Miracle-dz/UniFAR-FTUs huggingface dataset:
Measurement of Exam Anxiety Levels Among Medical Students and Their Association With the Influencing Factors

Introduction Studying medical science is a demanding task, often leading to exam anxiety among medical students. This study aims to measure anxiety levels among medical students and their relationship with gender, age, grades, study time, year of study, and learning methods. Methods It is a cross-sectional study involving third- to sixth-year medical students, who filled in the questionnaire related to the personal data, studying methods, and the Westside Test Anxiety Scale, to estimate the exam anxiety levels before the final examinations of the academic year 2020-2021. Completed questionnaires were reviewed, entered in Microsoft Excel, and analyzed using SPSS. Results We found a significant association between gender and high-test anxiety (p < 0.001), with a higher prevalence among females (47.9%) compared to males (22.5%). Although non-significant, its prevalence was higher among the 20 years old (34%) and those with a GPA 4.00-4.49 (37.9%). Anxiety decreased as the students progressed to higher years of studies (37.9% in the third year to only 9.1% in sixth year, p=0.073), with the lower incidence among those who studied five days or more per week (26.7%) and no significant difference was observed whether students studying in a group or individually. Though insignificant (p=0.754), learning through textbooks was found to be less stressful (29% vs 33%). Conclusion Our findings suggest that mediocre and female students are more vulnerable to exam high-test anxiety. Progression to senior years and use of textbooks were associated with lower anxiety levels. A cohort longitudinal study to establish an association between specific factors and anxiety levels is recommended.
Effect of Dapagliflozin on Clinical Outcome after Drug-Eluting Stent Implantation in Elderly T2DM Patients: A Real-World Study

Objective To investigate the effect of dapagliflozin therapy on the clinical outcome of drug-eluting stent (DES) implantation in elderly patients with type 2 diabetes mellitus (T2DM). Methods We retrospectively studied the real-world data of patients with coronary heart disease who received DES implantation in our hospital from May 2019 to May 2021. Baseline general data and laboratory results of patients were collected. All patients were followed up for two years after PCI, and the follow-up endpoints included in-stent restenosis, major adverse cardiovascular events (MACE), revascularization, rehospitalization, and all-cause mortality. Results Compared with those before treatment, body mass index, systolic blood pressure, diastolic blood pressure, TG, TC, LDL-C, FBG, and HbA1c were decreased in both groups after treatment, while HDL-C was increased after treatment (P < 0.05). There were significant differences in BMI, systolic blood pressure, diastolic blood pressure, FBG, and HbA1c between the two groups before and after treatment. At the end of follow-up, the incidence of in-stent restenosis and MACE in the dapagliflozin group was lower than that in the nondapagliflozin group. K-M curve analysis showed a significant difference in in-stent restenosis and MACE after DES implantation between the dapagliflozin group and the nondapagliflozin group (logrankχ2 = 5.093, 4.524; P = 0.024, 0.033). Conclusion In accurate clinical data, dapagliflozin could significantly improve the postoperative BMI, blood pressure, and blood glucose outcome of patients with T2DM complicated with coronary heart disease and positively impact in-stent restenosis and MACE.
Big and Small Footballing Nations and the Harmful Effects of Systemic Corruption on International Sports Performance: An Investigation of Potentially Unique Susceptibility Among Small States

This paper explores the claim that small states are particularly sensitive to thedetrimental effects of systemic corruption on international sports performance, whichwas previously made on the basis of medal counts at the Games of the Small States ofEurope and the summer and winter editions of the Olympic Games. The present studyaimed to further investigate the validity of such a claim and its generalisability in othersporting contexts. Due to its worldwide popularity and expansive global infrastructure,international football was selected as an ideal main discipline for probing such effects.The points system used by its highest international governing federation to rank countriesacross mens and womens categories was used as the main dependent variable of interest.A multiple regression analysis was then carried out to estimate the effects of smallstate status on performance, across all levels of corruption, while controlling for overallpopulation size. The findings strongly support the central thesis that small states havea unique susceptibility to the effects of systemic corruption on sports performance ininternational football. Serious concerns are consequently raised about the capacity for realimprovements in international sports performance by Malta or other small states, shouldpolicymakers and sports administrators fail to more meaningfully promote transparency,trustworthiness, accountability, and indeed any fundamental principles antithetical tosystemic corruption both within and beyond the microcosm of sports communities.
The Influence of Fitrah Based Learning on Strengthening the Character of Students

Education that does not depart from human nature will fail to produce a generation that has the best specific role in civilization. To overcome the problem of the personality of the nation's children, strengthening character education is the entry point for making overall improvements to education. The purpose of this study was to determine the effect of nature-based learning on strengthening student character. This study uses a quantitative approach which will examine the effect of "Fitrah Based Learning" in learning and its effect on strengthening student character. This research was conducted in January-February 2023 at the Faculty of Tarbiyah and Teacher Training UIN Sultan Syarif Kasim Riau. The sampling technique used random sampling technique with a total sample of 333 respondents. The data used is primary data by distributing questionnaires. The data analysis used is simple linear regression with SPSS. The results of the study show that the majority of fitrah based learning variables are very good as much as 74% and the majority student character variables are as much as 77%. The results of the Linear Regression test showed that the t observation was 9.343 and the p-value (sig.) was 0.000. Because the p-value = 0.00 is smaller than the value α = 0.05, then H0 is rejected and Ha is accepted, so it can be concluded that there is an influence of Fitrah Based Learning on strengthening student character
Study of radial heat transport in W7-X using the transfer entropy

In this work, we analyze data obtained using the electron cyclotron emission radiometer at the Wendelstein 7-X stellarator using a relatively new technique: the transfer entropy. Thus, we detect the propagation of information and find that it occurs in a stepwise fashion: we observe both ‘trapping zones’ and radial ‘jumps’, when the information is apparently skipping over intermediate positions. Using scans of the rotational transform, we observe that the ‘trapping zones’ appear to be associated with rational surfaces. Power scan experiments show that these ‘jumps’ increase in importance when power is increased, thus enhancing the effective diffusivity. The observations are interpreted in terms of a resistive magneto-hydrodynamic model, which displays behavior similar to the experimental results. The ‘trapping zones’ are explained in terms of zonal flows associated with rational surfaces, while the ‘jumps’ are ascribed to mode coupling effects, i.e. the transmission of turbulent energy via the magnetic field.
Effect of LH Hormone on Premenstrual Syndrome in Female Adolescents at Darul Arqam Islamic Boarding School Makassar

This study aims to determine the effect of LH on premenstrual syndrome in young women at Darul Arqam Makassar. The research method used was the t test to see the effect of LH concentrations on young women who experienced and did not experience premenstrual syndrome. The population of this study were all young women at the Darul Arqam Makassar Islamic Boarding School. The sample used was 50 young women consisting of 25 young women with PMS and 25 young women who were not. The results showed that there was an influence of the LH hormone with the average value of respondents whose average LH value was 7.36, which was higher than that of PMS, which was 7.35. After the data is processed with the t test obtained p = 0.000 < α = 0.05. This means that there is a significant effect of LH hormone concentration between no PMS, mild PMS, and severe PMS. The conclusion is that there is a significant effect of the concentration of the hormone LH f2 α among young women who do not have PMS and PMS and between young women who experience mild PMS and severe PMS at Darul Arqam Islamic Boarding School Makassar.
Arranging simple neural networks to solve complex classification problems

In "decomposition/reconstruction" strategy, we can solve a complex problem by 1) decomposing the problem into simpler sub-problems, 2) solving sub-problems with simpler systems (sub-systems) and 3) combining the results of sub-systems to solve the original problem. In a classification task we may have "label complexity" which is due to high number of possible classes, "function complexity" which means the existence of complex input-output relationship, and "input complexity" which is due to requirement of a huge feature set to represent patterns. Error Correcting Output Code (ECOC) is a technique to reduce the label complexity in which a multi-class problem will be decomposed into a set of binary sub-problems, based oil the sequence of "0"s and "1"s of the columns of a decomposition (code) matrix. Then a given pattern can be assigned to the class having minimum distance to the results of sub-problems. The lack of knowledge about the relationship between distance measurement and class score (like posterior probabilities) has caused some essential shortcomings to answering questions about "source of effectiveness", "error analysis", " code selecting ", and " alternative reconstruction methods" in previous works. Proposing a theoretical framework in this thesis to specify this relationship, our main contributions in this subject are to: 1) explain the theoretical reasons for code selection conditions 2) suggest new conditions for code generation (equidistance code)which minimise reconstruction error and address a search technique for code selection 3) provide an analysis to show the effect of different kinds of error on final performance 4) suggest a novel combining method to reduce the effect of code word selection in non-optimum codes 5) suggest novel reconstruction frameworks to combine the component outputs. Some experiments on artificial and real benchmarks demonstrate significant improvement achieved in multi-class problems when simple feed forward neural networks are arranged based on suggested framework To solve the problem of function complexity we considered AdaBoost, as a technique which can be fused with ECOC to overcome its shortcoming for binary problems. And to handle the problems of huge feature sets, we have suggested a multi-net structure with local back propagation. To demonstrate these improvements on realistic problems a face recognition application is considered. Key words: decomposition/ reconstruction, reconstruction error, error correcting output codes, bias-variance decomposition.
Age of Information-Aware Scheduling for Dynamic Wireless Body Area Networks

Wireless body area network (WBAN) can be applied to a variety of scenarios, such as physical training, patient care, and health monitoring for the aged. To prolong the lifetime of WBANs and respond to an emergency, energy efficiency and age of information (AOI) become two most important performance indicators. The dynamic characteristic of WBANs makes the link quality of wireless communication vary intensely, which brings challenges to the reliability of data transmission. Conventional scheduling policies do not take into account the AOI and that the life time of the data packets from some sensor nodes may exceed the time limit, which are energy-inefficient and may cause an accident when unforeseen emergency happens. As a remedy, first, in order to fulfill the channel prediction, we adopt a deep learning method based on neural basis expansion analysis for interpretable time series (NBEATS). The transmit power according to channel prediction results is adjusted, to improve the energy efficiency of data transmission. Then, we propose an AOI-aware scheduling (AOI-AS) strategy which takes into account energy efficiency and data freshness. Simulation experiments show that our proposed scheduling strategy can reduce the AOI by 7% and the average energy consumption by 6% compared with the stochastic scheduling (SS) mechanism.
Bilinear bi-parameter singular integrals: Representation theorem and boundedness properties

Our setup is a natural class of operators $T$, which we think of as general (not necessarily of tensor product or convolution type) bilinear bi-parameter singular integrals on the product space $\mathbb{R}^{n+m} = \mathbb{R}^n \times \mathbb{R}^m$. Starting from $T1$ type assumptions, we show a representation theorem for these operators using dyadic model operators. For singular integrals that are free of full paraproducts we use the representation to show weighted estimates $L^p(w_1) \times L^q(w_2) \to L^r(v_3)$, where $1 < p, q < \infty$, $1/2 < r < \infty$, $1/p+1/q = 1/r$, $w_1 \in A_p(\mathbb{R}^n \times \mathbb{R}^m)$, $w_2 \in A_q(\mathbb{R}^n \times \mathbb{R}^m)$ and $v_3 := w_1^{r/p} w_2^{r/q}$. We also consider mixed-norm estimates. Somewhat weaker unweighted estimates are obtained for all singular integrals. As an application we give a new proof of a result of Muscalu-Pipher-Tao-Thiele: a bi-parameter version of the bilinear multiplier theorem of Coifman and Meyer. In fact, we prove a weighted version of the result, and recover, apart from some $L^{\infty}$ endpoints, the full range of mixed-norm estimates proved by Benea-Muscalu.
Comparisons of Transport and Dispersion Model Predictions of the Joint Urban 2003 Field Experiment

Abstract For a hazardous material release in a city or densely populated area, effective mitigation requires an understanding of the transport and dispersion of these hazards in the complex urban environment. Improved characterization and understanding of urban transport and dispersion will allow for more robust modeling. The Defense Threat Reduction Agency has developed a Hazard Prediction Assessment Capability (HPAC) that includes features to address hazardous releases within an urban environment. During the summer of 2003, a series of tracer gas releases were carried out in Oklahoma City, Oklahoma, and extensive meteorological and tracer concentration measurements were collected in a field experiment known as Joint Urban 2003 (JU03). This analysis uses the observations of JU03 to evaluate “Urban HPAC. ” Twenty sets of simulations, or “predictions,” using four Urban HPAC modes and five meteorological input options, were created and compared using a variety of metrics. Strong consistency was found between.
Assessment of Potential Drug-drug Interactions (pDDIs) and Their Risk Factors Among Hospitalized Cardiac Patients in a Tertiary-care Center of Central India: A Retrospective Record-based Study

Background: Patients with cardiovascular disorders (CVD) possess multiple comorbidities and are prone to be prescribed multiple drugs, thus predisposing them to various drug-drug interactions (DDIs). Objective: This study was carried out to assess the potential-DDIs (pDDIs) among the drugs prescribed to hospitalized patients with CVD and associated factors. Method: It was a retrospective study conducted with the help of the medical records department. Medical records of all the patients admitted to the cardiology department of our tertiary care center from January 1st, 2019, to December 31st, 2019, were included for analysis using Lexicomp, an up-to-date drug interaction screening tool. The pDDIs were divided into classes A, B, C, D, and X, and those belonging to classes D or X were considered clinically significant. Multiple logistic regression was used to analyze the association between the factors associated with and the occurrence of clinically significant pDDIs, with a P-value < . 05 considered statistically significant. Results: Almost all the records reflected (335/338) at least 1 pDDI. A total of 4966 pDDIs were detected, of which the majority belonged to category C (75.3%), and 5.1% of pDDIs were clinically significant. The patients who were prescribed more than 10 drugs per day (OR = 2.46; 95% CI: 1.27-4.82; P = .008), prescribed parenteral formulation (OR = 1.84; 95% CI: 1.57-2.21; P < .0001), or had a diagnosis of acute coronary syndrome (OR = 2.33; 95% CI:1.1-5.12; P = .03) were associated with clinically significant pDDIs. Other factors, that is, female sex, use of fixed-dose combinations, and the triad of diabetes mellitus, hypertension, and dyslipidemia, were positively associated with clinically significant pDDIs. Conclusion: Even though every patient had at least 1 pDDI, the prevalence of clinically significant pDDIs was relatively less. Use of >10 drugs/day, parenteral formulation, patients with acute coronary syndrome were significantly associated with clinically significant pDDIs.
Etude numérique de l'époque de réionisation avec le code de simulation EMMA

L’epoque de reionisation (EoR) est une phase de grands changements qu’a subit l’Univers dans son premier milliard d’annees. Suite a l’apparition des premieres etoiles et a l’emission de photons energetique par ces dernieres, l’hydrogene a ete reionise. Cette transition a eu un impact sur la formation des galaxies. J’ai activement participe au developpement d’EMMA, un code de simulation numerique ayant pour objectif d’etudier les processus a l’œuvre durant l’EoR. J’ai developpe et implemente un modele de formation et d’evolution stellaire. Ces travaux ont contribue a la realisation d’une simulation dediee a l’etude de l’EoR parmi les plus grosses realisees a l’heure actuelle. J’ai contribue au developpement d’outils dedies a l’exploration de simulations de ce type. J’ai etudie la facon dont le rayonnement s’echappe des galaxies en fonction des parametres du modele stellaire, et montre que les supernovae peuvent augmenter la fraction de photons liberes. J’ai egalement etudie la propagation des fronts d’ionisation et montre qu’il etait possible de reduire la vitesse de la lumiere par trois (et ainsi diminuer le temps de calcul du transfert du rayonnement par 3), tout en conservant des resultats corrects ?
From Patterns to Function in Living Systems: Dryland Ecosystems as a Case Study

Spatial patterns are ubiquitous in animate matter. Besides their intricate structure and beauty they generally play functional roles. The capacity of living systems to remain functional in changing environments is a question of utmost importance, but its intimate relationship to pattern formation is largely unexplored. Here, we address this relationship using dryland vegetation as a case study. Following a brief introduction to pattern-formation theory, we describe a mathematical model that captures several mechanisms of vegetation pattern formation and discuss ecological contexts that showcase different mechanisms. Using this model, we unravel the different vegetation patterns that keep dryland ecosystems viable along the rainfall gradient, identify multistability ranges where fronts separating domains of alternative stable states exist, and highlight the roles of front dynamics in mitigating or reversing desertification. The utility of satellite images in testing model predictions is discussed. An outlo.
A Theoretical Model of Soil Freezing Characteristic Curve Considering the Freezing of Adsorbed Water and Capillary Water

The soil freezing characteristic curve (SFCC) represents the constitutive relationship between sub‐zero temperature and unfrozen water content in soil. It governs the hydrologic and mechanical behaviors associated with freezing soil. Numerous studies have investigated the mechanisms of soil water freezing and attempted to predict SFCC using soil water characteristic curve (SWCC) and Clapeyron equation. However, limited attention has been given to the physical disparities between adsorbed and capillary water during freezing, including variations in pressures and water‐ice interfaces. In this study, we present a novel theoretical model for predicting SFCC. The model determines the freezing point by calculating the chemical potential of soil water and ice with their respective pressures, thus capturing the distinctions in freezing behaviors between adsorbed and capillary water. All model parameters possess clear physical interpretations, and the model solely relies on the SWCC as input. The validity of the proposed model was confirmed through experimental measurements involving the water phase diagram, SWCCs, and the corresponding SFCCs of sandy, silty, and clayey soils. The model exhibits strong capabilities in predicting SFCC regardless of the soil type and outperforms the conventional method in predicting the SFCC of soil with high adsorbed water content. Model analyses were performed to investigate the effects of individual pore size, soil type, and initial water content on the freezing process, revealing the distinct contributions of adsorption and capillarity in soil water freezing. This study elucidates the mechanisms underlying soil water freezing, offering a theoretical framework for the analysis and prediction of frozen soil behaviors.
Extremely Low-Frequency Electromagnetic Stimulation (ELF-EMS) Improves Neurological Outcome and Reduces Microglial Reactivity in a Rodent Model of Global Transient Stroke

Extremely low-frequency electromagnetic stimulation (ELF-EMS) was demonstrated to be significantly beneficial in rodent models of permanent stroke. The mechanism involved enhanced cerebrovascular perfusion and endothelial cell nitric oxide production. However, the possible effect on the neuroinflammatory response and its efficacy in reperfusion stroke models remains unclear. To evaluate ELF-EMS effectiveness and possible immunomodulatory response, we studied neurological outcome, behavior, neuronal survival, and glial reactivity in a rodent model of global transient stroke treated with 13.5 mT/60 Hz. Next, we studied microglial cells migration and, in organotypic hippocampal brain slices, we assessed neuronal survival and microglia reactivity. ELF-EMS improved the neurological score and behavior in the ischemia-reperfusion model. It also improved neuronal survival and decreased glia reactivity in the hippocampus, with microglia showing the first signs of treatment effect. In vitro ELF-EMS decreased (Lipopolysaccharide) LPS and ATP-induced microglia migration in both scratch and transwell assay. Additionally, in hippocampal brain slices, reduced microglial reactivity, improved neuronal survival, and modulation of inflammation-related markers was observed. Our study is the first to show that an EMF treatment has a direct impact on microglial migration. Furthermore, ELF-EMS has beneficial effects in an ischemia/reperfusion model, which indicates that this treatment has clinical potential as a new treatment against ischemic stroke.