Optimization of eco-friendly concrete with recycled coarse aggregates and rubber particles as sustainable industrial byproducts for construction practices.

In this technology era, sustainable construction practices have become quite imperative. The exploration of alternative materials to reduce the environmental footprint is of paramount importance. This research paper delves into an exhaustive investigation concerning the utilization of recycled coarse aggregates (RCA) and rubber particles (RP) in concrete.

Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model.

This work aims to provide an effective hybrid beam forming method with Dual-Deep-Network to overcome overhead for mm-wave massive MIMO systems. In this paper, a Dual-Deep-Network technique is described for the extraction of statistical structures from a hybrid beam forming model based on mmWave logics, as well as training logic for the network map functions. The proposed approach of DDN is trained with proper data sequences used for communication and the training phase is conducted with the norms of numerous channel variants.

A mathematical model for investigation of dry band location on 22 kV bushing with and without RTV coating: Experimental study.

As different pollutants are deposited on the high voltage bushings, a dry band forms, which causes a flashover. The bushing's contaminated layer will weaken its insulation and have an impact on its electrical characteristics. The performance of bushings in dry band conditions of various lengths was investigated in this proposed piece of work, and a dynamic arc model is presented for the arc process in polluted bushings.

A comprehensive review of critical analysis of biodegradable waste PCM for thermal energy storage systems using machine learning and deep learning to predict dynamic behavior.

This article explores the use of phase change materials (PCMs) derived from waste, in energy storage systems. It emphasizes the potential of these PCMs in addressing concerns related to fossil fuel usage and environmental impact. This article also highlights the aspects of these PCMs including reduced reliance on renewable resources minimized greenhouse gas emissions and waste reduction.

Insitu synthesis of Al- MgAlO composites and parametric optimization of tribological characteristics.

In this research, multiobjective optimization of tribological characteristics of Al-4Mg/in-situ MgAlO composites fabricated via ultrasonic cavitation treatment assisted stir casting technique was carried out. Al-4Mg alloy dispersed with 0.5, 1 and 2 wt% in-situ MgAlO was prepared and the microstructural and mechanical characterisation of the same has been carried out.

Optimizing laser cladding powder injection parameters to shape bioactive glass nano-coated zirconium oxide for biomedical application.

Human body is highly sensitive and repairing often incurs pain and expenses. Strength of the materials degraded by poor joint (either weld or link). New material technology is proposed many biomaterials for repairing bone and tissue and also many bio-implantation applications.

The impact of 180° return bend inclination on pressure drop characteristics and phase distribution during oil-water flow.

The present work aims to capture the influence of the inclination of the return bend on flow patterns and pressure drop during oil-water flow. The experiments were carried out for different inclinations (0°, 15°, 30°, and 45°) of return bend for various superficial velocity combinations of oil (kerosene) and water ranging from 0.07 to 0.

Advances in functional lipid nanoparticles: from drug delivery platforms to clinical applications.

Since Doxil's first clinical approval in 1995, lipid nanoparticles have garnered great interest and shown exceptional therapeutic efficacy. It is clear from the licensure of two RNA treatments and the mRNA-COVID-19 vaccination that lipid nanoparticles have immense potential for delivering nucleic acids. The review begins with a list of lipid nanoparticle types, such as liposomes and solid lipid nanoparticles.

Marine-derived κ-carrageenan-coated zinc oxide nanoparticles for targeted drug delivery and apoptosis induction in oral cancer.

Background: Kappaphycus alvarezii, a marine red algae species, has gained significant attention in recent years due to its versatile bioactive compounds. Among these, κ-carrageenan (CR), a sulfated polysaccharide, exhibits remarkable antimicrobial properties. This study emphasizes the synergism attained by functionalizing zinc oxide nanoparticles (ZnO NPs) with CR, thereby enhancing its antimicrobial efficacy and target specificity against dental pathogens.

Optimizing the selection of natural fibre reinforcement and polymer matrix for plastic composite using LS-SVM technique.

The manufacturing sector is paying close attention to plastic matrix composites (PMCs) reinforced with natural fibres for improving their products. Due to the fact that PMC reinforced with naturally occurring fibres is more affordable and has superior mechanical qualities. Based on the application material requirements, An important step in the production of PMC is choosing the right natural fibres for reinforcing and determining how much of each.

Unlocking Precision Medicine for Prognosis of Chronic Kidney Disease Using Machine Learning.

Chronic kidney disease (CKD) is a significant global health challenge that requires timely detection and accurate prognosis for effective treatment and management. The application of machine learning (ML) algorithms for CKD detection and prediction holds promising potential for improving patient outcomes. By incorporating key features which contribute to CKD, these algorithms enhance our ability to identify high-risk individuals and initiate timely interventions.

Experimental investigation of HPO activated papaya peels for methylene blue dye removal from aqueous solution: Evaluation on optimization, kinetics, isotherm, thermodynamics, and reusability studies.

This investigation is centered on the effectiveness of methylene blue (MB), a cationic dye, adsorbed from an aqueous media by HPO activated papaya skin/peels (PS), with initial pH (2-10), contact time (30-180 min), MB dye concentration (varying from 10 to 50 mg/L), and MB dose (0.1-0.5 gm).

Designing face resemblance technique using near set theory under varying facial features.

Near sets (also called Descriptively Near Sets) classify nonempty sets of objects based on object feature values. The Near Set Theory provides a framework for measuring the similarity of objects based on features that describe them in much the same way humans perceive the similarity of objects. This paper presents a novel approach for face recognition using Near Set Theory that takes into account variations in facial features due to varying facial expressions, and facial plastic surgery.

A Comparative Study on Predication of Appropriate Mechanical Ventilation Mode through Machine Learning Approach.

Ventilation mode is one of the most crucial ventilator settings, selected and set by knowledgeable critical care therapists in a critical care unit. The application of a particular ventilation mode must be patient-specific and patient-interactive. The main aim of this study is to provide a detailed outline regarding ventilation mode settings and determine the best machine learning method to create a deployable model for the appropriate selection of ventilation mode on a per breath basis.

Future forecasting prediction of Covid-19 using hybrid deep learning algorithm.

Due the quick spread of coronavirus disease 2019 (COVID-19), identification of that disease, prediction of mortality rate and recovery rate are considered as one of the critical challenges in the whole world. The occurrence of COVID-19 dissemination beyond the world is analyzed in this research and an artificial-intelligence (AI) based deep learning algorithm is suggested to detect positive cases of COVID19 patients, mortality rate and recovery rate using real-world datasets. Initially, the unwanted data like prepositions, links, hashtags etc.

Experimental Evaluation of Industrial Mushroom Waste Substrate Using Hybrid Mechanism of Vermicomposting and Effective Microorganisms.

Mushroom waste substrates are highly resistant lignocellulosic wastes that are commercially produced by industries after harvesting. These wastes produce large environmental challenges regarding disposal and, thus, require treatment facilities. In the present article, the effect of Eisenia-fetida-based vermicomposting and an effective microorganism solution on the mushroom waste substrate were investigated using four different composting mixtures: mushroom waste [MW] substrate composting with effective microorganisms [MW+EM], raw mushroom waste [RWM] substrate composting with effective microorganisms [RMW+EM], mushroom waste substrate composting with vermicomposting and effective microorganisms [MW+V+EM], and raw mushroom waste substrate composting with vermicomposting and effective microorganisms [RWM+V+EM].

Performance and exhaust emission characteristics investigation of compression ignition engine fuelled with microalgae biodiesel and its diesel blends.

Biofuels extracted from plant biomass can be used as fuel in CI engines to lower a hazardous atmospheric pollutant and mitigate climate risks. Furthermore, its implementation is hampered by inevitable obstacles such as feedstocks and the crop area required for their cultivation, leading to a lack of agricultural land for the expansion of food yields. Despite this, microalgae have been discovered to be the most competent and unwavering source of biodiesel due to their distinguishing characteristics of being non-eatable and requiring no cropland for cultivation.

Fractional chaotic maps based short signature scheme under human-centered IoT environments.

Introduction: The Internet of Things (IoT) comprises of various smart devices for the sharing of sensed data through online services. People will be directly contacted to check their health parameters and the reports will be collected centrally through smart devices. The requirement is protection of messages during the exchange of data between sender and receiver in order to tackle human malicious attacks.

Synthesis and Characterization of Mechanical Properties and Wire Cut EDM Process Parameters Analysis in AZ61 Magnesium Alloy + BC + SiC.

Wire Cut Electric Discharge Machining (WCEDM) is a novel method for machining different materials with application of electrical energy by the movement of wire electrode. For this work, an AZ61 magnesium alloy with reinforcement of boron carbide and silicon carbide in different percentage levels was used and a plate was formed through stir casting technique. The process parameters of the stir casting process are namely reinforcement %, stirring speed, time of stirring, and process temperature.

Design and simulation of AI-based low-cost mechanical ventilator: An approach.

In this situation of COVID 19, many people are being exposed to coronavirus, resulting in difficulty in breathing and a drop in oxygen percentage of blood. A mechanical ventilator is playing a vital role in tackling this situation but the ventilation process is neither readily available nor affordable. The idea behind this work is to propose a simplified design of a mechanical ventilator to reduce the cost and automate the Mechanical ventilation process.

An Efficient Mobile-Healthcare Emergency Framework.

Mobile technologies are capable of offering individual level health care services to users. Mobile Healthcare (m-Healthcare) frameworks, which feature smartphone (SP) utilizations of ubiquitous computing made possible by applying wireless Body Sensor Networks (BSNs), have been introduced recently to provide SP clients with health condition monitoring and access to medical attention when necessary. However, in a vulnerable m-Healthcare framework, clients' personal info and sensitive data can easily be poached by intruders or any malicious party, causing serious security problems and confidentiality issues.