Energy-exergy and environ-economic (4E) analysis of heat storage-based single-slope solar stills integrated with solar air heater.

The energy-exergy and environ-economic (4E) analysis was conducted on a solar still with and without a hybrid thermal energy storage system (TESS) and a solar air heater. The proposed solar still was modified by integrating a rectangular aluminium box filled with paraffin wax and black gravel as the TESS and coupled with a solar air heater. Paraffin wax was selected due to its widespread availability and proven effectiveness in accelerating desalination, improving process uniformity, and maintaining optimal temperature levels.

Efficient Explainable Models for Alzheimer's Disease Classification with Feature Selection and Data Balancing Approach Using Ensemble Learning.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder and is the most common cause of dementia. Early diagnosis of Alzheimer's disease is critical for better management and treatment outcomes, but it remains a challenging task due to the complex nature of the disease. Clinical data, including a range of cognitive, functional, and demographic variables, play a crucial role in Alzheimer's disease classification.

Beyond templates: exploring uncharted territory in anisotropic gold nanostructure-oligomer composites synthesis and electrocatalytic performance towards environmental pollutants.

The synthesis of polymer/oligomer-stabilized metal nanostructures (MNS) opens up a wide range of possibilities, from fundamental materials science to practical applications in domains such as medicine, catalysis, sensing, and energy. Because of the versatility of this synthetic approach, it is a dynamic and ever-changing field of study. These polymers/oligomers have precise control over the nucleation and growth kinetics, allowing the production of mono-disperse MNS with well-defined properties.

Bismuth-based nanoparticles and nanocomposites: synthesis and applications.

In the vast landscape of materials science, bismuth emerges as a compelling element with unique properties and diverse applications. Its intriguing characteristics and advancements in nanotechnology have propelled bismuth-based nanoparticles to the forefront of scientific exploration, promising breakthroughs in various disciplines. This comprehensive review explores diverse methods for synthesizing bismuth-based nanoparticles and nanocomposites, ranging from conventional approaches such as hydrothermal and sol-gel to innovative techniques such as microwave-assisted, microemulsion, and green synthesis.

Waste to Energy: Combustion, Performance, and Emission Characteristics of Waste Animal Fats/Diesel Blends Premixed with Various Alcohols as Port Fuels.

Animal flesh is a major food source with economic and industrial value for consumer demand. These meats produced biowaste during and after preparation and use. Chicken intestines make up most of the waste thrown away after processing or frying.

Explainable and Interpretable Model for the Early Detection of Brain Stroke Using Optimized Boosting Algorithms.

Stroke stands as a prominent global health issue, causing con-siderable mortality and debilitation. It arises when cerebral blood flow is compromised, leading to irreversible brain cell damage or death. Leveraging the power of machine learning, this paper presents a systematic approach to predict stroke patient survival based on a comprehensive set of factors.

Analyzing steady-state equilibria and bifurcations in a time-delayed SIR epidemic model featuring Crowley-Martin incidence and Holling type II treatment rates.

This article presents a time-delayed SIR epidemiological model that has been quantitatively examined. The model incorporates a logistic growth function for the susceptible population, a Crowley-Martin type incidence, and Holling type II treatment rates. We investigated two separate time delays.

Heuristic machine learning approaches for identifying phishing threats across web and email platforms.

Life has become more comfortable in the era of advanced technology in this cutthroat competitive world. However, there are also emerging harmful technologies that pose a threat. Without a doubt, phishing is one of the rising concerns that leads to stealing vital information such as passwords, security codes, and personal data from any target node through communication hijacking techniques.

Chemical functionalization of Chitosan biopolymer with diacetyl monoxime for enhanced Cr(VI) removal from aqueous media.

Hexavalent chromium is known for high toxicity as well as carcinogenicity and leads to contamination of water bodies through various anthropogenic activities. Chitosan biopolymer has limited adsorption capacity towards this toxicant. In order to boost hexavalent chromium adsorption, diacetylmonoxime was used to modify thiolated chitosan.

Predictive modelling and optimization of WEDM parameter for Mg-Li alloy using ANN integrated CRITIC-WASPAS approach.

This work intended to improve the precision and machining efficiency of Magnesium alloy (Mg-Li-Sr) using Wire electrical discharge machining (WEDM). Mg-Li-Sr alloy is prepared through inert gas assisted stir casting route. Taguchi approach is used for experimental design for WEDM parameter such as pulse OFF time, pulse ON time, wire feed rate, servo voltage and current.

Stability Development, Optimization and Evaluation of Gastro-Retentive Microspheres of Antidiabetic Agent by Full Factorial Design.

Objective: This work is aimed to Formulate, Optimize and Evaluate Gastro-Retentive Microspheres of Antidiabetic Agent by Full Factorial Design.

Methods: Microspheres were prepared using Emulsification-cross linking technique. To this HPMC-K4M and Carbopol was dissolved in 250 ml of water and allowed to swell for 24 hr at room temperature.

Performance assessment of hybrid machine learning approaches for breast cancer and recurrence prediction.

Breast cancer is a major health concern for women everywhere and a major killer of women. Malignant tumors may be distinguished from benign ones, allowing for early diagnosis of this disease. Therefore, doctors need an accurate method of diagnosing tumors as either malignant or benign.

Comparative Analysis of Classification of Neonatal Bilirubin by Using Various Machine Learning Approaches.

Background Neonatal jaundice poses significant risks to newborn health, necessitating early detection and management. Machine learning (ML) offers promising avenues for improving classification and monitoring, potentially revolutionizing neonatal care. Materials and methods A comparative analysis was conducted using various ML algorithms to classify neonatal bilirubin levels.

Advances in Computational Biology for Diagnosing Neurodegenerative Diseases: A Comprehensive Review.

The numerous and varied forms of neurodegenerative illnesses provide a considerable challenge to contemporary healthcare. The emergence of artificial intelligence has fundamentally changed the diagnostic picture by providing effective and early means of identifying these crippling illnesses. As a subset of computational intelligence, machine-learning algorithms have become very effective tools for the analysis of large datasets that include genetic, imaging, and clinical data.

Revolutionizing Chronic Heart Disease Management: The Role of IoT-Based Ambulatory Blood Pressure Monitoring System.

Chronic heart disease (CHD) is a widespread and persistent health challenge that demands immediate attention. Early detection and accurate diagnosis are essential for effective treatment and management of this condition. To overcome this difficulty, we created a state-of-the-art IoT-Based Ambulatory Blood Pressure Monitoring System that provides real-time blood pressure readings, systolic, diastolic, and pulse rates at predefined intervals.

Piperine-coated zinc oxide nanoparticles target biofilms and induce oral cancer apoptosis via BCl-2/BAX/P53 pathway.

Background: Dental pathogens play a crucial role in oral health issues, including tooth decay, gum disease, and oral infections, and recent research suggests a link between these pathogens and oral cancer initiation and progression. Innovative therapeutic approaches are needed due to antibiotic resistance concerns and treatment limitations.

Methods: We synthesized and analyzed piperine-coated zinc oxide nanoparticles (ZnO-PIP NPs) using UV spectroscopy, SEM, XRD, FTIR, and EDAX.

Selenium Nanoparticles as Neuroprotective Agents: Insights into Molecular Mechanisms for Parkinson's Disease Treatment.

Oxidative stress and the accumulation of misfolded proteins in the brain are the main causes of Parkinson's disease (PD). Several nanoparticles have been used as therapeutics for PD. Despite their therapeutic potential, these nanoparticles induce multiple stresses upon entry.

Hierarchically, Low Band Gap Nanohybrid InVO-CdS Heterojunction for Visible Light-Driven Toxic Organic Dye Degradations.

The synthesis of InVO-CdS heterojunction photocatalysts has been achieved by a novel two-step approach, including a microwave-assisted technique, followed by a moderate hydrothermal method, marking the first successful instance of such a synthesis. X-ray diffraction, field-emission scanning electron microscopy, elemental color mapping, high-resolution transmission electron microscopy, UV-vis diffuse reflectance spectroscopy, Raman analysis, photoluminescence, X-ray photoelectron spectroscopy, and Brunauer-Emmett-Teller were employed to investigate the crystal structures, surface morphologies and particle sizes, chemical compositions, and optical characteristics of the as-synthesized materials. The research results indicated that the heterojunction InVO-CdS, as synthesized, consisted of InVO microrods with an average size of around 15 nm and cadmium sulfide (CdS) microflowers with a diameter of 1.

BT-CNN: a balanced binary tree architecture for classification of brain tumour using MRI imaging.

Deep learning is a very important technique in clinical diagnosis and therapy in the present world. Convolutional Neural Network (CNN) is a recent development in deep learning that is used in computer vision. Our medical investigation focuses on the identification of brain tumour.

Weighted Bayesian Belief Network for diabetics: a predictive model.

Diabetes is an enduring metabolic condition identified by heightened blood sugar levels stemming from insufficient production of insulin or ineffective utilization of insulin within the body. India is commonly labeled as the "diabetes capital of the world" owing to the widespread prevalence of this condition. To the best of the authors' last knowledge updated on September 2021, approximately 77 million adults in India were reported to be affected by diabetes, reported by the International Diabetes Federation.

Polystyrene nanoplastics synergistically exacerbate diclofenac toxicity in embryonic development and the health of adult zebrafish.

In this study, we investigated the possible ecotoxicological effect of co-exposure to polystyrene nanoplastics (PS-NPs) and diclofenac (DCF) in zebrafish (Danio rerio). After six days of exposure, we noticed that the co-exposure to PS-NP (100 μg/L) and DCF (at 50 and 500 μg/L) decreased the hatching rate and increased the mortality rate compared to the control group. Furthermore, we noted that larvae exposed to combined pollutants showed a higher frequency of morphological abnormalities and increased oxidative stress, apoptosis, and lipid peroxidation.

Immunomodulatory zymosan/ι-carrageenan/ agarose hydrogel for targeting M2 to M1 macrophages (antitumoral).

Several studies have been performed on the immunomodulatory effects of yeast β-(1,3) glucan, but there is no proper evaluation of the thermal and immunomodulating properties of zymosan (ZM). Thermogravimetry analysis indicated a 54% weight loss of ZM at 270 °C. Circular dichroism showed absorption peaks in the region of 250 to 400 nm, suggesting a helical coil β-sheet configuration.