Miracle-dz/UniFAR-FTUs huggingface dataset:
Does explanatory language convey the auditor’s perceived audit risk? A study using a novel big data analysis metric

Purpose The purpose of this study is to examine the relationship between explanatory language, audit fees and audit hours to demonstrate that auditors use explanatory language in audit reports to explain perceived audit risk. Design/methodology/approach The authors construct the sentiment value, a novel audit risk proxy derived from audit reports, using big data analysis. The relationship between sentiment value and explanatory language is then investigated. The authors present the validity of their new metric by examining the relationship between sentiment value and accounting quality, taking audit fees and hours into account. Findings The authors first find that reporting explanatory language is positively related to audit fees. More importantly, the authors provide an evidence that explanatory language in audit reports is indicative of increased audit risk as it is negatively correlated with sentiment value. As a positive (negative) sentimental value means that the audit risk is low (high), the results indicate that auditors describe explanatory language in a negative manner to convey the inherent audit risk and receive higher audit fees from the risky clients. Furthermore, the relationship is strengthened when the explanatory language is more severe, such as reporting the multiple numbers of explanatory language or going-concern opinion. Finally, the sentiment value is correlated with accounting quality, as measured by the absolute value of discretionary accruals. Originality/value Contrary to previous research, the authors’ findings suggest that auditors disclose audit risks of client firms by including explanatory language in audit reports. In addition, the authors demonstrate that their new metric effectively identifies the audit risk outlined qualitatively in audit report. To the best of the authors’ knowledge, this is the first study that establishes a connection between sentiment analysis and audit-related textual data.
Current Landscape of Immunotherapy for Advanced Sarcoma

Simple Summary The systemic treatment of advanced sarcoma remains challenging. Conventional chemotherapy and anti-angiogenic agents, even in the most responsive histologic subtypes, result in short responses and poor clinical outcomes. In a context where new therapeutic approaches are required, several strategies of immunotherapy have emerged as promising options, such as immune checkpoint inhibitors, vaccines, and adoptive cell therapy. In this review, we aim to summarize the current state and challenges of immunotherapy in patients with advanced bone and soft-tissue sarcomas. Abstract There is substantial heterogeneity between different subtypes of sarcoma regarding their biological behavior and microenvironment, which impacts their responsiveness to immunotherapy. Alveolar soft-part sarcoma, synovial sarcoma and undifferentiated pleomorphic sarcoma show higher immunogenicity and better responses to checkpoint inhibitors. Combination strategies adding immunotherapy to chemotherapy and/or tyrosine–kinase inhibitors globally seem superior to single-agent schemes. Therapeutic vaccines and different forms of adoptive cell therapy, mainly engineered TCRs, CAR-T cells and TIL therapy, are emerging as new forms of immunotherapy for advanced solid tumors. Tumor lymphocytic infiltration and other prognostic and predictive biomarkers are under research.
Improving Metabolic Syndrome in Ghanaian Adults with Type 2 Diabetes through a Home-Based Physical Activity Program: A Feasibility Randomised Controlled Trial

There is a high prevalence of metabolic syndrome (MetS) among people with type 2 diabetes mellitus (T2DM). Physical activity has the potential to improve health outcomes for individuals with type 2 diabetes. Our study aim was to determine the effect of a 12-week culturally appropriate home-based physical activity program on metabolic syndrome markers and quality of life in Ghanaian adults with T2DM. A secondary objective was to examine the feasibility of implementing the PA program. A feasibility randomised controlled trial (RCT) was conducted. A purposive sample of 87 adults with T2DM at the Korle-Bu Teaching Hospital, Ghana, were randomized into either the control group (CG) (n = 43) or the intervention group (IG) (n = 44). Participants in the IG received the physical activity program in addition to their usual diabetes care; those in the CG received their usual diabetes care. Measurements for feasibility, MetS markers, and quality of life (SF-12) were performed at baseline and 12-week follow-up. Following the 12-week program, participants in the IG showed a significant improvement in fasting blood glucose (2.4% vs. 0.4%, p < 0.05), waist circumference (5.4% vs. 0.4%, p < 0.05), and systolic blood pressure (9.8% vs. 1.5%, p < 0.05). There were no statistical differences between the IG and CG regarding high-density lipoprotein, triglycerides, and diastolic blood pressure at the 12-week follow-up. Classification of MetS were reduced in the IG compared to the CG (51.2% vs. 83.3%, p < 0.05). The MetS severity score improved in the IG compared to the CG (8.8% vs. 0.5%, p < 0.05). The IG improved in two of the eight SF-12 dimensions (physical function and vitality, p < 0.05) compared to the CG. Thirty-two (72.7%) participants completed all 36 exercise sessions. Another 11 (25%) participants completed 80% of the exercise sessions. No adverse events were reported. In conclusion, a 12-week home-based physical activity program is feasible and safe. The intervention has the potential to improve MetS and quality of life in Ghanaian adults with T2DM. The preliminary findings of this study need to be confirmed in a large-scale multi-centre RCT.
Neonatal jaundice: magnitude of the problem in Cairo University's neonatal intensive Care unit as a referral center

Background Neonatal jaundice is one of the most common physiologic problems requiring medical attention in newborns. It is benign in most cases; however, high levels of bilirubin are neurotoxic and can lead to serious brain damage. Objectives This study aimed at assessment of magnitude of neonatal jaundice in cases of neonatal hyperbilirubinemia admitted into neonatal intensive care unit (NICU), Cairo University Pediatric Hospital and to detect possible etiologies, management and outcome. Methods The present work is a retrospective study, included 789 neonates suffered from hyperbilirubinemia over a two-year period. Results Intensive phototherapy and exchange transfusion were used together in 6 cases. Two hundreds and twenty-two cases (28.1%) had exchange transfusion once, 44 cases had it twice, 6 cases had it 3 times and one case had it 4 times. Number of exchange transfusion significantly affects mortality among cases (P= 0.02). Conclusion Neonatal hyperbilirubinemia is an existing problem in our NICU. Intensive phototherapy is an excellent substitute for exchange transfusion. Respiratory distress and sepsis are significantly higher among dead cases. Screening for risk factors is needed to avoid critical hyperbilirubenemia.
The Scientific Questioning and Experimental Skills of Elementary School Students: The Intervention of Research-Based Learning

Research-based learning is a learning strategy that encourages the use of scientific inquiry, thereby allowing students to develop an understanding of the scientific process. The aim of this study was to design a research-based, scientific learning activity on the topic of the mass and volume of matter, to be implemented with elementary school students. The study sample consisted of 16 fourth-grade students selected by purposive sampling. This mixed methods study, performed as an embedded design, examined the pre-experimental results of this research-based learning activity on students’ scientific questioning and experimental skills. The science process skills evaluation form was used as a quantitative instrument. The quantitative data were analyzed by simple statistics including mean and standard deviation. Meanwhile, the gathering of qualitative data was accomplished through the taking of field notes. Deductive analysis was employed to highlight the patterns that emerged regarding the students’ science process skills. The findings revealed that this research-based learning design encouraged students’ scientific questioning and experimental skills, with the mean level being at the developing level. This was achieved by giving students the opportunity to engage in challenging, age-appropriate activities with explicit scientific methodology guidance provided by their teachers. Furthermore, it was found that the students were very much satisfied with this research-based learning activity. This suggests that incorporating research-based practices would serve to fulfill the educational aims of the science classroom. The science inquiry-based approach represents an area worthy of increased focus in order to encourage elementary school students to practice science process skills.
Large Eddy Simulation of a Flow Past a Free Surface Piercing Circular Cylinder

Interactions between surface waves and underlying viscous wake are investigated for a turbulent flow past a free surface piercing circular cylinder at Reynolds number Re =2.7×10 4 using large eddy simulation (LES). The computations have been performed for three Froude numbers Fr=0.2, 0.5 and 0.8 in order to examine the influence of the Froude number A second-order finite volume method coupled with a fractional step method is used for solving the grid-filtered incompressible Navier-Stokes equations
Stimulant Use Associated With Psychosocial Factors, HIV Risk, and Concurrent Hazardous Alcohol Use Among US Adults: Exploratory Cross-Sectional Questionnaire Study

Background Stimulant use is a major public health problem that contributes to morbidity and mortality among men who have sex with men (MSM) in the United States. To reduce the harms associated with stimulant use, there is a need to identify the factors associated with stimulant use to inform interventions. Additionally, there is a need to use large crowdsourcing platforms like Amazon Mechanical Turk (MTurk) to engage more individuals who use substances across the United States. Objective We identified the correlates of stimulant use among people who use alcohol or stimulants in the United States recruited using MTurk. Methods Participants who were aged ≥18 years in the United States and reported alcohol or stimulant (ie, cocaine, crack cocaine, and methamphetamine) use were deemed eligible and recruited via the web platform MTurk. Participants completed a baseline survey, which assessed sociodemographics, psychosocial (ie, depression, affect, self-esteem, and stress) factors, substance use, and sexual behaviors. Data were collected and analyzed with STATA (version 17; StataCorp). Stratifying by MSM status, bivariate and multivariable logistic regression models were built in STATA to examine the correlates of stimulant use. Multivariable models controlled for age, race, health insurance, and relationship status. Results Of 272 participants, 201 (73.9%) identified as male, 134 (49.2%) were MSM, 52 (19.1%) were from racial and ethnic minoritized communities, and 158 (58%) were in a relationship. The mean age was 36.10 (SD 10.3) years. A total of 40 (14.7%) participants reported stimulant use in the past 6 months. Factors significantly associated with stimulant use were being MSM (adjusted odds ratio [aOR] 4.61, 95% CI 1.97-10.81), a higher Alcohol Use Disorders Identification Test-Concise score (aOR 1.24, 95% CI 1.08-1.42), more intense cravings for alcohol in the past 24 hours (aOR 1.03, 95% CI 1.01-1.04), a higher depression score (aOR 1.06, 95% CI 1.01-1.12), a greater number of male partners in the last 6 months (aOR 1.32, 95% CI 1.08-1.61), a greater number of female partners in the last 6 months (aOR 1.42, 95% CI 1.04-1.92), and being diagnosed with a sexually transmitted infection (eg, syphilis, gonorrhea, chlamydia, herpes simplex virus, human papillomavirus, and other) in the last 6 months (aOR 14.61, 95% CI 3.45-61.87). Additionally, there was a significant additive interaction between MSM status and negative affect, such that the impact of negative affect on stimulant use was significantly greater among MSM compared with non-MSM (relative excess risk due to interaction 0.085, 95% CI 0.037-0.13). Conclusions Interventions that address stimulant use should use evidence-based approaches that reduce negative affect, depression, and cravings for alcohol. Additionally, interventions should be customized for MSM populations.
Predictability of seasonal precipitation in the Nordic region

Predictability of seasonal precipitation in the Nordic countries (Denmark, Finland, Iceland, Norwayand Sweden) is investigated using a nine-member ensemble of atmospheric general circulation modelsimulations with prescribed sea-surface temperature from October 1950 until March 1999. The simulationsand corresponding observations from 65 stations in the Nordic countries are used to identifylarge-scale patterns of seasonal precipitation, the predictability of which is investigated. Subsequently, the identified large-scale patterns are used in a statistical downscaling of the model simulated precipitation.The downscaling, which is of the model output statistics type, yields seasonal predictions for theindividual stations. The model simulations of precipitation are compared to predictions of precipitationdirectly from observed sea-surface temperature using a statistical prediction method and no dynamicmodel. The two different methods give consistent results. It is demonstrated that seasonal precipitationin the Nordic region contains a weak predictable signal in several seasons. The most skilful predictionscan be made in spring, especially in the April’June season when precipitation appears to be influencedboth by tropical and North Atlantic sea surface temperature. In particular, the North Atlantic Oscillationin winter appears to influence the North Atlantic sea-surface temperature in spring, which in turn hasan effect on precipitation in Scandinavia.
Popularity-Aware Caching for Vehicle Clusters With Federated Deep Reinforcement Learning

This letter investigates the popularity-aware content caching problem in resource-constrained Cellular-Vehicle-to-Everything (C-V2X) scenarios. A federated Deep Q Network (DQN)-based content caching scheme for vehicle cluster is presented to maximize the fee of caching vehicles. We first cluster vehicles based on their mobility and preferences, and combine historical request frequency with preferences to derive the popularity of the content. Moreover, multiple cluster heads within the coverage area of the Central Server (CS) use DQN to train local caching models, and the CS aggregates local model parameters to obtain a global popular content caching model. Simulation results verify that the proposed scheme outperforms other benchmarks in terms of the cache hit rate and content delivery rate.
Γ-limit for the extended Fisher–Kolmogorov equation

We consider the Lyapunov functional, of the rescaled Extended Fisher-Kolmogorov equation This is a fourth order generalization of the Fisher–Kolmogorov or Allen–Cahn equation. We prove that if ε → 0, then tends to the area functional in the sense of Γ-limits, where the transition energy is given by the one-dimensional kink of the Extended Fisher–Kolmogorov equation.
Celiac Disease Is a Risk Factor for Mature T and NK Cell Lymphoma: A Mendelian Randomization Study

Celiac disease (CeD) is an immune-mediated disorder triggered by gluten ingestion that damages the small intestine. Although CeD has been associated with a higher risk for cancer, the role of CeD as a risk factor for specific malignancies, such as enteropathy-associated T-cell lymphoma (EATL), remains controversial. Using two-sample Mendelian randomization (2SMR) methods and the summarized results of large genome-wide association studies from public repositories, we addressed the causal relationship between CeD and eight different malignancies. Eleven non-HLA SNPs were selected as instrumental variables (IVs), and causality estimates were obtained using four 2SMR methods: random-effects inverse variance-weighted, weighted median estimation, MR-Egger regression, and MR pleiotropy residual sum and outlier (MR-PRESSO). We identified a significant causal relationship between CeD and mature T/NK cell lymphomas. Under a multivariate Mendelian randomization model, we observed that the causal effect of CeD was not dependent on other known lymphoma risk factors. We found that the most instrumental IV was located in the TAGAP locus, suggesting that aberrant T cell activation might be relevant in the T/NK cell malignization process. Our findings provide new insights into the connection between immune imbalance and the development of severe comorbidities, such as EATL, in patients with CeD.
Weather Regimes: Recurrence and Quasi Stationarity

Abstract Two different definitions of midlatitude weather regimes are compared. The first seeks recurrent atmospheric patterns. The second seeks quasi-stationary patterns, whose average tendency vanishes. Recurrent patterns are identified by cluster analysis, and quasi-stationary patterns are identified by solving a nonlinear equilibration equation. Both methods are applied on the same dataset: the NMC final analyses of 700-hPa geopotential heights covering 44 winters. The analysis is performed separately over the Atlantic and Pacific sectors. The two methods give the same number of weather regimes—four over the Atlantic sector and three over the Pacific sector. However, the patterns differ significantly. The investigation of the tendency, or drift, of the clusters shows that recurrent flows have a systematic slow evolution, explaining this difference. The patterns are in agreement with the ones obtained from previous studies, but their number differs. The cluster analysis algorithm used here is a partiti.
Predicting Moral Elevation Conveyed in Danmaku Comments Using EEGs

Moral elevation, the emotion that arises when individuals observe others’ moral behaviors, plays an important role in determining moral behaviors in real life. While recent research has demonstrated the potential to decode basic emotions with brain signals, there has been limited exploration of affective computing for moral elevation, an emotion related to social cognition. To address this gap, we recorded electroencephalography (EEG) signals from 23 participants while they viewed videos that were expected to elicit moral elevation. More than 30,000 danmaku comments were extracted as a crowdsourcing tagging method to label moral elevation continuously at a 1-s temporal resolution. Then, by employing power spectra features and the least absolute shrinkage and selection operator regularized regression analyses, we achieved a promising prediction performance for moral elevation (prediction r = 0.44 ± 0.11). Our findings indicate that it is possible to decode moral elevation using EEG signals. Moreover, the small-sample neural data can predict the continuous moral elevation experience conveyed in danmaku comments from a large population.
ANNALES DE LA FACULTÉ DES SCIENCES

A BSTRACT . — Steepness is a generic geometric property which, together with complex-analyticity, is needed in order to ensure stability of a nearly-integrable hamiltonian system over exponentially long times. Following a strategy developed by Nekhoroshev, we construct sufficient conditions for steepness of a given function that involve algebraic equations on its derivatives up to order five. This is important in view of applications (e
Modified Lagrangian-Mean Diagnostics of the Stratospheric Polar Vortices. Part I. Formulation and Analysis of GFDL SKYHI GCM

Abstract An exact, two-dimensional (height–latitude type) diagnostic model of tracer transport in the stratosphere is formulated. The model is a generalization of the area analysis method devised by Butchart and Remsberg but uses the mass element enclosed by the contours of a quasi-conservative tracer on a given isentropic surface as a “meridional” coordinate. This modified Lagrangian-mean coordinate is transparent to the advective effects of the winds, and thus unambiguously extracts the nonconservative effects on the tracer distribution. The derived transport equation takes an equivalent advective form; that is, the tracer contours are “advected” by the mean nonconservative mass flow while them are no “eddy flux” contributions. Hence, the mass flux is implied in the motion of the tracer contours. Not only is this model conceptually simple, it is also computationally economical for analyzing large, high-resolution datasets since time averaging can be omitted to define a robust mean field of the tracer. T.
Bayesian Analysis Of Mixture Distributions

In this thesis, we consider type-I mixtures of the members of a subclass of one parameter exponential family.This subclass includes Exponential, Rayleigh, Pareto, a Burr type XII and Power function distributions. Except the Exponential, mixtures of distributions of this subclass get either no or least attention in literature so far.The elegant closed form expressions for the Bayes estimators of the parameters of each of these mixtures are presented along with their variances assuming uninformative and informative priors.The proposed informative Bayes estimators emerge advantageous in terms of their least standard errors.An extensive simulation study is conducted for each of these mixtures to highlight the properties and comparison of the proposed Bayes estimators in terms of sample sizes, censoring rates, mixing proportions and different combinations of the parameters of the component densities. A type-IV sample consisting of ordinary type-I, right censored observations is considered. Bayesian analysis of the real life mixture data sets is conducted as an application of each mixture and some interesting observations and comparisons have been observed.The systems of non-linear equations to evaluate the classical maximum likelihood estimates, the components of the information matrices, complete sample expressions, the posterior predictive distributions and the equations for the evaluation of the Bayesian predictive intervals are derived for each of these mixtures as relevant algebra. The predictive intervals are evaluated in case of the Rayleigh mixture only for a number of combinations of the hyperparameters to look for a trend among the hyperparameters that may lead towards an efficient estimation.