Effect of very low-carbohydrate high-fat diet and high-intensity interval training on mental health-related indicators in individuals with excessive weight or obesity.

Very low carbohydrate high fat (VLCHF) diet and high-intensity interval training (HIIT) are widely utilized for weight reduction and cardiorespiratory fitness improvement, respectively. To assess the acceptability of these approaches, it is essential to examine mental health-related indicators. This secondary analysis of a randomized controlled trial investigated the isolated and synergistic effects of VLCHF and HIIT on mental health-related indicators in individuals with excessive weight or obesity.

Development of rare earth element-based hybrid aluminium composites using stir casting process.

Aerospace and marine industries are constantly in search of materials that can provide good strength and durability while also being lightweight. Aluminium composites with adequate reinforcements have been proven to be effective in achieving incredible mechanical properties while also maintaining a good strength to weight ratio. Numerous studies have been done to study the various possibilities of matrix reinforcement combinations in aluminium composites.

Discovery of Lipoxygenase-Like Materials for Inducing Ferroptosis.

Recent research has highlighted the pivotal role of lipoxygenases in modulating ferroptosis and immune responses by catalyzing the generation of lipid peroxides. However, the limitations associated with protein enzymes, such as poor stability, low bioavailability, and high production costs, have motivated researchers to explore biomimetic materials with lipoxygenase-like activity. Here, we report the discovery of lipoxygenase-like two-dimensional (2D) MoSnanosheets capable of catalyzing lipid peroxidation and inducing ferroptosis.

Magnetically Propelled Microrobots toward Photosynthesis of Green Ammonia from Nitrates.

Ammonia (NH₃) production is a critical industrial process, as ammonia is a key component in fertilizers, essential for global agriculture and food production. However, the current method of synthesizing ammonia, the Haber-Bosch process, is highly energy-intensive, and relies on fossil fuels, contributing substantially to greenhouse gas emissions. Moreover, the centralized nature of the Haber-Bosch process limits its accessibility in remote or resource-limited areas.

Wear and Dynamic Mechanical Analysis (DMA) of Samples Produced via Fused Deposition Modelling (FDM) 3D Printing Method.

In recent years, plastic and metal 3D printing has experienced massive development in the professional and hobby spheres, especially for rapid prototyping, reverse engineering, maintenance and quick repairs. However, this technology is limited by a number of factors, with the most common being the cost and availability of the technology but also the lack of information on material properties. This study focuses on investigating the material properties of PLA, PETG, HIPS, PA, ABS and ASA in order to elucidate their behavior in terms of wear and thermal resistance.

On the similar spectral manifestations of protonic and hydridic hydrogen bonds despite their different origin.

Previously studied complexes with protonic and hydridic hydrogen bonds exhibit significant similarities. The present study provides a detailed investigation of the structure, stabilization, electronic properties, and spectral characteristics of protonic and hydridic hydrogen bonds using low-temperature infrared (IR) spectroscopy and computational methods. Complexes of pentafluorobenzene with ammonia (C₆F₅H⋯NH₃) and triethylgermane with trifluoroiodomethane (Et₃GeH⋯ICF₃) were analyzed using both experimental and computational tools.

2D Nitrogen-Doped Graphene Materials for Noble Gas Separation.

Noble gases, notably xenon, play a pivotal role in diverse high-tech applications. However, manufacturing xenon is an inherently challenging task, due to its unique properties and trace abundance in the Earth's atmosphere. Consequently, there is a pressing need for the development of efficient methods for the separation of noble gases.

An AI-driven approach for modeling the compressive strength of sustainable concrete incorporating waste marble as an industrial by-product.

A key goal of environmental policies and circular economy strategies in the construction sector is to convert demolition and industrial wastes into reusable materials. As an industrial by-product, Waste marble (WM), has the potential to replace cement and fine aggregate in concrete which helps with saving natural resources and reducing environmental harm. While many studies have so far investigated the effect of WM on compressive strength (CS), it is undeniable that conducting experimental activities requires time, money, and re-testing with changing materials and conditions.

Advanced optimal control approaches for immune boosting and clinical treatment to enhance dengue viremia models using ABC fractional-order analysis.

Introduction: This work focuses on the Dengue-viremia ABC (Atangana-Baleanu Caputo) fractional-order differential equations, accounting for both symptomatic and asymptomatic infected cases. Symptomatic cases are characterized by higher viremia levels, whereas asymptomatic cases exhibit lower viremia levels. The fractional-order model highlights memory effects and other advantages over traditional models, offering a more comprehensive representation of dengue dynamics.

Characterisation of AZ31/TiC composites fabricated via ultrasonic vibration assisted friction stir processing.

In this study, the effect of ultrasonic vibration during Friction Stir Vibration Processing (FSVP) on the microstructure and mechanical behaviour of AZ31/TiC surface composites was investigated. Specifically, Titanium Carbide (TiC) particles were introduced as a reinforcement (15 vol%) into the magnesium alloy AZ31 using both Friction Stir Processing (FSP) and FSVP. Comprehensive examinations were carried out to analyse the microstructure, hardness, and tensile behaviour of the resulting composites.

Sustainable sentiment analysis on E-commerce platforms using a weighted parallel hybrid deep learning approach for smart cities applications.

Sentiment analysis (SA) of several user evaluations on e-commerce platforms can be used to increase customer happiness. This method automatically extracts and identifies subjective data from product evaluations using natural language processing (NLP) and machine learning (ML) methods. These statistics may eventually reveal information on the favourable, neutral, or negative attitudes of the consumer base.

Prediction of power conversion efficiency parameter of inverted organic solar cells using artificial intelligence techniques.

Organic photovoltaic (OPV) cells are at the forefront of sustainable energy generation due to their lightness, flexibility, and low production costs. These characteristics make OPVs a promising solution for achieving sustainable development goals. However, predicting their lifetime remains challenging task due to complex interactions between internal factors such as material degradation, interface stability, and morphological changes, and external factors like environmental conditions, mechanical stress, and encapsulation quality.

Experimental validation of effective zebra optimization algorithm-based MPPT under partial shading conditions in photovoltaic systems.

This study introduces a novel approach for analyzing photovoltaic (PV) systems that employ block lookup tables for speedy and efficient simulation. It introduces an innovative method for tracking the Global Maximum Power Point (GMPP) by utilizing Zebra Optimization Algorithm (ZOA). The suggested method was carefully evaluated under difficult Partial Shading Conditions (PSCs) and Dynamic Shading Conditions (DSCs) to determine its global and local search capability.

Taguchi optimization of Wire EDM process parameters for machining LM5 aluminium alloy.

LM5 alloy is suitable for metal castings for marine and aesthetic uses due to its admirable resistance to corrosion. In order to make intricate shapes in the LM5 alloy, this study intends to assess the impact of Wire Electric Discharge Machining process variables, like Pulse on Time (Ton), Pulse off Time (Toff), Gap Voltage (GV) and Wire Feed (WF) on responses like Material Removal Rate (MRR), Surface Roughness (SR), and Kerf Width (Kw). The LM5 aluminium alloy plate was produced through stir casting process.

Overlapping community detection in weighted networks via hierarchical clustering.

In real-world networks, community structures often appear as tightly connected clusters of nodes, with recent studies suggesting a hierarchical organization where larger groups subdivide into smaller ones across different levels. This hierarchical structure is particularly complex in trade networks, where actors typically belong to multiple communities due to diverse business relationships and contracts. To address this complexity, we present a novel algorithm for detecting hierarchical structures of overlapping communities in weighted networks, focusing on the interdependency between internal and external quality metrics for evaluating the detected communities.

Spin and orbital magnetic moments of UTe induced by the external magnetic field.

Correlated band theory implemented as a combination of the relativistic density functional theory with exact diagonalization [DFT+U(ED)] of the Anderson impurity term with Coulomb repulsion U in the 5f shell is applied to the magnetic field polarized state of [Formula: see text]. We demonstrate that the DFT+U(ED) approach provides a good agreement with very recent x-ray absorbtion near edge structure (XANES) and x-ray magnetic circular dichroism (XMCD) experiments. The branching ratio for the [Formula: see text] edge transitions of uranium, and the valence spin-orbit interaction per hole were evaluated in a perfect agreement with the XANES.

Active Quantum Biomaterials-Enhanced Microrobots for Food Safety.

Timely disruptive tools for the detection of pathogens in foods are needed to face global health and economic challenges. Herein, the utilization of quantum biomaterials-enhanced microrobots (QBEMRs) as autonomous mobile sensors designed for the precise detection of endotoxins originating from Salmonella enterica (S. enterica) as an indicator species for food-borne contamination globally is presented.

2D-convolutional neural network based fault detection and classification of transmission lines using scalogram images.

The reliable operation of power transmission systems is essential for maintaining the stability and efficiency of the electrical grid. Rapid and accurate detection of faults in transmission lines is crucial for minimizing downtime and preventing cascading failures. This research presents a novel approach to fault detection and classification in transmission lines employing 2D Convolutional Neural Networks (2D-CNN).

Pulling the Rug Out from Under: Biomechanical Microenvironment Remodeling for Induction of Hepatic Stellate Cell Quiescence.

Hepatic fibrosis progresses concomitantly with a variety of biomechanical alternations, especially increased liver stiffness. These biomechanical alterations have long been considered as pathological consequences. Recently, growing evidence proposes that these alternations result in the fibrotic biomechanical microenvironment, which drives the activation of hepatic stellate cells (HSCs).