http://localhost:80/xmlui/handle/123456789/1057 PUB Sun, 07 Jun 2026 15:03:19 GMT 2026-06-07T15:03:19Z http://localhost:80/xmlui/handle/123456789/11244 Title: A novel molecularly imprinted graphene-graphite conductive paper electrode for selective electrochemical detection of hyaluronic acid in cosmetic formulations Authors: Ghorai, Santanu; Dhara, Milan; Banerjee, Sanjoy; Ahamed, Sk Sohel; Biswas, Don; Naskar, Sudip; Sarkar, Utsa; Das, Nityananda; Mandal, Dipankar; Bandyopadhya, Rajib; Tudu, Bipan Sat, 01 Aug 2026 00:00:00 GMT http://localhost:80/xmlui/handle/123456789/11244 2026-08-01T00:00:00Z http://localhost:80/xmlui/handle/123456789/11243 Title: Precise oxygen therapy to emphysema patients by fuzzy-based gain tuning control of set-point regulated MRAC Authors: Pal, A.K.; Naskar, Indrajit Abstract: Emphysema, a primary component of chronic obstructive pulmonary disease (COPD), causes progressive dyspnea through the destruction of alveolar membranes. This structural degradation reduces the available surface area for gas exchange, significantly impairing oxygen delivery to the bloodstream. While oxygen therapy is a critical intervention, the inherent physiological complexities, specifically transit time delays and dynamic respiratory demands, make precise oxygen regulation exceptionally difficult. To address these challenges, this study develops a comprehensive mathematical model of the emphysema-affected respiratory system, incorporating specific parameters for time delays in oxygen exchange. A novel Intelligent Set-point Modulated Fuzzy Model Reference Adaptive Controller (SFMRAC) is proposed to enhance oxygen regulation. This control architecture advances traditional Model Reference Adaptive Controller (MRAC) by integrating a normalization factor, fuzzy logic tuning, and set-point modulation. This hybrid approach allows the system to adapt to nonlinear physiological variations and maintain stability despite the transit delays characteristic of damaged pulmonary tissue. The effectiveness of the SFMRAC was evaluated through a simulation study conducted in MATLAB/Simulink. Results demonstrate that the proposed controller provides superior tracking performance and robustness compared to MRAC, particularly when subjected to varying set-points and significant exchange delays. The results suggest that the SFMRAC offers a promising computational framework to improve the automated delivery of oxygen therapy in clinical settings for COPD patients. Thu, 01 Jan 2026 00:00:00 GMT http://localhost:80/xmlui/handle/123456789/11243 2026-01-01T00:00:00Z http://localhost:80/xmlui/handle/123456789/10962 Title: A novel Alzheimer detection rapid-testing low-cost technique by a gate engineered gate stack dual-gate FET device Authors: Kolay, Anirban; Kumar, Amitesh Abstract: This study explores a quick, low-cost method to detect Alzheimer's disease (AD) by evaluating the accomplishment of a Gate-Stack (GS) Field Effect Transistor (FET). We investigate Single-Metal (SM), Dual-Metal (DM), and Tri-Metal Double Gate (DG) configurations, where cavities have been created by etching the oxide layer underneath the gate to immobilize grey matter samples collected through Solid-phase microextraction (SPME). Healthy and AD-affected grey matter have different dielectric characteristics at high frequencies. The dielectric constant of the etched nanocavities changes when the sample, which was formerly filled with air, is immobilized in the nanocavities. The alteration in the device drain current as well as performance at 2.4 GHz has been connected to the specimen's modified dielectric constant. To distinguish between the grey matter samples from AD patients and healthy individuals, the of the suggested device along with the variation in device drain current, has been utilized as the foundation for the identification. The SM configuration has been examined by varying the cavity orientation and gate oxide stacking. To monitor the functioning of the suggested devices, the gate metal of the DM and TM devices has been altered, and a comparison has been made between SM, DM, and TM structures. The other recorded work from literature has been compared with the suggested detection technique. To ascertain whether the sample is impacted by AD, the proposed method can be used as a point of care (POC) diagnosis. Tue, 01 Apr 2025 00:00:00 GMT http://localhost:80/xmlui/handle/123456789/10962 2025-04-01T00:00:00Z http://localhost:80/xmlui/handle/123456789/10959 Title: A Blockchain-Based Distributed and Intelligent Clustering-Enabled Authentication Protocol for UAV Swarms Authors: Karmakar, Raja; Kaddoum, Georges; Akhrif, Ouassima Abstract: Unmanned aerial vehicles (UAVs) are operated remotely without the presence of a unified system of identity authentication, and wireless communications in untrusted environments can cause the loss of valuable data carried by UAVs. Traditional UAV authentication mechanisms are centralized approaches, which suffer from a single point of failure problem and may incur high complexity computations. Therefore, it is crucial to establish a distributed authentication mechanism between the ground station controller (GSC) and a UAV. Moreover, in case of UAV swarms, the high mobility of the UAVs affects the stability of UAV communications, which leads to the degradation of the UAV authentication performance. Addressing these challenges, we design a blockchain-based distributed authentication mechanism, known as SwarmAuth, for UAV swarms, where the GSC and UAVs follow a mutual authentication approach using physical unclonable functions (PUFs), and the K-means clustering-based intelligent approach is used to dynamically create location-based clusters. The blockchain helps store UAVs’ authentication information in an immutable storage and the associated smart contracts provide a convenient access control model. The security analysis of SwarmAuth is carried out through both formal and informal proofs considering general attacks. Experimental evaluation shows that SwarmAuth can assure trustworthy communications and improve the network performance. Sun, 05 May 2024 00:00:00 GMT http://localhost:80/xmlui/handle/123456789/10959 2024-05-05T00:00:00Z