Miracle-dz/UniFAR-FTUs huggingface dataset:
Perspectives of Learning and Training Practitioners on Gamification

United States’ information technology (IT) training professionals provided perspectives regarding the gamification of employee training to address turnover and reskilling needs. Participants (N = 9) aged 23 or above, with 5 years of training experience, provided their perceptions about gamified training during semi-structured interviews. A generic qualitative inquiry data analysis technique led to five themes: gamification is for onboarding and skills development and meets a variety of training needs; going beyond characteristics and elements of the game motivates employees; keeping the training end goal in mind is vital; gamification reduces time and resources by creating auto-nudges which track and remind employees to complete training; and, gamification assists with team building and collaboration, career development, and employee retention. Gamification can provide varied training, including compliance, onboarding, technical, and career training. Gamification training costs could be offset by reduced employee travel or location costs of live training.
Rank estimation of a transformation model with observed truncation

This paper introduces rank estimators for a general transformation model with observable truncation points. The estimators, which are modified versions of the rank estimators of Han (1987) and Cavanagh and Sherman (1998), are asymptotically normal and require no bandwidth choice. Log-concavity of the error disturbance? s survival function is a sufficient condition for the associated monotonicity conditions. Monte Carlo simulations investigate the estimators? behavior for various sample sizes.
SERPINB3, Adult-Onset Immunodeficiency, and Generalized Pustular Psoriasis

Background: Generalized pustular psoriasis (GPP; MIM 614204) is a rare and severe pustular autoinflammatory skin disease in which acute generalized erythema and scaling develop with numerous sterile pustules. GPP shares skin manifestations, especially pustular skin reaction, with adult-onset immunodeficiency (AOID) with anti-interferon-γ autoantibodies, an autoimmune disease. Methods: Clinical examinations and whole-exome sequencing (WES) were performed on 32 patients with pustular psoriasis phenotypes and 21 patients with AOID with pustular skin reaction. Immunohistochemical and histopathological studies were performed. Results: WES identified three Thai patients presenting with similar pustular phenotypes—two with a diagnosis of AOID and the other with GPP. A heterozygous missense variant chr18:g.61325778C>A NM_006919. 2: c.438G>T; NP_008850. 1: p.Lys146Asn; rs193238900 in SERPINB3 was identified in two patients: one with GPP and the other with AOID. The other patient who had AOID carried a heterozygous missense variant chr18:g.61323147T>C NM_006919. 2: c.917A>G; NP_008850. 1: p.Asp306Gly in SERPINB3. Immunohistochemical studies showed overexpression of SERPINA1 and SERPINB3, a hallmark of psoriatic skin lesions. Conclusions: Genetic variants in SERPINB3 are associated with GPP and AOID with pustular skin reaction. The skin of patients with GPP and AOID carrying SERPINB3 mutations showed overexpression of SERPINB3 and SERPINA1. Clinically and genetically, GPP and AOID appear to share pathogenetic mechanisms.
Data-driven Model Reduction via Operator Inference for Coupled Aeroelastic Flutter

This paper presents a data-driven, physics-informed model reduction technique applied to two large-scale applications: parametric nonlinear aerodynamics and coupled aeroelastic flutter. We first develop a reduced-order model (ROM) parameterized by Mach number for the compressible Navier-Stokes equations solved via a computational fluid dynamics code. We use the non-intrusive operator inference scientific machine learning method as our model reduction technique. We then extend this technique to the coupled aeroelastic case by incorporating a modal decomposition model obtained from a finite element analysis code. We use NASA’s FUN3D software to run the high-fidelity simulations. We demonstrate the parametric ROM for nonlinear subsonic fluid flow over the VAT aircraft and the coupled ROM for flutter of the AGARD wing. We show that compared to the high-fidelity FUN3D simulations, parametric operator inference speeds up computation time by approximately three orders of magnitude, and coupled operator inference speeds up flutter computation time by approximately two orders of magnitude. ∗∗
Linear stability of a ridge

We investigate the stability of the three-phase contact line of a thin liquid ridge on a hydrophobic substrate for flow driven by surface tension and van der Waals forces. We study the role of slippage in the emerging instability at the three-phase contact line by comparing the lubrication models for no-slip and slip conditions at the liquid/substrate interface. For both cases we derive a sharp-interface model via matched asymptotic expansions and derive the eigenvalues from a linear stability analysis of the respective reduced models. We compare our asymptotic results with the eigenvalues obtained numerically for the full lubrication models.
Impact of Traditional and Digital Financial Inclusion on Enterprise Innovation: Evidence from China

Financial inclusion refers to a process that ensures the ease of access, availability, and usage of the financial system for all members of an economy. This paper aims to study financial inclusion’s impact on enterprise innovation and compare the different effects of traditional and digital financial inclusion. Existing papers mainly focus on digital financial inclusion’s influence. Based on China’s data, this paper fills the gap by constructing an index system to measure traditional financial inclusion and discussing the impact mechanism of the two kinds of financial inclusion on enterprise innovation (output and efficiency). The results illustrate that traditional financial inclusion inhibits the innovation output of enterprises, while digital financial inclusion has a positive effect. However, both traditional and digital financial inclusion is still in the stage of constraining the innovation efficiency of enterprises. Moreover, the two types of financial inclusion function differently for enterprises of different sizes and ownership. Evidence from China is expected to reveal the features of this relationship and inspire research in more economies.
A DIRECT PARALLEL ALGORITHM FOR THE EFFICIENT SOLUTION OF THE PRESSURE-CORRECTION EQUATION OF INCOMPRESSIBLE FLOW PROBLEMS USING LOOSELY COUPLED COMPUTERS

The numerical simulation of time-accurated complex flows needs large computational resources. For the case of incompressible flows, the solution of the pressure-correction equation is typically the main bottleneck, especially on loosely coupled parallel computers such as PC clusters. An algorithm intended to solve this problem is presented. It is a variant of the Schur complement method that uses direct solvers for each subdomain and for the interface equation. The inverse of the interface matrix is evaluated and stored in parallel. Simulation of turbulent natural convection is used as a benchmark to show its potential and limitations.
Dietary Sodium Butyrate Improves Intestinal Health of Triploid Oncorhynchus mykiss Fed a Low Fish Meal Diet

Simple Summary Soybean meal is currently one of the most widely used ingredients in aquafeed due to its consistent supply, reasonable price, and well-balanced amino acid profile. However, anti-nutritional factors such as antigen proteins and soybean agglutinin in soybean meal can also cause intestinal barrier injury and inflammatory reactions in fish, harming fish growth, immunity, and intestinal health. Intestinal health is especially important for carnivorous fish such as rainbow trout (Oncorhynchus mykiss), which have a relatively small intestinal length index. In this study, it was confirmed that dietary NaB levels of 0.20% improved the growth of juvenile O. mykiss and reduced the severity of anti-nutritional factor-induced enteropathy by enhancing digestive enzymes and improving intestinal morphology. Dietary NaB enhanced the mRNA expression of TJ proteins while decreasing the mRNA expression of pro-inflammatory cytokines, NF-κB, and MLCK-MLC, likely reinforcing the intestinal mucosal barrier and protecting against pathogenic bacterial infections. In addition, the gut microbial composition was more conducive to O. mykiss health with the inclusion of 0.20% NaB in the diet. Furthermore, when challenged with Aeromonas salmonicida, dietary 0.20% NaB increased the survival rate of O. mykiss. This study provides a theoretical basis for the development of feed additives for use in low-fish meal feeds. Abstract This study aimed to determine the effects of dietary sodium butyrate (NaB) on the growth and gut health of triploid Oncorhynchus mykiss juveniles (8.86 ± 0.36 g) fed a low fish meal diet for 8 weeks, including the inflammatory response, histomorphology, and the composition and functional prediction of microbiota. Five isonitrogenous and isoenergetic practical diets (15.00% fish meal and 21.60% soybean meal) were supplemented with 0.00% (G1), 0.10% (G2), 0.20% (G3), 0.30% (G4), and 0.40% NaB (G5), respectively. After the feeding trial, the mortality for G3 challenged with Aeromonas salmonicida for 7 days was lower than that for G1 and G5. The optimal NaB requirement for triploid O. mykiss based on weight gain rate (WGR) and the specific growth rate (SGR) was estimated to be 0.22% and 0.20%, respectively. The activities of intestinal digestive enzymes increased in fish fed a NaB diet compared to G1 (p < 0.05). G1 also showed obvious signs of inflammation, but this inflammation was significantly alleviated with dietary NaB supplementation. In comparison, G3 exhibited a more complete intestinal mucosal morphology. Dietary 0.20% NaB may play an anti-inflammatory role by inhibiting the NF-κB-P65 inflammatory signaling pathway. Additionally, the relative abundance of probiotics was altered by dietary NaB. In conclusion, dietary 0.20% NaB improved the intestinal health of triploid O. mykiss fed a low fish meal diet.
First Detection of Global Ionospheric Disturbances Associated with the Most Powerful Gamma Ray Burst GRB221009A

We present the first report of global ionospheric disturbances due to the most powerful Gamma Ray Burst GRB221009A occurred on 9 October 2022. Very Low Frequency (VLF) and Low Frequency (LF) sub-ionospheric radio signals are used to diagnose the effect of the GRB on the lower ionosphere. Both daytime and nighttime effects are analyzed in VLF and LF bands. The magnitude of VLF signal perturbations varied with the propagation condition (day/night), path length, and frequency of the signal. The recovery times for the VLF/LF signals to get back to their pre-GRB levels varied from 2–60 min. Radio signals reflected from the E-region ionosphere for nighttime VLF signals and daytime LF signals showed greater effects compared to the daytime VLF signals reflected from the lower parts of the D-region.
Generalized sixth-order gravity and inflation

The authors consider sixth-order theories of gravity with Lagrangians containing the term RN Square Operator R, where N>1 is an integer. A conformal transformation gives a picture with two scalar fields in Einstein's theory. They find de Sitter and power law inflationary solutions. However, the theory has an unstable weak-field behaviour, because the linearized field equation is of lower order than the non-linear one.
Low‐Temperature Thermochronologic Response to Magmatic Reheating: Insights From the Takab Metallogenic District of NW Iran, (Arabia‐Eurasia Collision Zone)

The interpretation of low‐temperature thermochronology (LTT) data in magmatic and metallogenic provinces requires a knowledge of the geothermal field through time. There, the challenge is differentiating rapid cooling following transient perturbations of the geotherms (reheating) from exhumational cooling induced by erosion during tectonic uplift or normal faulting. The Takab Range Complex (NW Iran) is a basement‐cored range of the Arabia‐Eurasia collision zone that experienced voluminous Eocene to Miocene magmatism and mineralization. Our new apatite and zircon (U‐Th‐Sm)/He and apatite fission track data, together with field observations, a dedicated numerical thermal model, and a re‐evaluation of available geochronology data document the occurrence of a complex geological and thermal history including: (a) late Cretaceous‐Paleocene exhumation possibly controlled by regional contractional deformation followed by Eocene deposition; (b) Oligocene to possibly early Miocene (29 to 22–20 Ma) exhumation of basement rocks from 13 to 8 km of depth, most likely through normal faulting during a thermal anomaly that led to migmatization and partial melting; (c) early to late Miocene (∼22–20 or earlier to 11–10 Ma) regional subsidence with deposition of an up to ∼2‐ to 3‐km‐thick Oligo‐Miocene sedimentary sequence in association with the emplacement of shallow intrusions, which led to a partial to total reset of our LTT systems sometime between 18 and 13 Ma; and (e) erosional exhumation after 11–10 Ma with the development of a transpressional system and a master, right‐lateral, strike slip fault (Chahartagh Fault). Our data highlights the impact of magmatic reheating on LTT ages in areas affected by intense magmatism.
Virtual Screening of a Library of Naturally Occurring Anthraquinones for Potential Anti-Fouling Agents

Marine biofouling is the undesired accumulation of organic molecules, microorganisms, macroalgae, marine invertebrates, and their by-products on submerged surfaces. It is a serious challenge for marine vessels and the oil, gas, and renewable energy industries, as biofouling can cause economic losses for these industries. Natural products have been an abundant source of therapeutics since the start of civilisation. Their use as novel anti-fouling agents is a promising approach for replacing currently used, harmful anti-fouling agents. Anthraquinones (AQs) have been used for centuries in the food, pharmaceutical, cosmetics, and paint industries. Citreorosein and emodin are typical additives used in the anti-fouling paint industry to help improve the global problem of biofouling. This study is based on our previous study, in which we presented the promising activity of structurally related anthraquinone compounds against biofilm-forming marine bacteria. To help uncover the anti-fouling potential of other AQ-related structures, 2194 compounds from the COCONUT natural products database were analysed. Molecular docking analysis was performed to assess the binding strength of these compounds to the LuxP protein in Vibrio carchariae. The LuxP protein is a vital binding protein responsible for the movements of autoinducers within the quorum sensing system; hence, interrupting the process at an early stage could be an effective strategy. Seventy-six AQ structures were found to be highly docked, and eight of these structures were used in structure-based pharmacophore modelling, resulting in six unique pharmacophore features.
The ALICE Silicon Pixel Detector: readiness for the first proton beam

The Silicon Pixel Detector (SPD) is the innermost element of the ALICE Inner Tracking System (ITS). The SPD consists of two barrel layers of hybrid silicon pixels surrounding the beam pipe with a total of ≈ 107 pixel cells. The SPD features a very low material budget, a 99.9% efficient bidimensional digital response, a 12 μm spatial precision in the bending plane (r) and a prompt signal as input to the L0 trigger. The SPD commissioning in the ALICE experimental area is well advanced and it includes calibration runs with internal pulse and cosmic ray runs. In this contribution the commissioning of the SPD is reviewed and the first results from runs with cosmic rays and circulating proton beams are presented.
All-Year Dropout Prediction Modeling and Analysis for University Students

The core of dropout prediction lies in the selection of predictive models and feature tables. Machine learning models have been shown to predict student dropouts accurately. Because students may drop out of school in any semester, the student history data recorded in the academic management system would have a different length. The different length of student history data poses a challenge for generating feature tables. Most current studies predict student dropouts in the first academic year and therefore avoid discussing this issue. The central assumption of these studies is that more than 50% of dropouts will leave school in the first academic year. However, in our study, we found the distribution of dropouts is evenly distributed in all academic years based on the dataset from a Korean university. This result suggests that Korean students’ data characteristics included in our dataset may differ from those of other developed countries. More specifically, the result that dropouts are evenly distributed throughout the academic years indicates the importance of a dropout prediction for the students in any academic year. Based on this, we explore the universal feature tables applicable to dropout prediction for university students in any academic year. We design several feature tables and compare the performance of six machine learning models on these feature tables. We find that the mean value-based feature table exhibits better generalization, and the model based on the gradient boosting technique performs better than other models. This result reveals the importance of students’ historical information in predicting dropout.
Wave-CISK in a Baroclinic Basic State

Abstract Prefrontal squall lines are mesoscale convective systems that often cannot be linked to any preexisting organizing mechanism. This suggests the possibility that they are manifestations of a mesoscale instability involving the interaction between convective and larger scales. To investigate this hypothesis, a wave-CISK model is developed for two-dimensional disturbances in a baroclinic basic state with constant vertical wind shear. The governing equations are the linearized Boussinesq equations for an inviscid and hydrostatic fluid on an f-plane. The model domain is infinite in the horizontal and consists of two layers in the vertical representing the troposphere and the stratosphere. The model stratosphere has a larger static stability and no wind shear. The convective heating is confined to the troposphere. Normal mode solutions are assumed, and the convective heating is parameterized in the standard simple fashion its vertical structure is specified, and it is set proportional to the low-level .
A Versatile Toolset for Genetic Manipulation of the Wine Yeast Hanseniaspora uvarum

Hanseniaspora uvarum is an ascomycetous yeast that frequently dominates the population in the first two days of wine fermentations. It contributes to the production of many beneficial as well as detrimental aroma compounds. While the genome sequence of the diploid type strain DSM 2768 has been largely elucidated, transformation by electroporation was only recently achieved. We here provide an elaborate toolset for the genetic manipulation of this yeast. A chromosomal replication origin was isolated and used for the construction of episomal, self-replicating cloning vectors. Moreover, homozygous auxotrophic deletion markers (Huura3, Huhis3, Huleu2, Huade2) have been obtained in the diploid genome as future recipients and a proof of principle for the application of PCR-based one-step gene deletion strategies. Besides a hygromycin resistance cassette, a kanamycin resistance gene was established as a dominant marker for selection on G418. Recyclable deletion cassettes flanked by loxP-sites and the corresponding Cre-recombinase expression vectors were tailored. Moreover, we report on a chemical transformation procedure with the use of freeze-competent cells. Together, these techniques and constructs pave the way for efficient and targeted manipulations of H. uvarum.
A Novel Pet Trajectory Prediction Method for Intelligent Plant Cultivation Robot

Intelligent plant cultivation robots will have certain working obstacles due to various moving objects, such as pets. This letter studies how to predict the trajectory of pets to avoid collisions. In previous intelligent plant cultivation robot systems, target-tracking technology was used to track pets and avoid collisions. However, collisions often occur even after tracking the trajectory of the pet because the trajectory of the pet's movement is difficult to determine. Therefore, the Informer algorithm is used to predict the trajectory of pets in this letter. It is presented that collisions can be avoided based on the predicted trajectory. Experimental results on the data set show that this algorithm has better accuracy than most common algorithms, so trajectory prediction based on this algorithm can make the robot avoid obstacles better. Finally, by verifying two data sets, the public data set and the self-made data set, it is determined that the performance of the proposed method is optimized by 3%–50% compared with other methods.
Sparse representation of smooth linear operators

Abstract : A wide variety of problems in differential and integral equations require application and inversion of linear operators. For large-scale physical problems, the size of the problem n is such that the work expended by general algorithms-O(n squared) for application of a transformation and O(n cubed) for application of its inverse-is often prohibitive. Several methods have been devised in recent years to reduce these complexities by exploiting the structure of particular problems. This thesis puts earlier methods into a unified framework by developing new wavelet-like bases for spaces, which lead to efficient algorithms for operator application and inversion. It is based on the observation that in many cases of interest, while the matrices involved are dense, their elements vary smoothly as a function of their indices, except along a collection of bands of fixed width. Algorithms are presented for transforming such locally smooth matrices into matrices which are sparse (to a finite but arbitrarily high accuracy). The resulting sparse representations support fast algorithms for matrix application and inversion, requiring variously O(n), O(n log n), and O(n log squared n) operations. Programs have been developed applying these techniques to the solution of second-kind integral equations with non- oscillatory kernels. Numerical results are presented to demonstrate the effectiveness of the approach. (kr)
The Effect of GeO2 and In2O3 Doping on the Dielectric Properties of CaCu3Ti4O12 Ceramics Prepared via Vibro-Milling Method

In this work, effects of GeO2 and In2O3 doping on the dielectric properties of CCTO were investigated. Doping levels range from 0.5 to 2.0 mol%. The vibro-milling method was employed for processing. The dopant addition produced a slightly smaller grain size. A reduction in dielectric constant was observed, but it is still high. The 2.0 mol% GeO2 and In2O3 doped samples exhibited high dielectric constant of about 25,000 and 23,000 and low dielectric loss with 0.06 and 0.05 respectively at room temperature and at 10 kHz. The dielectric measurements showed that the modified samples exhibited a strong dielectric independency of temperature and frequency. In addition, the loss tangent reduced after doping. From this results, it can be incurred that GeO2 and In2O3 doping, processed via vibro-mill are the suitable methods to achieve the stability of high ϵr and low loss ceramics.