This study investigates the structural, thermal, and mechanical properties of Se–Te–Cd chalcogenide glassy alloys by introducing Cd doping into the Se₉₀Te₁₀ system....
PEDOT:PSS-based hydrogel strain sensors have been widely adopted in wearable electronics, human-machine interfaces, and flexible electronics, owing to their wide...
This study presents an energy-aware path-tracking framework for autonomous mobile robots using an Enhanced Whale Optimization Algorithm (E-WOA) to tune a fractional-order...
Tech Science Press is pleased to announce the latest enhancements to the Intelligent Journal System (IJS), introducing an updated interface and a series of workflow improvements to support manuscript...
On 17 June, Clarivate released the 2026 edition of the Journal Citation Reports (JCR). In this year's release, 18 journals published by Tech Science Press (TSP) have received their updated...
Flaviviruses, including Dengue, West Nile, Zika, and Japanese encephalitis viruses, are arthropod-borne RNA viruses that pose an increasing global health...
Cytokines, as key signaling molecules, are involved in the regulation of physiological and pathological processes such as inflammation, immunity, and...
Severe immune-mediated complications following viral infections and vaccinations, including COVID-19 and anti–SARS-CoV-2 immunization, display remarkable...
Structural health monitoring (SHM) of ship piping systems is a core component of predictive maintenance strategies for complex marine engineering systems....
In bearing fault diagnosis for Prognostics and Health Management (PHM), the overall performance of data-driven models is strongly influenced by the coupled...
In industrial and service robotics, autonomous mobile robots must achieve accurate trajectory tracking while maintaining low energy consumption to avoid...
Objectives: Metabolic substrate deficiency is a key factor in many pathologies, with organ vulnerability depending on specialized metabolic profiles....
Cellular senescence and the Senescence-Associated Secretory Phenotype (SASP) play both physiological and pathological roles in the cardiovascular system....
Enterovirus 71 (EV71), a member of the family Picornaviridae, genus Enterovirus, is an agent of hand, foot, and mouth disease (HFMD) and remains a persistent...
Nowadays, battery electric vehicles are increasingly used, from passenger cars to heavy-duty commercial vehicles, trains, and ships, all in an effort...
The big challenge in developing wind energy over the past century, which has focused on environmentally friendly production methods to meet the requirements...
In response to the high energy consumption, large load fluctuations, and insufficient adaptability associated with conventional control strategies in...
Breast cancer (BC) is the most frequently diagnosed malignancy in women worldwide and remains one of the leading causes of cancer-related mortality, with...
Classic Hodgkin lymphoma (CHL) constitutes a B-cell malignant lymphoid neoplasm derived from the germinal center. Despite current treatment protocols...
Antibody–drug conjugates (ADCs) are a promising strategy in non-small cell lung cancer (NSCLC), but early-generation drugs were limited by suboptimal...
Unfavorable epidemiological forecasts indicating a significant increase in cancer incidence and mortality, as well as limitations of traditional cancer...
The rapid evolution of chemical biology, medicinal chemistry, and molecular pharmacology continues to drive the discovery of innovative anticancer compounds...
Cancer development and therapeutic response are governed not only by genetic alterations but also by dynamic regulatory mechanisms at the epigenetic and...
The transition toward decentralized smart grids is reshaping the way energy is generated, exchanged, controlled, and consumed. The increasing penetration...
Cancer remains one of the leading causes of morbidity and mortality worldwide, and its onset and progression are closely linked to dysregulated epigenetic...
The tumor microenvironment (TME) plays a crucial role in cancer progression, metastasis, and resistance to therapy, prompting a shift in focus from targeting...
Tumor biomarkers have become an essential foundation for advancements in cancer diagnosis, prognosis, and targeted therapy. As oncology moves towards...
We propose a special issue titled "Innovative Smart Polymeric Materials for Sustainable Energy Solutions: Bridging Advances in Energy and Biomedical...
Artificial Intelligence of Things (AIoT) is considered a collaborative application of artificial intelligence (AI) and the Internet of Things (IoT). The...
Flaviviruses, including Dengue, West Nile, Zika, and Japanese encephalitis viruses, are arthropod-borne RNA viruses that pose an increasing global health...
Cytokines, as key signaling molecules, are involved in the regulation of physiological and pathological processes such as inflammation, immunity, and...
Severe immune-mediated complications following viral infections and vaccinations, including COVID-19 and anti–SARS-CoV-2 immunization, display remarkable...
Structural health monitoring (SHM) of ship piping systems is a core component of predictive maintenance strategies for complex marine engineering systems....
In bearing fault diagnosis for Prognostics and Health Management (PHM), the overall performance of data-driven models is strongly influenced by the coupled...
In industrial and service robotics, autonomous mobile robots must achieve accurate trajectory tracking while maintaining low energy consumption to avoid...
Objectives: Metabolic substrate deficiency is a key factor in many pathologies, with organ vulnerability depending on specialized metabolic profiles....
Cellular senescence and the Senescence-Associated Secretory Phenotype (SASP) play both physiological and pathological roles in the cardiovascular system....
Enterovirus 71 (EV71), a member of the family Picornaviridae, genus Enterovirus, is an agent of hand, foot, and mouth disease (HFMD) and remains a persistent...
Nowadays, battery electric vehicles are increasingly used, from passenger cars to heavy-duty commercial vehicles, trains, and ships, all in an effort...
The big challenge in developing wind energy over the past century, which has focused on environmentally friendly production methods to meet the requirements...
In response to the high energy consumption, large load fluctuations, and insufficient adaptability associated with conventional control strategies in...
Breast cancer (BC) is the most frequently diagnosed malignancy in women worldwide and remains one of the leading causes of cancer-related mortality, with...
Classic Hodgkin lymphoma (CHL) constitutes a B-cell malignant lymphoid neoplasm derived from the germinal center. Despite current treatment protocols...
Antibody–drug conjugates (ADCs) are a promising strategy in non-small cell lung cancer (NSCLC), but early-generation drugs were limited by suboptimal...
Unfavorable epidemiological forecasts indicating a significant increase in cancer incidence and mortality, as well as limitations of traditional cancer...
The rapid evolution of chemical biology, medicinal chemistry, and molecular pharmacology continues to drive the discovery of innovative anticancer compounds...
Cancer development and therapeutic response are governed not only by genetic alterations but also by dynamic regulatory mechanisms at the epigenetic and...
The transition toward decentralized smart grids is reshaping the way energy is generated, exchanged, controlled, and consumed. The increasing penetration...
Cancer remains one of the leading causes of morbidity and mortality worldwide, and its onset and progression are closely linked to dysregulated epigenetic...
The tumor microenvironment (TME) plays a crucial role in cancer progression, metastasis, and resistance to therapy, prompting a shift in focus from targeting...
Tumor biomarkers have become an essential foundation for advancements in cancer diagnosis, prognosis, and targeted therapy. As oncology moves towards...
We propose a special issue titled "Innovative Smart Polymeric Materials for Sustainable Energy Solutions: Bridging Advances in Energy and Biomedical...
Artificial Intelligence of Things (AIoT) is considered a collaborative application of artificial intelligence (AI) and the Internet of Things (IoT). The...
Accurate energy consumption forecasting faces two major challenges: limited historical data and complex consumption patterns. To address these challenges, this study proposes a new hybrid framework named the Decomposition-based Grey-Neuro-Fuzzy Architecture (DeGNA). The model first uses the Denton method to convert limited annual records into high-frequency monthly data. Next, it applies STL decomposition to separate the data into trend, seasonal and residuals components. A rolling-window GM(1,1) model is then used to predict the main growth…
The basic operation of a mobile robot is navigating to some target, avoiding collisions and possibly minimizing other criteria. A diversity of methods have been developed since the past century, and the research is still active, but there is one aspect that is often neglected: the duration of the steps in which computational devices divide the navigation process. Usually, it is set heuristically to a small, constant value for sampling observations frequently enough to ensure…
High-resolution remote sensing semantic segmentation is a fundamental task in Geospatial Artificial Intelligence (GeoAI). Existing CNN-based methods are effective for local and multiscale feature extraction but often lack progressive cross-scale semantic propagation, while attention- and Transformer-based methods improve global spatial modeling but generally ignore frequency-domain regularities. To address these limitations, this study proposes a Multiscale Long-Distance Feature Aggregation Network (MLFANet), a unified spatial-frequency segmentation framework for high-resolution remote sensing imagery. MLFANet introduces three key components:…
Traditionally, speech emotion recognition has relied on supervised models that require task-specific training and annotated data. However, the recent emergence of audio-language models introduces a more flexible paradigm that enables multimodal reasoning through speech and natural language interaction. Nevertheless, their effectiveness for emotion recognition remains unclear. In this study, we evaluate audio-language models for speech emotion classification using the Spanish MEACorpus dataset and compare three approaches: prompt-based inference, embedding-based classification with lightweight classifiers, and instruction-tuned…
Kawasaki disease (KD) is an acute, self-limited pediatric vasculitis of unknown etiology and is one of the leading causes of acquired coronary artery complications in children. Endothelial dysfunction, vascular endothelial growth factor (VEGF) activity, adhesion molecule/chemokine activation, and inflammatory cytokine responses play important roles in its pathogenesis. This paper presents a delay differential equation model with stochastic perturbations to study lesion-level inflammatory mechanisms involved in Kawasaki disease pathogenesis. The model describes interactions among healthy endothelial…
A single droplet heating, vaporization, and detailed combustion model is developed for pure
In the era of artificial intelligence, pattern recognition techniques have become fundamental in advancing medical image processing, diagnosis, and automated disease classification systems. Among various clinical challenges, breast cancer is the second most dangerous leading cause of death in women worldwide. Early and accurate detection of breast cancer is crucial to develop advanced diagnostic methods to control further loss or reduce mortality rates. This study proposes a dynamic graph multi-scale network for breast cancer diagnosis,…
This study investigates the passive amplification of aerodynamic excitation forces through coordinated bluff-body geometric modifications to quantify the vortex-induced vibration (VIV) energy harvesting potential of stationary cylinders in the laminar regime. Two-dimensional laminar simulations on fixed bodies isolate geometric effects from structural feedback. Circumferential biomimetic grooves are first optimised on a circular baseline at
Digital pathology is rapidly transforming histopathological diagnosis, yet many existing deep learning models treat all spatial regions uniformly and do not exploit the multi-frequency structure of tissue, which limits both diagnostic accuracy and computational efficiency. This paper proposes WaSA-Net, an end-to-end architecture that integrates three complementary modules for histopathological image analysis. First, the Wavelet-Guided Tokenization (WGT) module decomposes input images into frequency-aware representations using learnable wavelet-like filters, so that both global tissue structures and fine-grained…
Optimal task assignment in holonic multi-agent systems has emerged as a pivotal problem in modern distributed systems. Despite substantial gains in agent coordination, many large-scale systems still suffer from poor job allocation, resulting in performance bottlenecks and resource waste. Effective task assignment is critical for these systems since it influences individual agent performance and overall adaptability. A significant challenge within holonic multi-agent systems is ensuring optimal task assignment while resolving performative inconsistencies, such as role…
Body armor prevents projectile penetration, but thoracic visceral injury may still result from pressure-wave transmission and back-face deformation. However, thoracic responses to single and multiple impacts remain insufficiently understood, numerical human thoracic models need further validation, and load transfer between the rib cage and cardiopulmonary system remains unclear. Therefore, this study combined live-fire blunt-impact tests on a biomimetic thoracic target with a human thoracic finite element model with filled thoracic cavity gaps. Load transfer and…
Bearing fault diagnosis in industrial deployment must contend with two simultaneous distributional shifts: fault severity increases as damage progresses, and motors operate at loads unseen during training. We define this compound setting as the double domain shift and present a rigorous few-shot benchmark on the Case Western Reserve University (CWRU) and Paderborn University (PU) bearing datasets. Six architectures spanning distinct learning paradigms—a multilayer perceptron (MLP), a capsule network (CapsNet), a residual capsule network (ResCaps), a prototypical…
The Animated Oat Optimization Algorithm (AOO) is a novel evolutionary algorithm inspired by the behavior of animated oats. This paper proposes a Competitive Parallel Animated Oat Optimization Algorithm (CPAOO) comprising two components. First, a parallel strategy is employed in which inter-subpopulation communication is triggered at predefined iteration thresholds to balance exploration and exploitation. Second, a grouped competition strategy with incentive mechanisms is introduced, enabling the prioritized evolution of superior individuals to enhance the algorithm’s efficiency.…
Climate change modifies environmental exposure conditions and affects the corrosion-driven deterioration of steel bridges, thereby challenging conventional maintenance planning approaches. Thus, more advanced maintenance management strategies are required to address the challenges associated with varying corrosion rate projections. In this study, a novel adaptive maintenance management framework is proposed for steel truss bridges to address climate change-induced corrosion under evolving deterioration conditions. Adaptivity is achieved by updating corrosion rates to consider time-varying deterioration conditions associated…
Future mobile Internet and convergence applications increasingly rely on encrypted protocols, making security monitoring difficult because payload inspection is unavailable while traffic classes and threats evolve continuously. Encrypted traffic classification models must therefore adapt to newly emerging traffic classes without repeatedly overwriting or fully retraining large Transformer backbones. This study presents and extends an ET-BERT Adapter Fusion framework for AI/ML-driven encrypted-traffic security monitoring in future mobile Internet and convergence applications. The framework keeps the ET-BERT…
The resilient modulus (MR) is a key mechanical parameter in geotechnical engineering, but conventional laboratory measurement is time-consuming and labor-intensive. Deep learning models provide an alternative for predicting MR using easily obtainable soil properties, yet their performance is often limited by the small size of available datasets. To address this limitation, this study develops an interpretable data-enhanced deep learning framework for MR prediction. In the proposed framework, a multilayer perceptron (MLP) is adopted as the base prediction…
Guest Editors: Hung-Yu Lin; Hsing-Ju Wu Deadline: 31 May 2027
Guest Editors: Carlos Vargas-Salgado; Dácil Diaz-Bello Deadline: 30 April 2027
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Guest Editors: Wenlong Sun; Mengyao Li Deadline: 31 March 2027
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Guest Editors: Wei-Chiang Hong; Yi Liang; Ming-Wei Li; Zhong-Yi Yang Deadline: 15 February 2027
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Guest Editors: Denise Mafra; Jessyca Sousa de Brito Deadline: 31 January 2027
Guest Editors: Qi Chen; Yunhui Tang Deadline: 31 December 2026
Guest Editors: Hung-Yu Lin Deadline: 31 December 2026
Guest Editors: Hoon Ko; Marek R. Ogiela Deadline: 31 December 2026
Guest Editors: Víctor García Deadline: 31 December 2026
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