Miracle-dz/UniFAR-FTUs huggingface dataset:
An attempt of using public ambient temperature data in swine genetic evaluation for litter size traits at birth in Japan

To obtain the fundamental information on using ambient temperature information in developing the model for routine swine genetic evaluation in Japan, we analyzed total number born (TNB), number born alive (NBA), and number stillborn (NSB) collected at a Japanese farm, together with off-farm ambient temperature measured at a nearest Automated Meteorological Data Acquisition System station. Five repeatability animal models were exploited, considering the effects of farrowing season (model 1), farrowing month (model 2), quadratic regressions of daily maximum ambient temperature of farrowing day (model 3), season and temperature (model 4), or month and temperature (model 5). Patterns of the effects of daily maximum temperature of farrowing day estimated using model 3 was similar to those of farrowing season by model 1 and those of farrowing month by model 2. Adding the effect of daily maximum temperature of farrowing day (models 4 and 5) could explain phenotypic variability greater than only considering either of farrowing season and month (models 1 and 2). Estimated heritability was stable among the models and the rank correlation of predicted breeding values between models was >0.98 for all traits. The results indicate the possibility that using public ambient temperature can capture a large part of the phenotypic variability in litter size traits at birth caused by the seasonality in Japan and do not harm, at least, the performance of genetic evaluation. This study could support the availability of public meteorological data in flexible developing operational models for future swine genetic evaluation in Japan.
A survey of light-vehicle driver education programs to determine the prevalence of curriculum on sharing the road with heavy vehicles : final report

The NSTSCE stakeholders have jointly funded this research for the purpose of developing and disseminating advanced transportation safety techniques and innovations. The authors of this report would like to thank the subject matter experts for reviewing the survey and providing valuable feedback prior to distribution. The authors would also like to thank the many driver education administrators and association members, both at the state and national level, who provided support by assisting in the distribution of the survey to participants. Their level of support was crucial in the overall success of this project. The mission of NSTSCE is to use " …state-of-the-art facilities, including the Virginia Smart Road, to develop and test transportation devices and techniques that enhance driver performance, examine advanced roadway delineation and lighting systems, and address age-related and fatigued driver issues. " (1) One of the primary goals of NSTSCE is to develop a greater understanding of driver decision making and performance. Recent research investigated light-vehicle/heavy-vehicle near-crashes and crashes (critical incidents) and found that 78 percent were initiated by the light-vehicle driver. (2) The most common incident type involved the light vehicle changing lanes without sufficient gap to the heavy vehicle. This larger proportion of light-vehicle, at-fault incidents may result from inadequate training about heavy-vehicle dynamics during light-vehicle driver education programs. The purpose of this project was to survey curricula of light-vehicle driver education programs and assess any information that is relevant to heavy-vehicle characteristics and procedures for light-vehicle drivers safely driving around heavy vehicles (sharing the road).
Direct and Indirect Effects of Social Support and School Social Capital on the Academic Success of 11–19-Year-Old Students Using Distance Learning

In the context of current changes in the education process due to the pandemic, the main aims of this study were to highlight social capital factors within the school community that are associated with better students’ outcomes in the context of distance learning. This study was a cross-sectional population-based study. The research sample consisted of 1483 students, whose ages varied from 11 to 19 years old (56.9% were girls). Academic success in this study was measured in terms of average grade and students’ perception of their learning process or outcomes by six single items. A Five-item WHO-5 questionnaire was used to measure students’ psychological well-being. Social capital was measured in terms of relationship, trust, reciprocity, and communication within different social contexts in the school community in total by 16 items. School social capital and social support scales were developed from these items. Students’ gender and age were also taken into consideration. The research results show that although social capital from parents and peers also matters, the relationship with teachers emerges as the main and the most important resource in supporting positive attitudes and outcomes in to learning (std.β varied from 0.116 to 0.439). The results also show that higher psychological wellbeing is associated with higher perceived school social capital (std.β 0.260) and social support (std.β 0.326) and mediates the effects of the latter two for better academic success outcomes. The findings also highlight the importance of close and trusting social ties, especially between students and their teachers as well as parents for better learning outcomes in times of crises and in the context of distance learning. The study results prove that social support and social capital at school are essential factors for sustainable psychological development. The results presumably support the idea that the school is sustainable if it is developing as an ecosystem not solely aimed at academic outcomes. The results of the current study may aid policymakers and practitioners in developing interventions, policies and practices that focus resources where they will have the greatest benefit.
RS-20 type repetitive generator with planar configuration of plasma opening switch

Existing experience in production of rep. rate accelerators with a high peak power (over than 10 10 W) and average power above 50 kW enables to resolve a row of physics and technology tasks which are connected with reliability and life of the accelerator. This paper considers the design and results on optimization of simple plasma opening switch (POS).
Interactions between Sleep and Emotions in Humans and Animal Models

Recently, increased interest and efforts were observed in describing the possible interaction between sleep and emotions. Human and animal model studies addressed the implication of both sleep patterns and emotional processing in neurophysiology and neuropathology in suggesting a bidirectional interaction intimately modulated by complex mechanisms and factors. In this context, we aimed to discuss recent evidence and possible mechanisms implicated in this interaction, as provided by both human and animal models in studies. In addition, considering the affective component of brain physiological patterns, we aimed to find reasonable evidence in describing the two-way association between comorbid sleep impairments and psychiatric disorders. The main scientific literature databases (PubMed/Medline, Web of Science) were screened with keyword combinations for relevant content taking into consideration only English written papers and the inclusion and exclusion criteria, according to PRISMA guidelines. We found that a strong modulatory interaction between sleep processes and emotional states resides on the activity of several key brain structures, such as the amygdala, prefrontal cortex, hippocampus, and brainstem nuclei. In addition, evidence suggested that physiologically and behaviorally related mechanisms of sleep are intimately interacting with emotional perception and processing which could advise the key role of sleep in the unconscious character of emotional processes. However, further studies are needed to explain and correlate the functional analysis with causative and protective factors of sleep impairments and negative emotional modulation on neurophysiologic processing, mental health, and clinical contexts.
The Effect of Occupational Health Risk Perception on Job Satisfaction

This study explored the relationship between occupational health risk perception and job satisfaction. Based on the job demand-resources model and resource conservation theory, eight hypotheses were proposed in this study. In a survey of 237 production line workers and managers, we found that perceived occupational health risks significantly negatively affected job satisfaction. Both work stress and organizational commitment mediate the relationships between perceived occupational health risks and job satisfaction. We also examined whether safety culture could weaken the negative impact of perceived occupational health risks on job satisfaction. However, the results of our study did not support this hypothesis. This study not only helped managers to realize the hazards of occupational health risks, but also encouraged employees to actively participate in safety construction and pay attention to their own health. In addition, we also put forward some targeted intervention measures to reduce the negative impact of perceived occupational health risks on job satisfaction. Therefore, this study had certain practical implications.
Single-view 3D Body and Cloth Reconstruction under Complex Poses

Recent advances in 3D human shape reconstruction from single images have shown impressive results, leveraging on deep networks that model the so-called implicit function to learn the occupancy status of arbitrarily dense 3D points in space. However, while current algorithms based on this paradigm, like PiFuHD, are able to estimate accurate geometry of the human shape and clothes, they require high-resolution input images and are not able to capture complex body poses. Most training and evaluation is performed on 1k-resolution images of humans standing in front of the camera under neutral body poses. In this paper, we leverage publicly available data to extend existing implicit function-based models to deal with images of humans that can have arbitrary poses and self-occluded limbs. We argue that the representation power of the implicit function is not sufficient to simultaneously model details of the geometry and of the body pose. We, therefore, propose a coarse-to-fine approach in which we first learn an implicit function that maps the input image to a 3D body shape with a low level of detail, but which correctly fits the underlying human pose, despite its complexity. We then learn a displacement map, conditioned on the smoothed surface and on the input image, which encodes the high-frequency details of the clothes and body. In the experimental section, we show that this coarse-to-fine strategy represents a very good trade-off between shape detail and pose correctness, comparing favorably to the most recent state-of-the-art approaches. Our code will be made publicly available.
The effectiveness of standardized investigative tactics in clearing non-fatal shooting investigations

Much research explores the correlates of clearing fatal shooting incidents. It is suggested that common investigative resources and tactics, such as the number of detectives and witness interviews, may be associated with clearing both fatal and non-fatal shooting cases. This study examines the effect of a standardized list of investigative tools in the clearing of non-fatal shooting incidents. For this study, detectives from the Buffalo Police Department's Gun Violence Unit completed an “Investigative Checklist” for non-fatal shootings that occurred between November 2019 and December 2020 (N = 234 usable cases). Bivariate correlation analysis shows a strong association between uncooperative victims and a detective conducting multiple canvases as part of the investigation. Logistic regression shows that examining a suspect's social media information, and detectives accessing patrol car reports, contributed to successfully clearing a non-fatal shooting case. An uncooperative victim was negatively associated with clearing a case. Police practitioners should be aware, based on the findings of this and other research, that a small number of investigative techniques contribute to non-fatal shooting case clearance rates. It may be necessary for police agencies to construct detective units, and focus on a narrow set of investigative tactics, in a way that improved clearance rates in non-fatal shootings.
Forecasting of Daily Gold Price using ARIMA-GARCH Hybrid Model

Gold is a multifunctional precious metal. Apart from being jewelry, gold is a form of investment. For this reason, the public or investors need to know the estimated daily gold price for transactions for the public or investors who want to invest or also want to sell their gold, so they do not lose. This is the aim of this study. Many forecasting methods can be used to predict the daily gold price, but this study uses the ARIMA-GARCH hybrid model because this model can predict econometric models such as the daily gold price which usually contains high volatility. Daily gold price data was secondary data obtained from the investing.com website. The data was for the period March 12, 2016, to December 31, 2020. The results of this study are obtained for the ARIMA (1,1,1) -GARCH (2,1) hybrid model with a root mean square error (RMSE) forecasting accuracy value is 2.375454, the mean absolute error (MAE) is 1.702908, and the mean absolute percentage error (MAPE) is 0.001168113. From the results of this study, long-term investment is very profitable because there is an upward trend from the model obtained. For short-term investments, the public or investors have to update the research result model because the current gold price is influenced by the gold price only one period ago, so that when trading does not lose.
Aspects of linear estimation in H

A recent but rapidly maturing field in the area of system identification has been that of ‘estimation in ’. Greatly influencing this work has been the phenomenon that no linear (in-the-data) algorithm exists which is ‘robustly convergent’. This paper conducts a study of the nature of this issue by combining specific new analysis together with existing results from the mathematics literature on the topic of polynomial approximation theory. Particular attention is paid in this paper to the role of model order, and this leads to the consideration of model order selection from a deterministic worst-case perspective. Technical Report EE9833, Department of Electrical and Computer Engineering University of Newcastle, Callaghan 2308, AUSTRALIA
Parametric inference on quantile residual life

The need for residual life analysis arises in many fields including medicine and life testing. For instance, in medicine, a clinician and a patient would be interested in knowing by how long a new drug can extend the life span of that patient. Problems in remaining life time after surviving up to a certain time are often framed and addressed statistically in terms of mean, hazard rate or quantile. The quantile approach enjoys some practical advantages over the other approaches such as robustness, ease of interpretation, and existence. Most of the methodological work on quantile residual life in the literature has been semi-parametric or non-parametric. However, parametric approaches are expected to be optimal or asymptotically efficient under a correct specification of the model. Furthermore, the parametric approach does not require nonparametric estimation of the probability density function of the underlying distribution under informative or noninformative censoring to evaluate the variance of the quantile estimator. In this dissertation, parametric inference procedures for the quantile residual life under competing and non-competing risks settings are developed for the one-sample, two-sample and regression cases. We adopt the accelerated failure time (AFT) framework to incorporate covariates for the regression case. The finite sample properties of the proposed methods are studied through extensive simulations. The simulation results indicate that the proposed methods perform well. The proposed methods are applied to a breast cancer data. PUBLIC HEALTH SIGNIFICANCE: The results established in this dissertation will provide new parametric methods to researchers and investigators in public health who conduct quantile residual life analysis, which will facilitate efficient communication between researchers and stakeholders regarding the efficacy of new interventions.
The Determinants of Visitor's Revisit Intention: A Lesson from Ijen Car Free Day

Event industry currently is considered as one of interesting business opportunity in contributing major positive economic impact. Event could be categorized into some activities conducted by an event management or event organizer in the case of achieving some specific outcomes. An event is also recognized as an essential marketing tool in branding of particular destination. It has a powerful function to make a differentiation between one destination and others. This study aims to establish a theoretical event brand equity for which the key components of the brand equity were evaluated from visitor perspective in the tourism context. Brand equity is constructed by four multidimensions which are event brand awareness (EBA), event brand image (EBI), event brand quality (EBQ), and event revisit intention (ERI). By using convenience sampling, 205 visitors of Ijen Car Free Day (ICFD) as the event object were used as respondents to obtain the data. This study uses Partial Least Square (PLS) to analyze the data both in outer model and inner model measurements. The finding of this study indicate that EBA has positive and significant influence to EBI, EBQ, and ERI. Then, EBI is also proven giving positive and significant influence to EBQ and ERI. In contrary, EBQ does not show significant influence to ERI. The significance movement of this study could be useful measurement in assessing event brand equity management in the future.
Numerical Modeling of Self-heating in MOSFET and FinFET Basic Logic Gates Using Effective Thermal Conductivity

Recent trend of minimization in microprocessors has introduced increasing self-heating effects in FinFET and MOSFET transistors. To study these self-heating effects, we developed selfconsistent 3D models of FinFET and MOSFET basic logic gates, and simulated steady-state thermal transport for the worst heating case scenario. Incorporating size-dependent effective thermal conductivity of thin films instead of bulk values, these simulations provide a more accurate prediction of temperature rise in the logic gates. Results of our simulations predict higher temperature rise in FinFETs, compared to MOSFETs. Existence of buried oxide layer and confined geometry of FinFET structure are determined to be the most contributing to this higher temperature rise. To connect the results of our simulations to higher scale simulations, we proposed an equivalent thermal conductivity for each basic logic gate. These values were tested and found to be independent of the magnitude of chosen boundary conditions, as well as heat
Low-cost fluorinated diatomaceous earth polyurethane foam for the absorption of oil

In the present work, we intend to focus on the synthesis, characterization, and application of a high-performing hydrophobic and oleophilic polyurethane foam functionalized with diatomaceous earth and fluorosilane, which are eco-friendly and low-cost materials for their potential use as absorbents for hydrophobic materials. The scanning electron microscopic studies and thermogravimetric analysis showed that the surface-modified polyurethane has a significant micro–nano-structure and surface functionalization, and the water contact angle measurement showed an increase in hydrophobicity due to the fluorosilane-functionalized diatomaceous earth particles anchoring onto the polyurethane foam. Also, the thermogravimetric analysis revealed an increased thermal stability due to the surface functionalization. The novel fluorosilane—diatomaceous earth—polyurethane foam exhibited a silver mirror-like effect when immersed into water due to inherent hydrophobicity and had an enhanced absorption of oil and organic solvents compared to the unmodified polyurethane. This research presents the successful synthesis of surface-modified polyurethane for its suitability for oil absorption capacity for cleaning the oil pollutants from water and for organic solvents clean-up purposes. Overview of the research approach, which represents stepwise synthesis of the polyurethane (PU) foam surface modified with diatomaceous earth (DE) and fluorosilane (FS) to form low-density and high-absorbing surface-functionalized PU foam exhibiting enhanced oil absorption making this novel composite as a potential candidate for crude oil clean-up and recovery process.
Ginseng for the Treatment of Chronic Fatigue Syndrome: A Systematic Review of Clinical Studies

Background Chronic fatigue syndrome (CFS) is a complex and often disabling chronic condition emerging worldwide, with no curative or definitive therapy yet identified. Ginseng has been widely used to treat fatigue in other patient groups and conditions; however, a systematic review focusing solely on the impact of ginseng on fatigue in patients with CFS has not been performed. Objective This study aimed to assess the current state of evidence regarding ginseng for CFS. Methods Multiple databases were searched from inception to October 2020. All data was extracted independently and in duplicates. Outcomes of interest included the effectiveness and safety of ginseng in patients with CFS. Results 2 studies enrolling 68 patients were deemed eligible, including one randomized clinical trial and one prospective observational study. The certainty of evidence in the effectiveness outcome was low and moderate from both studies, while the safety evidence was very low as reported from one study. Conclusion Study findings highlight a potential benefit of ginseng therapy in the treatment of CFS. However, we are not able to draw firm conclusions due to limited clinical studies. The paucity of data warrants limited confidence. There is a need for future rigorous studies to provide further evidence.
Improving the EHMRG Prognostic Evaluation of Acute Heart Failure with TAPSE/PASp: A Sequential Approach

The Emergency Heart Failure Mortality Risk Grade (EHMRG) can predict short-term mortality in patients admitted for acute heart failure (AHF) in the emergency department (ED). This paper aimed to evaluate if TAPSE/PASp, an echocardiographic marker of ventricular desynchronization, can improve in-hospital death prediction in patients at moderate-to-high risk, according to EHMRG score classification. From 1 January 2018 to 30 December 2019, we retrospectively enrolled all the consecutive subjects admitted to our Internal Medicine Department for AHF from the ED. We performed bedside echocardiography within the first 24 h of admission. We evaluated EHMRG and NYHA in the ED, days of admission in Internal Medicine, and in-hospital mortality. We assessed cutoffs with ROC curve analysis and survival with Kaplan–Meier and Cox regression. We obtained a cohort of 439 subjects; 10.3% underwent in-hospital death. Patients with normal TAPSE/PASp in EHMRG Classes 4, 5a, and 5b had higher survival rates (100%, 100%, and 94.3%, respectively), while subjects with pathologic TAPSE/PASp had lower survival rates (81.8%, 78.3%, and 43.4%, respectively) (p < 0.0001, log-rank test). TAPSE/PASp, an echocardiographic marker of ventricular desynchronization, can further stratify the risk of in-hospital death evaluated by EHMRG.