Miracle-dz/UniFAR-FTUs huggingface dataset:
Numerical investigation of magnetic multiphase flows by the fractional-step-based multiphase lattice Boltzmann method

In the present study, a fractional-step-based multiphase lattice Boltzmann (LB) method coupled with a solution of a magnetic field evolution is developed to predict the interface behavior in magnetic multiphase flows. The incompressible Navier–Stokes equations are utilized for the flow field, while the Cahn–Hilliard equation is adopted to track the interface, and these governing equations are solved by reconstructing solutions within the LB framework with the prediction–correction step based on a fractional-step method. The proposed numerical model inherits the excellent performance of kinetic theory from the LB method and integrates the good numerical stability from the fractional-step method. Meanwhile, the macroscopic variables can be simply and directly calculated by the equilibrium distribution functions, which saves the virtual memories and simplifies the computational process. The proposed numerical model is validated by simulating two problems, i.e., a bubble rising with a density ratio of 1000 and a viscosity ratio of 100 and a stationary circular cylinder under an external uniform magnetic field. The interfacial deformations of a ferrofluid droplet in organic oil and an aqueous droplet in ferrofluid under the external magnetic field are, then, simulated, and the underlying mechanisms are discussed. Moreover, the rising process of a gas bubble in the ferrofluid is investigated, which shows that the rising velocity is accelerated under the effect of the external magnetic field. All the numerical examples demonstrate the capability of the present numerical method to handle the problem with the interfacial deformation in magnetic multiphase flows. Published under license by AIP Publishing. https://doi.org/10.1063/5.0020903. , s
HEADLESS INTERNET OF THINGS DEVICES THAT PROVIDE USER INTERFACE MODELS

: Internet of Things devices are becoming more frequent and used in the lives of everyone. Starting with sensor networks that are monitoring certain parts of an experiment in a laboratory and continuing with simple appliances almost everyone has such a device. With the increasing usage of the devices the need for quick implementation of such a device became obvious. Besides the core functionality of a device, the user interface is the most important part, the simpler it is to use the higher the chance for a user to try the device. In this paper we present the concept and implementation of a framework that provides the tooling for creating user interface models that can be stored on the device itself and rendered on request in a prepared environment.
Strategies to improve the efficiency of beef cattle production

Abstract: Globally, there are approximately one billion beef cattle, and compared with poultry and swine, beef cattle have the poorest conversion efficiency of feed to meat. However, these metrics fail to consider that beef cattle produce high-quality protein from feeds that are unsuitable for other livestock species. Strategies to improve the efficiency of beef cattle are focusing on operational and breeding management, host genetics, functional efficiency of rumen and respiratory microbiomes, and the structure and composition of feed. These strategies must also consider the health and immunity of the herd as well as the need for beef cattle to thrive in a changing environment. Genotyping can identify hybrid vigor with positive consequences for animal health, productivity, and environmental adaptability. The role of microbiome–host interactions is key in efficient nutrient digestion and host health. Microbial markers and gene expression patterns within the rumen microbiome are being used to identify hosts that are efficient at fibre digestion. Plant breeding and processing are optimizing the feed value of both forages and concentrates. Strategies to improve the efficiency of cattle production are a prerequisite for the sustainable intensification needed to satisfy the future demand for beef.
The Role of Assets In Place: Loss of Market Exclusivity and Investment

We utilize a novel identification strategy to analyze the impact of assets in place on firms' decisions for future projects. We exploit the context in the pharmaceutical industry, where the loss of market exclusivity for a branded drug can be used to separate the impact of cash flows generated by a firm's current assets in place from the characteristics of its future investment opportunities. We first show that around the exclusivity losses in our sample of large drugs, the affected firms' profitability drops significantly. The timing of this profitability decrease was predetermined many years ago, and therefore, arguably independent of current investment opportunities. Nevertheless, we find that R&D spending drops by approximately 25% over two years following the loss of exclusivity of these pre-existing drugs. We also find that stock repurchases and cash balances decline significantly. Our findings do not support the predictions of traditional capital budgeting, but are more consistent with the pecking order theory. These results further point to a lack of long-term lifecycle management that could mitigate the effect of predictable negative shocks to cash flows.
A Systematic Review of Empirical Evidence on Teachers’ Organizational Commitment 1994–2018

ABSTRACT This article aims to integrate over two decades of empirical research findings on teachers’ organizational commitment (OC) to explore its antecedents and outcomes. Via a criteria-based approach, 68 peer-reviewed quantitative empirical articles published between 1994 and 2018 were identified and included for analysis. A systematic review revealed three core themes: demographic, within-person, and role-related predictors of teachers OC; interpersonal and contextual predictors of teachers’ OC; and outcomes of teachers OC. Our review detected major “blind spots” related to antecedents, mediators, and moderators, and outcomes. Recommendations are provided to help advance knowledge on teachers’ OC in upcoming decades.
Molecular Dynamics Simulation of Interfacial Tension of Ultra-Thin Liquid Films on a Solid Surface

The effect of wall proximity on the interfacial tension of ultra-thin liquid films of Lennard-Jones (12,6) fluid has been studied using Molecular Dynamics Simulation. The wall’s presence can potentially affect drop-wise condensation and other phase change phenomena such as boiling. Initially the Lennard-Jones atoms are placed near a solid wall with FCC lattice structure in a doubly periodic box. Once equilibrated at a desired temperature, a thin liquid film forms on the solid wall. The surface tension of the liquid-vapor interface is computed statistically. When the film is thick (> 40 Å), surface tension at the liquid-vapor interface is found to be unaffected by the presence of the solid wall and matches bulk values reported for Argon. However for thinner films (< 15 Å), surface tension of the liquid-vapor interface deviates from the macroscopic value. This has been investigated for various temperatures ranging from the triple point to the critical point. As the film thins further (1–2 molecules thickness), the liquid-vapor interface resembles a solid-vapor interface. Surface tension of this solid-vapor interface is evaluated for a solid wall modeled both by an equivalent interacted potential and discrete atoms. The two cases are found to yield different results. The Equivalent potential for the wall gives lower surface tension and liquid density near the solid wall compared to the discrete atoms case.
Post-Dispersal Seed Removal in a Large-Seeded Palm by Frugivore Mammals in Western Ecuador

Post-dispersal seed removal by ground-foraging frugivores promotes secondary dispersal of large seeds, reducing seed predation and increasing recruitment and regeneration. We studied how habitat disturbance influences seed removal patterns in the large-seeded palm Phytelephas aequatorialis within three habitats forming a continuum of disturbance (agroforestry system, disturbed forest, and less-disturbed forest) using seed removal experiments and camera trapping. We tested whether seed removal rates, and both richness and composition of seed remover communities varied between the habitats. On average, 15 seeds were removed under each tree in the agroforestry system over seven days, which was significantly lower compared to the disturbed forest (18) and the less-disturbed forest (19). Eight mammal species were identified removing seeds in the three habitats. On average, one mammal species removed seeds at each station in the agroforestry system, which was significantly lower than the two species observed in the two forests. The composition of seed remover communities was significantly different between the three habitats. Our results suggest that the loss of forest cover in the agroforestry system has reduced the richness of seed removers, which subsequently caused decreased removal rates. Nevertheless, this habitat could still maintain effective seed dispersal events because spiny rats were important seed removers. Our camera trap data should be taken as preliminary because we could only identify less than half of the animals responsible for seed removal. This study highlights the importance of medium- and large-sized rodents for the removal and effective dispersal of large seeds in disturbed tropical habitats.
Multiple-Platform and Multiple-Doppler Radar Observations of a Supercell Thunderstorm in South America during RELAMPAGO

On 10 November 2018, during the RELAMPAGO field campaign in Argentina, South America, a thunderstorm with supercell characteristics was observed by an array of mobile observing instruments, including three Doppler on Wheels radars. In contrast to the archetypal supercell described in the Glossary of Meteorology, the updraft rotation in this storm was rather short lived (~25 min), causing some initial doubt as to whether this indeed was a supercell. However, retrieved 3D winds from dual-Doppler radar scans were used to document a high spatial correspondence between midlevel vertical velocity and vertical vorticity in this storm, thus providing evidence to support the supercell categorization. Additional data collected within the RELAMPAGO domain revealed other storms with this behavior, which appears to be attributable in part to effects of the local terrain. Specifically, the IOP4 supercell and other short-duration supercell cases presented had storm motions that were nearly perpendicular to the long axis of the Sierras de Córdoba Mountains; a long-duration supercell case, on the other hand, had a storm motion nearly parallel to these mountains. Sounding observations as well as model simulations indicate that a mountain-perpendicular storm motion results in a relatively short storm residence time within the narrow zone of terrain-enhanced vertical wind shear. Such a motion and short residence time would limit the upward tilting, by the left-moving supercell updraft, of the storm-relative, antistreamwise horizontal vorticity associated with anabatic flow near complex terrain.
Industry 4.0-Related Digital Divide in Enterprises: An Analysis for The European Union-28

Digital divide has been measured using various indicators in the literature so far. In contrast from the literature, this paper addresses the digital divide within European Union member states according to Industry 4.0-related indicators that have been used for the first time in empirical literature. While Finland, the UK and Germany are among the countries with economic development levels above the EU average, Cyprus, Bulgaria, and Romania are among the countries that are below the Union average in terms of Industry 4.0-related development. It is clear that an Industry 4.0-related digital divide is observable within EU member countries. The European Union should try to decrease the digital gap between member countries by developing and supporting special Industry 4.0 policies, especially for members below the EU average. Therefore, the results of this article will help policy makers in the EU and in member countries.
Exploring the effects of gender grouping and the cognitive processing patterns of a Facebook-based online collaborative learning activity

ABSTRACT Efficient collaborative learning relies on productive interaction among learners. Previous studies have suggested that group gender composition might affect the group dynamics. While previous studies have generally focused on the learning performance of different gender groups, relatively little effort has been devoted to scrutinising the learning process. Therefore, this study seeks to further explore students’ cognitive processing patterns in the collaborative learning process among different gender groups, namely, five female-only groups (4 female students in each group), five male-only groups (4 male students in each group), and five balanced-gender groups (2 male and 2 female students in each group). This study employed quantitative content analysis and lag sequential analysis to explore students’ cognitive processing patterns in a Facebook-based online discussion learning activity. A total of 3230 messages in the online discussion were retrieved and analysed. The results indicate that the female-only groups were the most active groups in terms of the messages generated. By contrast, male-only groups were the least active but exhibited a more diverse discussion pattern. Meanwhile, the balanced-gender groups showed the most diverse cognitive transition patterns. Our findings could serve as a guideline for gender grouping and collaborative learning activity design.
Monitoring Public Transit Ridership Flow by Passively Sensing Wi-Fi and Bluetooth Mobile Devices

Real-time public transit ridership flow and origin-destination (O–D) information is essential for improving transit service quality and optimizing transit networks in smart cities. The effectiveness and accuracy of the traditional survey-based methods and smart card data-driven methods for O–D information inference have multiple disadvantages in terms of biased results, high latency, insufficient sample size, and the high cost of time and energy. By considering the ubiquity of smart mobile devices in the world, monitoring public transit ridership flow can be accomplished by passively sensing Wi-Fi and Bluetooth (BT) mobile devices of passengers. This study proposed a system for monitoring real-time public transit passenger ridership flow and O–D information based on customized Wi-Fi and BT sensing device. By combining the consideration of the assumed overlapping feature spaces of passenger and nonpassenger media access control address data, a three-step data-driven algorithm framework for estimating transit ridership flow and O–D information is proposed. The observed ridership flow is used as the ground truth for evaluating the performance of the proposed algorithm. According to the evaluation results, the proposed algorithm outperformed all selected baseline models and the existing filtering methods. The findings of this study can help to provide real time and precise transit ridership flow and O–D information for supporting transit vehicle management and the quality of service enhancement.
Research on Baidu Street View Road Crack Information Extraction Based on Deep Learning Method

Rapid and effective identification and extraction of road cracks has always been a major difficulty in road detection and maintenance. This paper applies the Deeplabv3 + model to road crack extraction, and proposes a new joint identification method for road cracks based on open network data and open source convolutional neural network. Based on the semantic segmentation theory and Deeplabv3+ neural network, this method uses baidu street view map as the training data set. By adjusting the proportion weight of road cracks and background, the training network model can quickly and accurately identify road cracks. Experimental results show that this method has achieved a good effect on crack segmentation: Mean Intersection over Union(MIOU) of this method is more than 70%, and the processing speed is 1 second/sheet, which is better than FCN algorithm.The results of road crack information extraction are similar to those of manual interpretation, which indicates that this method is feasible for quality evaluation of municipal roads.
Safe tracheostomy in COVID-19 patients: a case series

Currently, there is an increasing proportion of cities in the United States and countries around the world being severely affected by the COVID-19 virus. The current strain on healthcare systems due to an increased need for prolonged use of ventilators and medical supplies related to COVID-19 has brought to light the possible need for tracheostomy. Some institutions have been hesitant to perform tracheostomies in these patients because of the high-risk of aerosolization and dissemination of the virus to healthcare providers. Most proposed guidelines for tracheostomy in COVID-19 patients have all included negative pressure rooms, a dedicated and trained staff, proper personal protective equipment (PPE), and preference for open tracheostomy to percutaneous in an effort to minimize aerosolization. We have reviewed the various recently proposed guidelines by the United States and other countries for tracheostomies in general and specifically for COVID-19 patients to create our own institution-specific protocol. We implemented this protocol in all of the COVID-19 patients that received a tracheostomy at our institution. Our study expanded on the current published protocols for performance of tracheostomy in COVID-19 patients, examining key demographic and procedure related data, which is limited in the current literature. ABSTRACT
Inhibition of Exo-miR-19a-3p derived from cardiomyocytes promotes angiogenesis and improves heart function in mice with myocardial infarction via targeting HIF-1α

Background: Myocardial infarction (MI), a common presentation for cardiovascular disease, is caused by reduction of blood flow and oxygen supply and is one of the main causes of death worldwide. MicroRNAs participate in multiple physiological and pathological processed and play crucial role in myocardial infarction. Results: qRT-PCR analysis showed that expression level of miR-19a-3p was increased in serum of patient with MI. In vitro study indicated that the miR-19a-3p level was upregulated in response to H2O2 treatment and transferred by exosome, and then, uptake occurred in endothelial cells. Furthermore, western blot and immunostaining showed that treatment of exosome enriched miR-19a-3p suppressed the proliferation of endothelial cells and induced cell death, which was inhibited by AMO-19 transfection. Administration of antagomiR-19a-3p promoted angiogenesis and improved heart function of MI mice. Moreover, miR-19a-3p overexpression downregulated the protein level of HIF-1α and transfection of si-HIF-1α reversed the promotion of endothelial cells proliferation caused by AMO-19 transfection. In addition, antagomiR-19a-3p treatment accelerated angiogenesis and infection of AAV5-shHIF-1α inhibited that effect in MI mice. Conclusions: In conclusion, our finding indicated that miR-19a-3p inhibited endothelial cells proliferation and angiogenesis via targeting HIF-1α and attenuated heart function of mice after MI, and suggested a new mechanism of cell-to-cell communication between cardiomyocytes and endothelial cells.
Establishing management zones of soil sulfur and micronutrients for sustainable crop production

Deficiency of nutrients in agricultural soils of the world is one of the major factors of soil degradation. The deficiency of nutrients especially sulfur (S) and micronutrients in different soils affect global crop production. Delineation of soil management zones (MZs), by understanding spatial distribution of soil parameters, could be an efficient way for devising strategies for effective nutrient management and sustainable crop production. In this study, we aimed at creation of soil MZs for ameliorating S and micronutrients deficiencies in the Narmada River basin (NRB), an important agricultural area of central India. We collected 5,984 geo‐referenced top layer (0–15 cm) soil samples from the NRB, India, and analyzed for soil acidity (soil‐water suspension), electrical conductivity (soil‐water suspension), soil organic carbon (Walkley and Black carbon), phyto‐available S (0.15% calcium chloride [CaCl2] extractable), and phyto‐available (diethylene triamine penta acetic acid extractable) micronutrients namely zinc (Zn), copper (Cu), manganese (Mn), iron (Fe), and boron (B) (hot‐water‐soluble). The values of studied soil parameters varied widely with coefficient of variation values ranging from 11.0 to 74.9%. Pearson's correlation coefficient analysis revealed significant correlations among the soil parameters. Geostatistical analysis revealed exponential, pentaspherical, K‐Bessel, and circular best‐fit semi‐variogram models for different soil parameters with moderate to strong spatial dependence. About 41.2, 78.6, 10.1, 2.70, and 32.6% of the area of the NRB had a deficit concentration of phyto‐available S, Zn, Fe, Mn, and B, respectively. The principal component analysis and fuzzy c‐means clustering produced five MZs. The produced MZ maps could be utilized for prioritization of nutrients supply and adoption of zone‐specific soil nutrient management strategies in order to achieve sustainable crop production in the NRB of India.
Non-zero-sum reinsurance and investment game between two mean-variance insurers under the CEV model

This paper considers a non-zero-sum stochastic differential game between two competitive mean-variance insurers, who aim to seek the time-consistent reinsurance and investment strategies. These two insurers are allowed to purchase proportional reinsurance to mitigate individual claim risks; and can invest in one risk-free asset and one risky asset whose price dynamics follows the constant elasticity of variance model. The main objective of each insurer is to maximizing the mean-variance utility of his relative terminal wealth with respect to that of his competitor. Applying the techniques of stochastic control theory, we derive the Nash equilibrium reinsurance and investment strategies explicitly and present the corresponding verification theorem. Furthermore, Nash equilibrium strategies and value functions are also provided under the diffusion approximation model. Finally, we perform some numerical examples to illustrate the influence of model parameters on the equilibrium reinsurance and investment strategies and draw some economic interpretations from these results.
Computational Drug Repositioning: Current Progress and Challenges

Novel drug discovery is time-consuming, costly, and a high-investment process due to the high attrition rate. Therefore, many trials are conducted to reuse existing drugs to treat pressing conditions and diseases, since their safety profiles and pharmacokinetics are already available. Drug repositioning is a strategy to identify a new indication of existing or already approved drugs, beyond the scope of their original use. Various computational and experimental approaches to incorporate available resources have been suggested for gaining a better understanding of disease mechanisms and the identification of repurposed drug candidates for personalized pharmacotherapy. In this review, we introduce publicly available databases for drug repositioning and summarize the approaches taken for drug repositioning. We also highlight and compare their characteristics and challenges, which should be addressed for the future realization of drug repositioning.