CAT: Class-aware adaptive-thresholding for robust semi-supervised domain generalization.

Domain Generalization (DG) seeks to transfer knowledge from multiple source domains to unseen target domains, even in the presence of domain shifts. Achieving effective generalization typically requires a large and diverse set of labeled source data to learn robust representations that can generalize to new, unseen domains. However, obtaining such high-quality labeled data is often costly and labor-intensive, limiting the practical applicability of DG.

A byzantine-resistant blockchain framework for secure and scalable immigration management.

Modern immigration management systems face three critical challenges: security vulnerabilities in centralized databases exemplified by a 2023 breach exposing over 120,000 records processing inefficiencies resulting in delays over 30 days, and interoperability gaps among stakeholders. Although blockchain has been proposed, current implementations often sacrifice regulatory compliance (e.g.

A cost effective real time rail track monitoring system leveraging multi sensor fusion and multi objective optimization.

Derailments, common in developing nations, often result from dislodged or defective rail blocks, leading to substantial property damage and loss of life. Developing an automated real-time wireless sensing system for preventing derailments is a complex challenge, particularly in resource-constrained regions with limited network infrastructure. Existing research has yet to provide a practical solution that effectively addresses the need for long-distance sensing and optimized sensor deployment.

Monitoring LULC dynamics and detecting transformation hotspots in sylhet, Bangladesh (2000-2023) using Google Earth Engine.

Sylhet, located in the northeastern part of Bangladesh, is characterized by a unique topography and climatic conditions that make it susceptible to flash floods. The interplay of rapid urbanization and climatic variability has exacerbated these flood risks in recent years. Effective monitoring and planning of land use/land cover (LULC) are crucial strategies for mitigating these hazards.

CrustChain: Resolving the blockchain trilemma via decentralized storage and proof-of-capacity consensus.

The blockchain trilemma-achieving scalability, security, and decentralization simultaneously-remains an unsolved challenge in distributed systems. This paper introduces CrustChain, a novel framework that advances decentralized storage and consensus via three key innovations: (1) a reputation-weighted (where node influence scales with storage contribution and historical reliability) Proof-of-Capacity mechanism with temporal Sealed-Post (SPoSt) challenges, (2) hybrid erasure-network coding for 82% storage cost reduction, and (3) MDP-optimized sharding for sub-second cross-shard latency. By combining storage resource guarantees with a sharded validation layer, CrustChain processes 1,450 transactions per second (TPS) at sub-second latency while maintaining a chain quality score (fraction of blocks produced by honest nodes) of 0.

Mechanical performance analysis of a 3D printing-based transtibial prosthetic socket against the gait cycle using the finite element method.

In order to restore near-normal gait patterns and increase patients' mobility post-amputation, prosthetic sockets are crucial. Currently, few 3D-printed prosthetic sockets are available, and little research has been conducted on their mechanical performance. Thus, the purpose of this study is to assess and characterize the performance of polyethylene terephthalate (PET), polycarbonate (PC), and polyamide 6/Nylon 6 (PA6) materials in prosthetic sockets fabricated 3D printing.

Leveraging transformers and explainable AI for Alzheimer's disease interpretability.

Alzheimer's disease (AD) is a progressive brain ailment that causes memory loss, cognitive decline, and behavioral changes. It is quite concerning that one in nine adults over the age of 65 have AD. Currently there is almost no cure for AD except very few experimental treatments.

Advancing biomedical applications: integrating textile innovations with tissue engineering.

Textile technologies are significantly advancing the field of tissue engineering (TE) by providing innovative scaffolds that closely mimic the extracellular matrix and address crucial challenges in tissue regeneration. Techniques such as weaving, knitting, and braiding allow for creating structures with customizable porosity, mechanical properties, and fiber alignment, which are essential for supporting cellular behaviors such as adhesion, proliferation, and differentiation. Recent developments have incorporated bioactive materials-like growth factors, peptides, and nanoparticles-into these textile-based scaffolds, greatly enhancing their functionality for applications in wound healing, skin regeneration, and organ engineering.

Influence of sinker timing on loop shape, width and areal density of weft-knitted cotton plain jersey fabric.

This study aims to explore the influence of sinker timing-a relative positional setting of two primary knitting elements, i.e., needle and sinker, on some important knitted fabric parameters and related properties.

Enhancing operational efficiency through overall equipment efficiency optimization and Kaizen initiatives.

This case study aims to investigate the causes of low efficiency in a carton production line by calculating Overall Equipment Effectiveness (OEE). A typical carton factory has been chosen for this study, which has two production lines, namely finished goods and corrugated boards. The define, measure, analyze, improve, and control approach is applied while implementing Six Sigma principles such as Kaizen, fishbone diagrams, and 5W+1H as its systematic procedure.

Correction: Functional coatings for textiles: advancements in flame resistance, antimicrobial defense, and self-cleaning performance.

[This corrects the article DOI: 10.1039/D5RA01429H.].

Corrigendum to "Optimization of hydrothermal performance in industrial heat sinks with innovative perforated pin fin designs: A numerical approach" [Heliyon Volume 11, Issue 1, January 2025, Article e41496].

[This corrects the article DOI: 10.1016/j.heliyon.

Functional coatings for textiles: advancements in flame resistance, antimicrobial defense, and self-cleaning performance.

The continuous evolution of textile technologies has led to innovative functional coatings that enhance protective textiles by integrating flame retardancy, antimicrobial efficacy, and self-cleaning properties. These multifunctional coatings address the growing demand for high-performance materials in healthcare, military, and industrial applications. This study reviews advancements in coating techniques, including dip-coating, spray-coating, sol-gel processes, and layer-by-layer assembly, highlighting their effectiveness in imparting durability, thermal stability, and biological activity to textile substrates.

Chemical Valorization of Textile Waste: Advancing Sustainable Recycling for a Circular Economy.

As textile production continues to grow worldwide, managing the mounting waste generated by this industry is becoming an urgent environmental concern. Globally, over 92 million tons of textile waste are produced annually, much of which is incinerated or disposed of in landfills, contributing to greenhouse gas emissions, soil and water contamination, and ecosystem harm. This review explores how chemical and biotechnological methods, such as acid hydrolysis (achieving up to 70% glucose recovery) and enzymatic recycling (reducing energy consumption by approximately 20% compared to conventional methods), can transform textile waste into valuable resources, fostering a shift toward a circular economy that minimizes reliance on virgin materials.

ECG-based heart arrhythmia classification using feature engineering and a hybrid stacked machine learning.

A heart arrhythmia refers to a set of conditions characterized by irregular heart- beats, with an increasing mortality rate in recent years. Regular monitoring is essential for effective management, as early detection and timely treatment greatly improve survival outcomes. The electrocardiogram (ECG) remains the standard method for detecting arrhythmias, traditionally analyzed by cardiolo- gists and clinical experts.

Enhancing hydrodynamic efficiency in Autonomous Underwater Vehicles (AUVs) utilizing adjoint method and proper orthogonal decomposition.

In recent years, there has been a significant need for high-performing and efficient Autonomous Underwater Vehicles (AUVs). This is primarily because of their use in offshore mineral exploitation and oceanographic research. While there have been notable breakthroughs in applying the adjoint technique to optimize air and land vehicles, there is still a deficiency in optimizing AUVs using the adjoint method.

A sustainable approach to develop antimicrobial composite film incorporating novel Dalbergia reniformis seed-derived microcrystalline cellulose and medicinal Mikania micrantha extract in PVA.

This study presents a sustainable approach to develop antimicrobial films (AMFs) using agricultural wastes. Microcrystalline cellulose (MCC) was extracted from a novel source of Dalbergia reniformis seeds (DRS) through chemical hydrolysis, and bioactive powder from Mikania micrantha (MM) leaves was reinforced into a polyvinyl alcohol (PVA) matrix to create antimicrobial films. The morphological, antimicrobial, physical, mechanical, and thermal properties of the films were investigated.

Enhancing Typhoid Fever Diagnosis Based on Clinical Data Using a Lightweight Machine Learning Metamodel.

Typhoid fever remains a significant public health challenge, especially in developing countries where diagnostic resources are limited. Accurate and timely diagnosis is crucial for effective treatment and disease containment. Traditional diagnostic methods, while effective, can be time-consuming and resource-intensive.

Investigation of mechanical, morphological and thermal properties of waste glass powder and wood flour reinforced polypropylene composite.

The focus of this study was to investigate the potential of using waste materials like, waste glass powder and wood flour as fillers in polypropylene thermoplastic, and to assess their mechanical, morphological and thermal properties, as a means to add value to these wastes. Waste glass powder, with particle sizes of 125 μm, 63 μm, and 45 μm, was used as a filler material in the polypropylene matrix, along with wood flour particles of 250 μm in size. After identifying the optimal particle size (45 μm) sample, the WGP content was increased from 10 wt% to 15 wt% and 20 wt%.

Quantification of external disturbance forces in sliding microwire.

Due to microscale size and infinitesimal stiffness, the undesirable surface and external forces influence the mechanical behaviors of microstructures. It hinders MEMS functions, degrades reliability, and acts as a disturbance. Since MEMS functions based on microstructure mechanical behaviors, therefore, their quantification in microstructures is vital.

Towards automated recipe genre classification using semi-supervised learning.

Sharing cooking recipes is a great way to exchange culinary ideas and provide instructions for food preparation. However, categorizing raw recipes found online into appropriate food genres can be challenging due to a lack of adequate labeled data. In this study, we present a dataset named the "Assorted, Archetypal, and Annotated Two Million Extended (3A2M+) Cooking Recipe Dataset" that contains two million culinary recipes labeled in respective categories with extended named entities extracted from recipe descriptions.

Synthesis and characterization of surface modified MWCNTs reinforced PVA composite films.

Polymers have been ruling the packaging industry for decades due to their versatility, easy manufacturability, and low cost. The overuse of non-biodegradable plastics in food packaging has become a serious environmental concern. Multi-walled carbon nanotube (MWCNT) reinforced nanocomposites have exceptional electrical, thermal, and mechanical properties.

Investigating the impact of oligo-chitosan on the growth dynamics and yield traits of L. 'BRRI dhan29' under subtropical conditions.

Reducing the harmful chemical use along with obtaining potential yield in field is a worth exploring practice in rice cultivation. To mitigate the prevailing yield gap, the current study was designed to evaluate the effect of chitosan in improving growth, yield contributing characters and yield of rice. The experiment comprised eight different treatments control (no fertilizer and Chitosan) (T), conventional method (with fertilizers) (T), conventional method with foliar spray of 100 ppm chitosan solution (T), conventional method with foliar spray of 300 ppm chitosan solution (T), conventional method with foliar spray of 500 ppm chitosan solution (T), only foliar spray of 100 ppm chitosan solution (T), only foliar spray of 300 ppm chitosan solution (T), and only foliar spray of 500 ppm chitosan solution (T).

Optimization of hydrothermal performance in industrial heat sinks with innovative perforated pin fin designs: A numerical approach.

This study emphasizes the importance of optimizing pin-finned heat sinks as a means of addressing thermal engineering issues. It aims to investigate the use of perforations and unique fin designs in relation to staggered pin arrays in order to fill a gap in existing research. Three-dimensional incompressible flow simulation is performed with the Fluent software.

Triboelectric Nanogenerators for Self-Powered Degradation of Chemical Pollutants.

Environmental and human health is severely threatened by wastewater and air pollution, which contain a broad spectrum of organic and inorganic pollutants. Organic contaminants include dyes, volatile organic compounds (VOCs), medical waste, antibiotics, pesticides, and chemical warfare agents. Inorganic gases such as CO, SO, and NO are commonly found in polluted water and air.