Development of a Multi-Modal Cervical Spine Motion Analysis System for Cervical Spondylosis Assessment See

Cervical spondylosis is typically assessed with global range-of-motion tests that miss level-specific dysfunction and do not quantify mechanical loading on the cervical spine. This project proposes a portable system with three inertial sensors at the forehead, C1, and C7 to capture segment-level kinematics during standardized movements and daily-task postures. Filtered orientation signals are resampled and segmented into clean trials, then converted to relative angles for upper (Head-C1) and ...

Enhancing Pneumonia Detection from Chest X-Rays Using Probabilistic Pooling with Pretrained CNN Backbones See

Pneumonia is a significant global health problem, especially among vulnerable populations. Although chest X-rays are commonly used for diagnosis, their interpretation is subjective and prone to variability. Deep learning has improved medical image analysis, while convolutional neural network (CNN) architectures are limited by pooling methods. This work investigates a probabilistic pooling mechanism (ProbPool) that uses softmax-based spatial weighting to include diagnostically salient regions ...

Shannon Entropy Based DDoS Attack Detection Using Adaptive Threshold See

Distributed Denial of Service (DDoS) attacks pose a significant threat to high-speed networks. This paper proposes a lightweight entropy-based DDoS detection method using Shannon entropy combined with adaptive statistical thresholding. The approach calculates entropy values of network traffic and dynamically determines thresholds based on mean and standard deviation to classify traffic into normal, suspicious, and attack states. The proposed method is evaluated using benchmark datasets such a...

Probing the Jet Power of the Blazar OJ 287 from Multiwavelength Broadband SED Modelling See

OJ 287 is one of the most extensively studied blazars and exhibits strong variability across the entire electromagnetic spectrum, making it an ideal laboratory for investigating the physics of relativistic jets and their connection to the central supermassive black hole. In this work, we explore the jet energetics of OJ 287 through detailed multiwavelength spectral energy distribution (SED) modelling using quasi-simultaneous observations spanning the optical/UV, X-ray, and high-energy γ-ray b...

Probing Exotic Core Phases of Neutron Stars through Spacetime Curvature in Modified Gravity See

Neutron stars (NSs), superdense objects with exceptionally strong gravitational fields, provide an ideal laboratory for exploring general relativity (GR) in the high-curvature regime. They also present an exciting opportunity to investigate new gravitational physics beyond the traditional framework of GR. Thus, investigating modified theories of gravity in the context of superdense stars is intriguing and essential for advancing our understanding of gravitational phenomena in extreme environm...

Active Polymer Models: Unravelling the 3D Organization and Dynamics of Chromosomes See

Genome organization refers to how genetic material (DNA) is arranged, packaged, and regulated inside a cell. It operates at multiple hierarchical levels - nucleotide sequence to 3D spatial arrangement in the nucleus, and is crucial for gene regulation, replication, and evolution. Recent studies on chromosomal dynamics reveal that chromatin behaves neither like a passive elastic fiber nor a perfectly orderly folded structure, but as an active, viscoelastic polymer driven by both thermal fluctu...

Investigating the Emerging Neurotoxic Potential of Acetonitrile-d3 in a Zebrafish Model: Implications for Human Mental Health See

Acetonitrile-d3 is a commonly used solvent in the chemical and pharmaceutical industries. However, it has become a growing environmental pollutant with potential neurotoxic effects that are not well understood Ahmed et al [1]. The rise in industrial discharge containing acetonitrile-d3 raises concerns about its impact on aquatic ecosystems and vertebrate neurobiology. This is particularly concerning due to the compound’s capacity to disrupt ionic balance and impair neurotransmitterfunction. T...

Seasonal and Anthropogenic Controls on Slow-moving Landslides: A Case Study of Uttarakhand Himalaya, India See

The 2023 landslide event in Joshimath, Uttarakhand Himalaya, signifies the coupling between hydrological cycles and anthropogenic modifications in controlling long-term slope instability of slow moving landslides (SMLs). Using multi-temporal Interferometric Synthetic Aperture Radar (InSAR) data spanning from 2017 to 2023, combined with field observations, land use land cover analysis, and numerical modeling, we quantify the temporal evolution, driving mechanisms, and potential failure scenari...

Projection of Epigenetic Markers of Type 2 Diabetes Reveal Pancreatic Cancer Prognostic Tumour States See

Type 2 diabetes (T2D) and Pancreatic Duct Carcinoma (PDAC), are two diseases with a chronic metabolic disorder related to a deregulated cellular energy metabolism, insulin resistance and an increased inflammatory reaction within the organism. T2D Literature suggests that the metabolic dysregulations related to T2D are known to be implicated in the progression of PDAC, yet it is unclear whether the epigenetic alterations associated with T2D are similarly altered in pancreatic tumours. In this ...

Synthesis of gamma alumina (γ-Al2O3) from waste aluminium foil and its application in adsorptive removal of Malachite Green (MG) Dye from wastewater See

This study explores the sustainable synthesis of gamma alumina from waste aluminium foil and its efficacy in separating Malachite Green (MG) dye from water-based solutions. The synthesis process involves the transformation of waste aluminium foil into gamma alumina through a controlled procedure using Hydro Chloric Acid and Sulfuric Acid. The structural and morphological properties of the obtained γ-Al2O3 are characterized using BET, FTIR, FESEM, and XRD. The γ-Al2O3 is then employed as an ad...

Hydrographic features in the Tropical Indian Ocean: Insights from coupled and uncoupled models from the CMIP6 group See

Coupled Model Intercomparison Project (CMIP) and Ocean Model Intercomparison Project phase 2 (OMIP2) models from the 6th phase of the CMIP group were used in the current study to represent the annual mean biases of hydrographic features. The OMIP2 models are ocean-only simulations, while the CMIP models are coupled ocean-atmosphere-land-sea ice simulations. These models are assessed against the observations in the Tropical Indian Ocean (TIO). This study identified that many of the models...

Building Trust Through Green Marketing: Examining Repurchase Intention in Peer-to-Peer Lodging Platforms See

The global popularity of sharing accommodation platforms has significantly influenced consumer behavior over the past decade. This study investigates how green marketing orientation, trust in the platform, and green image affect consumers' repurchase intentions on such platforms. Data were collected from users aged 18 and older in New Delhi, India, who had prior experience with sharing accommodation platforms. Confirmatory factor analysis and structural equation modeling were employed to anal...

The Impact of Source Credibility Dimensions on Customer Engagement and Purchase Intention in Virtual Influencer Marketing See

The use of virtual influencers (VIs) or computer-generated characters has changed traditional influencer marketing, but the mechanisms driving their convincing effectiveness remain empirically underexplored. Based on Source Credibility Theory this study investigates how three core attributes of virtual influencers expertise, attractiveness, and trustworthiness influence customer engagement and, subsequently, purchase intention. The data were collected from active social media users familiar w...

Bot with a Heart: Can AI-Bot Sensory Experience and Employee Sustainability Manufacture Happiness? See

Within the current VUCA technological environment, manufacturing industry in emerging countries faces serious challenges, such as disengagement of employees, increased stress levels, and high turnover rate. Even though artificial intelligence (AI) is increasingly being incorporated into work processes, little research has been conducted on AI and its impact on the emotional reactions of employees. Thus, this research fills this gap by using outside-in perspective to investigate the impact of ...

Influence of Conventional Shot Peening on Adhesion, Microstructure, and Corrosion Resistance of Electrodeposited Nickel Coatings on Copper See

Copper is highly vulnerable to degradation in corrosive environments, necessitating effective surface protection strategies. In this study, nickel coatings were electrodeposited onto copper substrates to improve their properties. However, the as-deposited coatings exhibited inadequate adhesion with surface defects, indicating the need for an additional post-treatment. To overcome this limitation, a surface mechanical treatment through conventional shot peening (CSP) was employed to refine the...

From Point to Batch: Advancing Incremental Clustering with Mass-based Dissimilarity See

Non-incremental clustering algorithms (NICLAs) dealing with dynamic data suffer from issues related to their compute-intensive behaviour. A plausible approach to address these issues lie in transforming the NICLAs into intelligent (incremental) methods that are capable of processing dynamic data. MBSCAN is one such robust NICLA that leverages the idea of data-dependent dissimilarity to find clusters. An incremental version of MBSCAN namely 𝑖𝑀𝑎𝑠𝑠 was designed to handle single-point inser...

Digital Coded Metasurface Design Based on Deep Learning Technique: A Study See

This paper presents a comprehensive study of advanced techniques for designing digitally coded metasurfaces, highlighting their ability to manipulate electromagnetic wave propagation. Five key methodologies are investigated and compared: Back Projection (BP), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Superposition, and Deep Learning (DL). While the computationally efficient BP method is suitable for single-beam configurations, it is inadequate for multi-beam or complex radiat...

Antiproliferative and Anti-Metastatic effects of ethanolic Leaf Extract of Cascabela Thevetia against Cholangiocarcinoma Cells See

Cascabela thevetia (syn. Thevetia peruviana) is a medicinally important flowering plant traditionally used for the treatment of wounds, skin infections, tumours, and other ailments. With the increasing incidence of multidrug-resistant (MDR) bacterial infections and aggressive cancers such as cholangiocarcinoma, the present study aimed to evaluate the phytochemical composition, antibacterial activity, and anticancer potential of C. thevetia leaf and flower extracts. Ethanolic and aqueous extra...

Synergistic polymicrobial biofilm of Pseudomonas oryzihabitans GAT2212B and Aspergillus niger KCRE2202F as a blue biotechnological strategy to enhance the growth of mangrove Avicennia officinalis L. See

Mangrove ecosystems are a foundational pillar of the emerging blue economy. However, environmental stressors such as salinity fluctuations, pollution, and climate change threaten mangrove survival and regeneration. This study aim to evaluate the role of a synergistic polymicrobial bacterial-fungal inoculum as a blue biotechnology strategy to promote seed germination and enhance the growth of Avicennia officinalis L.. Amplicon-based metagenomic analysis revealed 1,372 bacterial and 2...