The Effect of the Linguistic Status of Text Previewing in Arabic on the Reading Comprehension Outcomes Among Second and Sixth Grade Native Arabs Readers: A Cross-Sectional View.

The current study examined the effect of the linguistic status of the verbal previewing strategy on the outcomes of reading comprehension tasks among second (N = 25, age 7.08 ± .3), and sixth-grade students (N = 25, age 11.

HMCDA: a novel method based on the heterogeneous graph neural network and metapath for circRNA-disease associations prediction.

Circular RNA (CircRNA) is a type of non-coding RNAs in which both ends are covalently linked. Researchers have demonstrated that many circRNAs can act as biomarkers of diseases. However, traditional experimental methods for circRNA-disease associations identification are labor-intensive.

Associations between Birth Weight and Adult Sleep Characteristics: A Cross-Sectional Analysis from the UAEHFS.

Abnormal birth weight, particularly low birth weight (LBW), is known to have long-term adverse health consequences in adulthood, with disrupted sleep being suggested as a mediator or modifier of this link. We thus aimed to assess the associations between birth weight and self-reported adult sleep characteristics: sleep duration, difficulty waking up in the morning, daily nap frequency, sleep problems at night, snoring, daytime tiredness or sleepiness, and ever-stop breathing during sleep. This cross-sectional analysis used the United Arab Emirates Healthy Future Study data collected from February 2016 to March 2023 involving 2124 Emiratis aged 18-61 years.

Exploring the Variables of the Psychological Well-Being of Mothers of Children with Autism Spectrum Disorder Through Self-Compassion and Psychological Hardiness.

Present study aimed to evaluate the relationship between self-compassion and psychological hardiness, and psychological well-being among mothers of children with autism. The research design was correlational, and its statistical population sample consisted of 101 mothers of children with an autism spectrum disorder. The results of a correlational analysis showed a significant positive relationship between self-compassion and psychological hardiness, and psychological well-being.

UAE Women's Knowledge and Attitudes towards Physical Activity during Pregnancy.

The benefits of being physically active during pregnancy are widely acknowledged. It is important for the prevention of chronic diseases and the promotion of good health for mothers and children. However, physical activity by women in the UAE is notoriously low and reduced further during pregnancy.

Association of the gut microbiota with clinical variables in obese and lean Emirati subjects.

Background: Growing evidence supports the role of gut microbiota in obesity, yet exact associations remain largely unknown. Specifically, very little is known about this association in the Emirati population.

Methods: We explored differences in gut microbiota composition, particularly the Firmicutes/Bacteroidetes (F/B) ratio, between 43 obese and 31 lean adult Emirate counterparts, and its association with obesity markers, by using V3-V4 regions of 16 S ribosomal RNA gene sequencing data.

Sequence pre-training-based graph neural network for predicting lncRNA-miRNA associations.

MicroRNAs (miRNAs) silence genes by binding to messenger RNAs, whereas long non-coding RNAs (lncRNAs) act as competitive endogenous RNAs (ceRNAs) that can relieve miRNA silencing effects and upregulate target gene expression. The ceRNA association between lncRNAs and miRNAs has been a research hotspot due to its medical importance, but it is challenging to verify experimentally. In this paper, we propose a novel deep learning scheme, i.

Mental illness stigma as a moderator in the relationship between religiosity and help-seeking attitudes among Muslims from 16 Arab countries.

Background: Determining the potential barriers responsible for delaying access to care, and elucidating pathways to early intervention should be a priority, especially in Arab countries where mental health resources are limited. To the best of our knowledge, no previous studies have examined the relationship between religiosity, stigma and help-seeking in an Arab Muslim cultural background. Hence, we propose in the present study to test the moderating role of stigma toward mental illness in the relationship between religiosity and help-seeking attitudes among Muslim community people living in different Arab countries.

Green synthesis of lead oxide nanoparticles for photo-electrocatalytic and antimicrobial applications.

Synthesis of nanoparticles (NPs) for many different uses requires the development of environmentally friendly synthesis protocols. In this article, we present a simple and environmentally friendly method to synthesize lead oxide (PbO) NPs from the plant material of the . Analytical techniques such as spectroscopy, X-ray diffraction, and microscopy were used to characterize the synthesized PbO NPs, and their photo-electrocatalytic and antifungal properties were also evaluated.

Removal of crystal violet dye using a three-dimensional network of date pits powder/sodium alginate hydrogel beads: Experimental optimization and DFT calculation.

Biodegradable and very low-cost adsorbent beads were prepared from date pits powder (DP) and sodium alginate (SA). DP to SA ratios was varied (1/2, 1/4 and 1/6) and used to eliminate Crystal violet (CV) a cationic dye. Adsorbents were characterized by FTIR, SEM-EDS, UV-vis DR, TGA and the point of zero charge (pH).

Association of Maternal Pre-Pregnancy Overweight and Obesity with Childhood Anthropometric Factors and Perinatal and Postnatal Outcomes: A Cross-Sectional Study.

Background: Pre-pregnancy overweight and obesity in reproductive-aged women becomes a growing tendency in middle- and high-income populations. This study aimed to evaluate whether maternal excess body mass index (BMI) before gestation is associated with children's anthropometric characteristics, as well as perinatal and postnatal outcomes.

Methods: This was a cross-sectional study performed on 5198 children aged 2-5 years old and their paired mothers, assigned from 9 different areas of Greece.

Religious coping and levels of posttraumatic stress disorder symptomatology after the Beirut explosion.

Objective: Religious coping has implications for the development of psychopathology in the aftermath of traumatic events. This study explored the relationship between religious coping (positive and negative) and posttraumatic stress disorder (PTSD) symptomology among survivors of a large industrial explosion that devastated parts of Beirut in August of 2020.

Method: Three months after the disaster, 996 residents of Beirut and Lebanon completed validated measures of religious coping (RCOPE) and PTSD symptomatology (Impact of Events Scale-Revised) in either English or Arabic.

StrokeNet: An automated approach for segmentation and rupture risk prediction of intracranial aneurysm.

Intracranial Aneurysms (IA) present a complex challenge for neurosurgeons as the risks associated with surgical intervention, such as Subarachnoid Hemorrhage (SAH) mortality and morbidity, may outweigh the benefits of aneurysmal occlusion in some cases. Hence, there is a critical need for developing techniques that assist physicians in assessing the risk of aneurysm rupture to determine which aneurysms require treatment. However, a reliable IA rupture risk prediction technique is currently unavailable.

A TRANSCRIPTOMIC APPRECIATION OF CHILDHOOD MENINGOCOCCAL AND POLYMICROBIAL SEPSIS FROM A PRO-INFLAMMATORY AND TRAJECTORIAL PERSPECTIVE, A ROLE FOR VASCULAR ENDOTHELIAL GROWTH FACTOR A AND B MODULATION?

This study investigated the temporal dynamics of childhood sepsis by analyzing gene expression changes associated with proinflammatory processes. Five datasets, including four meningococcal sepsis shock (MSS) datasets (two temporal and two longitudinal) and one polymicrobial sepsis dataset, were selected to track temporal changes in gene expression. Hierarchical clustering revealed three temporal phases: early, intermediate, and late, providing a framework for understanding sepsis progression.

Dynamic spillovers and portfolio implication between green cryptocurrencies and fossil fuels.

Are green investments decoupled from the dirty investment such as the fossil fuel markets? We address this issue by extending the literature on environmental, social, and governance (ESG) assets by examining the dynamic relationship between fossil fuels and digital ESG assets proxied by green cryptocurrencies using the TVP-VAR(Time-varying parameter vector auto regression) spillover framework. Furthermore, we analyze the hedging attributes of green cryptocurrencies and fossil fuels in a minimum connectedness framework. The main findings are as follows: First, green cryptocurrencies are the main shock transmitters in all asset systems.

Empowering Patient Similarity Networks through Innovative Data-Quality-Aware Federated Profiling.

Continuous monitoring of patients involves collecting and analyzing sensory data from a multitude of sources. To overcome communication overhead, ensure data privacy and security, reduce data loss, and maintain efficient resource usage, the processing and analytics are moved close to where the data are located (e.g.

Prompt-Based Tuning of Transformer Models for Multi-Center Medical Image Segmentation of Head and Neck Cancer.

Medical image segmentation is a vital healthcare endeavor requiring precise and efficient models for appropriate diagnosis and treatment. Vision transformer (ViT)-based segmentation models have shown great performance in accomplishing this task. However, to build a powerful backbone, the self-attention block of ViT requires large-scale pre-training data.

Zinc nanoparticles encapsulated in porous biopolymer beads for reduction of water pollutants and antimicrobial activity.

This work focuses on the preparation of composite beads from alginate crosslinked with copper at several loading percent and also loaded with ZnNPs. Th obtained samples were applied as catalysts for the reduction of the organic polluants 4-NP, MB, OG, MO, and CR in simple and binary systems. XRD results and TEM images confirmed the presence of ZnNPs in the polymer matrix.

Artificial intelligence tool for the study of COVID-19 microdroplet spread across the human diameter and airborne space.

The 2019 novel coronavirus (SARS-CoV-2 / COVID-19), with a point of origin in Wuhan, China, has spread rapidly all over the world. It turned into a raging pandemic wrecking havoc on health care facilities, world economy and affecting everyone's life to date. With every new variant, rate of transmission, spread of infections and the number of cases continues to rise at an international level and scale.

A novel higher order appearance texture analysis to diagnose lung cancer based on a modified local ternary pattern.

Background And Objective: Lung cancer is an important cause of death and morbidity around the world. Two of the primary computed tomography (CT) imaging markers that can be used to differentiate malignant and benign lung nodules are the inhomogeneity of the nodules' texture and nodular morphology. The objective of this paper is to present a new model that can capture the inhomogeneity of the detected lung nodules as well as their morphology.

Prolonged school closure during the pandemic time in successive waves of COVID-19- vulnerability of children to sexual abuses - A case study in Tamil Nadu, India.

Objectives: The Tamil Nadu government mandated several stay-at-home orders, with restrictions of varying intensities, to contain the first two waves of the COVID-19 pandemic. This research investigates how such orders impacted child sexual abuse (CSA) by using counterfactual prediction to compare CSA statistics with those of other crimes. After adjusting for mobility, we investigate the relationship between situational factors and recorded levels of cases registered under the Protection of Children from Sexual Offences Act (POCSO).

Disease progression modelling of Alzheimer's disease using probabilistic principal components analysis.

The recent biological redefinition of Alzheimer's Disease (AD) has spurred the development of statistical models that relate changes in biomarkers with neurodegeneration and worsening condition linked to AD. The ability to measure such changes may facilitate earlier diagnoses for affected individuals and help in monitoring the evolution of their condition. Amongst such statistical tools, disease progression models (DPMs) are quantitative, data-driven methods that specifically attempt to describe the temporal dynamics of biomarkers relevant to AD.