Miracle-dz/UniFAR-FTUs huggingface dataset:
SARS-CoV-2 seroprevalence and risk factors among meat packing, produce processing, and farm workers

Meat packing, produce processing, and farm workers are known to have an elevated risk of COVID-19, but occupational risk factors in this population are unclear. We performed an observational cohort study of meat packing, produce processing, and farm workers in North Carolina in fall 2020. Blood, saliva, and nasal turbinate samples were collected to assess for SARS-CoV-2 seropositivity. Risk factors for SARS-CoV-2 seropositivity were investigated using chi-square tests, two-sample t-tests, and adjusted risk ratio analyses. Among 118 enrolled workers, the baseline SARS-CoV-2 seroprevalence was 50.0%. Meat packing plant workers had the highest SARS-CoV-2 seroprevalence (64.6%), followed by farm workers (45.0%) and produce processing workers (10.0%), despite similar sociodemographic characteristics. Compared to SARS-CoV-2 seronegative workers, seropositive workers were more likely to work in loud environments that necessitated yelling to communicate (RR: 1.83, 95% CI: 1.25–2.69), work in cold environments (RR: 1.58, 95% CI: 1.12–2.24), or continue working despite developing symptoms at work (RR: 1.63, 95% CI: 1.14–2.32). After adjusting for age and working despite symptoms, high occupational noise levels were associated with a 1.72 times higher risk of SARS-CoV-2 seropositivity (95% CI: 1.16–2.55). Half of food processing workers showed evidence of past SARS-CoV-2 infection, a prevalence five times higher than most of the United States population at the time of the study. Work environments with loud ambient noise may pose elevated risks for SARS-CoV-2 transmission. Our findings also highlight the disproportionate burden of COVID-19 among underserved and economically disadvantaged Latinx communities in the United States.
An IoT Machine Learning-Based Mobile Sensors Unit for Visually Impaired People

Visually impaired people face many challenges that limit their ability to perform daily tasks and interact with the surrounding world. Navigating around places is one of the biggest challenges that face visually impaired people, especially those with complete loss of vision. As the Internet of Things (IoT) concept starts to play a major role in smart cities applications, visually impaired people can be one of the benefitted clients. In this paper, we propose a smart IoT-based mobile sensors unit that can be attached to an off-the-shelf cane, hereafter a smart cane, to facilitate independent movement for visually impaired people. The proposed mobile sensors unit consists of a six-axis accelerometer/gyro, ultrasonic sensors, GPS sensor, cameras, a digital motion processor and a single credit-card-sized single-board microcomputer. The unit is used to collect information about the cane user and the surrounding obstacles while on the move. An embedded machine learning algorithm is developed and stored in the microcomputer memory to identify the detected obstacles and alarm the user about their nature. In addition, in case of emergencies such as a cane fall, the unit alerts the cane user and their guardian. Moreover, a mobile application is developed to be used by the guardian to track the cane user via Google Maps using a mobile handset to ensure safety. To validate the system, a prototype was developed and tested.
Learning Malicious Circuits in FPGA Bitstreams

Computing platforms are integrating field-programmable gate arrays (FPGAs) to support domain-specific customization. Multiple tenants can share these FPGAs by configuring them at runtime. However, attackers can abuse this capability by programming the FPGAs with malicious functions. A malicious configuration bitstream can launch denial of service, overheat the FPGA, leak sensitive information via side channels, enable remote monitoring, and launch voltage and timing attacks. We consider time-based multitenancy, where multiple tenants use the FPGA at different time intervals and not at the same time. We propose a defense based on machine learning (ML) algorithms to detect bitstreams of malicious circuits and malicious circuits mixed with legitimate circuits by analyzing the static features extracted from FPGA bitstreams. The proposed approach can help detect malicious bitstreams without the need for reverse engineering of the bitstream or having access to the design netlist. Our results on Xilinx FPGAs indicate that supervised classifiers may identify malicious bitstreams representing ring-oscillator circuits with a true-positive rate (TPR) of 100% and a false-positive rate (FPR) of only 4%. In addition, for the extremely difficult problem of detecting malicious bitstreams embedded in legitimate bitstreams, a pipeline of a random forest and a support vector machine classifiers trained on subarrays of bitstreams can help detect bitstreams of malicious circuits embedded in legitimate designs with TPR of 95.5% and FPR of 30.4%.
Teachers’ intention to continue using virtual learning environment (VLE): Malaysian context

Malaysian teachers have been using Virtual Learning Environment (VLE) technology in their instructional activities since it was introduced by the Ministry of Education in 2012. This study aimed to measure Malaysian teachers’ level of intention to continue using VLE technology and investigate factors influencing teachers’ decision to keep using VLE into teaching and learning process. Implementing sequential explanatory design, we addressed 850 questionnaires and conducted interview with 10 teachers. After data screening procedure, only 643 questionnaires were usable and measurable in the data analysis. Fifty-one teachers answered the open ended question included in the questionnaire. We further asked questions adapted from the data analysis of the questionnaires to ten teachers. The results of the study informed that the overall mean score of teachers’ intention to continue using VLE is 4.21. This mean score indicated that the intention to continue using VLE technology among the Malaysian teachers is at the moderate level. Despite this, the percentage of the teachers with high intention to use VLE whenever they have access is higher than those with the low intention. Qualitatively, accessibility factor was the main factor experienced by the participants of this study reducing the VLE integration into teaching. Further investigation is necessary to study the factors and suitable planning and policy that contribute to the intention to continue using VLE among Malaysian teachers.
The Impact of Different Levels of Income Inequality on Subjective Well-Being in China: A Panel Data Analysis

Abstract Income inequality is one of the most serious issues globally and China is the representative examples of this issue. Income inequality remains high in China and may negatively affects subjective well-being. This study clarifies whether income inequality affects subjective well-being in China. Using five waves of the 2010-2018 data from China Family Panel Studies, a panel data analysis reveals the following: First, general income inequality measured by provincial Gini coefficients has a significant U-shaped impact. Second, between-group income inequality, measured as income ratio between urban hukou residents and migrants with rural hukou, has a significant U-shaped impact. Third, urban-rural income inequality measured by provincial urban to rural household per capita income ratio has an inverted-U-shaped impact. To address endogeneity problems of income inequality, this study adopts instrumental variable approach. For the further robustness checks of the validity of the instrumental variable used, this study adopts the recent Conley et al. (2012) bounds approach. Our results are robust after addressing endogeneity problem. One important policy implication stemming from our results is the need to adopt strategies that ensure a more inclusive society without hukou-related and urban–rural discrimination.
Chaos Embedded Meta-heuristic Algorithms for Optimal Design of Truss Structures

The success of embedded chaos in meta-heuristic algorithms is mainly due to providing good balance between exploration and exploitation for meta-heuristics. Comparison of optimization results with algorithms in standard mode and embedded of chaos shows a significant improvement in quality of the meta-heuristic algorithms, thus reducing the weight of truss structures. Four chaos meta-heuristic algorithms with logistic, Tenet and Gaussian maps are considered to improve the results. Despite truss optimization being severely nonlinear and non-convex and often having several local optima, the use of different chaos allows the local optima to be escaped and global optimums to be achieved.
How Team Composition and Collaborative Planning Jointly Shape Analytic Effectiveness

This study investigates the separate and joint effects of the inclusion of experts and collaborative planning on the performance of analytic teams. Teams either did or did not include members with expert-level task-relevant cognitive abilities, and either did or did not receive an intervention that fostered collaborative planning. Results support the authors’ hypothesis that analytic performance requires both task-appropriate expertise and collaborative planning to identify strategies for optimally using that expertise. Indeed, high expertise in the absence of collaborative planning actually decreased team performance. Teams engaging in collaborative planning were more likely to effectively integrate their information on key aspects of the analytic problem, which significantly enhanced their analytic performance. Furthermore, information integration mediated the effects of the interaction of expertise and collaboration on performance. The implications of the findings for the optimal use of team member skills and the development of team performance strategies are discussed.
Non-Controlling Shareholders and Innovation: Evidence from Chinese State-Owned Enterprises

ABSTRACT We examine the effect of non-controlling shareholders (NCSs) on innovation in Chinese state-owned enterprises (SOEs). Using a sample of Chinese SOEs during 2007–2016, we find that the voting rights of NCSs positively relate to SOEs’ innovation. Furthermore, we distinguish the identities of NCSs in terms of state-owned attributes and show that this positive relationship is concentrated in SOEs whose NCSs are state-owned. Additionally, we find that the effect of NCSs is more pronounced in financially constrained SOEs, and that SOEs with influential NCSs reduce inefficient investments while make more R&D investments. Overall, our results indicate that influential NCSs have a positive effect on SOEs’ innovation through retaining more resources for innovation projects, and this effect varies somewhat depending on the state-owned attributes of NCSs.
The losses and temperature comparison in three-phase distribution transformer with various assembly core designs

ABSTRACT Losses in a three-phase transformer can be minimised to a considerable extent by improving the core design. In this paper, a new proposed model (hexagon and hemisphere) of T-joint designs is presented as one of the solutions to reduce the losses for a three-phase transformer. The behaviours of magnetic flux density, load variation, core and winding temperature have been considered and discussed accordingly in this study. The losses of the core and windings were considered a heat source inside the transformer. A nonlinear behaviour of the core material and a 3D finite-element method were employed for the simulation of the proposed models of the transformer cores. The simulation results of the proposed models showed a reduction of no-load and total losses ranging from 7% to 16% compared with the conventional designs. The verification of the results was compared with the experimental results for the 1 MVA and the 11/0.433 kV distribution transformer. This work confirms that it is still possible to reduce the losses of transformer by reassembling the core, particularly in the joint area.
Bilingual processing of case-marking and locative verbs in Korean: Use of L2-unique information

Aims and objectives/purpose/research questions: Previous studies show conflicting findings regarding bilingual processing of target information not instantiated in learners’ first language. The current study addresses this issue by investigating whether Chinese speakers can integrate case-marking information, which is unique to Korean, with locative verb information in their processing of the Korean locative constructions. Design/methodology/approach: We conducted an acceptability judgment task to assess Chinese–Korean bilinguals’ explicit knowledge of case-marking constraints on Korean locative constructions, and a self-paced reading task to probe their application of the knowledge to real-time sentence processing. Data and analysis: Twenty-four advanced Chinese–Korean bilinguals’ acceptability judgments and reading times were compared with those of 24 Korean monolingual speakers, using mixed-effects regression modeling. Findings/conclusions: Results from the offline acceptability judgment task revealed the bilinguals’ native-like judgment patterns. Both Korean monolingual and Chinese–Korean bilinguals rejected sentences with wrong case-marking sequences paired with locative verbs. In the self-paced reading task, both monolingual and bilingual speakers showed increased reading times when a mismatch arose between case-marking and locative verb information, indicating their sensitivity to locative agreement violations. Originality: While previous studies have investigated bilinguals’ integration of multiple sources of information, this study adds a new perspective to this issue by testing whether bilinguals can use L2-unique information (i.e., case marking) to integrate it with other types of information (i.e., locative verbs) for sentence processing. Significance/implications: Our findings are consistent with the competition model which predicts that L2-unique information presents little processing difficulty for bilinguals. At the same time, the current results lend credence to the idea that increased proficiency allows bilinguals to integrate multiple information sources during processing.
Minimizing Regret

In repeated games with di®erential information on one side, the labelling \general case" refers to games in which the action of the informed player is not known to the uninformed, who can only observe a signal which is the random outcome of his and his opponent's action. Here we consider the problem of minimizing regret (in the sense ¯rst formulated by Hannan [8]) when the information available is of this type. We give a simple condition describing the approachable set.
Stripe segmentation of oceanic internal waves in synthetic aperture radar images based on Mask R-CNN

Abstract The development of deep learning and remote sensing makes it possible to obtain information about oceanic internal waves from massive data. Oceanic internal waves play an important role in ocean activities. To obtain the light and dark stripes from synthetic aperture radar (SAR) images, a stripe segmentation algorithm for oceanic internal waves is proposed based on Mask R-CNN. The research results show that the proposed method can not only identify whether there are oceanic internal waves, but also obtain the respective locations of the light and dark stripes in the images. The width and the direction angle of each light and dark stripe can be obtained efficiently by a separation and matching method with the sector region (SMMSR). Moreover, based on the identified relative locations of the light and dark stripes, it is possible to further determine the time when the oceanic internal waves undergo polarity conversion.
Impact of COVID-19 lockdown on food habits, appetite and body weight in Tunisian adults

Abstract Tunisia recorded the highest rate of COVID-19 positive cases and deaths in Africa but no studies assessed the impact of the pandemic on eating patterns as in the case of several countries. The objective of the present study was to investigate the perception of changes in food habits, appetite and body weight in Tunisian adults of both genders aged 20–74 years old. A cross-sectional study has been carried out with a non-probabilistic sampling method based on an online self-administered survey. Of overall 1082 adults included in the study, 57⋅8 % reported a change in their eating habits: 21⋅2 % an increase in their consumption of fresh fruits, vegetables, pulses, pasta and bread, while 36⋅6 % an increase of homemade cakes and biscuits, sweets, processed meat, sugary drinks and alcoholic drinks. In addition, tea, coffee and herbal tea have been reported as excessively consumed during the lockdown period. More than half experienced appetite variations (34⋅6 % increased appetite and 23⋅0 % appetite loss). Inequality detrimental to women was reported regarding eating habit changes (women consumed more unhealthier foods than men). Elderly subjects (over 60 years) were less likely to negatively change food habits in comparison with young adults (20–25 years), while ungraduated respondents were more prone to negatively change their food habits. Almost half reported weight gain. As the negative influence of the lockdown period on eating habits with the increase of obesity risk has been detected, health policy may be advised to focus on using mass media campaigns to promote healthy eating habits, in particular for illiterate and young people.
Creation of competitive advantage in improving the business performance of banking companies

Purpose – This study aimed to examine the impact of innovation, intellectual capital and knowledge management, and competitive advantage on business performance. Design/methodology/approach – This study was conducted in Padang City, West Sumatra, Indonesia. The respondents are bank employees who have worked for more than five years and have structural positions in the company. The data has been collected using a survey with questionnaires. This study got 109 responses out of 135 questionnaires, so the response rate was 80.7%. It employed the Structural Equation Modeling (SEM) approach using Smart-PLS as the data analysis software. Findings – This study found that (1) innovation has a positive and significant effect on competitive advantage; (2) knowledge management has a negative but insignificant effect on competitive advantage; (3) intellectual capital has a positive and significant effect on competitive advantage; and (4) competitive advantage has a positive and significant effect on business performance. Surprisingly, it found that innovation significantly indirectly affects business performance through competitive advantage as a mediating variable. Intellectual capital has a significant indirect effect on business performance through competitive advantage as a mediating variable. Research limitations/implications – This study result can be more impactful considering several factors. First, this study is a cross-sectional study. Hence, it has a limitation in finding generalizations. Therefore, for further research, it could be expanded to a longitudinal study. Second, it is one country study. Future research might be extended to some countries with similar cultures, such as Southeast Asian Countries. Practical implications – This study has implications for the decision-makers. First, companies need to develop their intellectual capital through improving employee skills and applying information technology in business processes in order to maintain the company's competitive advantage so that it has an impact on improving the company's business performance. Second, the company is expected to be able to manage the knowledge owned by the company so that the knowledge it has can increase the creation of company innovation it provides a competitive advantage for the company. Originality/value –The contribution of this research is that the results of this study can be used as empirical evidence for banking companies of the importance of the role of IC, innovation, and KM in improving company performance by constantly creating the company's competitive advantage.
Improving the Restorability of Bulk Power Systems With the Implementation of a WF-BESS System

This paper proposes a restorability improvement strategy to accelerate system restoration through the implementation of a wind farm-battery energy storage system (WF-BESS) system. The concept of restorability is introduced and a restorability improvement model (RIM) is proposed and formulated as a mixed integer linear programming problem. To simulate the cylinder temperature drop during outages, the cranking time of a unit is modeled as a stepwise function of its startup time in the RIM. The WF might fail to meet its scheduled generation outputs optimized by the RIM due to the intermittency of wind. To tackle this problem, a linearized control strategy for the BESS (CSBESS) is proposed to minimize the difference between the scheduled wind power outputs and the combined power of the WF-BESS system. An iterative method is employed to efficiently solve the RIM and CSBESS by introducing optimality cuts. An actual power system case is employed to illustrate the effective performance of the proposed approach.
Numerical study of uneven wall-heating effect for a one side rib-roughened cooling channel subject to rotation

ABSTRACT This paper investigates the impact of the wall-heating conditions on the heat transfer performance of a rotating channel with one side smooth and one side roughened by 45° inclined ribs. Previous experimental and numerical studies for single-ribbed wall-heated channels showed that rotation has a significant negative impact on heat transfer performance. In order to investigate this uncommon behaviour, RANS simulations were conducted under three different wall-heating conditions in the present study: ribbed wall heated, all walls heated and adiabatic conditions. Numerical results show that the presence of uneven wall-heating conditions has a negligible impact on the stationary case, but it has a large influence on rotational cases, in both, the heat transfer and the flow field. The underlying reason is that in rotating cases, uneven heating results in different buoyancy effects on the trailing and leading walls of the channel that alter the main flow velocity profile. As a consequence, also secondary flows and heat transfer performance are affected.
Prevalence and Pattern of Mandibular Fractures: A Retrospective Study in India

Objective: The main objective of this study is to analyze the prevalence of age, gender distribution, etiology, anatomic distribution, and treatment of mandibular fractures. Materials and Methods: This 2-year retrospective study was carried out in few multispeciality hospitals in India. The results were collected, and descriptive statistics were analyzed using SPSS. Results: Of 180 patients that were analyzed, males and the age group of 20–30 years had a higher prevalence of mandibular fractures with road traffic accidents being the most common etiological factor. Condyle was the most common site affected. Open treatment with rigid and nonrigid fixation was the commonly used method of treatment. Conclusion: Stratification of various epidemiological studies with data obtained over a large study period and sample size must be obtained to understand the plausible factors associated with mandibular fractures for appropriate diagnosis and management of mandibular fractures.