A novel Swin transformer based framework for speech recognition for dysarthria.

Dysarthria frequently occurs in individuals with disorders such as stroke, Parkinson's disease, cerebral palsy, and other neurological disorders. Well-timed detection and management of dysarthria in these patients is imperative for efficiently handling the development of their condition. Several previous studies have concentrated on detecting dysarthria speech using machine learning-based methods.

Association between heavy menstrual bleeding and depression among women in South Asia: a cross-sectional study.

Objective: Heavy menstrual bleeding-clinically defined as excessive menstrual blood loss that interferes with physical, emotional, social, or material quality of life -adversely affects health and functional outcomes among individuals who menstruate. However, the full extent of the relationships between heavy menstrual bleeding and health outcomes remains unknown, especially in low- and middle-income countries. To begin to fill this evidence gap, we investigated associations between heavy menstrual bleeding and depression symptomology among women in South Asia.

A comprehensive investigation of structural, mechanical and optoelectronics attributes of MAsC (M = Zr, Hf, Ta, W) MAX phase carbides: A DFT investigation.

This research utilizes first-principles calculations to systematically investigate the phase stability, mechanical properties, and optoelectronic characteristics of the MAsC (M = Zr, Hf, Ta, and W) MAX phase carbides. The phase stability of these MAsC compounds is evaluated through the computation of formation enthalpies, which demonstrates that all analyzed compounds exhibit both structural and thermodynamic stability. To evaluate mechanical stability, we calculated the elastic stiffness constants, confirming the mechanical robustness of the studied MAX phases.

PERI_DEP: A dataset of mother's mental health in Pakistan.

Perinatal depression (PND) represents a multifaceted mental health issue that impacts women throughout the perinatal period. Existing datasets have a class imbalance issue, resulting in biased outcomes. In Pakistan, we developed a novel dataset called PERI_DEP.

Information Needs for Opioid Use Disorder Treatment Using Buprenorphine Product: Qualitative Analysis of Suboxone-Focused Reddit Data.

Background: Buprenorphine is a Food and Drug Administration-approved medication for opioid use disorder. However, individuals with opioid use disorder often report information needs regarding buprenorphine treatment on social media platforms such as Reddit. The field lacks a systematic approach to organizing these data and characterizing treatment information needs that may be unique and unavailable elsewhere.

Stochastic optimization for minimizing operational costs in smart hybrid energy networks considering electric vehicle.

The residential energy hub (REH) effectively satisfies power demands, but the incorporation of renewable energy sources (RES) and the increasing use of plug-in hybrid electric vehicles (PHEVs), with their unpredictable nature, complicates its optimal functionality and challenges the accurate modeling and optimization of REH. This work proposed a stochastic model for REH using mixed integer linear programming (MILP) to optimally handle the associated uncertainties of RES and PEHVs, which was then solved using GAMS software. Four case studies with varying conditions were conducted to verify the performance of the proposed scheme, and the results indicate that the approach is superior in optimally handling the system's associated limitations.

Draft genome sequence of strain NGMBE-25A isolated from fecal samples of migratory birds at Jahangirnagar University, Bangladesh.

We report the draft genome sequence of from migratory birds at Jahangirnagar University, Bangladesh. The 6.27 Mb genome, sequenced using Illumina MiSeq, contains 5,719 coding sequences, including antibiotic resistance genes.

Improving thyroid disorder diagnosis via innovative stacking ensemble learning model.

Objective: Hypothyroidism, hyperthyroidism, thyroid nodules, and other thyroid disorders are common around the world, affect millions of people worldwide, and untreated health conditions may lead to serious health issues. An accurate and timely diagnosis serves as crucial for proper management and medication. This study utilizes a dataset from the UCI machine-learning repository to put forward the comprehensive machine-learning technique for diagnosing thyroid disorders.

SPaSE: Spatially resolved pathology scores using optimal transport on spatial transcriptomics data.

Pathological events often impact tissue regions in a spatially variable manner, making it challenging to identify therapeutic targets. Spatial transcriptomics (ST) is a powerful technology to map spatially variable molecular mechanisms, yet suitable analytical methods have been lacking. We introduce spatially resolved pathology score (SPaSE), an optimal transport-based algorithm to compare ST data from diseased and control tissues.

A simple approach in balancing the slider-crank mechanisms applied to new systems.

This study presents a simple method for balancing a slider-crank mechanism which is applied to a new system. A counterweight is designed and located on the crank link to solve the vibration of slider-crank mechanism. The calculation of counterweight design is proposed to balance the single and double slider-crank mechanisms which are exploited to develop the fast scanning module of scanning acoustic microscopy (SAM) system.

Comparative effects of ZnSO and ZnO-NPs in improving cotton growth and yield under drought stress at early reproductive stage.

Drought episodes, especially during the reproductive stages, have posed a significant threat to cotton production on a global scale. Finding an efficient solution that would bring immediate advantages to cotton producers has received unprecedented interest from the research community. Mineral supplements can play an important role in combating drought, while also improving fiber yield and cotton quality.

Intermittent pneumatic compression therapy as a preventive measure for venous thromboembolism after total hip arthroplasty: A systematic review.

Background: Venous thromboembolism (VTE) is a significant and avoidable complication that may occur after total hip arthroplasty (THA). Various mechanical and chemical prophylactic measures may mitigate this elevated risk of death and functional impairment. Consequently, early prevention of VTE is essential via the identification of related risk factors.

MULTICAUSENET temporal attention for multimodal emotion cause pair extraction.

In the realm of emotion recognition, understanding the intricate relationships between emotions and their underlying causes remains a significant challenge. This paper presents MultiCauseNet, a novel framework designed to effectively extract emotion-cause pairs by leveraging multimodal data, including text, audio, and video. The proposed approach integrates advanced multimodal feature extraction techniques with attention mechanisms to enhance the understanding of emotional contexts.

Antibacterial and electrical performance of triboelectric nanogenerators based on polyhexamethylene guanidine hydrochloride in high humidity environments.

A humidity-resistant, antibacterial triboelectric nanogenerator (TENG) was developed using polyhexamethylene guanidine hydrochloride (PHMG) as the primary functional material. To enhance performance stability, PHMG was integrated with natural chitosan (CS) to create a positively charged triboelectric electrode. When combined with a negatively charged fluorinated ethylene propylene (FEP) membrane, the TENG demonstrated outstanding electrical output, achieving a maximum peak-to-peak voltage ( ) of 1470.

Synthesis, characterization and mechanistic studies of an activated carbon-supported nickel (Ni/C) catalyst for the effective amidation of aldehydes.

A novel reusable activated carbon-supported nickel (Ni/C) catalyst was prepared, characterized and used as a heterogeneous catalyst for the synthesis of amide compounds through the amidation of aldehydes with amines. Mechanistic studies were also performed. This heterogeneous catalyst was reusable and could be employed three times without any notable degradation in its catalytic efficacy.

Imo-induced changes in gut hormones and glucose metabolism: A key to improving insulin sensitivity in type 2 diabetes.

Isomalto-oligosaccharides (IMO) are prebiotic oligosaccharides that have shown promise in improving insulin sensitivity and glucose metabolism, making them potential therapeutic agents for Type 2 Diabetes (T2D). IMO selectively stimulates beneficial gut microbiota, particularly Bifidobacterium and Lactobacillus, leading to the production of short-chain fatty acids (SCFAs) like acetate, propionate, and butyrate. These SCFAs play a pivotal role in enhancing the release of gut hormones such as GLP-1 (Glucagon-like peptide-1) and PYY (Peptide YY), which improve insulin secretion and promote satiety, thus improving glucose homeostasis.

Progress in silicon-based materials for emerging solar-powered green hydrogen (H) production.

The imperative demand for sustainable and renewable energy solutions has precipitated profound scientific investigations into photocatalysts designed for the processes of water splitting and hydrogen fuel generation. The abundance, low toxicity, high conductivity, and cost-effectiveness of silicon-based compounds make them attractive candidates for hydrogen production, driving ongoing research and technological advancements. Developing an effective synthesis method that is simple, economically feasible, and environmentally friendly is crucial for the widespread implementation of silicon-based heterojunctions for sustainable hydrogen production.

Physicomechanical Properties of Tissue Conditioner Reinforced with Glass Fibers.

Tissue conditioners are temporary lining materials applied to dentures to soothe and cushion inflamed or traumatized oral tissues, typically resulting from ill-fitting dentures. This laboratory study aimed to evaluate the physicomechanical properties of a clinical tissue conditioner with 0.5 and 1 wt.

Evaluation of chip breaker designs on tool life and hole integrity in drilling of HFRP/Al composite.

In this study, drilling of a newly developed lightweight fire-retardant carbon/glass-fiber-reinforced polymer epoxy sandwich that includes an aluminum honeycomb core with modified epoxy (HFRP/Al sandwich composite) is investigated. A new high-performance insert combination comprising central-stepped and peripheral-wiper inserts is evaluated. The geometry of the central insert is kept constant while two variations in chip breaker (C) designs are introduced on wiper inserts differentiated mainly based on C width and C depth.

Cyber security Enhancements with reinforcement learning: A zero-day vulnerabilityu identification perspective.

A zero-day vulnerability is a critical security weakness of software or hardware that has not yet been found and, for that reason, neither the vendor nor the users are informed about it. These vulnerabilities may be taken advantage of by malicious people to execute cyber-attacks leading to severe effects on organizations and individuals. Given that nobody knows and is aware of these weaknesses, it becomes challenging to detect and prevent them.

Detection of Mycotoxins in Cereal Grains and Nuts Using Machine Learning Integrated Hyperspectral Imaging: A Review.

Cereal grains and nuts are the world's most produced food and the economic backbone of many countries. Food safety in these commodities is crucial, as they are highly susceptible to mold growth and mycotoxin contamination in warm, humid environments. This review explores hyperspectral imaging (HSI) integrated with machine learning (ML) algorithms as a promising approach for detecting and quantifying mycotoxins in cereal grains and nuts.

Beyond Handcrafted Features: A Deep Learning Framework for Optical Flow and SLAM.

This paper presents a novel approach for visual Simultaneous Localization and Mapping (SLAM) using Convolution Neural Networks (CNNs) for robust map creation. Traditional SLAM methods rely on handcrafted features, which are susceptible to viewpoint changes, occlusions, and illumination variations. This work proposes a method that leverages the power of CNNs by extracting features from an intermediate layer of a pre-trained model for optical flow estimation.

Compact dual band crossover for 5G low and mid band applications using a metamaterial branch line coupler.

This research paper introduces a compact dual-band crossover designed for the low and mid-band 5G frequencies at 0.7 GHz and 3.5 GHz.