Emerging nanotechnologies in wound care: The role of metal and polymeric nanocomposites in enhancing healing and combating infections.

Chronic wounds are a foremost cause of death, affecting 6.5 million people annually. Traditional treatments, such as metal-based formulations and biomaterials, are ineffective due to their toxicity and the rising incidence of chronic wound cases, necessitating the advancement of new therapies for efficient wound healing.

Effects of Deposition Time and Phosphorus Concentration on the Structural, Morphological, and Magnetic Properties of Galvanostatically Electrodeposited NiFeP Thin Films.

The influence of varying parameters such as current density (5-20 mA/cm), bath temperature (30-90 °C), deposition time (15-60 min), and phosphorus concentration (0.1-0.4 M) on the successful synthesis of NiFeP thin films using the electrodeposition method was examined.

Enhancing privacy in IoT-based healthcare using provable partitioned secure blockchain principle and encryption.

The Internet of Things (IoT) has attained significant interest recently, particularly in the medical field due to the quick development of IoT devices. Medical related data contains a significant volume of personal information, and it is crucial to maintain privacy. As medical information becomes increasingly electronic in the era of big data, securely and accurately storing medical information is critical.

Density of States Proportion on Electron-Hole Symmetrical-to-Asymmetrical Transport in Free-Electron Solids to Interacting Fermionic Systems: A Perspective of Entropy-Ruled Method.

Conceptualization, theory/method development, and implementation are always of great importance and interesting tasks to explore a new dimension in science and technology, which is highly solicited for various functional-driven potential applications (e.g., electronic devices, charge storage devices).

Compressive strength modelling of cenosphere and copper slag-based geopolymer concrete using deep learning model.

Geopolymer concrete (GPC) is an eco-friendly alternative for conventional concrete. It exploits industrial by-products in production to reduce the environmental impact and improve sustainability. This study focuses on envisaging the 28-day compressive strength of cenosphere-based geopolymer concrete incorporating copper slag using Artificial Neural Networks (ANN).

Redefining IoT networks for improving energy and memory efficiency through compressive sensing paradigm.

Wireless Sensor Networks (WSNs) have a wide range of applications across multiple platforms within the Internet of Things (IoT), yet face serious challenges like constrained resources, energy, and memory limitations. Current techniques often struggle to efficiently manage energy consumption, resulting in faster battery drain and reduced network lifetimes. Additionally, memory limitations in sensor nodes can affect data storage, further reducing the productivity and scalability of WSNs.

Optimization of tribo-mechanical properties of kenaf/jute-SiC hybrid composites using integrated grey-fuzzy approach.

An increasing need for wear-resistant hybrid materials has prompted researchers to develop alternative materials that comprise different reinforcements and fillers. In recent studies, the combination of natural fibers and ceramic fillers has resulted in hybrid composites with improved tribological characteristics for automotive and aircraft applications. Even though natural fibers have some disadvantages, the combined effect of natural fibers and ceramics with suitable multi-response optimization techniques can overcome the limitations and provide a composite with enhanced mechanical and tribological properties at minimal cost.

An overview of thermosensitive hydrogel based nanocomposites for high temperature and fire resistance applications.

The modern world demands sophisticated materials by modifying every aspect of each atom for further acceleration in any specific domain. Fire resistant materials are also the most researched topic of materialists as this open avenue for various fire-related applications. Development of sustainable materials might reduce the harmful environmental effects of the synthetic materials.

Advanced finite segmentation model with hybrid classifier learning for high-precision brain tumor delineation in PET imaging.

Brain tumor segmentation plays a crucial role in clinical diagnostics and treatment planning, yet accurate and efficient segmentation remains a significant challenge due to complex tumor structures and variations in imaging modalities. Multi-feature selection and region classification depend on continuous homogeneous features to improve the precision of tumor detection. This classification is required to suppress the discreteness across various extraction rates to consent to the smallest segmentation region that is infected.

Secure bio-inspired optimization with intrusion aware on-demand routing in MANETs.

Mobile Ad-Hoc Networks (MANETs) are specialized networks that operate in a decentralized manner. As it has no centralized control over communication, the overall network is generally vulnerable to various security threats such as Blackhole, Wormhole, Flooding and Unauthorized access. Although several studies have analysed these issues, ensuring security in MANETs remains a significant challenge.

CRITIC-EDAS Approach for Evaluating Mechanical Properties of Flax/Vetiver/MFF Hybrid Composites.

This study investigates the mechanical properties and optimization of hybrid composites composed of flax, vetiver, and mahogany fruit fillers (MFFs) using epoxy resin as the matrix material. Nine distinct composite configurations were fabricated using different MFF concentrations (0, 5, and 10 wt.%) to evaluate their influence on tensile strength, flexural strength, and impact resistance.

Modelling, implementation and analysis of double-side slotted axial flux PMGs suitable to small-scale wind energy conversion systems.

In the contemporary landscape of wind energy, low-speed wind turbine technology has gained prominence for its ability to harness continuous power even in conditions of minimal wind velocity. Effective design methodologies are crucial for optimizing the conversion of low-speed wind energy, particularly concerning the Permanent Magnet Generator (PMG) component. Radial Flux Permanent Magnet Generators (RFPMGs) have traditionally been utilized in low-speed wind turbines.

Cross-correlation-based signal pruning method (CCSPM) for effective signal distortion reduction in massive MIMO communications.

Massive Multiple-Input-Multiple-Output (MIMO) ensures spectral and energy improvements for a large number of communicating terminals in the base station. Signal distortion is observed due to overlapping channels that are adaptable to the receiving terminal's radiation patterns. For addressing this specific issue, a Cross Correlation-based Signal Pruning Method (CCSPM) is introduced.

Role of shielding gas in tailoring microstructure and anisotropy in wire arc additive manufactured Inconel 686.

This study examines the effect of shielding gas composition on the microstructure and mechanical properties of Inconel 686 components fabricated via wire arc additive manufacturing (WAAM). Thin-walled structures were produced using pure Argon (Ar), a 50% Helium-Argon mixture (Ar + 50% He), and pure Helium (He). Cooling rates were highest with pure He and lowest with pure Ar.

A hybrid Spatial Ant Lion optimization and utilitarian data transmission approach for intelligent optimization for energy-efficient wireless sensor networks.

Numerous researches on wireless sensor networks was conducted to design proficient algorithms not only to minimalize the exploitation of energy and delay, but also to increase the network lifetime and throughput. Optimization techniques will provide the proper balance among the parameters considered and help us to achieve the target of lifetime prolongation in wireless sensor networks. The proposed scheme comprises of two phases namely optimal cluster head selection and an effective data transmission phase.

Quadratic mixed convection of Maxwell-Buongiorno nanofluid over cubic stratified surface incorporating cross diffusion effects and solar radiation.

Cubic stratification dramatically enhances thermal and mass transport in quadratic mixed convection, which is advantageous for electronics cooling, biomedical technology, and power plants. Nanofluids are essential to the development of next-generation cooling and environmental management solutions because of their exceptional thermal characteristics. Motivated by such impactful applications in thermal and engineering systems, this work uses the Buongiorno model to examine heat and mass transfer in Maxwell nanofluids over a vertically extended permeable surface under Darcy-Forchheimer porous flow situations.

Anion Exchange Membranes with Tuned Hydrophilic-Hydrophobic Phase Separation for Efficient Ion Transportation.

The development of high-performance anion exchange membranes (AEMs) remains a major challenge in commercializing alkaline fuel cells. Significant efforts have been directed toward enhancing the ionic conductivity, mechanical strength, and alkaline stability of AEMs. Among various strategies, modifying commercially available polymers has emerged as an effective and straightforward approach.

Additive Manufacturing of Metal-Infilled Polylactic Acid-Based Sustainable Biocomposites-A Review of Methods, Properties and Applications Abetted with Patent Landscape Analysis.

Innovations in additive manufacturing (AM) methods represent a significant advancement in manufacturing technology, opening new avenues for creating objects in various shapes and sizes. Fused deposition modeling (FDM) is a specialized AM technique in which computers build layers upon each other to form a complete 3D object. The feasibility of producing metal parts using these methods has been thoroughly analyzed, but the design process has yet to catch up with manufacturing capabilities.

Performance improvement of DC motor control system using PID controller with Kookaburra and Red Panda optimization algorithm.

In recent years, DC motors have found widespread use in numerous industrial applications. Precise speed control is required and would be achieved via the implementation of a Proportional-Integral-Derivative (PID) controller in the system. The tuning of controller gain has received significant attention, and conventional metaheuristic algorithms have been utilized for tuning.

Federated stochastic gradient averaging ring homomorphism based learning for secure data aggregation in WSN.

Nodes in a wireless sensor network (WSN) are usually contrived by hardware and environmental circumstances and high system security susceptibilities. This certainty necessitates distinctive prerequisites for designing unique network protocol, security evaluation prototypes and energy efficient techniques. Data aggregation is an efficient energy saving mechanism that eliminates unnecessary information from the aggregated data, therefore minimizing the network energy consumption significantly.

Experimental investigation of flexible eight-port asymmetric fed MIMO antenna with narrow-super-widebandn-s characteristics for future applications including internet of things.

In this work, an eight-port MIMOn-s antenna with dual-band operation is presented. The proposed work involves several wireless applications with FR1 and FR2 millimeter-wave bands. Also, a need for conformal antenna with capability of reduced SAR can cater the need for applications in flexible electronics.

A super resolution generative adversarial networks and partition-based adaptive filtering technique for detect and remove flickers in digital color images.

Eliminating flickering from digital images captured by cameras equipped with a rolling shutter is of paramount importance in computer vision applications. The ripple effect observed in an individual image is a consequence of the non-synchronized exposure of rolling shutters utilized in CMOS sensor-based cameras. To date, there have been only a limited number of studies focusing on the mitigation of flickering in single images.

Decalcify cardiac CT: unveiling clearer images with deep convolutional neural networks.

Decalcification is crucial in enhancing the diagnostic accuracy and interpretability of cardiac CT images, particularly in cardiovascular imaging. Calcification in the coronary arteries and cardiac structures can significantly impact the quality of the images and hinder precise diagnostics. This study introduces a novel approach, Hybrid Models for Decalcify Cardiac CT (HMDC), aimed at enhancing the clarity of cardiac CT images through effective decalcification.

Exploring Antibacterial, Antioxidant, Cytotoxic Potential of Oscillatoria sp.-Derived Metabolites and Their Molecular Docking with Estrogen Receptor-α.

Anthropogenic activities have led to the accumulation of carcinogenic toxicants in the food chain, posing severe risks to both human and animal health. Bioactive molecules derived from terrestrial and aquatic systems offer promising solutions to various health challenges. Presently, the cyanobacterial metabolites from ethyl acetate extract of Oscillatoria sp.

Analysis of thrust force generation during the drilling of natural fiber based hybrid composite.

In this study, thrust force generation during drilling in natural fiber-reinforced epoxy has been investigated. Three natural fibers Abaca (A), Hemp (H) and Jute (J) have been utilized. Four different point angles of the twisted drill tools have been employed: 90°, 100°, 105° and 118°.