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252 articles for “heterogeneity”
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Synthesis of Magnetically Recoverable Nickel (II) Complex-Functionalized Fe3O4@ISNA (ISNA= Isonicotinic acid) Nanomaterials: Catalytic Studies on Nitrophenol Reduction and TD- DFT Studies
Abstract: In this study, we aimed to develop a novel, environmentally sustainable, and magnetically separable heterogeneous nanocatalyst, denoted as Fe3O4@ISNA@NiL (where L represents the ligand). The synthesis involved a two-step process, first, isonicotinic acid was chemically grafted onto the surface of iron oxide nanoparticles (Fe3O4) to introduce functional groups capable of further chemical modification. Subsequently, a nickel(II) Schiff base monomeric complex was anchored onto the modified surface, resulting in a nanocatalyst …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 88–96 Read article
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Synthesis of Magnetically Recoverable Nickel (II) Complex-Functionalized Fe 3 O 4 @ISNA (ISNA= Isonicotinic acid) Nanomaterials: Catalytic Studies on Nitrophenol Reduction and TD- DFT Studies
Abstract: In this study, we aimed to develop a novel, environmentally sustainable, and magnetically separable heterogeneous nanocatalyst, denoted as Fe 3 O 4 @ISNA@NiL (where L represents the ligand). The synthesis involved a two-step process, first, isonicotinic acid was chemically grafted onto the surface of iron oxide nanoparticles (Fe 3 O 4 ) to introduce functional groups capable of further chemical modification. Subsequently, a nickel(II) Schiff base monomeric complex was anchored …
Published in Journal of Polymer & Composites Read article
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Comparative Proteomics: From Cell Lines to Clinical Samples
Abstract: Comparative proteomics is a powerful tool for understanding the molecular differences between various biological samples. It entails identifying and measuring proteins in complex biological samples to assess their abundance, modifications, and interactions under various conditions. This approach plays a crucial role in advancing biomedical research, especially in disease understanding, biomarker discovery, and therapeutic development. While cell lines are widely used for proteomic studies due to their controlled environments and reproducibility, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 30–34 Read article
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Computational Approaches to Understanding Cellular Signaling Pathways
Abstract: Cellular signaling pathways are fundamental in regulating vital processes, such as cell growth, differentiation, and apoptosis. The intricate and interconnected nature of these signaling networks requires sophisticated methods for their analysis. Computational approaches, including mathematical modeling, network analysis, and machine learning, have revolutionized the way researchers analyze and simulate cellular signaling. This article provides a comprehensive overview of computational strategies employed to model signaling pathways, with a focus on integrating …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 8–13 Read article
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Innovative Approaches to Reducing Data Traffic in IoT Networks Using Deep Learning and Compressive Sensing
Abstract: The exponential growth of internet of things (IoT) devices has posed unprecedented challenges in managing the massive data generated by real-time monitoring, automation, and analytics. Existing network infrastructures lack scalability, bandwidth, and suffer from latency problems, further making data transmission less efficient. This study surveys innovative approaches using deep learning and compressive sensing to reduce IoT data traffic. Deep learning is able to upgrade data processing by means of very …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 46–62 Read article
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Nanocomposites of Polyethylene-Closite 20A: Preparation and Characteristics
Abstract: Low-density polyethylene/closite 20A nanocomposites with different organoclay contents were made in the current study by a melt mixing technique with two different compatibilizers of varying contents: low molecular weight oxidized polyethylene and low molecular weight trimethoxysilyl modified polybutadiene. The inclusion of compatibilizers and concentrations of organoclay were analyzed in relation to the mechanical and thermal properties of the nanocomposites. The dispersibility of the silicate clay in the nanocomposites was investigated …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 1, 2025 · pp. 01–12 Read article
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Emerging Paradigms in Parallel Computing: Trends and Innovations
Abstract: Parallel computing is at an inflection point with revolutionary new paradigms and technologies. The goal of this paper is to survey the recent trend in parallel computing from architecture, programming model and applications. Mahajan cites a litany of architectural developments such as heterogeneous computing systems with integrated graphics processing unit/central processing unit ; the emerging promise from quantum and neuromorphic architectures (please see later); advances in packing transistors using novel …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 1, 2025 · pp. 39–43 Read article
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Investigation of Process Specifications on Friction Stir Welded Aluminium 5083 and 6082 Alloys
Abstract: Aluminium 5083 alloys were mainly used for naval based applications because of better corrosion resistance feature. Similarly aluminium 6082 alloy being a structurally significant material found its applications in construction sector. Fusion welding of these two heterogeneous alloys is bit hard, since it evolves many defects. Present Investigation deals with two cases of distinct alloys through FSW process. Case 1 represents 31 experimental trails performed by 5 various tool pin …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 1–11 Read article
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Role of Organizational Culture in Mediating AI-Induced Social Alienation: A Meta-Analysis
Abstract: The fast adoption of artificial intelligence (AI) in the workplace has raised worries about its influence on employee well-being, particularly social alienation. Social alienation is characterised by feelings of detachment and estrangement at work. It can harm job satisfaction, staff engagement, and organisational performance. Existing literature suggests that organizational culture is crucial in shaping employee experiences with AI technologies. This meta-analysis investigates how organizational culture mediates the relationship between AI …
Published in Recent Trends in Social Studies · Vol. 2, Issue 1, 2025 · pp. 28–33 Read article
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Advances in Biological Systems Modeling for Predicting Drug Effects in Chronic Disease
Abstract: Biological systems modeling has emerged as a promising tool for understanding and predicting the effects of drugs in the treatment of chronic diseases. Chronic diseases, such as diabetes, cardiovascular diseases, and neurodegenerative disorders pose significant challenges to traditional drug development due to their complex, multifactorial nature. Systems biology approaches, which integrate computational modeling with experimental data, provide a holistic view of disease mechanisms and treatment responses. This review explores recent …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 17–22 Read article
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Revolutionizing oncology - role of artificial intelligence in early cancer detection and diagnostic advances-A comprehensive review
Abstract: Oncology has experienced a remarkable transformation with the adoption of artificial intelligence (AI), which has greatly enhanced cancer detection and diagnosis. As one of the leading causes of death worldwide, cancer highlights the importance of early detection in improving patient outcomes and survival rates. AI’s ability to analyze vast and complex datasets has enabled groundbreaking innovations in imaging, pathology, biomarker discovery, and predictive analytics. This review highlights key AI-driven advancements …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 1, 2025 · pp. 18–22 Read article
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Understanding Leukemogenesis: Challenges and Advancements in Diagnostic Approaches
Abstract: Leukaemia development, or leukemogenesis, is a multifactorial process driven by a complex interplay of environmental, genetic, and epigenetic factors. Despite substantial advancements in technology and medicine, which have enhanced our understanding of the contributing factors, early and accurate diagnosis remains a major challenge due to the overlapping clinical features shared by the various leukaemia subtypes. This study explores the molecular and cellular mechanisms underlying leukemogenesis, while also addressing the difficulties …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 1, 2025 · pp. 11–22 Read article
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Computational Analysis of Tinospora Cordifolia Phytochemicals as Potential Inhibitors of BRCA1-BRCT Domain Interaction in Breast Cancer
Abstract: Breast cancer is a leading cause of cancer-related deaths worldwide, accounting for a significant proportion of mortality rates among women. Despite current therapeutic approaches, the disease remains characterized by molecular heterogeneity, making it challenging to develop effective treatments. This study explores the potential of Tinospora cordifolia, a medicinal plant, in breast cancer therapy. Guduchi, scientifically known as Tinospora cordifolia, boasts a centuries-long history of use in traditional medicine, with a …
Published in International Journal of Molecular Biotechnological Research · Vol. 3, Issue 1, 2025 · pp. 27–37 Read article
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Optimizing Data Processing Efficiency in Big Data: Advanced MapReduce Algorithm Innovations
Abstract: The exponential growth of big data in recent years has created an urgent need for innovative and efficient processing frameworks capable of managing and analyzing massive and complex datasets. Among these, MapReduce has gained prominence as a powerful tool for distributed data processing due to its simplicity and scalability. However, traditional MapReduce frameworks often encounter significant limitations in terms of efficiency, scalability, and resource optimization, particularly when handling large-scale and …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 1–7 Read article
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Preparation, Categorization and Anticancer Study of Novel Bicyclic Compounds from Various Types for (Five and Six)- Membered Ring
Abstract: The characteristics of ring systems change in the presence of functional groups, but in some cases, elements that are considered functional groups can be classified within the same ring. Compounds that contain only carbon and hydrogen are called homogeneous rings, while those that contain other elements are called heterogeneous rings. The atom substituted in place of the carbon atom is referred to as a heteroatom. Generally, the heterocyclic atom is …
Published in Journal of Catalyst & Catalysis · Vol. 12, Issue 3, 2025 · pp. 18–30 Read article
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Advances in Multiclass Oral Cancer Detection Using Spectroscopic and AI Techniques
Abstract: Oral cancer, primarily OSCC, is still a major health issue worldwide, especially in low-HDI countries. Early diagnosis is essential since survival rates for early detection are much higher than for late-stage detection. However, traditional methods like visual inspection and biopsy are time-consuming, invasive, and rely on the clinician's skill, which is a limitation in accessibility and efficiency. Oral cancer detection has just been revolutionized by recent advances in spectroscopic techniques, …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 3, 2025 · pp. 39–48 Read article
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Optimizing Sampling Techniques Using Fuzzy Set Theory: A Comprehensive Approach
Abstract: Sampling is a critical process in statistics, used to estimate population parameters without needing to examine the entire population. Traditional sampling methods, such as simple random sampling, stratified sampling, and cluster sampling, face limitations when applied to complex or heterogeneous populations with imprecise boundaries. These methods often fail to accurately represent populations with overlapping characteristics or missing data, resulting in sampling bias and reduced accuracy. To address these challenges, this …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 29–43 Read article
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Pathophysiology Reimagined: Integrating Systems Biology and AI for Disease Understanding
Abstract: Pathophysiology, the study of disease mechanisms at molecular, cellular, and systemic levels, has traditionally relied on reductionist approaches that often fail to capture the complex, dynamic, and interconnected nature of biological systems. Diseases such as cancer, neurodegenerative disorders, and infectious diseases arise from intricate interactions among genetic, epigenetic, metabolic, and environmental factors, necessitating integrative, data-driven methodologies for a deeper understanding. Systems biology has emerged as a powerful approach by leveraging …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 63–71 Read article
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Big Data in Chemistry: Problems and Answers
Abstract: The rapid growth of experimental and computational chemistry data, researchers now have access to vast datasets, presenting both significant opportunities and challenges. This paper explores the primary challenges associated with managing, processing, and utilizing big data in chemistry, including data heterogeneity, integration across various scales and systems, lack of standardized formats, and the need for advanced tools for data analysis. Additionally, the paper discusses the ethical concerns of data ownership, …
Published in International Journal of Cheminformatics · Vol. 2, Issue 1, 2024 · pp. 9–14 Read article
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Melanoma Skin Cancer Detection Using Deep Learning
Abstract: Melanoma, a fatal type of skin cancer, is a major global health concern. For better patient outcomes, early and precise detection is essential. A branch of artificial intelligence called deep learning has demonstrated encouraging outcomes in medical image analysis, particularly the identification of skin cancer, in recent years. We present a new method for detecting melanoma skin cancer in this paper by utilizing the ResNet-50 architecture, a deep convolutional neural …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 · pp. 1–9 Read article