Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Covid-19 lockdown on Intention to Follow Preventive Measures in Vietnam: Integrated Protection Motivation Theory and Theory Planed Behavior

Abstract Coronavirus (COVID-19), a highly transmissible disease that poses a global danger to human populations from 2019, had a pandemic breakout in Vietnam in May 2021. A total of 311 people responded to the online survey, which had 29 questions. The causal linkages of the latent factors construct were determined using structural equation modeling (SEM). Moreover, it integrated Protection Motivation Theory (PMT) and extended Theory of Planned Behavior (TPB) to evaluate factors affecting the intention to follow of COVID-19 prevention measures. As a consequence, SEM revealed that understanding of COVID-19 has a direct impact on risk perception. Moreover, the perceived risk of COVID-19 also had significant impacts on people’s attitude and perceived behavior control. While this study discovered a positive influence of attitude and perceived behavioral control on subjective norms. Intention to follow had been significant direct effects by subjective norm, perceived risk. Thus, the current study is one of the first studies to analyze factors affecting the intention to follow COVID-19 prevention measures during the global pandemic. This study also contributes to the managers and operators of measures to prevent the spread of diseases to find appropriate methods based on the factors affecting the effectiveness of COVID-19 prevention approaches.
Building a Transnational Network of Capitals: Korean Immigrant Mothers of Children with Disabilities in an Online Forum

ABSTRACT This online ethnographic study illuminates how Korean immigrant mothers of children with disabilities use their capitals to communicate, build community, and share resources in an online space. Employing the construct of community cultural wealth (CCW), we analyzed posts and comments by the mothers in an online forum on a transnational website. Findings revealed that the mothers actively (1) leverage their linguistic capital for sharing information and experience; (2) support each other through building a social network; and (3) cultivate aspirational capital through sharing feelings and empathy. This study counters the deficit-oriented paradigm on immigrant mothers of children with disabilities and reframes mothers as advocates who build community to collaboratively navigate their parenting journeys. This study also calls attention to the transnational network of capitals that immigrant mothers collaboratively build and encourages researchers and professionals to inquire into ways to better support immigrant mothers and their children.
Challenges and Opportunities for the Agricultural Producers in Sinana District in Reflection of COVID-19 Pandemic

Introduction. Analyzing the effect of COVID-19 is an important issue in agricultural sectors. However, such analysis requires a complex hierarchical statistical model. Rapid spread of the COVID-19 pandemic has disrupted the world’s production and productivity in many sectors. Among those sectors, the agricultural sector is highly affected. The Bale zone in the larger extent and Sinana district, in particular, is one of the potential agricultural areas in the Oromia regional state, Ethiopia where agriculture is the major sector in supporting the livelihood of thousands of subsistence farmers in the area as well as the country at large. Research Methodology. This study involved primary data collected from the farmers in the Sinana district during the period 2020–2021. A total of 991 farmers were selected from the entire 22 kebeles in the district. The data were analyzed using multilevel binary logistic random intercept regression models with maximum-likelihood parameter estimation. Results. Of the 991 farmers, 549 (55.4%) responded that COVID-19 has brought only challenges in their agricultural production and 311 (31.4%) responded both challenges and opportunities. About 632 (63.8%) of the farmers said that there was wastage of products such as milk, dairy, fruits, and vegetables. Three hundred twenty-eight (33.1%) of the participants obtained modernization in their agricultural production system like use of tractors and irrigation systems. According to the model results, farmer’s sex, age, educational level, family size, farmland size, types of effect, aggravation in food insecurity, input delay, lack of workers, slowdown of service, falling in income, modernization in the system of production, wastage of product, and types of wasted products were identified as significant factors. About 8% of the total variability in the effect of COVID-19 is due to differences across kebeles (ICC = 0.08, P value ≤0.05), and the remaining is due to individual differences. Conclusion. This study further demonstrated the potential of a hierarchical model for the study of COVID-19 effect variation within and between the kebeles. The majority, about 92% variation in the effect, is due to the disparity of individuals (farmers). The farmers with large family sizes and high capacity to produce and who were females were negatively related to the effect of COVID-19 in agricultural production.
The application of nonthermal plasma in methanol synthesis via CO2 hydrogenation

CH3OH is an energy carrier that can be generated from renewable resources and be used as a fuel in fuel cells and internal combustion engines and a platform chemical for the synthesis of value‐added chemicals or gasoline. Carbon dioxide (CO2) hydrogenation is one of the widely researched methods to generate methanol. The traditional CO2 hydrogenation reaction method (requires high H2 pressure and temperatures) has attracted considerable attention. However, the new emerging field of catalysis referred to as nonthermal plasma (NTP) catalysis has also been developed extensively for methane reforming and CO2 hydrogenation to methane and CO. The plasma‐assisted approach not only presents remarkable advantages, such as room temperature and atmospheric H2 pressure but also has great potential to be powered by renewable electricity in a flexible way since it can be easily switched on/off. In this account, we review the recent articles published on methanol synthesis from CO2 and H2 using NTP. We reviewed and discussed the mechanism of this reaction under NTP, the modification of the reactor configurations, and the rationale behind the catalyst design. In the end, we discussed the advantages and disadvantages of each of these works and the future perspectives of this interesting privileged reaction. We believe this review is of interest to researchers active in sustainable heterogeneous catalysis.
The activation of SIRT3 by dexmedetomidine mitigates limb ischemia-reperfusion–induced lung injury

Background The lung is one of the most sensitive organs, and is vulnerable to injury caused by limb ischemia-reperfusion (LIR). Dexmedetomidine, an anesthetic adjunct, has been shown to have therapeutic effects on lung injury secondary to LIR. This study aimed to investigate the role of dexmedetomidine in ameliorating LIR-induced lung injury in a mouse model of bilateral hind LIR. Methods In this study, 75 mice were randomly divided into 5 groups to prepare the LIR model. After the model was established, arterial blood was extracted for blood gas analysis. The pathological changes of lung tissue, lung wet/dry weight ratio, arterial blood gas analysis, detection of myeloperoxidase (MPO) activity, the content of reactive oxygen species (ROS), superoxide dismutase (SOD), glutathione peroxidase (GSH-Px) and malondialdehyde (MDA) in oxidative stress indexes, mitochondrial membrane potential (MMP), adenosine triphosphate (ATP) content and cytochrome c content were measured, and the relative protein expression levels of sirtuin-3 (SIRT3) and apoptosis factor Bcl-2 related X protein (Bax), B-cell Lymphoma 2 (Bcl-2), cleaved caspase 3, and nuclear factor erythroid 2-related factor 2 (Nrf2) and cytoplasmic heme oxygenase-1 (HO-1). Results Pretreatment with dexmedetomidine dramatically ameliorated LIR-induced lung injury, the wet/dry weight ratio, the arterial blood gas parameters, and enhanced SIRT3 expression. Moreover, dexmedetomidine significantly inhibits ROS and MDA level and restores antioxidant enzyme activities (SOD, GSH-Px). Of note, dexmedetomidine suppressed LIR-induced lung tissue apoptosis by modulating apoptosis-associated protein such as Bax, Bcl-2, and cleaved caspase 3. Moreover, dexmedetomidine inhibited the LIR-induced decreases in MMP, ATP levels, and the release of cytochrome c of LIR to maintain mitochondrial function. Latest study has shown that activating Nrf2 could promote SIRT3 expression to alleviate IR injury. Intriguingly, dexmedetomidine could facilitate nuclear Nrf2 and cytoplasmic HO-1 expression. Conclusions Our findings suggest that dexmedetomidine protects against LIR-induced lung injury by inhibiting the oxidative response, mitochondrial dysfunction and apoptosis. The mechanism appears to be at least partly mediated through the upregulation of SIRT3 expression.
Current Therapeutic Approach to Atrial Fibrillation in Patients with Congenital Hemophilia

Cardiovascular disease in hemophiliacs has an increasing prevalence due to the aging of this population. Hemophiliacs are perceived as having a high bleeding risk due to the coagulation factor VIII/IX deficiency, but it is currently acknowledged that they also have an important ischemic risk. The treatment of atrial fibrillation (AF) is particularly challenging since it usually requires anticoagulant treatment. The CHA2DS2-VASc score is used to estimate the risk of stroke and peripheral embolism, and along with the severity of hemophilia, guide the therapeutic strategy. Our work provides the most complete, structured, and updated analysis of the current therapeutic approach of AF in hemophiliacs, emphasizing that there is a growing interest in therapeutic strategies that allow for short-term anticoagulant therapy. Catheter ablation and left atrial appendage occlusion have proven to be efficient and safe procedures in hemophiliacs, if appropriate replacement therapy can be provided.
Technological Change and the Finance Wage Premium

We use a massive matched employer-employee database to explain the financial wage premium in the Netherlands. Using this data, we show that the excessive wage in the finance industry steadily increased over the period 2006-2018 despite the Global Financial Crisis (GFC) and the European Debt Crisis. Consistent with the substitution of capital for unskilled labor to exploit technical change, we also observe that the number of high-skilled workers and the capital associated with information and computer technologies (ICT) increased rapidly post-GFC. Guided by these facts, we study if the finance wage premium is explained by ICT capitalskill complementary at industry level when controlling by the observed and unobserved worker and firm characteristics. Contrary to a long literature documenting an excessive and unexplained wage premium in the finance industry, we find a low (even negative) finance wage premium.
Silicon Sensors for the Upgrades of the CMS Pixel Detector

The Compact Muon Solenoid (CMS) is a general purpose detector at the Large Hadron Collider (LHC). The LHC luminosity is constantly increased through upgrades of the accelerator and its injection chain. Two major upgrades will take place in the next years. The first upgrade involves the LHC injector chain and allows the collider to achieve a luminosity of about 2 · 10 cms. A further upgrade of the LHC foreseen for 2025 will boost its luminosity to 5 · 10 cms. As a consequence of the increased luminosity, the detectors need to be upgraded. In particular, the CMS pixel detector will undergo two upgrades in the next years. The first upgrade (phase I) consists in the substitution of the current pixel detector in winter 2016/2017. The upgraded pixel detector will implement new readout electronics that allow efficient data taking up to a luminosity of 2 · 10 cms, twice as much as the LHC design luminosity. The modules that will constitute the upgraded detector are being produced at different institutes. Hamburg (University and DESY) is responsible for the production of 350 pixel modules. The second upgrade (phase II) of the pixel detector is foreseen for 2025. The innermost pixel layer of the upgraded detector will accumulate a radiation damage corresponding to an equivalent fluence of Φeq = 2 · 10 cm and a dose of ≈ 10MGy after an integrated luminosity of 3000 fb. Several groups are investigating sensor designs and configurations able to withstand such high doses and fluences. This work is divided into two parts related to important aspects of the upgrades of the CMS pixel detector. For the phase I upgrade, a setup has been developed to provide an absolute energy calibration of the pixel modules that will constitute the detector. The calibration is obtained using monochromatic X-rays. The same setup is used to test the buffering capabilities of the modules’ readout chip. The maximum rate experienced by the modules produced in Hamburg will be 120MHz/cm. For this rate the modules’ efficiency has been measured to be 99%. In view of the module production, the energy calibration procedure has been automated. The modules assigned to the Hamburg production center should be completed by the end of February 2016. For the phase II upgrade, thin silicon sensors with an active thickness of 100μm irradiated with protons up to Φeq = 1.3 · 10 cm have been characterized. The charge collection efficiency has been measured using pad diodes. Charge multiplication effects have been observed for both nand p-bulk sensors. P-bulk strip sensors with an active thickness of 100 and 200μm have been characterized with a beam test. The signal of these sensors lies between 4000 and 5000 e− after a fluence of 1.3 · 10 cm. The 200μm thick sensors require a higher bias voltage than the 100μm thick sensors to reach this signal height. The threshold necessary to obtain 95% detection efficiency is found to be around 2000 e− for the 100μm
Forecasts of MJO during DYNAMO in a coupled tropical channel model, Part I: Impact of parameterization schemes

A coupled tropical channel model is developed to forecast the Madden–Julian Oscillation (MJO) event during the Dynamics of the MJO (DYNAMO) campaign period. Eight sets of 30‐day hindcast experiments are performed using different combinations of cumulus parameterization and planetary boundary layer (PBL) schemes. The results indicate that a well‐simulated mean state is a prerequisite for MJO forecast, and the model's ability to reproduce the mean state is sensitive to the parameterization schemes. The experiment with Tiedtke (TDK) cumulus parameterization and University of Washington (UW) PBL schemes can successfully predict the MJO event. Over the equatorial Indian Ocean, this experiment has a good representation of zonal sea surface temperature (SST) gradient and low‐level westerly wind, favouring a reasonable atmospheric circulation. As a result of boundary‐layer convergence in the eastern Indian Ocean, more water vapour is gathered in the low‐middle troposphere by updrafts, contributing to the PBL moistening ahead of the MJO convection and the eastward‐propagation of MJO precipitation. Further analysis reveals that the high cloud is accompanied by strong convection. A better simulation in tropical high cloud fraction helps trap the cloud radiation heating to warm middle‐upper troposphere, which promotes the MJO propagation. Our results suggest that the selection of proper parameterization schemes with a better‐simulated mean state is crucial to predicting the MJO event in the tropical channel model.
An investigation into the base pressure of simplified automotive squareback geometries

Since the fuel crisis of the 1970s, aerodynamic design has become essential to the vehicle design process in order to reduce fuel consumption and lower emissions as well as (in more recent years) increase the range on vehicles with alternative powertrains. Production car manufacturers have developed shape optimisation techniques that have generated significant improvements over the years however, in order to achieve further gains, a deeper understanding of the fundamental flow structures around vehicles must be achieved. This thesis reports the findings of three studies that aim to understand how the base pressure is manipulated on vehicle like geometries by applying shape optimisations. The base pressure typically contributes approximately 30% of the overall vehicle drag on production vehicles and so presents an opportunity for significant drag saving. A fundamental One-Box model was used to investigate how changing fore-body drag can effect the base pressure and wake topology at varying ground clearances. It was found that at high ground clearances the total drag changes were generated by base pressure changes however when the model was lowered into ground effect the fore-body and skin friction drag produced significantly larger changes than the base pressure. Analysis of the unsteady results showed that with a thinner boundary layer over the model the unsteadiness in the wake was increased. A second study was then conducted on a generic vehicle geometry, the Windsor model, where the lower separation was manipulated through the use of different underbody profiles . As the lower boundary layer on the model was thickened the lower recirculation region grew and lowered the pressure on the base. This was also seen to increase the unsteadiness of the pressures recorded on the base when the upper and lower shear layers were of significantly different strengths. Finally, a rear end optimisation was conducted on the Windsor model using high aspect ratio tapers on the top and bottom trailing edges. It was seen that the amount of downwash or upwash created by the tapers acted on the wake balance which moved the impingement region on the base. This changed the near wall velocities of the wake flow and resulted in changing base pressures. Overall the work has shown that, by controlling the flow conditions at separation, the base pressure can be modified, particularly by altering the relative strengths of the upper and lower shear layers and the impingement location on the base.
Joint Optimization of Depth and Ego-Motion for Intelligent Autonomous Vehicles

The three-dimensional (3D) perception of autonomous vehicles is crucial for localization and analysis of the driving environment, while it involves massive computing resources for deep learning, which can’t be provided by vehicle-mounted devices. This requires the use of seamless, reliable, and efficient massive connections provided by the 6G network for computing in the cloud. In this paper, we propose a novel deep learning framework with 6G enabled transport system for joint optimization of depth and ego-motion estimation, which is an important task in 3D perception for autonomous driving. A novel loss based on feature map and quadtree is proposed, which uses feature value loss with quadtree coding instead of photometric loss to merge the feature information at the texture-less region. Besides, we also propose a novel multi-level V-shaped residual network to estimate the depths of the image, which combines the advantages of V-shaped network and residual network, and solves the problem of poor feature extraction results that may be caused by the simple fusion of low-level and high-level features. Lastly, to alleviate the influence of image noise on pose estimation, we propose a number of parallel sub-networks that use RGB image and its feature map as the input of the network. Experimental results show that our method significantly improves the quality of the depth map and the localization accuracy and achieves the state-of-the-art performance.
Gaps, Trends and Challenges in Assessing Quality of Service at Airport Terminals: A Systematic Review and Bibliometric Analysis

This study investigates the main aspects of the quality of service (QoS) assessment process at airport passenger terminals to find gaps, highlight trends, and discuss current day challenges. A systematic literature review (SLR) was conducted in Scopus and ISI Web of Science databases. Excluding redundancies, the searches resulted in an initial set of 565 articles. After preliminary steps, 61 of these studies were selected for in depth analysis. The research findings and discussions are organized into subsections focused on: (1) places of application (countries/regions); (2) airport areas; (3) evaluators profile; (4) methods; and (5) evaluation criteria. The main gaps revealed are the lack of: (a) applied studies in underdeveloped or developing countries; (b) specific studies for important airport areas, such as those related to access; (c) studies using assessments from arriving and transfer passengers, as well as from travel professionals and experts; and (d) full noncompensatory multicriteria sorting methods. In terms of trends, there is a clear advance in the use of data mining and sentiment analysis, evidencing the challenge for airport managers in dealing with the sources of online information as a management tool. Finally, the challenge of including in assessment process new criteria related to sustainability and COVID-19 era aspects is also noteworthy.
Individual Preventive Behaviors of COVID-19 and Associated Psychological Factors Among Chinese Older Adults: A Cross-Sectional Online Survey

Purpose Older adults aged 60 years and above are classified as being of high-risk for infection during the COVID-19 pandemic. This study aimed to investigate the associations of psychological factors (motivational factors: risk perception, health knowledge, attitude, subjective norm, motivational self-efficacy, and intention; volitional factors: volitional self-efficacy, planning, and action control) of preventive behaviors with three preventive behaviors (hand washing, facemask wearing, and social distancing) among Chinese older adults during the COVID-19 pandemic. Methods A cross-sectional questionnaire survey was administered via SOJUMP, a widely used online survey platform in China. A total of 928 older adults (mean = 67.24 years, age range: 60–90 years, SD = 6.43, 55.9% females) were recruited using a snowball sampling approach from Hubei Province (n = 667) and outside Hubei Province (n = 261) in China during May 18, 2020 to June 7, 2020. Multiple hierarchical regressions were conducted with four models to examine the association between demographic, past behavior, psychological factors and each preventive behavior. Principal Findings All three preventive behaviors in older adults increased dramatically during the pandemic of COVID-19. Gender, living status, educational level, past behavior, health knowledge, intention and planning significantly predicted hand washing behavior, R2 = 0.395, F(10, 927) = 54.372, p < 0.001. Gender, education level, important others (e.g., family members or friends) infection, past behavior, health knowledge, planning and action control significantly predicted mask wearing behavior, R2 = 0.202, F(10, 927) = 23.197, p < 0.001. Living place, past behavior and health knowledge significantly predicted social distancing behavior, R2 = 0.204, F(9, 927) = 26.201, p < 0.001. Major Conclusions Past behavior and health knowledge predicted all three preventive behaviors. Planning was an important psychological factor for both hand washing and mask wearing behaviors. All those critical demographic and psychological factors are critical for future interventions to facilitate older adults to comply with three preventive behaviors in daily life and to stay healthy during the COVID-19 pandemic.