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50 articles for “Inversion”
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Unveiling Bihar's Atmospheric Crisis: A Synoptic Review of PM 2.5 Dynamics, Source Attribution, and Airshed Vulnerabilities in the Eastern Indo-Gangetic Plain (Bihar)
Abstract: Bihar, situated in the pollution-trapping Indo-Gangetic Plain (IGP), faces a severe air pollution crisis characterized by annual PM2.5 concentrations of 80–100 μg m-3 exceeding WHO guidelines (5 μg m-3) and Indian NAAQS (40 μg m-3) by 4–6-fold. This review synthesizes data from CPCB/BSPCB monitoring, MODIS satellite retrievals, and peer-reviewed studies (2000–2025) to assess ambient air quality, sources, health impacts, policies, and research gaps in the state. PM2.5 and PM10 dominate, …
Published in International Journal of Pollution: Prevention & Control · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
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On the link of global warming and cloudiness in mid hills of Himachal Himalayas, India
Abstract: The present study investigated the monthly, seasonal, and annual cloud cover variability over two stations in the mid hills sub-temperate subhumid zone of Himachal Pradesh, by using Pearson’s correlation coefficient, Mann-Kendall (MK), and Sen’s slope estimator test. Daily data on cloud cover, sunshine hours, maximum and minimum temperature, morning and evening relative humidity, evaporation and rainfall for the period of 22 years (2001–2022) were used in the investigation. In the …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 39–49 Read article
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Parallel Privacy-Preserving Adaptive Federated Learning on GPU-Enabled Multi-Core Architectures
Abstract: The increasing deployment of parallel and distributed intelligent systems has intensified the need for privacy-preserving learning frameworks that can exploit multi-core and GPU-based architectures without centralizing sensitive data. This work proposes a parallel Adaptive Federated Learning (AFL) framework that integrates Differential Privacy and Secure Aggregation over heterogeneous multi-core and GPU platforms to enhance both data confidentiality and convergence efficiency. The framework dynamically adjusts client participation, learning rates, and aggregation weights …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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Quantitative Image-Based Assessment of Degradation Patterns in Polymer-Based Medical Implants
Abstract: Polymer-based medical devices are widely used in clinical practice, where long-term material degradation can compromise performance and patient safety. Traditional polymer degradation studies predominantly rely on laboratory-based experiments, which often fail to capture real-world operational and usage conditions. In this study, a multimodal, data-driven framework is proposed for the quantitative assessment of degradation patterns in polymer-based medical devices using publicly available clinical failure data. Structured operational parameters, including cumulative usage …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1510–1518 Read article
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Enhanced Sustainable Concrete Mix Design Using LLMs and Advanced Machine Learning Techniques
Abstract: Large Language Models (LLMs) are emerging as transformative tools in materials science, offering human-like reasoning, zero-shot problem solving, and the ability to integrate fuzzy laboratory knowledge with structured data. This study extends and reinterprets the original systematic benchmark for using LLMs in sustainable concrete design, particularly for Alkali-Activated Concrete (AAC). We introduce an enhanced, multi-model framework combining LLM-based inverse design, Random Forest regression, Gaussian Process Regression (GPR), and a lightweight …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Heavy Metal Removal from Textile Industrial Effluent using Banana Exocarp Derived Cellulose Acetate Graphene Nanocomposite Membranes
Abstract: The disposal of textile effluent is responsible for serious human health concerns and above all environmental concerns to all kind of species. This indicates that there is immediate and urgent need of emerging, efficient with sustainable recycling technologies. In this paper, banana exocarp as agriculture-based waste, in terms of substrate was utilised as major raw material. The extracted cellulose from the substrate with homogeneous acetylation process, transformed into cellulose acetate …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 51–62 Read article
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Autonomous 6G Physical Layer Architectures for Space-Air-Ground Integrated Networks
Abstract: The emergence of sixth generation (6G) wireless systems calls for a significant shift away from conventional deterministic communication models. As communication infrastructures evolve into Space- Air-Ground Integrated Networks (SAGIN), traditional physical layer (PHY) techniques struggle to operate effectively under the severe Doppler effects and long propagation delays associated with space environments. This paper examines the role of artificial intelligence embedded directly within the 6G transceiver architecture to enable ultra-reliable and …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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Cardiac Structural and Functional Changes in Anaemia: A 2D Echocardiographic Study in an Indian Population
Abstract: Anemia is a widespread global health concern, particularly prevalent in developing countries, like India, where it contributes significantly to cardiovascular morbidity. This study aimed to evaluate cardiac structural and functional changes in anaemic patients using 2D echocardiography and to assess correlations between haemoglobin levels and echocardiographic parameters. A cross-sectional observational study was conducted on 125 anaemic patients (defined as haemoglobin <13 g/dL in males and <12 g/dL in females) at …
Published in Research and Reviews: A Journal of Medicine · Vol. 16, Issue 2, 2026 · pp. 39–44 Read article
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Predicting Dielectric Constants of Polymers Using Molecular Structural Descriptors and Explainable Machine Learning: A Data-Driven Approach
Abstract: Accurate prediction of dielectric constants in polymeric materials is fundamental to the rational design of advanced electronic components, energy storage capacitors, flexible substrates, and high-frequency communication circuits. Conventional approaches to identifying suitable polymer dielectrics rely on extensive experimental synthesis and characterisation, which are both time-consuming and resource-intensive. In this work, an explainable machine learning framework is developed to predict the dielectric constant of polymers directly from molecular structural descriptors derived …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 297–304 Read article
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Early Pregnancy Levels of Fasting Glucose, HbA1c, and Adiponectin as Predictors of Gestational Diabetes Mellitus Among Pregnant Women in Tamil Nadu, India
Abstract: Background: Gestational diabetes mellitus (GDM) is rapidly becoming a major public health issue across India, and Tamil Nadu continues to report some of the country’s highest incidence figures. Identifying women at elevated risk during the first trimester allows health workers to intervene early and improve outcomes for both mothers and babies. This research, therefore, examines whether fasting plasma glucose, glycated haemoglobin, and adiponectin measured at that initial visit can reliably …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 2, 2026 · pp. 10–18 Read article