determine the state of the surrounding environment. We utilize concepts from robot assembly planning to develop a systematic framework for presenting augmentation stimuli for the assembly domain. An interactive augmentation design and control engine called is described. The engine can be used for developing and visualizing multi-modal augmentation schemes for assembly, as well as controling information presentation in an Augmented Reality system. Its functionality is demonstrated with the help of specific scenarios where the goal is to create effective multi-modal augmentation displays for evaluating assembly. For providing the appropriate augmentation stimulus at the right position and time, an AR system needs some sensor to interpret the surrounding scene. We take an incremental approach using computer vision to address the sensing problem. First, we develop real-time tracking of a marker-based coding scheme. The fiducials are placed on each assembly components to uniquely identify and track them. An experimental prototype system is described, which implements computer vision algorithms for real-time marker-based tracking. Even though fiducials offer relative simplicity and flexibility, the problems of occlusion by the manipulator as well as other assembly parts make the use of more general computer vision techniques desirable. A domain specific problem is the changing shape and appearance of assembly objects as they are connected together. A combination of concepts from robotics assembly planning, model-based object recognition, and image feature classification is used to develop an object recognition scheme in the context of parts being assembled together by a human. Problems in the assembly domain include changing shape and appearance of objects as they are connected together, as well as high occlusion by the manipulator and other objects. Constraints from the domain of assembly, as well as transformation space search-based vision algorithms make the problem tractable. We use this scheme for subassembly recognition, tracking, and assembly state verification.
Clinical Outcome of Hospitalized COVID-19 Patients with History of Atrial Fibrillation

Background and objectives: Pre-existing atrial fibrillation (AF) is a frequent comorbidity in hospitalized patients with COVID-19; however, little is still known about its prognostic role in infected patients. The aim of our study was to evaluate whether the pre-existing AF as comorbidity would contribute to increase the risk for severe forms of COVID-19, worse prognosis, or even higher mortality. Materials and Methods: We retrospectively evaluated all consecutive COVID-19 patients admitted to the emergency department of nine Italian Hospitals from 1 March to 30 April 2020.The prevalence and the type of pre-existing AF have been collected. The correlation between the history and type of AF and the development of severe ARDS and in-hospital mortality has been evaluated. Results: In total, 467 patients (66.88 ± 14.55 years; 63% males) with COVID-19 were included in the present study. The history of AF was noticed in 122 cases (26.1%), of which 12 (2.6%) with paroxysmal, 57 (12.2%) with persistent and 53 (11.3%) with permanent AF. Among our study population, COVID-19 patients with AF history were older compared to those without AF history (71.25 ± 12.39 vs. 65.34 ± 14.95 years; p < 0.001); however, they did not show a statistically significant difference in cardiovascular comorbidities or treatments. Pre-existing AF resulted in being independently associated with an increased risk of developing severe ARDS during the hospitalization; in contrast, it did not increase the risk of in-hospital mortality. Among patients with AF history, no significant differences were detected in severe ARDS and in-hospital mortality between patients with permanent and non-permanent AF history. Conclusions: Pre-existing AF is a frequent among COVID-19 patients admitted to hospital, accounting up to 25% of cases. It is independently associated with an increased risk of severe ARDS in hospitalized COVID-19 patients; in contrast, it did not affect the risk of death. The type of pre-existing AF (permanent or non-permanent) did not impact the clinical outcome.
Positive Effects of an Online Workplace Exercise Intervention during the COVID-19 Pandemic on Quality of Life Perception in Computer Workers: A Quasi-Experimental Study Design

Computer workers’ sedentary work, together with less active lifestyles, aggravated by the COVID-19 pandemic, represents a high risk for many chronic diseases, leading to a decrease in health-related quality of life (QoL). Workplace exercises consist of a set of physical exercises, implemented during work breaks, that have multiple benefits for workers’ health. Aim: To assess the impact of online workplace exercises on computer workers’ perception of quality of life. Methods: Quasi-experimental study with two groups: a control group (n = 26) and an intervention group (n = 13). The inclusion criteria were that participants must be aged between 18 and 65 years old and the exclusion criteria included diagnosis of non-work-related medical conditions. The interventions consisted of workplace exercises, which were applied for 17 consecutive weeks, each session lasting 15 min, three times a week. The exercise programme, performed online and guided by a physiotherapist, consisted of mobility exercises, flexibility and strength exercises, with the help of a TheraBand® for elastic resistance. The control group were not subjected to any intervention. A socio-demographic questionnaire and the Health Survey Questionnaire (SF-36v2) were used in two assessment stages (M0—baseline and M1—final of intervention). A mixed ANOVA with interaction time*group was used to evaluate the effect of the exercise programme. Results: A good perception of the QoL was obtained in both stages. The exercise programme had a positive effect in the domains of Pain (ptime*group = 0.012, η2p = 0.158), Physical Function (ptime*group = 0.078, η2p = 0.082), Physical Performance (ptime*group = 0.052, η2p = 0.098), and Emotional Performance (ptime*group = 0.128, η2p = 0.061). Conclusion: After 17 weeks of workplace exercises, it became clear that the intervention group positively increased their QoL perception, with this improvement being significant in the Pain domain, which resulted in an improvement in their health condition. Therefore, further studies are needed to determine the optimal exercise for CWs, with detailed exercise types, different intensities and focused on various health conditions.
VSLN: View‐aware sphere learning network for cross‐view vehicle re‐identification

Cross‐view vehicle Reidentification (ReID) has attracted widespread attention as an increasingly important vision task in intelligent transportation and urban surveillance. Benefiting from Convolutional Neural Network (CNN), recent studies have promoted the development of vehicle ReID by extracting discriminative local features. However, two fundamental challenges of small interclass discrepancy caused by different views and large intraclass distance caused by similar appearance still hinder the performance of cross‐view vehicle ReID. In this paper, a novel View‐aware Sphere Learning Network (VSLN) is proposed to alleviate the above issues while maintaining the merits of CNN‐based approaches to generate view‐aware sphere‐based features. First, a Sphere Feature Embedding Network (SFEN) is proposed to constrain the images into hypersphere for extracting sphere features. On the other hand, this study presents a sphere similarity triple loss to help SFEN concentrate more on robust and discriminative vehicle parts. Second, since the vehicle images are usually captured from different viewpoints, this study further extends SFEN by introducing a Vehicle Viewpoint Predictor (VVP) combined with global attention mechanism to enlarge the discrepancy of interclass and shorten the distance of intraclass. Moreover, a city‐scale data set, named Vehicle from Different Viewpoints, containing image‐level viewpoint labels, is collected for training VVP. As a result, the proposed VLSN can achieve 96.31% Top‐1 accuracy and 79.46% Top‐1 accuracy on VeRi‐776 and VRIC data sets, respectively. Overall, extensive experimental results on two benchmark data sets show that the proposed VSLN outperforms state‐of‐the‐art methods.