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2580 articles
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Improving Dataset Integrity Through Automated Data Cleaning Techniques
Abstract: High-quality data is a fundamental requirement in data science for producing trustworthy analytical insights and effective machine learning models. Problems, including incomplete records, inconsistent entries, duplicate observations, and anomalous values, can severely reduce the accuracy and robustness of predictive systems. As modern datasets continue to expand in both volume and structural complexity, relying on manual data cleaning methods become time-consuming and error-prone, highlighting the growing importance of automated data preprocessing …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 40–45 Read article
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Learning Data Structures: Key to Good Programming
Abstract: Data structures are the most crucial feature of good programming and are needed to solve hard computational problems. This model makes use of two different recurrent neural network architectures, specifically long short-term memory (LSTM), and gated recurrent unit (GRU) networks. It explains how selecting and using the correct data structures may speed up computations, optimize memory, and scale code. How data structures and algorithms relate and how to think about …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 29–39 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
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India’s Changing Skies: Unravelling the Rise of Unpredictable Weather Extremes
Abstract: India is currently experiencing a significant transformation in its climate system, characterized by rising temperatures, irregular rainfall patterns, and an increasing frequency of extreme weather events. These changes are no longer gradual or isolated but are becoming more visible and impactful across different regions of the country. This study provides a detailed examination of long-term climatic trends in India by analysing temperature variations, monsoon behaviour, and the growing occurrence of …
Published in International Journal of Climate Conditions · Vol. 3, Issue 1, 2026 · pp. 11–18 Read article
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Phosphorescence of Carbon Nanodots – The Phenomena and the Applications
Abstract: Photoluminescence has emerged as a fundamental phenomenon in modern biomedical science, enabling advanced diagnostic, therapeutic, and theranostic applications through light–matter interactions at the nanoscale. The ability of photoluminescent materials to absorb electromagnetic radiation and emit light at distinct wavelengths has been widely exploited in bioimaging, biosensing, drug delivery tracking, and photodynamic therapy. Among various photoluminescent nanomaterials, carbon nanodots have attracted significant attention due to their strong emission intensity, tunable fluorescence, …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 4, Issue 1, 2026 · pp. 01–05 Read article
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Climate Change Threat in Jaipur: Mitigating and Sustainable Attributes Through Carbon Footprint Reduction
Abstract: Challenges of climate change are significantly increasing on a forward time scale. Such a phenomenon is predominantly seen in urban sectors where population is rapidly increasing, thereby resulting in extensive resource consumption leading to release of significant carbon footprint. An attempt has been made in the present paper by the authors initially to assess the carbon footprint of Jaipur, Rajasthan on a backward and forward time scale partly to suggest …
Published in International Journal of Climate Conditions · Vol. 3, Issue 1, 2026 · pp. 35–50 Read article
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Association Between Smartphone Addiction and Functional Exercise Capacity in College Students
Abstract: Smartphone addiction has become increasingly prevalent among college students and is associated with various negative physical and psychological outcomes. Functional exercise capacity, a key indicator of physical fitness and health, may be adversely affected by excessive smartphone use due to sedentary behavior and reduced physical activity. This article examines the association between smartphone addiction and functional exercise capacity in college students by analysing behavioral, psychological, physiological, and methodological perspectives. Evidence …
Published in International Journal of Orthopedic Nursing and Practices · Vol. 4, Issue 1, 2026 Read article
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64 Bit ALU DESIGN USING VEDIC MATHEMATHICS
Abstract: High-speed arithmetic operations are crucial for better performance in contemporary digital systems. Particularly for high bit-width operations, conventional arithmetic logic units (ALUs) frequently experience increased latency and complexity. This work presents the design and implementation of a 64-bit Arithmetic Logic Unit (ALU) using notions from Vedic mathematics. The suggested design makes use of a Kogge-Stone Adder for effective addition and the Urdhva Tiryagbhyam sutra for quick multiplication. Among other mathematical …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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Integrative Structural-Functional Genomics of Fc and Fab: Precision Models for Monoclonal Antibody Stability and Anti-Aggregation Engineering
Abstract: Monoclonal antibodies (mAbs) represent the cornerstone of biotherapeutics, yet aggregation propensity compromises up to 50% of candidates during development, driven by Fab hypervariability and Fc vulnerabilities.(1,2) This review integrates functional genomics from OAS (4B+ sequences)(5) and structural databases (SAbDab: 10K+ structures)(6) with machine learning models achieving R=0.97 for SAP prediction.(11) We dissect biophysical mechanisms, benchmark predictive tools (DeepSP, ESM2), and engineering strategies (YTE, FW mutations) that enhance Tm by 5-10°C …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 1, 2026 Read article
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The Next Era of Molecular Biotechnology: Beyond DNA
Abstract: Molecular biotechnology has advanced much beyond conventional DNA manipulation, into a phase characterised by precision, integration, and invention. This article examines the evolving domain of next-generation biotechnological instruments, encompassing gene editing technologies like CRISPR-Cas systems, synthetic biology, and RNA-based medicines. It shows how these new technologies are changing medicine by making treatments more personalised, making farming more productive by using genetically modified crops, and making industrial processes more environmentally friendly …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 1, 2026 Read article
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Need of a Comprehensive and Feasible Psychometric Test in the Assessment of Perinatal Mental Health - A Systematic Review
Abstract: The perinatal period is a period of happiness as well as hardships. A woman undergoes many psychological changes during this period which makes her prone to mental health disorders that can be detrimental to the health of the women and her child. Its essential to detect these disorders as early as possible and hence a psychometric test or tool which is easy to administer and interpret is needed. Globally various …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 104–111 Read article
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Oceanmind Systems: AI-Driven Marine Life Intelligence for Climate Prediction and Ocean Ecosystem Stability
Abstract: Oceans regulate global climate systems, support biodiversity, and serve as critical carbon sinks, yet they remain under-monitored relative to their ecological importance. Traditional oceanographic methods rely heavily on satellite sensing, buoy networks, and periodic marine surveys, which often fail to capture real-time biological dynamics at micro-ecosystem levels. This paper introduces OceanMind Systems, an artificial intelligence (AI)-driven marine intelligence framework that integrates marine life behavior, oceanographic data, and computational modeling to …
Published in International Journal of Marine Life · Vol. 3, Issue 2, 2026 Read article
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Comparative Analysis and Future Research Directions in AI in Healthcare: Medical Imaging and Diagnostics
Abstract: Artificial intelligence (AI) is reshaping healthcare, particularly in the areas of medical imaging and diagnostic practice. By using advanced techniques like machine learning and deep learning, AI systems help improve the accuracy, speed, and effectiveness of identifying diseases and analyzing medical images. This paper provides a comprehensive overview of the application of artificial intelligence in medical imaging and highlights its growing importance in clinical diagnostics. It discusses how AI-based systems …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 8–13 Read article
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MBSR for Better Health: A Narrative Review
Abstract: Introduction: MBSR is a mindfulness-based intervention created by John Kibbat Zinn in the 1970's using the principles of the Buddhist tradition. Since its creation it has found to be effective in various physiological and psychological issues such as cardiovascular diseases, diabetes, blood pressure, hypertension, anxiety, depression, and other ailments. In this particular narrative review, we screened and selected various studies that observed better physiological and psychological health post the MBSR …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 89–98 Read article
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An Overview on AI-Driven IoT Based Decision Making in Climate change Study: KSK approach in Climate Change Study
Abstract: As the Earth’s climate enters a state of unprecedented volatility, the traditional methods of ecological observation—characterized by delayed reporting and fragmented data—are no longer sufficient. This study investigates the paradigm shift toward AI-driven IoT (KSK Approach)-based decision-making frameworks as the primary frontier in climate science. By deploying a "planetary nervous system" of interconnected sensors—measuring everything from soil moisture in the Sahel to glacial melt rates in the Arctic—we generate a …
Published in International Journal of Climate Conditions · Vol. 3, Issue 1, 2026 · pp. 1–10 Read article
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Effectiveness of Evidence-Based Pediatric Nursing Practices on Clinical and Developmental Outcomes in Children: A Comprehensive Systematic Review
Abstract: Evidence-based pediatric nursing practices are essential for improving health outcomes among children by integrating clinical expertise with the best available research evidence and patient-centered care approaches. This systematic review examines the effectiveness of evidence-based pediatric nursing interventions on clinical and developmental outcomes in children across various healthcare settings. A comprehensive search of databases including PubMed, CINAHL, Scopus, and the Cochrane Library was conducted for studies published between 2016 and 2026. …
Published in International Journal of Evidence Based Nursing And Practices · Vol. 4, Issue 1, 2026 Read article
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Photochemical Detoxification of Arsenic- and Mercury-Contaminated Soils: Geochemical Mechanisms and Pathways
Abstract: This study evaluates the geochemical aspects of soil detoxification in areas contaminated with arsenic (As) and mercury (Hg), emphasizing sustainable strategies for improving soil health and ensuring safe crop production. The research provides an ecological and toxicological assessment of regional soils and classifies them base on the concentration and mobility of toxic elements. Although the current levels of As and Hg do not yet present a critical risk to agricultural …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 4, Issue 1, 2026 · pp. 06–10 Read article
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DFT/Data Guided Predictive Modelling of Absorption Maxima in the OLED Rubrene Derivatives
Abstract: This study investigates the optical properties of rubrene derivatives to develop an accurate predictive model for absorption maxima using computational chemistry and chemoinformatic techniques. We benchmarked various quantum chemical methods, identifying that the M06-2X/aug-cc-pVDZ method in dichloromethane (DCM) provided the strongest correlation with experimental data. Key molecular descriptors such as band gap, ionization potential, and electrophilicity index were calculated and analyzed using principal component analysis (PCA) to identify significant factors …
Published in International Journal of Cheminformatics · Vol. 4, Issue 1, 2026 · pp. 41–56 Read article
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Molecular Dynamics and Therapeutic Architectures of Cannabinoid Receptors: A Comprehensive Review
Abstract: Expanding on these foundations, recent structural biology studies using cryo-electron microscopy have provided high-resolution insights into the conformational dynamics of CB₁ and CB₂ receptors. These findings have enabled a more precise understanding of ligand–receptor interactions, particularly how agonists, antagonists, and reverse agonists stabilize distinct receptor states. Such knowledge is critical for rational drug design, allowing researchers to selectively modulate downstream signaling pathways. For instance, CB₁ receptors primarily couple to Gi/o …
Published in International Journal of Cheminformatics · Vol. 4, Issue 1, 2026 · pp. 36–40 Read article
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The Renaissance and Resilience of CB1 Reverse Agonists: From Central Liabilities to Peripheral Promise
Abstract: Building upon these foundational insights, current research has increasingly focused on refining the pharmacological profile of CB1 reverse agonists to maximize therapeutic benefit while minimizing central adverse effects. The adverse neuropsychiatric outcomes associated with first-generation agents such as Rimonabant including anxiety, depression, and suicidal ideation highlighted the critical role of central CB1 receptors in mood regulation. Consequently, drug development strategies have shifted toward peripherally restricted CB1 reverse agonists that exhibit …
Published in International Journal of Cheminformatics · Vol. 4, Issue 1, 2026 · pp. 30–35 Read article