Live birth prevalence of major congenital anomalies in the United Arab Emirates.

Major congenital anomalies (MCAs) significantly contribute to perinatal mortality and morbidity. Globally, the United Arab Emirates has the sixth-highest prevalence rate of congenital anomalies. The lack of clear baseline prevalence data for MCAs impedes the development of interventions to alleviate this burden.

Tackling misinformation in mobile social networks a BERT-LSTM approach for enhancing digital literacy.

The rapid proliferation of mobile social networks has significantly accelerated the dissemination of misinformation, posing serious risks to social stability, public health, and democratic processes. Early detection of misinformation is essential yet challenging, particularly in contexts where initial content propagation lacks user feedback and engagement data. This study presents a novel hybrid model that combines Bidirectional Encoder Representations from Transformers (BERT) with Long Short-Term Memory (LSTM) networks to enhance the detection of misinformation using only textual content.

Federated Learning with Privacy Preserving for Multi- Institutional Three-Dimensional Brain Tumor Segmentation.

Background And Objectives: Brain tumors are complex diseases that require careful diagnosis and treatment. A minor error in the diagnosis may easily lead to significant consequences. Thus, one must place a premium on accurately identifying brain tumors.

Optical biosensor arrays based on nanozymes for environmental monitoring and food safety detection: principles, design, and applications.

Typical biosensing platforms are based on the "lock-and-key" approach, providing high specificity and sensitivity for environmental and food safety monitoring. However, they are limited in their ability to detect multiple analytes simultaneously. With the use of pattern identification methods, biosensor arrays can detect faint fluctuations caused by multiple analytes with similar properties in complex systems.

An information gap decision theory and improved gradient-based optimizer for robust optimization of renewable energy systems in distribution network.

In this paper, a robust fuzzy multi-objective framework is performed to optimize the dispersed and hybrid renewable photovoltaic-wind energy resources in a radial distribution network considering uncertainties of renewable generation and network demand. A novel multi-objective improved gradient-based optimizer (MOIGBO) enhanced with Rosenbrock's direct rotational technique to overcome premature convergence is proposed to determine the problem optimal decision variables. The deterministic optimization framework without uncertainty minimizes active energy loss, unmet customer energy, and renewable generation costs.

Glutathione-Driven Disassembly of Planar Organic Phototherapeutic Agents to Enhance Photodynamic-Photothermal Therapy Performance for Nasopharyngeal Carcinoma.

The self-assembly of hydrophobic organic phototherapeutic agents (OPTAs) with expansive planar structures into nanoparticles (NPs) represents a pivotal strategy to bolster their biocompatibility. However, the tight molecular packing within these NPs significantly influences the generation of reactive oxygen species (ROS) and the photothermal conversion efficiency (PCE), posing a substantial hurdle to elevating the efficacy of photodynamic therapy (PDT) and photothermal therapy (PTT) for such NPs. In this article, three OPTAs by donor engineering are synthesized.

κ-carrageenan - Gelatin hydrogel embedding carvacrol loaded gold nanobipyramids for treating prostate cancer via fractionated photothermal-chemotherapy.

Conventional treatment of prostate cancer need more specificity, and higher efficiency. The present work is the first attempt to utilize hydrogel-loaded carvacrol-based chemotherapy with fractionated photothermal therapy (F-PTT) using a 635 nm laser for its treatment. Gold nanobipyramids (AuNBPs) were used as drug carrier and photosensitizer.

Plane coexistence behaviors for Hopfield neural network with two-memristor-interconnected neurons.

Memristors are commonly used as the connecting parts of neurons in brain-like neural networks. The memristors, unlike the existing literature, possess the capability to function as both self-connected synaptic weights and interconnected synaptic weights, thereby enabling the generation of intricate initials-regulated plane coexistence behaviors. To demonstrate this dynamical effect, a Hopfield neural network with two-memristor-interconnected neurons (TMIN-HNN) is proposed.

Enhancing unity-based AR with optimal lossless compression for digital twin assets.

The rapid development of Digital Twin (DT) technology has underlined challenges in resource-constrained mobile devices, especially in the application of extended realities (XR), which includes Augmented Reality (AR) and Virtual Reality (VR). These challenges lead to computational inefficiencies that negatively impact user experience when dealing with sizeable 3D model assets. This article applies multiple lossless compression algorithms to improve the efficiency of digital twin asset delivery in Unity's AssetBundle and Addressable asset management frameworks.

Neuromuscular and balance adaptations following acute stretching exercise: a randomized control trial.

Purpose: This study aimed to examine the acute effects of static stretching (SS) and dynamic stretching (DS) on neuromuscular function and balance in recreationally active men.

Method: Sixty participants were randomly assigned to SS, DS, or no stretching (NS) groups. Before and after their respective stretching protocols, participants were assessed using the stork balance test (SBT), Y-balance test (YBT), T-change of direction test (CoD T-test), countermovement jump test (CMJT), squat jump test (SJT), and five-time jump test (FJT).

Quantitative investigations on light emission profiles for interstitial laser treatment.

Interstitial laser treatment (ILT) using a diffusing applicator (DA) has been employed to treat tumors. However, the treatment efficacy and safety of the emission profiles from DAs have been poorly explored. This study investigated the effect of the emission profiles from DAs on prostate tumor treatment.

Vocal Biomarkers for Parkinson's Disease Classification Using Audio Spectrogram Transformers.

Parkinson's disease (PD) is a neurodegenerative disorder affecting motor and non-motor functions, including speech. This study evaluates the effectiveness of the audio spectrogram transformer (AST) model in detecting PD through vocal biomarkers, hypothesizing that its self-attention mechanism would better capture PD related speech impairments compared to traditional deep learning approaches. Speech recordings from 150 participants (100 from PC-GITA: 50 PD, 50 healthy controls (HC); 50 from Italian Parkinson's voice and speech (ITA): 28 PD, 22 HC) were analyzed using the AST model and compared against established architectures including VGG16, VGG19, ResNet18, ResNet34, vision transformer, and swin transformer.

Metaheuristic optimized complex-valued dilated recurrent neural network for attack detection in internet of vehicular communications.

The Internet of Vehicles (IoV) is a specialized iteration of the Internet of Things (IoT) tailored to facilitate communication and connectivity among vehicles and their environment. It harnesses the power of advanced technologies such as cloud computing, wireless communication, and data analytics to seamlessly exchange real-time data among vehicles, road-side infrastructure, traffic management systems, and other entities. The primary objectives of this real-time data exchange include enhancing road safety, reducing traffic congestion, boosting traffic flow efficiency, and enriching the driving experience.

A length-band fluorescence-based paper analytical device for detecting dipicolinic acid ofloxacin complexation with Cu.

Dipicolinic acid (DPA) is a key biomarker of bacterial spores. In this study, we present a novel distance-based paper analytical device (d-PAD) for the fluorescence sensing of DPA. The detection mechanism relies on the complexation of ofloxacin (OFL) with Cu ions, where Cu quenches the fluorescence of OFL static quenching.

Wound healing effect of fucoidan-loaded gelatin/oxidized carboxymethyl cellulose hydrogel.

Various wound dressings are under development to accelerate wound healing, and hydrogels in particular have the potential to create ideal conditions for wound healing. In this study, we investigated a novel hydrogel based on gelatin/oxidized carboxymethyl cellulose loaded with fucoidan derived from Ecklonia cava (ECF) for wound treatment. The mechanical stability and self-healing ability of the hydrogel were optimized, and its cytocompatibility was demonstrated against RAW 264.

Configuration-Mediated Efficient Non-Radiative Transition for R848-Assisted Photothermal Immunotherapy to Inhibit Tumor Growth and Metastasis by An In Situ Tumor Vaccine Strategy.

Cancer metastasis remains a critical factor contributing to the current limitations in cancer treatment. Photothermal immunotherapy has emerged as a safe and potent therapeutic approach, demonstrating the capability to suppress tumor growth and metastasis. While researchers have extensively investigated various structural modifications to enhance photothermal conversion performance, the influence of molecular configuration has received comparatively limited attention.

A multi-objective improved horse herd optimizer based on convex lens imaging for stochastic optimization of wind energy resources in distribution networks considering reliability and uncertainty.

In this study, stochastic multi-objective allocation of wind turbines (WTs) in radial distribution networks is performed using a new multi-objective improved horse herd optimizer (MOIHHO) and an unscented transformation (UT) method for modeling the uncertainties of WTs power and network load. The objective function aims to minimize power loss, improve reliability, and reduce the costs associated with wind turbines (WTs), presenting these goals as a three-dimensional function. The Multi-Objective Improved Horse Herd Optimizer (MOIHHO) is derived from an enhanced version of the traditional horse herd optimizer.

Exploring the Psychological Mechanism of How the Multidimensional Service Quality of Fitness Centers Affects Consumer Satisfaction and Loyalty Depending on the Level of Exercise Involvement.

This study aimed to examine the influence of core services and the physical servicescape and social servicescape on consumer satisfaction and loyalty via perceived price fairness, flow experience, and rapport in fitness centers. Additionally, the present study explored how exercise involvement moderates the relationship between perceived price fairness, flow experience, rapport, and consumer satisfaction. For these purposes, targeting adults using fitness centers in South Korea, a total of 763 participants were sampled based on a cross-sectional design and used for data analyses involving confirmatory factor analysis for measurement validation and latent moderated structural equation modeling for hypothesis testing.

A fish fry dataset for stocking density control and health assessment based on computer vision.

Fish farming is a promising economic activity that promotes the social development, protects the ecological environment, and enhances the quality of human life. In recent years, various computer vision models have been established for assessing aquaculture density and monitoring fish health. However, existing datasets are generally characterised by larger fish sizes and low density, making them unsuitable for detecting small targets such as fish fry.

Marine polysaccharides for antibiofilm application: A focus on biomedical fields.

Microbial pathogens such as bacteria and fungi form biofilms, which represent substantial hurdles in treating human illness owing to their adaptive resistance mechanism to conventional antibiotics. Biofilm may cause persistent infection in a variety of bodily areas, including wounds, oral cavity, and vaginal canal. Using invasive devices such as implants and catheters contributes significantly to developing healthcare-associated infections because they offer an ideal surface for biofilm formation.

A hybrid healthy diet recommender system based on machine learning techniques.

Obesity is a chronic disease correlated with numerous risk factors that not only negatively affect all body functions but also increase the chances of developing chronic diseases and the associated morbidity and mortality rates. This study proposes a novel system that bridges the gap between healthcare providers and patients by offering both parties some tools for navigating the intricacies of dietary planning. In this system, machine learning techniques are used to determine the required calories before starting an obesity treatment.

A series of blue phosphorescent iridium complexes with thermally activated delayed fluorescence and efficiency roll-off properties.

Six iridium complexes were designed and studied using the DFT approach, (ppy)Ir(pic) (1), (fppy)Ir(pic) (2), (ppy)Ir(tmd) (3), (fppy)Ir(tmd) (4), (ppy)Ir(tpip) (5) and (fppy)Ir(tpip) (6). Here ppy denotes phenylpyridine, fppy denotes 2-(2,3,4,5-tetrafluorophenyl) pyridine, pic denotes benzoic acid, tmd denotes 5-hydroxy-2,2,6,6-tetramethylhept-4-en-3-one and tpip denotes tetraphenylimido-diphosphinate. The geometries, absorptions, emissions, frontier molecular orbitals, and spin-orbit coupling (SOC) constants of the 6 complexes were evaluated.

Proactive personality and its impact on online learning engagement through positive emotions and learning motivation.

The rapid change in information technology has made online or blended learning a new norm in higher education. However, the problem of low student engagement in online learning is becoming more prominent. This study explores how college students' proactive personality affects their online learning engagement through the mediating effects of positive emotions and learning motivation.