From quantum communication fundamentals to decoherence mitigation strategies: Addressing global quantum network challenges and projected applications.

In the aftermath of unparalleled disruptive technologies, the quantum realm has become a fundamental field of research due to unrivaled computational power and super-secure communication. In addition to conventional networks, a new word in the quantum domain is quantum network. The quantum network uses quantum communication (QC) to send quantum information bits known as qubits, to predetermined destination nodes.

Experimental analysis and gene expression programming optimization of sustainable concrete containing mineral fillers.

Rapid urbanization has led to a high demand for concrete, causing a significant depletion of vital natural resources, notably river sand, which is crucial in the manufacturing process of concrete. As a result, there is a growing need for environmentally sustainable alternatives to fine aggregate in concrete. Quarry dust (QD) has evolved as a viable and ecologically friendly substitute in response to this demand.

Investigating impact of in-process cooling mediums on microstructural and mechanical properties of FSWed AA2219 T6 joints.

This study investigates the influence of various in-process cooling techniques on the microstructural characteristics and mechanical properties of the friction stir-welded AA-2219-T6 alloy. The in-process cooling methods used include normal air, dry fan, an oil-water mixture (20:80), and water. The primary objective is to determine the optimal cooling strategy for enhancing the quality of the weldment.

Development of sustainable alkali activated composite incorporated with sugarcane bagasse ash and polyvinyl alcohol fibers.

The infrastructure boom has driven up cement demand to 30 billion tons annually. To address this and promote sustainable construction, researchers are developing solutions for carbon-neutral building practices, aiming to transform industrial waste into an eco-friendly alternative. This study aims to develop and enhance the mechanical and durability properties of alkali-activated composites (AACs) by incorporating varying amounts (5, 10, 15, and 20%) of finely ground bagasse ash (GBA) and polyvinyl alcohol (PVA) fibers.

On-the-move heterogeneous face recognition in frequency and spatial domain using sparse representation.

Heterogeneity of a probe image is one of the most complex challenges faced by researchers and implementers of current surveillance systems. This is due to existence of multiple cameras working in different spectral ranges in a single surveillance setup. This paper proposes two different approaches including spatial sparse representations (SSR) and frequency sparse representation (FSR) to recognize on-the-move heterogeneous face images with database of single sample per person (SSPP).

Optimizing agricultural data security: harnessing IoT and AI with Latency Aware Accuracy Index (LAAI).

The integration of Internet of Things (IoT) and artificial intelligence (AI) technologies into modern agriculture has profound implications on data collection, management, and decision-making processes. However, ensuring the security of agricultural data has consistently posed a significant challenge. This study presents a novel evaluation metric titled Latency Aware Accuracy Index (LAAI) for the purpose of optimizing data security in the agricultural sector.

Enhancing diagnosis: ensemble deep-learning model for fracture detection using X-ray images.

Aim: Orthopedic trauma results in the injury of bone joints and tendons of the body. A radiologist reviews and monitors large numbers of radiographs daily, which can lead to the diagnostic error. Therefore, there is a need to automate the detection of bone fractures in X-ray images, particularly humerus bone fractures.

Dialysis treatment, in vitro, and anticoagulation activity of polysulfone-polyacrylamide based-blend membranes: an experimental study.

The majority of treatments are performed with polysulfone (PSf) membranes. The main issue of the PSf membrane is its lack of endothelial function, leading to various processes like platelet adhesion, protein adsorption, and thrombus formation when comes in contact with blood. The crucial aspect in the development of hemodialysis (HD) membrane materials is a biocompatibility factor.

Microstructural and mechanical characterization of electron beam welded low-nickel nitrogen-strengthened austenitic stainless steel.

In this paper, the Electron Beam Welding (EBW) was used to join thin plates of low-nickel nitrogen-strengthened austenitic stainless steel (LNiASS), a material valued for its superior mechanical properties and cost-effectiveness. Traditional welding techniques often lead to issues such as hot cracking, reduced toughness, and undesirable microstructures. The objective was to address these challenges using EB·W.

Development of machine learning models for forecasting the strength of resilient modulus of subgrade soil: genetic and artificial neural network approaches.

Accurately predicting the Modulus of Resilience (M) of subgrade soils, which exhibit non-linear stress-strain behaviors, is crucial for effective soil assessment. Traditional laboratory techniques for determining M are often costly and time-consuming. This study explores the efficacy of Genetic Programming (GEP), Multi-Expression Programming (MEP), and Artificial Neural Networks (ANN) in forecasting MR using 2813 data records while considering six key parameters.

Soft computing models for prediction of bentonite plastic concrete strength.

Bentonite plastic concrete (BPC) is extensively used in the construction of water-tight structures like cut-off walls in dams, etc., because it offers high plasticity, improved workability, and homogeneity. Also, bentonite is added to concrete mixes for the adsorption of toxic metals.

Non-linear finite element analysis of SFRC beam-column joints under cyclic loading: enhancing ductility and structural integrity.

Brittle shear failure of beam-column joints, especially during seismic events poses a significant threat to structural integrity. This study investigates the potential of steel fiber reinforced concrete (SFRC) in the joint core to enhance ductility and overcome construction challenges associated with traditional reinforcement. A non-linear finite element analysis (NLFEA) using ABAQUS software was conducted to simulate the behavior of SFRC beam-column joints subjected to cyclic loading.

Glycolipids biosurfactants production using low-cost substrates for environmental remediation: progress, challenges, and future prospects.

The production of renewable materials from alternative sources is becoming increasingly important to reduce the detrimental environmental effects of their non-renewable counterparts and natural resources, while making them more economical and sustainable. Chemical surfactants, which are highly toxic and non-biodegradable, are used in a wide range of industrial and environmental applications harming humans, animals, plants, and other entities. Chemical surfactants can be substituted with biosurfactants (BS), which are produced by microorganisms like bacteria, fungi, and yeast.

Development of innovative alkali activated paste reinforced with polyethylene fibers for concrete crack repair.

Concrete structures are susceptible to cracking, which can compromise their integrity and durability. Repairing them with ordinary Portland cement (OPC) paste causes shrinkage cracks to appear in the repaired surface. Alkali-activated binders offer a promising solution for repairing such cracks.

2D Materials in Advanced Electronic Biosensors for Point-of-Care Devices.

Since two-dimensionalal (2D) materials have distinct chemical and physical properties, they are widely used in various sectors of modern technologies. In the domain of diagnostic biodevices, particularly for point-of-care (PoC) biomedical diagnostics, 2D-based field-effect transistor biosensors (bio-FETs) demonstrate substantial potential. Here, in this review article, the operational mechanisms and detection capabilities of biosensing devices utilizing graphene, transition metal dichalcogenides (TMDCs), black phosphorus, and other 2D materials are addressed in detail.

Evaluation of machine learning models for predicting TiO photocatalytic degradation of air contaminants.

The escalation of global urbanization and industrial expansion has resulted in an increase in the emission of harmful substances into the atmosphere. Evaluating the effectiveness of titanium dioxide (TiO) in photocatalytic degradation through traditional methods is resource-intensive and complex due to the detailed photocatalyst structures and the wide range of contaminants. Therefore in this study, recent advancements in machine learning (ML) are used to offer data-driven approach using thirteen machine learning techniques namely XG Boost (XGB), decision tree (DT), lasso Regression (LR2), support vector regression (SVR), adaBoost (AB), voting Regressor (VR), CatBoost (CB), K-Nearest Neighbors (KNN), gradient boost (GB), random Forest (RF), artificial neural network (ANN), ridge regression (RR), linear regression (LR1) to address the problem of estimation of TiO photocatalytic degradation rate of air contaminants.

Enhancing gain and isolation of a quad-element MIMO antenna array design for 5G sub-6 GHz applications assisted with characteristic mode analysis.

This paper presents a novel quad-element array with multiple inputs and multiple outputs (MIMO) designed for 5th generation sub-6 GHz applications. The MIMO system achieves a wide impedance bandwidth, high gain, and high isolation among its components, representing significant advancements in sub-6 GHz antenna applications. The single element, an elliptical resonator with a circular slot, is fed by a 50 Ω microstrip feedline, achieves a broad characteristic bandwidth from 3.

High solid-state photoluminescence quantum yield of carbon-dot-derived molecular fluorophores for light-emitting devices.

Several recent studies of carbon dots (CDs) synthesized by bottom-up methods under mild conditions have reported the presence of organic molecular fluorophores in CD dispersions. These fluorophores have a tendency to aggregate, and their properties strongly depend on whether they are present in the form of discrete molecules or aggregates. The aggregation becomes more prominent in the solid state, which motivates the study of the properties of the fluorophores associated with CDs in the solid state.

Development of Biocompatible Electrospun PHBV-PLLA Polymeric Bilayer Composite Membranes for Skin Tissue Engineering Applications.

Bilayer electrospun fibers aimed to be used for skin tissue engineering applications were fabricated for enhanced cell attachment and proliferation. Different ratios of PHBV-PLLA (70:30, 80:20, and 90:10 /) blends were electrospun on previously formed electrospun PHBV membranes to produce their bilayers. The fabricated electrospun membranes were characterized with FTIR, which conformed to the characteristic peaks assigned for both PHBV and PLLA.

An Artificial Intelligence model for implant segmentation on periapical radiographs.

Objective: To segment dental implants on PA radiographs using a Deep Learning (DL) algorithm. To compare the performance of the algorithm relative to ground truth determined by the human annotator.

Methodology: Three hundred PA radiographs were retrieved from the radiographic database and consequently annotated to label implants as well as teeth on the LabelMe annotation software.

Elucidating the performance of hexamethylene tetra-amine interlinked bimetallic NiCo-MOF for efficient electrochemical hydrogen and oxygen evolution.

Bimetallic metal-organic frameworks (MOFs) play a significant role in the electrocatalysis of water due to their large surface area and availability of increased numbers of pores. For the inaugural time, we examine the effectiveness of a hexamethylene tetra-amine (HMT)-induced 3D NiCo-MOF-based nanostructure as a potent bifunctional electrocatalyst with superior performance for overall water splitting in alkaline environments. The structural, morphological, and electrochemical properties of the as-synthesized bifunctional catalyst were examined thoroughly before analyzing its behavior towards electrochemical water splitting.