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1680 articles for “BCS Class II/IV drugs”
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Formulation and Evaluation of Herbal Skin Cream
Abstract: Herbal cosmetics have gained significant attention in recent years due to increasing consumer preference for natural and safe skincare products. Herbal skin creams are semisolid formulations enriched with plant-derived ingredients that provide therapeutic as well as cosmetic benefits. These formulations are designed to enhance skin health by utilizing bioactive phytoconstituents such as flavonoids, alkaloids, tannins, essential oils, and vitamins. Herbal creams are generally prepared using oil-in-water (O/W) or water-in-oil (W/O) …
Published in Recent Trends in Cosmetics · Vol. 3, Issue 2, 2026 · pp. 20–32 Read article
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Genomic Characterization of Emerging Arboviruses in Rural India
Abstract: Arboviruses (arthropod-borne viruses) represent a rapidly evolving group of pathogens responsible for significant morbidity and mortality, particularly in tropical and subtropical regions. Rural India, characterized by dense vector populations, changing ecological patterns, and limited healthcare infrastructure, has become a hotspot for the emergence and re-emergence of arboviral diseases such as dengue, chikungunya, Japanese encephalitis, and more recently, Zika virus infections. Advances in genomic technologies, including next-generation sequencing (NGS), metagenomics, and …
Published in International Journal of Pathogens · Vol. 3, Issue 2, 2026 · pp. 1–8 Read article
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Review on the Effects of Chemical Compounds Toxicity on Workers in Chemical Laboratories.
Abstract: Chemical laboratories are considered high-risk work environments due to the wide range of chemicals that workers handle, which may be toxic, corrosive, or flammable. Improper handling of these substances can lead to serious health problems, ranging from mild irritation to death in cases of exposure to chemical compounds such as phenols and amines, which cause various types of lung and laryngeal cancers and respiratory diseases in laboratory workers who are …
Published in International Journal of Toxins and Toxics · Vol. 3, Issue 2, 2026 · pp. 17–26 Read article
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Synthesis, characterizations, and challenges of magnetic Zn x Fe 2-x O 3 nanoparticles
Abstract: Diluted magnetic semiconductors comprising magnetic nanoparticles are a driving force in a variety of applications, including biomedicine, bioelectronics, photocatalytic activities, and nanosensors. However, the functionality of these nanomaterials can be influenced by several factors, such as synthesis route, characterization procedures, source, crystal size, and morphology. In this research, emphasis is devoted to synthesizing and characterizing magnetic nanoparticles. Most importantly, it is focused on biological methods, Co-precipitation methods, hydrothermal Gravity methods, …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article
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Polymers and Composites in the Design and Construction of Unmanned Aerial Vehicles: A Comprehensive Technical Review
Abstract: The emergence of Unmanned Aerial Vehicles (UAVs) over the last few years has mostly been made possible by breakthroughs in material science. This review is concerned with an overview of some of the polymers and composites that are being commonly used in drone manufacturing in recent times, especially in relation to the influence of material choice on drone performance and capability. It sheds light on the drastic change in the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 874–882 Read article
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Physics-Informed Generative and Tensor-Based Framework for DNA Sequence Simulation and Genomic Structure Discovery
Abstract: In this paper, we explore the intersection of artificial intelligence (AI) and mathematical physics to propose advanced methods for DNA sequence generation and analysis. Specifically, we investigate how physics-informed Generative Adversarial Networks (GANs) and tensor network representations can be harnessed to restructure DNA for applications in genetic science. The proposed methodology offers a unique integration of concepts of thermodynamic modeling with innovative GAN architecture in order to allow the creation …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Optimized Utilization of Kota Stone Slurry Waste in Fly Ash–Based Geopolymer Mortar: A Taguchi-Driven Approach
Abstract: The large-scale generation of stone-processing wastes presents a critical sustainability challenge and an opportunity for value-added reuse in construction materials. This study develops a high-performance fly ash geopolymer mortar by partially replacing Class F fly ash with Kota stone slurry waste (KSSW) and optimizing the key mix parameters using a Taguchi design framework. Five governing factors—binder replacement level, NaOH molarity, sodium silicate–to–sodium hydroxide ratio (SS/SH), curing temperature, and alkaline solution-to-binder …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 426–445 Read article
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Explainable Artificial Intelligence in Personalized Medicine: Emerging Clinical Perspectives
Abstract: The convergence of artificial intelligence (AI) and precision medicine has transformed contemporary healthcare by enabling data-driven clinical decision-making, individualized therapeutic interventions, and predictive diagnostics. However, despite remarkable advances in machine learning (ML) and deep learning (DL), the widespread adoption of AI in healthcare remains constrained by the “black-box” nature of many computational systems. Clinicians, regulatory agencies, and patients increasingly demand transparency, interpretability, and trustworthiness in AI-guided medical recommendations. Explainable Artificial …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 13–29 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Functional Biomolecules in Animal Nutrition: Biochemical Mechanisms and Their Impacts on Growth Performance and Health Outcomes
Abstract: Functional biomolecules have emerged as critical modulators of animal nutrition, extending beyond conventional nutrient supply to regulate biochemical and physiological processes that determine growth performance and health outcomes. This review synthesizes current knowledge on diverse classes of bioactive compounds, including amino acids, peptides, fatty acids, vitamins, minerals, phytochemicals, and microbial-derived metabolites, and their roles in livestock systems. Emphasis is placed on underlying biochemical mechanisms such as enzyme activation, nutrient signaling …
Published in International Journal of Nutritions · Vol. 3, Issue 2, 2026 Read article
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Structural Performance Evaluation of Circular Perforated Plates under Mechanical Loading
Abstract: Circular perforated plates are structurally critical components in aerospace, automotive, and marine sectors, where perforation-induced stress concentrations govern failure under mechanical loading. This study conducts a systematic finite element analysis of stress distribution, deformation, and interlaminar behavior in aluminum and glass-epoxy laminates ([−45/45/90/0]S and [−45/45/90/0]AS) under uniform transverse pressure with clamped-free boundary conditions. Four perforation configurations—no hole, central hole, single-series, and 25-hole grid—were evaluated using ANSYS Shell-181, verified against Kirchhoff–Love, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 1–20 Read article
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Lightining Future With Non Degradable Waste
Abstract: This project focuses on addressing the growing problem of non-biodegradable waste, which creates major environmental and management issues. It proposes a smart system for waste segregation and energy production using the Arduino UNO R4 platform. The system classifies waste into three types dry, wet, and metal by using various sensors such as proximity, moisture, infrared, temperature, and weight sensors. After segregation, dry waste is sent to an incineration chamber where …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 16, Issue 2, 2026 Read article
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Machine Learning-Based Quantification of Polymer Structure Property Relationships for Predictive Material Design
Abstract: Polymer structures exhibit complex, hierarchical arrangements that strongly influence macroscopic properties, yet consistent quantification remains challenging due to nonlinear interactions and limited unified modeling strategies. Existing approaches inadequately capture generalized structure–property mappings across diverse polymer systems. This research aims to establish a machine learning-based quantification model for polymer structure–property relationships to support predictive material design. A Polymer Structure Property Dataset of 5,000 polymer samples includes structural descriptors and experimentally measured …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 737–754 Read article
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Antimicrobial Resistance: - A Growing Serious Threat for Global Public Health
Abstract: Antibiotics, among the most significant discoveries of the 20th century, have prevented infectious diseases from claiming millions of lives. However, their widespread use and misuse have created strong selection pressure, enabling microbes to develop antimicrobial resistance (AMR) to many drugs. Over time, AMR has spread primarily through human-to-human contact, both within healthcare settings and in the community. It is driven by a complex interplay of healthcare and agricultural factors, including …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 17, Issue 2, 2026 Read article
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Diabetes Risk Prediction from Survey Data Using Machine Learning Algorithms
Abstract: Diabetes mellitus represents one of the most significant global health challenges, affecting millions worldwide and leading to severe complications if left undiagnosed or poorly managed. Early detection and risk assessment are crucial for preventing the progression of this chronic condition. This research presents a comprehensive machine learning approach for predicting diabetes risk using survey-based health parameters. The study implements and compares four prominent classification algorithms: Logistic Regression, K-Nearest Neighbors (KNN), …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Mass Spectrometry–Based Phosphoproteomic Markers to Predict Kinase Inhibitor Response in Solid Tumors
Abstract: Mass spectrometry-based phosphoproteomics has emerged as a powerful tool for predicting kinase inhibitor responses in solid tumors, offering direct functional insights into signaling pathways that surpass traditional genomic profiling by capturing dynamic kinase activities and adaptive resistance mechanisms. Technological breakthroughs, including data- independent acquisition (DIA), trapped ion mobility spectrometry (timsTOF), and efficient enrichment methods like TiO2 or IMAC, now enable comprehensive profiling of over 40,000 phosphorylation sites from limited clinical …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 2, 2026 Read article
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Solid Acid Catalysts for the Selective Conversion of Biomass to Levulinic Acid
Abstract: Levulinic acid (LA) has emerged as a versatile platform chemical with significant potential for producing renewable fuels like gamma-valerolactone (GVL), biodegradable polymers, and fine chemicals from biomass (both terrestrial and marine which ae rich in carbohydrate). The selective conversion of biomass-derived carbohydrates to LA requires efficient catalytic systems that can overcome the recalcitrance of the biomass, namely the stiff-necked structural integrity of cellulose and the kind of strong interactions between …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 1, 2026 Read article
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A Constraint-Driven Generative Design Methodology for Modular Actuated Robotic Components in Decentralized Manufacturing
Abstract: This work formalizes a constraint-driven generative design framework for actuator-integrated robotic components intended for decentralized additive manufacturing. Conventional topology optimization typically prioritizes structural efficiency while treating actuator integration, modular interfaces, and fabrication constraints as secondary considerations. In contrast, the proposed methodology encodes these requirements as first-order geometric and mechanical constraints prior to automated material redistribution. The framework defines preserved actuator geometry, bounded design envelopes, representative loading abstractions, and manufacturability-aware domains …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 4, Issue 1, 2026 Read article
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Wear and Tribological Characteristics of Novel Metal Matrix Composites
Abstract: The development of advanced metal matrix composites (MMCs) with enhanced tribological performance has become increasingly important due to the premature failure of critical engineering components operating under severe wear conditions in automotive, aerospace, marine, defense, and power generation systems. Conventional composites such as Copper–Alumina and Aluminium–Silicon Carbide have demonstrated improved mechanical and wear characteristics; however, their widespread application is often limited by issues including particle agglomeration, non-uniform reinforcement distribution, porosity …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1326–1346 Read article
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An Auxiliary Array Indexing Approach for Efficient Binary Search in Linked Lists
Abstract: The paper covers an algorithm for searching a linked list structure using binary search. Binary search is a classic example of an algorithm that follows the divide-and-conquer approach. Binary search may be used to find elements in an array. Trying to apply the conventional binary search to a linked list simply does not work out very well; it still has an O(n) time complexity, the same as linear search. This …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 21–28 Read article