Miracle-dz/UniFAR-FTUs huggingface dataset:
Bystanders’ Victim Blaming and Minimizing Consequences of Weight-Based Cyberhate Attacks: The Roles of anti-Fat Attitudes, Body-Positive Online Content, and Gender

Physical appearance and, specifically, weight are common reasons for cyberhate attacks among adolescents. Using a between-subject experimental design, this study focuses on the bystanders of such attacks on Instagram. We investigate bystanders’ assessments in the form of two moral disengagement (MD) mechanisms—victim blaming and minimizing consequences—and we compare the assessments of attacks that are diversified by the victim’s weight (i.e., a victim who is plus-size and a victim who is thinner). We also examine the moderating roles of bystanders’ prejudice against people who are plus-size in the form of the so-called anti-fat attitudes, their frequency of viewing body-positive online content, and gender. The study’s data come from an online survey conducted in 2020 with a representative sample of 658 Czech adolescents, aged 13–18. We tested our hypotheses with structural equation modeling. The results show that the two MD mechanisms work differently. The victim’s displayed weight affected the bystanders’ tendency to victim blame: adolescents blamed the victim who is plus-size more than the victim who is thinner, but the victim’s weight made no difference in minimizing the consequences of the incident. A moderating effect for anti-fat attitudes and gender was found for victim blaming. Bystanders with higher anti-fat attitudes and boys blamed the victim who is plus-size more than the victim who is thinner. On the other hand, there was no effect for the frequency of viewing body-positive online content for either of the MD mechanisms. The results are discussed with regard to the differences between the two mechanisms and the practical implications for educational and prevention programs for youth.
Review of atmospheric turbulence over cities

This paper provides a comprehensive, critical review of turbulence observations over cities. More than fifty studies are analysed with their experimental conditions summarized in an appendix. The main results are based on 14 high‐quality experiments which met criteria based on stringent experimental requirements. The observations are presented as non‐dimensional statistics to facilitate comparison between urban studies and work conducted over other rough, inhomogeneous surfaces. Wake production associated with bluff bodies, and the inhomogeneous distribution of sources and sinks of scalars, result in a roughness sub‐layer which for the studies reviewed extends to about 2.5 to 3 times the height of the buildings. It is shown that within this region the basis of several traditional micrometeorological approaches to describe the turbulent exchange is in doubt. There are strong similarities to flow over plant canopies, and many of the turbulence characteristics can be interpreted in the framework of a plane mixing layer. Future field observations should concentrate on the turbulent exchange near the top and within the urban canopy as well as within the urban boundary layer.
How Can Quantitative Analysis Be Used to Improve Occupational Health without Reinforcing Social Inequalities? An Examination of Statistical Methods

Taking account of sex and gender in occupational health studies poses statistical challenges. Other sociodemographic variables, such as racialization, class, and age, also affect the relations between workplace exposures and health and interact with sex and gender. Our objective was to perform a critical review of conventional and emerging statistical tools, examining whether each analysis takes account of sociodemographic variables (1) in a way that contributes to identification of critical occupational determinants of health (2) while taking account of relevant population characteristics to reflect intersectional approaches to health and (3) using sample sizes and population characteristics available to researchers. A two-step search was conducted: (1) a scientific watch concerning the statistical tools most commonly used in occupational health over the past 20 years; (2) a screening of the 1980–2022 literature with a focus on emerging tools. Our examination shows that regressions with adjustment for confounders and stratification fail to reveal the sociodemographic mechanisms that interact with occupational health problems, endangering the identification of occupational risks. Multilevel (notably MAIHDA) analyses, decision tree, cluster, and latent analyses are useful methods to consider when seeking to orientate prevention. Researchers should consider methods that adequately reveal the mechanisms connecting sociodemographic variables and occupational health outcomes.
Numerical simulation of slider temperature rise caused by read/write current

The Joule heat caused by read/write operation leads to nanodeformation of slider body and variation of head-disk spacing. In this work, the heat transferring between slider and disk surfaces is numerically simulated based on an unstructured adaptive triangular mesh method and the Voronoi polygons control volume method. Results suggest that the heat transferring between slider and disk surfaces plays a very important role in determining the final temperature value and distribution over slider’s air-bearing surface (ABS). Furthermore, the writing operation, due to its high writing current, is of significant thermal effects to both writing head and MR sensor. The temperature distribution over the air bearing surface is asymmetrical and depends on the air bearing pressure and heat flux distribution. Also, higher slider flying speed increases the heat transferring between slider and disk surface. Furthermore, it is noticed that the heat conduction dominates the heat transferring between slider and disk surface.
BOUNDARY-CONFORMING MAPPING APPLIED TO COMPUTATIONS OF HIGHLY DEFORMED SOLIDIFICATION INTERFACES

SUMMARY A new boundary-conforming mapping is developed for the calculation of highly deformed cellular solidification interfaces in a model of directional solidification of a binary alloy. The mapping is derived through a variational fomulation that is designed so that the grid penetrates the grooves between cells along the interface without causing a loss of ellipticity of the mapping equations. A finite element/Newton method is presented for simultaneous solution of the free boundary problem described by the solutal model of directional solidification and the mapping equations. Results are compared to previous calculations and demonstrate the importance of accurate representation of the interface shape for understanding the solution structure.
Application of Discrete Fourier Transform to Find Reliable Shortest Paths

Reliable shortest paths, in this paper, are paths that ensure a desired probability of arriving on time or earlier with the least time budget. Finding reliable shortest paths requires the evaluation of path travel time distributions through numerical convolution, which is a computationally intensive procedure. This paper develops several convolution methods based on the discrete Fourier transform (DFT) and compares them with a direct convolution method implemented with adaptive discretization. Two shortcomings in the conventional DFT-based convolution are recognized, namely, the incompatibility with dynamic programming and the computational inefficiency associated with support points that have negligible probability mass. Remedies are proposed to overcome these shortcomings. However, numerical experiments suggest that, even with these improvements, the DFT-based convolution methods are still not as computationally competitive as the direct convolution method, contrary to the promise of the theoretical complexity analysis.
An MPI parallel level-set algorithm for propagating front curvature dependent detonation shock fronts in complex geometries

We present a parallel, two-dimensional, grid-based algorithm for solving a level-set function PDE that arises in Detonation Shock Dynamics (DSD). In the DSD limit, the detonation shock propagates at a speed that is a function of the curvature of the shock surface, subject to a set of boundary conditions applied along the boundaries of the detonating explosive. Our method solves for the full level-set function field, φ(x, y, t), that locates the detonation shock with a modified level-set function PDE that continuously renormalises the level-set function to a distance function based off of the locus of the shock surface, φ(x, y, t)=0. The boundary conditions are applied with ghost nodes that are sorted according to their connectivity to the interior explosive nodes. This allows the boundary conditions to be applied via a local, direct evaluation procedure. We give an extension of this boundary condition application method to three dimensions. Our parallel algorithm is based on a domain-decomposition model which uses the Message-Passing Interface (MPI) paradigm. The computational order of the full level-set algorithm, which is O(N 4), where N is the number of grid points along a coordinate line, makes an MPI-based algorithm an attractive alternative. This parallel model partitions the overall explosive domain into smaller sub-domains which in turn get mapped onto processors that are topologically arranged into a two-dimensional rectangular grid. A comparison of our numerical solution with an exact solution to the problem of a detonation rate stick shows that our numerical solution converges at better than first-order accuracy as measured by an L1-norm. This represents an improvement over the convergence properties of narrow-band level-set function solvers, whose convergence is limited to a floor set by the width of the narrow band. The efficiency of the narrow-band method is recovered by using our parallel model.
A Pilot Reanalysis Project at COLA

Abstract Results are presented from a retrospective analysis of 19 months (May 1982–November 1983) of global atmospheric observations. The National Meteorological Center Global Data Assimilation System was used in tandem with the atmospheric general circulation model of the Center for Ocean-Land-Atmosphere Studies to produce four-times-daily representations of the global atmosphere. Statistics were compiled regarding the use of data by the analysis and the decisions of the quality control procedures. Comparison of the reanalyses with both observation and the archived contemporaneous analyses showed substantial improvements in the representation of the global atmospheric circulation, possibly excepting the Southern Hemisphere south of 60°S. A list of data products from the reanalysis is given in an appendix.
Default Credit Predictive Analytics Model to Enhance Bank Decision Making Using Big Data

In the financial sector, figuring out a person›s creditworthiness may be exceedingly challenging. Individual credit scores or credit report data are a major component of traditional models that determine credit eligibility. If they can receive financial services at all, it will probably be at very high-interest rates and fees. This sort of strategy makes it exceedingly difficult for those with little to no credit to do so. Financial institutions have been looking for methods to include non-traditional data into the credit risk process to provide services to these people at more affordable prices while maintaining the risk at manageable levels. With an accuracy that is acceptable to financial institutions, Machine Learning (ML) could be utilized to estimate a person›s creditworthiness using atypical data. On the data supplied by Home Credit Group, we processed and engineered features. With an AUC of 0.7926 and 92% accuracy, the Light Gradient Boosting Machine (LGBM) model trained using this data can predict the probability of default using 5-fold cross-validation. The system produced promising results and outperformed all other state-of-the-art methods.
Antibody Avidity Maturation Following Recovery From Infection or the Booster Vaccination Grants Breadth of SARS-CoV-2 Neutralizing Capacity

Abstract Background Cross-neutralizing capacity of antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants is important in mitigating (re-)exposures. Role of antibody maturation, the process whereby selection of higher affinity antibodies augments host immunity, to determine SARS-CoV-2 neutralizing capacity was investigated. Methods Sera from SARS-CoV-2 convalescents at 2, 6, or 10 months postrecovery, and BNT162b2 vaccine recipients at 3 or 25 weeks postvaccination, were analyzed. Anti-spike IgG avidity was measured in urea-treated ELISAs. Neutralizing capacity was assessed by surrogate neutralization assays. Fold change between variant and wild-type neutralization inferred the breadth of neutralizing capacity. Results Compared with early-convalescent, avidity indices of late-convalescent sera were significantly higher (median, 37.7 [interquartile range 28.4–45.1] vs 64.9 [57.5–71.5], P < .0001). Urea-resistant, high-avidity IgG best predicted neutralizing capacity (Spearman r = 0.49 vs 0.67 [wild-type]; 0.18–0.52 vs 0.48–0.83 [variants]). Higher-avidity convalescent sera better cross-neutralized SARS-CoV-2 variants (P < .001 [Alpha]; P < .01 [Delta and Omicron]). Vaccinees only experienced meaningful avidity maturation following the booster dose, exhibiting rather limited cross-neutralizing capacity at week 25. Conclusions Avidity maturation was progressive beyond acute recovery from infection, or became apparent after the booster vaccine dose, granting broader anti-SARS-CoV-2 neutralizing capacity. Understanding the maturation kinetics of the 2 building blocks of anti-SARS-CoV-2 humoral immunity is crucial.
Peripheral T-Cell Lymphoma, Not Otherwise Specified – a case report and short literature review

ABSTRACT Peripheral T-cell lymphoma, not otherwise specified (PTCL-NOS) is the most common subgroup of peripheral T-cell lymphomas (PTCL), and constitutes a diagnosis of exclusion. At presentation, most patients exhibit B symptoms and generalized lymphadenopathy, with or without concomitant extra-nodal involvement. We present a case of a man admitted to the hospital with B symptoms, generalized lymphadenopathy and a pruritic exanthema. Laboratory workup reveled persistent eosinophilia and malignant hypercalcemia. The excisional lymph node biopsy diagnosed PTCL-NOS, and the skin biopsy demonstrated a lichenoid dermatitis, compatible with the presumptive clinical diagnosis of a drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome. The patient was treated with topical betamethasone with good overall response, and initiated the first cycle of chemotherapy before discharge. This case report describes a PTCL-NOS with a concomitant non-lymphoproliferative disease, the challenging diagnostic workup of the two diseases and reinforces the most important features of the lymphoproliferative neoplasm.
Direct numerical simulation and reduced chemical schemes for combustion of perfect and real gases

La premiere partie de cette these traite du developpement du code de simulation numerique directe YWC, principalement du developpement des conditions aux limites. En effet, une forte contribution scientifique a ete apportee aux conditions aux limites appelees "Three dimensional Navier-Stokes characteristic boundary condtions" (3D-NSCBC). Premierement, la formulation de ces conditions aux aretes et coins a ete completee, ensuite une extension de la formulation a ete proposee pour supprimer les deformations observees en sortie dans le cas d'ecoulements non-perpendiculaires a la frontiere. De plus, ces conditions ont ete etendues au cas des gaz reels et une nouvelle definition du facteur de relaxation pour la pression a ete proposee. Ce nouveau facteur de relaxation permet de supprimer les deformations observees en sortie pour des ecoulements transcritiques. Les resultats obtenus avec le code YWC ont ensuite ete utilises dans la seconde partie de la these pour developper une nouvelle methode de tabulation basee sur l'analyse en composantes principales. Par rapport aux methodes existante telles que FPI ou SLFM, la technique proposee, permet une identification automatique des variables a transporter et n'est, de plus, pas lie a un regime de combustion specifique. Cette technique a permis d'effectuer des calculs d'interaction flamme-vortex en ne transportant que 5 especes a la place des 9 requises pour le calcul en chimie detaillee complete, sans pour autant perdre en precision. Finalement, dans le but de reduire encore le nombre d'especes transportees, les techniques T-BAKED et HT-BAKED PCA ont ete introduites. En utilisant une ponderation des points sous-representes, ces deux techniques permettent d'augmenter la precision de l'analyse par composantes principales dans le cadre des phenomenes de combustion.
Metallicity and kinematics of a large sample of LMC and SMC clusters

Abstract We have carried out a large-scale investigation of the metallicity and kinematics for a number of LMC and SMC star clusters using Ca ii triplet spectra obtained at the VLT. Our sample includes 28 LMC and 16 SMC clusters, covering a wide range of ages and spatial extent of the host galaxy. We determine mean cluster velocities to about 2 km s−1 and metallicities to 0.05 dex (random error), from about 7 members per cluster. Herein we present the main results for this study for the cluster metallicity distributions, metallicity gradients, age-metallicity relations and kinematics.
The Influence of Training Design Factors on Training Transfer: A Preliminary Study

Organizations invest considerably in training and development programmes anticipating successful outcomes. An unsuccessful training is often associated with poor return on investment. An effective training focuses on two critical components, which are the design of the training, also known as training design factors comprising of perceived content validity and transfer design, as well as training transfer, but few of them focus on the context of academics in university. Thus, this preliminary study aims to expand training and development body of knowledge through the investigation of the relationships and influence of training design factors on training transfer. This quantitative, correlational research uses simple random sampling technique to determine the required sample size. This study involves a total of 100 academics who are working in a public, research university in Malaysia. The academics have previously attended a training programme organized by the university prior to participating in this study. Results show that both training design factors i.e., perceived content validity and transfer design are significantly related to but are not significantly influencing training transfer among the academics. It is highly recommended for future researchers to replicate this study with a bigger sample size and to include other variables related to training transfer as well.
Smoothing-aided long-short term memory neural network-based LTE network traffic forecasting

There is substantial demand for high network traffic due to the emergence of new highly demanding services and applications such as the internet of things (IoT), big data, blockchains, and next-generation networks like 5G and beyond. Therefore, network resource planning and forecasting play a vital role in better resource optimization. Accordingly, forecasting accuracy has become essential for network operation and planning to maintain the minimum quality of service (QoS) for real-time applications. In this paper, a hybrid network- bandwidth slice forecasting model that combines long-short term memory (LSTM) neural network and various local smoothing techniques to enhance the network forecasting model's accuracy was proposed and analyzed. The results show that the proposed hybrid forecasting model can effectively improve the forecasting accuracy with minimal data loss.
The Effect of Mealworm Frass on the Chemical and Microbiological Properties of Horticultural Peat in an Incubation Experiment

Insect farming is growing in popularity, and in addition to insect meal, it generates waste products such as exuviae and frass, which can be recycled in agriculture. The aim of this incubation experiment was to evaluate the effect of Tenebrio molitor L. frass on selected chemical and biological properties of deacidified peat, which is widely used in horticulture. The optimal rate of frass fertilizer in peat for growing vegetables and ornamental plants was determined, with special emphasis on mineral nitrogen levels. Peat was fertilized with five nitrogen rates, 0, 50, 100, 200, and 400 mg dm−3, and supplied with frass or urea. The study demonstrated that frass can be used as organic fertilizer. An increase in the nitrogen rate significantly increased mineral nitrogen content and electrical conductivity and decreased Ca content in peat. Both frass and urea increased the ammonification rate at the beginning of incubation and the nitrification rate from the second week of the experiment. Higher frass rates (5 and 10 g dm−3) increased the content of plant-available nutrients (nitrogen, phosphorus, magnesium, potassium, and sodium) in peat as well as the abundance of microorganisms supporting organic matter mineralization. Unlike frass, urea increased the counts of nitrogen-fixing bacteria in peat.
Phase-Coded FMCW for Coherent MIMO Radar

The phase-coded linear-frequency-modulated continuous-wave (PC-FMCW) waveform with a low sampling processing strategy is studied for coherent multiple-input multiple-output (MIMO) radar. The PC-FMCW MIMO structure, which jointly uses both fast-time and slow-time coding, is proposed to reduce sidelobe levels while preserving high range resolution, unambiguous velocity, good Doppler tolerance, and low sampling needs. The sensing performance and practical aspects of the introduced PC-FMCW MIMO structure are evaluated theoretically and verified experimentally. The numerical simulations and experiments demonstrate that the proposed MIMO keeps the advantages of the linear-frequency-modulated continuous-wave (LFMCW) waveform, including computational efficiency and low sampling demands, while having the ability to provide low sidelobe levels with simultaneous transmission.
On the Therapeutic Potential of ERK4 in Triple-Negative Breast Cancer

Simple Summary Patients with triple-negative breast cancer have a poor outcome owing to the clinically aggressive behavior of the disease and the lack of hormonal or targeted therapies. Identification of new actionable targets to guide the development of effective treatments remains a critical clinical need. It has been recently suggested that the protein kinase ERK4 has oncogenic signaling activity in triple-negative breast cancer cells and represents a promising novel therapeutic target. However, we raise questions about the experimental approaches used to validate the oncogenic function of ERK4 in breast cancer. Abstract ERK3 and ERK4 define a distinct and understudied subfamily of mitogen-activated protein kinases (MAPKs). Little is known about the physiological roles of these atypical MAPKs and their association with human diseases. Interestingly, accumulating evidence points towards a role for ERK3 and ERK4 signaling in the initiation and progression of various types of cancer. Notably, a recent study reported that ERK4 is expressed in a subset of triple-negative breast cancer (TNBC) cell lines and that this expression is critical for AKT activation and for sustaining TNBC cell proliferation in vitro and tumor growth in mice. The authors also showed that depletion of ERK4 sensitizes TNBC cells to phosphatidylinositol-3-kinase (PI3K) inhibitors. They concluded that ERK4 is a promising therapeutic target for TNBC and has potential for combination therapy with PI3K inhibitors. Here, we raise concerns about the cellular models and experimental approaches used in this study, which compromise the conclusions on the oncogenic role of ERK4 in TNBC.