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147 articles for “Heterogeneous”
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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
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Schizophenia – An Ayurvedic Review and Treatment – A Case study
Abstract: Schizophrenia is a complex, heterogeneous disorder. It is neuro developmental disorder characterized by problems with thinking (cognition),behavior- not focused on goals, negative symptoms, suicidal thoughts This means having a reduced or impaired ability to function normally and having noemotions(notmakingeyecontact,notchangingfacialexpressions,orspeakinginamonotone).Additionally, the person may lose interest in daily activities, withdraw from relationships, or be unable to sustain and reflection often associated with hearing or speech disorders, extreme confusion and associated functional impairments. …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 11, Issue 1, 2024 · pp. 40–48 Read article
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Record Linkage in Knowledge Discovery Process Using Angle Based Machine Learning
Abstract: Record linkage is a critical data cleansing step in the knowledge discovery process, aimed at identifying and resolving inconsistencies across datasets. This study proposes an enhanced record linkage framework tailored for uncertain and large-scale data using a combination of distance measurement, probabilistic modeling, and semantic reasoning. A novel angle-based distance measurement technique is introduced to optimize matching between candidate records. To further boost match accuracy, a Finite Mixture Model (FMM) …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1157–1170 Read article
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Mast Cell Activation Disorders: Diagnosis & Management
Abstract: Mast Cell Activation Disorder (MCAD) is a broad umbrella term which includes a heterogenous group of disorders characterized by the inappropriate and excessive release of mediators from mast cells. Mast Cell Activation Syndrome represents a severe and well-defined form within the broader spectrum of Mast Cell Activation Disorders. These disorders are generally divided into clonal and non-clonal categories. Clonal conditions include Systemic Mastocytosis, Cutaneous Mastocytosis, and Monoclonal Mast Cell Activation …
Published in Research and Reviews : A Journal of Immunology · Vol. 16, Issue 2, 2026 · pp. 31–40 Read article
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A Comparative Study of the Structure-Property Relationships in CAD/CAM Milled vs. 3D-Printed High-Performance Polymers: Impact of Molecular Orientation on Abrasive Wear
Abstract: Background: The transition from subtractive to additive manufacturing in prosthetic dentistry has introduced significant variations in the macromolecular architecture of high-performance polymers. While CAD/CAM milling utilizes high-density, industrially polymerized blocks, 3D printing (Additive Manufacturing) relies on layer-by-layer deposition, which may induce anisotropic molecular orientation. This retrospective study investigates how these distinct manufacturing "thermal histories" influence the long-term abrasive wear resistance of PEEK and PEKK restorations.Materials and Methods: Data were retrospectively …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Artificial Intelligence-Assisted Multi-Objective Optimization of Agricultural Biomass-Reinforced Polymer Composites
Abstract: Agricultural biomass can reduce the environmental burden of polymer composites, yet its heterogeneous structure creates competing effects on strength, moisture resistance, density, and process ability. This study developed an artificial intelligence-assisted framework for balanced composite formulation. Experimental data of agricultural biomass reinforced polymer composites were gathered, harmonized and validated using leakage controlled validation. The mechanical and physical properties were predicted by artificial neural networks and conventional regression models. Explainable analysis …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article