A comprehensive dataset for Arabic word sense disambiguation.

This data paper introduces a comprehensive dataset tailored for word sense disambiguation tasks, explicitly focusing on a hundred polysemous words frequently employed in Modern Standard Arabic. The dataset encompasses a diverse set of senses for each word, ranging from 3 to 8, resulting in 367 unique senses. Each word sense is accompanied by contextual sentences comprising ten sentence examples that feature the polysemous word in various contexts.

Unskilled and unaware: second-order judgments increase with miscalibration for low performers.

Overestimation and miscalibration increase with a decrease in performance. This finding has been attributed to a common factor: participants' knowledge and skills about the task performed. Researchers proposed that the same knowledge and skills needed for performing well in a test are also required for accurately evaluating one's performance.

AttentionPert: accurately modeling multiplexed genetic perturbations with multi-scale effects.

Motivation: Genetic perturbations (e.g. knockouts, variants) have laid the foundation for our understanding of many diseases, implicating pathogenic mechanisms and indicating therapeutic targets.

The efficiency of chlorophyll fluorescence as a selection criterion for salinity and climate aridity tolerance in barley genotypes.

Introduction: In the Near East and North Africa (NENA) region, crop production is being affected by various abiotic factors, including freshwater scarcity, climate, and soil salinity. As a result, farmers in this region are in search of salt-tolerant crops that can thrive in these harsh environments, using poor-quality groundwater. The main staple food crop for most of the countries in this region, Tunisia included, is barley.

Antimicrobial Resistance Profiles of Pseudomonas aeruginosa in the Arabian Gulf Region Over a 12-Year Period (2010-2021).

Objectives: To evaluate literature from a 12-year period (2010-2021) on the antimicrobial resistance profile of Pseudomonas aeruginosa from the Arabian Gulf countries (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates).

Methods: An electronic literature search was conducted for articles on antimicrobial resistance in P. aeruginosa and associated phenotypes, covering the period of 1st January 2010 to 1st December 2021.

Breathing in danger: Understanding the multifaceted impact of air pollution on health impacts.

Air pollution, a pervasive environmental threat that spans urban and rural landscapes alike, poses significant risks to human health, exacerbating respiratory conditions, triggering cardiovascular problems, and contributing to a myriad of other health complications across diverse populations worldwide. This article delves into the multifarious impacts of air pollution, utilizing cutting-edge research methodologies and big data analytics to offer a comprehensive overview. It highlights the emergence of new pollutants, their sources, and characteristics, thereby broadening our understanding of contemporary air quality challenges.

A generic blood banking and transfusion process-oriented architecture for virtual organizations.

Background: Blood banks are an important part of healthcare systems. They embrace critical processes that start with donor recruitment and blood collection, followed by blood processing to produce different types of blood components used in transfusions, blood storage, blood distribution, and transfusion. Blood components must be generated at high quality, preserved safely, and transfused in a timely manner.

Unveiling the Metaverse: A survey of user perceptions and the impact of usability, social influence and interoperability.

This review explores the Metaverse, focusing on user perceptions and emphasizing the critical aspects of usability, social influence, and interoperability within this emerging digital ecosystem. By integrating various academic perspectives, this analysis highlights the Metaverse's significant impact across various sectors, emphasizing its potential to reshape digital interaction paradigms. The investigation reveals usability as a cornerstone for user engagement, demonstrating how social dynamics profoundly influence user behaviors and choices within virtual environments.

Prevalence of premenstrual syndrome and its associations with dietary and other lifestyle factors among university female students in Dubai: A cross-sectional study.

Background: Premenstrual syndrome is a relatively prevalent condition that affects a significant number of menstruating women worldwide. It can range from mild to severe and may interfere with daily activities.

Objective: This study aims to investigate the prevalence of premenstrual syndrome and its associated factors among female university students in Dubai.

Identity and inequality misperceptions, demographic determinants and efficacy of corrective measures.

By conducting two waves of large-scale surveys in the United Kingdom and Germany, we investigate the determinants of identity and inequality misperceptions. We first show that people substantially overestimate the share of immigrants, Muslims, people under the poverty line, and the income share of the richest. Moreover, women, lower-income, and lower-educated respondents generally have higher misperceptions.

Associations between Polycystic Ovary Syndrome (PCOS) and Antibiotic Use: Results from the UAEHFS.

Women with polycystic ovary syndrome (PCOS) have a higher susceptibility to infections compared to those without PCOS. Studies evaluating antibiotic use based on PCOS status are scarce. Therefore, we aimed to (i) assess the associations between self-reported PCOS and antibiotic use, and (ii) whether PCOS treatment and the age at PCOS diagnosis modified the associations above.

Vitamin D regulates COVID-19 associated severity by suppressing the NLRP3 inflammasome pathway.

Background: The role of vitamin D3 (VitD3) in modulating innate and adaptive immunity has been reported in different disease contexts. Since the start of the coronavirus disease-2019 (COVID-19) pandemic, the role of VitD3 has been highlighted in many correlational and observational studies. However, the exact mechanisms of action are not well identified.

Cyclic AMP-regulatory element-binding protein: a novel UV-targeted transcription factor in skin cancer.

Common therapeutics in relation to melanoma and non-melanoma cancers include the use of kinase inhibitors. The long-term benefits of kinases, however, are limited by development of drug resistance. An alternative approach for treatment would be to focus on transcription factors.

Comparing and assessing four AI chatbots' competence in economics.

Artificial Intelligence (AI) chatbots have emerged as powerful tools in modern academic endeavors, presenting both opportunities and challenges in the learning landscape. They can provide content information and analysis across most academic disciplines, but significant differences exist in terms of response accuracy for conclusions and explanations, as well as word counts. This study explores four distinct AI chatbots, GPT-3.

Temporal dynamics of coordinated online behavior: Stability, archetypes, and influence.

Large-scale online campaigns, malicious or otherwise, require a significant degree of coordination among participants, which sparked interest in the study of . State-of-the-art methods for detecting coordinated behavior perform analyses, disregarding the temporal dynamics of coordination. Here, we carry out a analysis of coordinated behavior.

Associations of body adiposity index, body mass index, waist circumference, and percentage of body fat in young female Emirati adults.

Body Adiposity Index (BAI), which relies on an individual's hip circumference and height, was proposed as an alternative anthropometric measurement to Body Mass Index (BMI). Although this measure has been validated across different populations, its accuracy in predicting percent body fat (%BF) in the United Arab Emirates has not yet been assessed. The objective of this study was to examine the association between BAI, BMI, Waist Circumference (WC), and %BF in young female Emirati adults and determine the relative accuracy of BAI when predicting %BF.

Ozone as an environmental driver of influenza.

Under long-standing threat of seasonal influenza outbreaks, it remains imperative to understand the drivers of influenza dynamics which can guide mitigation measures. While the role of absolute humidity and temperature is extensively studied, the possibility of ambient ozone (O) as an environmental driver of influenza has received scant attention. Here, using state-level data in the USA during 2010-2015, we examined such research hypothesis.

Nanozyme-based sensing of dopamine using cobalt-doped hydroxyapatite nanocomposite from waste bones.

Dopamine is one of the most important neurotransmitters and plays a crucial role in various neurological, renal, and cardiovascular systems. However, the abnormal levels of dopamine mainly point to Parkinson's, Alzheimer's, cardiovascular diseases, etc. Hydroxyapatite (HAp), owing to its catalytic nature, nanoporous structure, easy synthesis, and biocompatibility, is a promising matrix material.

Validity of self-reported weight and height among female young adults in the United Arab Emirates.

Self-reported weight and height serve as important metrics in estimating overweight and obesity prevalence within epidemiological studies, primarily due to their cost and time efficiency. However, the accuracy and reliability of these self-reported measures remain controversial, with conflicting reports emerging from different regions. This study aims to compare self-reported weight and height with measured values among young female adults in the United Arab Emirates.

Learnable weight initialization for volumetric medical image segmentation.

Hybrid volumetric medical image segmentation models, combining the advantages of local convolution and global attention, have recently received considerable attention. While mainly focusing on architectural modifications, most existing hybrid approaches still use conventional data-independent weight initialization schemes which restrict their performance due to ignoring the inherent volumetric nature of the medical data. To address this issue, we propose a learnable weight initialization approach that utilizes the available medical training data to effectively learn the contextual and structural cues via the proposed self-supervised objectives.