Mingxia Li^1,*, Haowei Xu¹, Ruiqi Li¹, Bo Song², Wanxu Zhu^1,*

Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.075587 - 18 May 2026

Abstract Conventional fiber Bragg grating (FBG) sensors used for tensile monitoring have a limited measurement range and therefore cannot cover the entire service stage of prestressed carbon-fiber-reinforced polymer (CFRP)–strengthened members. In this study, a smart CFRP plate is developed by embedding a wide-range FBG sensor in a prestressed CFRP plate. Based on strain-transfer theory for the grating region, an analytical expression for the average strain-transfer rate is derived and then used to inversely design the groove geometry and bonding parameters; the resulting groove size is 0.5 mm × 0.5 mm. During bonding, a tensile force of… More >

Mosammat Jannatul Kobra¹, Muhammad Rashid Majeed^2,*, Md Owahedur Rahman¹

Journal of Blockchain and Intelligent Computing, Vol.2, pp. 27-44, 2026, DOI:10.32604/jbic.2026.081492 - 13 May 2026

Abstract The proposed study introduces a blockchain-based framework for an adaptive security solution with real-time incident response and usability feedback for non-expert users. Traditional security solutions are often designed with static, opaque policies, which makes them complex. These issues make them less effective in dealing with complex environments. Thus, to make them more effective, the proposed framework introduces supervised machine learning for attack classification, unsupervised machine learning for anomaly detection, a risk-aware, adaptive policy engine, and a lightweight, tamper-evident, hash-linked ledger for auditable decision-making. The proposed framework uses a Random Forest classifier for BENIGN/ATTACK classification, and… More >

Gyuri Han^#, Yun Hee Jeong^#, Ga Eun Kim, Jong-Sup Bae^*

BIOCELL, Vol.50, No.5, 2026, DOI:10.32604/biocell.2026.075139 - 13 May 2026

Abstract Objectives: Plant-derived bioactive molecules are increasingly recognized as valuable therapeutic resources for managing diverse pathological conditions, particularly those involving vascular inflammation. This study aimed to determine whether veratramine (VRT), a naturally occurring steroidal alkaloid found in Veratrum species of the Liliaceae family, attenuates LPS-induced vascular and pulmonary inflammation by upregulating heme oxygenase-1 (HO-1) and modulating the Nrf2, nuclear factor (NF)-κB, and signal transducer and activator of transcription (STAT1) signaling pathways. Methods: The study assessed the modulatory effects of VRT on HO-1, cyclooxygenase-2 (COX-2), and inducible nitric oxide synthase (iNOS) in LPS-activated human umbilical vein endothelial cells… More > Graphic Abstract

Bushra A. Hasan¹, Ameer J. Fadhl², Ahmad A. Hasan¹, Yasser A. Jebbar^3,*

Chalcogenide Letters, Vol.23, No.4, 2026, DOI:10.32604/cl.2026.079634 - 09 May 2026

Abstract Copper zinc tin sulfide selenide, Cu₂ZnSn(S_1−xSe_x)₄, absorbers are promising earth-abundant and environmentally benign materials for low-cost photovoltaic applications. This study investigates the structural and optical properties of Cu₂ZnSn(S_1−xSe_x)₄ nanostructured thin films prepared by pulsed laser deposition using melt-quenched targets with selenium compositions x = 0.0–1.0. X-ray diffraction revealed that films with low selenium content remained amorphous, whereas higher selenium incorporation promoted the formation of polycrystalline kesterite–stannite phases with preferred orientations along (112), (200), (220), and (312). The crystallite size increased from 12.3 to 17.9 nm as selenium reached x = 1.0, indicating enhanced crystal growth. Atomic force… More >

Emir Kuanyshev, Hashim Ali^*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.080737 - 08 May 2026

Abstract Refactoring improves maintainability without altering externally observable behavior, yet it remains costly and error-prone when applied manually at scale. While large language models (LLMs) can generate plausible refactorings, practical adoption is limited by uncontrolled edit scope, inconsistent outputs under stochastic decoding, and weak traceability of why a change was produced. This paper proposes a smell-targeted, scope-bound refactoring framework for JavaScript that couples deterministic AST-based smell detection with constrained LLM transformation. The key design principle is to bind generation to explicitly detected smell instances, enforce a structured output contract (refactored code plus per-smell rationale), and log… More >

Jesús Rosa-Bilbao^*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.080490 - 08 May 2026

Abstract The integration of Internet of Things (IoT) infrastructures with Distributed Ledger Technologies (DLT) remains challenging due to the reliance on complex, tightly coupled back-end systems or centralized oracle services that hinder scalability, maintainability, and trust. This paper introduces a lightweight middleware architecture based on a Low-Code Development Platform (LCDP) that enables flexible and secure IoT-to-blockchain orchestration. We develop a custom workflow extension for the n8n platform that supports direct interaction with smart contracts, thereby removing the need for third-party oracle intermediaries. The proposed system was evaluated in a real-world deployment involving a network of Netatmo More >

Akmalbek Abdusalomov¹, Mukhriddin Mukhiddinov^2,3, Fakhriddin Abdirazakov⁴, Alpamis Kutlimuratov⁵, Nodira Alimova⁶, Ilyos Kalandarov⁷, Ayhan Istanbullu⁸, Rashid Nasimov⁹, Young-Im Cho^1,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.080444 - 08 May 2026

Abstract Recent advancements in AI-synthesized speech have resulted in highly realistic deepfake audio, posing severe threats to authentication systems and digital media trust. Existing detection models struggle to generalize across diverse synthesis methods, especially those involving neural codec-based Audio Language Models (ALMs). In this work, we propose UniTector++, a novel prosody-aware, multi-stream detection architecture that generalizes across vocoder- and codec-based synthesis. UniTector++ incorporates three complementary streams—Whisper-based semantic embeddings, high-level prosodic features, and codec artifact representations—fused through a Multi-Domain Adaptive Graph Attention Fusion (MAGAF) module. Furthermore, an Emotion-Consistency Verification Module (ECVM) reinforces alignment between speech style and More >

Darren Chai Xin Lun, Lim Tong Ming^*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.080068 - 08 May 2026

Abstract The deployment of specialized language models in resource-constrained edge environments (≤1B parameters, ≤2 GB memory, ≤100 ms latency) faces a critical challenge: Supervised Fine-Tuning (SFT) achieves domain expertise but suffers from irreversible catastrophic forgetting, while traditional Low-Rank Adaptation (LoRA) with conservative ranks (r ≤ 64) often underperforms due to insufficient adaptation capacity. This work introduces H-LoRA (High-Rank LoRA) for edge-deployable models and establishes a fundamental distinction between destructive forgetting and controllable knowledge retention. Through comprehensive experiments on compact models (0.12B Minimind and Qwen-0.5B) across three domains (Human Resources, Medical, Mathematics) using 29,647 samples, we… More >

Jinsung Park^1,#, Jaehyuk Lee^1,2,#, Eunchan Kim^1,3,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079734 - 08 May 2026

Abstract Accurate short-term load forecasting is essential for reliable power system operation, particularly under the increasing uncertainty caused by abnormal weather and socio-economic fluctuations. This study presents a month-conditioned boosting framework that integrates SHapley Additive Explanations (SHAPs) into model refinement. A baseline XGBoost model was first compared with linear and tree-based regressors, followed by enhancements through lagged and rolling-window features as well as loss weighting for vulnerable months. To further improve the performance, SHAP analysis was employed to identify the dominant error-contributing features, which guided the construction of targeted month-specific interaction terms for retraining. Experimental results More >

Raza Hasan^*, Shakeel Ahmad, Ismet Gocer, Zakirul Bhuiyan

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079708 - 08 May 2026

Abstract Maritime Domain Awareness (MDA) is critical for global security and economic stability, yet it is increasingly challenged by sophisticated adversarial tactics such as signal spoofing and “dark vessel” activities. Traditional surveillance systems, often reliant on single-sensor modalities, are ill-equipped to handle these deceptive behaviors. To address this, we propose the Multimodal Attention-based Fusion Transformer (MAFT), a novel deep learning architecture that integrates four distinct data modalities—Aerial imagery, Synthetic Aperture Radar (SAR), acoustic signatures, and Automatic Identification System (AIS) data—to achieve robust and interpretable maritime anomaly detection. A key contribution of our work is a principled… More > Graphic Abstract