Search
1600 articles for “drying”
-
The Burden of Empirical Therapy: Analyzing the Predominance of Broad-Spectrum Antibiotic Usage in Lower Respiratory Tract Infections
Abstract: Lower respiratory tract infections (LRTIs) remain one of the leading causes of morbidity and hospitalization worldwide, particularly among older adults, immunocompromised individuals, and patients with chronic respiratory disorders. These infections include conditions such as community-acquired pneumonia, hospital-acquired pneumonia, bronchitis, and acute infective exacerbations of chronic lung disease, all of which often require rapid clinical intervention. Because microbiological confirmation of the causative pathogen frequently takes 48–72 hours, clinicians generally initiate empirical …
Published in International Journal of Antibiotics · Vol. 3, Issue 2, 2026 Read article
-
The Global and Regional Challenge of Pan-Antibiotic Resistance: A Review of Emerging Threats and Mechanisms
Abstract: Antimicrobial resistance (AMR) is one of the major and most intricate threats to the health of the 21st century as it is core to the undermined expertise of the common clinical practice and public health security worldwide. The problem is characterized by the extensive development of bacterial pathogens into extremely drug-resistant (XDR) and pan-drug-resistant (PDR) so- called superbugs faster than it can be done with therapeutics. It is a synthesis …
Published in International Journal of Antibiotics · Vol. 3, Issue 2, 2026 Read article
-
Enhancing Smart Grid Resilience Through AI-Based Fault Classification
Abstract: Traditional power grids can be developed into smart grids, and they are comprised of the latest information and communication technologies (ICTs), which are based on establishing the relationship between the conventional electricity systems along with the usage of smart meters and distributed generation. This dynamic improves energy efficiency and the integration of renewables. Well, the dynamic and reversible power injection from Distributed Energy Resources (DERs) creates substantial operational problems. These …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 10–15 Read article
-
AI-Based Discovery of High-Performance Energy Storage Polymer Composites: A Comprehensive Review
Abstract: The accelerating global demand for high-performance energy storage systems has stimulated significant research into advanced polymer composites as next-generation electrolytes, electrode binders, and functional membranes for batteries, supercapacitors, and photovoltaic devices. However, the vast compositional and structural design space of polymer materials presents formidable challenges for conventional trial-and-error discovery strategies, which remain slow, costly, and biased by prior expert knowledge. Machine learning (ML) and artificial intelligence (AI) have emerged as …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1083–1097 Read article
-
A Systematic Review of the Herbal Medicinal Plants With Anti-Obesity Potential
Abstract: Obesity is a chronic, multifactorial metabolic condition characterized by abnormal fat accumulation. It is mainly driven by the intricate influence of genetic, environmental, hormonal, metabolic and lifestyle determinants. The burden of obesity has risen considerably over the past few years, making it one of the major health concerns in both developed and developing countries alike. The rapid increase globally in obesity prevalence is linked with numerous health complications such as …
Published in Research & Reviews : Journal of Herbal Science · Vol. 15, Issue 2, 2026 Read article
-
Artificial Intelligence in Microbiological Research: Methods, Applications and Implications
Abstract: Artificial Intelligence (AI) is revolutionising microbiological research by enabling the rapid analysis of complex biological data and improving the accuracy, efficiency, and reliability of scientific investigations. Recent advances in machine learning, deep learning, and bioinformatics have transformed AI into a powerful tool for studying microorganisms, their genetic composition, evolutionary patterns, and interactions with hosts and the environment. AI-driven computational models can process large and complex datasets far more efficiently than …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 16, Issue 2, 2026 Read article
-
Legume-Induced Frothy Bloat in Tropical Cattle: Pathophysiology, Consequences and Preventative Measures
Abstract: Legume-induced bloat in tropical cattle is a complex and significant health challenge that affects livestock productivity and welfare. This review aims to elucidate the multifaceted causes of bloat associated with the consumption of leguminous forages, highlighting both the physiological mechanisms and environmental factors that contribute to this condition. Key factors include the high soluble protein content of legumes, rapid fermentation rates in the rumen, and the formation of stable foam, …
Published in Research and Reviews : Journal of Veterinary Science and Technology · Vol. 15, Issue 2, 2026 Read article
-
Optimization of a new Bebq2/BCP-based OLED structure for optimum performance
Abstract: Opto-electronic devices exhibit highly nonlinear current–voltage (I–V) characteristics that significantly affect charge injection, transport, and recombination, evaluating their performance remains a difficult challenge. Device optimization is a key research goal in organic light-emitting diodes (OLEDs), as the thickness and arrangement of individual functional layers greatly influence electrical and optical responses. For a suggested Bebq2/BCP-based OLED structure, this work methodically examines the movement of charge carriers, their transport behavior, and the …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, Issue 2, 2026 Read article
-
A Hybrid Multi-Physics Ensemble Deep Learning Framework for Simultaneous Prediction of Thermal and Electrical Conductivity in Functional Polymer-Based Nanocomposites
Abstract: Polymer-based nanocomposites have become promising materials for applications in energy storage, flexible electronics, biomedical devices, aerospace components, and advanced engineering because of their tunable thermal and electrical properties. Reliable prediction of these properties is essential for accelerating material design; however, existing analytical models and conventional machine learning techniques often fail to represent the complex interactions among filler characteristics, polymer matrices, processing conditions, and interfacial transport phenomena. This work presents HMEP-Net, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1062–1082 Read article
-
Explainable Sentiment Mining Model in Mental Health Forums for Emotion Classification and Justification
Abstract: Understanding and interpreting emotions expressed in online mental health discussions plays a crucial role in enabling early detection of psychological distress and facilitating timely interventions. As individuals increasingly turn to digital platforms to share personal experiences and seek support, automated systems capable of accurately identifying emotional states can significantly assist clinicians, moderators, and support communities. This paper presents a deep learning–based sentiment mining and emotion classification framework specifically designed to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 22–32 Read article
-
Design and Development of Lightweight Polymer Composite Manifold Using CF-ABS and GFRP for Aerodynamic Energy Recovery in Electric Vehicles
Abstract: Electric vehicles provide a number of advantages over conventional fuel vehicles due to their low to no emissions. High energy efficiency improves the driving performance of Electric vehicles. However, they have to face certain challenges such as the high purchase cost of batteries and lack of battery charging facilities. The major drawback of an Electric vehicle is to store sufficient energy to run the vehicle for a long time. This …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
-
The Tapper Approach: An Integrated Framework for Land Degradation, Restoration, and Climate-Conflict Dynamics
Abstract: Land systems across the globe are increasingly exposed to multiple and interacting pressures, including land degradation, climate change, biodiversity loss, unsustainable land-use practices, rapid population growth, and socio-economic conflicts. These challenges not only reduce ecosystem productivity and resilience but also threaten food security, water availability, rural livelihoods, and long-term environmental sustainability. Despite the growing recognition of these interconnected issues, most existing conceptual and analytical frameworks continue to address them in …
Published in Research & Reviews : Journal of Ecology · Vol. 15, Issue 2, 2026 Read article
-
In Vivo Hypoglycemic Activity of Aqueous Leaf and Root Extracts of Macaranga Barteri Müll. Arg. (Euphorbiaceae) In Swiss Albino Mice
Abstract: Background: Macaranga barteri Müll. Arg. is a perennial plant in the family Euphorbiaceae and is used in African traditional medicine for the management of several ailments, including diabetes. Although the leaves and stem bark have been studied for various pharmacological activities, little is known about the therapeutic value of the roots. Objective: This study evaluated the in vivo hypoglycemic activity of aqueous leaf and root extracts of M. barteri in …
Published in Research and Reviews : Journal of Veterinary Science and Technology · Vol. 15, Issue 2, 2026 Read article
-
White-Rot Fungi-Based Bioprocessing for Circular Bioeconomy & Valorization of Lignocellulosic Waste
Abstract: The escalating global demand for sustainable resource management and the imperative to reduce dependence on fossil-based products have positioned the circular bioeconomy as a transformative paradigm for the 21st century. Lignocellulosic biomass, generated abundantly as agricultural and forestry residues, constitutes one of the most underexploited renewable carbon sources on Earth, yet its recalcitrant structure, interlinking cellulose, hemicellulose, and lignin, has long impeded its efficient valorization. White-rot fungi (WRF), predominantly belonging …
Published in International Journal of Fungi · Vol. 3, Issue 2, 2026 Read article
-
Entomo-Analytics: Insect Behavioral Intelligence for Climate-Smart Environmental Monitoring Systems
Abstract: Rapid environmental change driven by climate variability, urbanization, and ecological degradation has intensified the need for innovative monitoring systems capable of providing real-time ecological intelligence. Traditional environmental monitoring methods often rely on satellite imaging and stationary sensors, which may lack fine-scale biological sensitivity. In contrast, insects—due to their abundance, ecological diversity, and rapid responsiveness to environmental shifts—offer a powerful yet underutilized source of bio-sensing data. This paper introduces the concept …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 17–26 Read article
-
Artificial Intelligence Techniques for Smart Polymer Nanocomposite Materials and Industrial Applications
Abstract: Protecting sensitive material data, manufacturing processes, and intelligent monitoring platforms is essential for the fast development of innovative polymer nanocomposite systems in fields such as aerospace, medicine, electronics, automobiles, and energy. In order to safeguard, consistently enhance, and optimize distributed industrial systems that consist of polymer nanocomposite materials, this study presents an AI-driven cybersecurity and cloud computing architecture. The suggested solution employs artificial intelligence (AI), machine learning (ML), cloud computing, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
-
Prediction of Mechanical Properties for Advanced Engineering Applications utilizing Polymer Composite Materials by Machine Learning
Abstract: Polymer composites show great promise as engineering materials because of their mechanical performance, resistance to corrosion, lightweight nature, and adaptability in design. Aerospace, automotive, biomedical, maritime, and civil engineers all rely on mechanical property prediction to cut down on trial expenses, expedite product development, and optimize material selection. Speedy design optimization is not possible using traditional numerical and experimental methods due to the high costs associated with material characterisation, computational …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
-
Physico-Mechanical Behavior of Euphorbia Abysinica and Wood Chips Composite
Abstract: In this study, we prepared composite test specimens from Eucalyptus chip particles of sizes 0.5 mm, 1 mm, and 2 mm combined with Euphorbia-Abyssinica fluid at an 80:20 mass ratio. We produced the particleboard under a compression load of 150 KN and kept it in the compression machine for thirty minutes inside the mold. After removing it from the machine, we secured it with C-clamps for twenty-four hours. We covered …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
Strategies for the Development and Optimization of Orally Disintegrating Tablets (ODTs) to Improve Bioavailability and Patient Compliance
Abstract: Background: Pharmaceutical scientists have developed Orally Disintegrating Tablets (ODTs) to advance patient drug acceptance and biological system availability through simplified medi-cation delivery especially for children and senior citizens and people who cannot swallow pills regularly. The oral disintegrating tablets dissolve in the mouth within thirty seconds or less (USP 701) while needing no additional liquid thus making them suitable for both emergency treatments. Objective: The research examines ODT development strategies …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 13, Issue 2, 2026 Read article
-
Passive Digital Phenotyping for Longitudinal Burnout and Occupational Mental Health Surveillance: A Transformer-Based Explainable Deep Learning Approach Using Smartphone Behavioral Streams
Abstract: Occupational burnout constitutes a pervasive yet chronically under-surveilled public health threat, its insidious temporal evolution rendering episodic self-report instruments structurally inadequate for early detection. This paper introduces BurnoutSense, a passive digital phenotyping framework that continuously harvests eight heterogeneous smartphone behavioral data streams encompassing application usage ecology, communication metadata, geospatial mobility, screen interaction dynamics, inferred sleep rhythmicity, keystroke kinematics, ambient noise exposure, and battery/charging cadence to construct individualized multivariate behavioral signatures …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 2, 2026 · pp. 44–53 Read article