Plants use complex strategies to survive cold stress, preventing ice formation and dehydration through hormonal, light, and genetic regulation. During autumn, they...
Endometrial cancer is the most common gynecologic cancer diagnosed in the United States and mortality is on the rise. Advanced and recurrent endometrial cancer...
Prostate cancer diagnosis often relies on systematic biopsy, yet the choice between transperineal and transrectal approaches remains debated. This study leverages...
June 2025 — Tech Science Press (TSP) is pleased to announce that several of its SCI-indexed journals have demonstrated steady and significant growth in their impact indicators, as reported in...
Berlin (Germany) and Henderson (USA), 12 June 2025 – ResearchGate, the professional network for researchers, and Tech Science Press, a publisher of fully open access journals in science...
Legged robots have always been a focal point of research for scholars domestically and internationally. Compared to other types of robots, quadruped robots...
Response analysis of structures involving non-probabilistic uncertain parameters can be closely related to optimization. This paper provides a review...
The evaporation of micrometer and millimeter liquid drops, involving a liquid-to-vapor phase transition accompanied by mass and energy transfer through...
Resource allocation remains a challenging issue in communication networks, and its complexity is continuously increasing with the densification of the...
Accurate medical diagnosis, which involves identifying diseases based on patient symptoms, is often hindered by uncertainties in data interpretation and...
Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation...
Conventional fault diagnosis systems have constrained the automotive industry to damage vehicle maintenance and component longevity critically. Hence,...
Magneto-electro-elastic (MEE) materials are a specific class of advanced smart materials that simultaneously manifest the coupling behavior under electric,...
The emergence of various technologies such as terahertz communications, Reconfigurable Intelligent Surfaces (RIS), and AI-powered communication services...
As Natural Language Processing (NLP) continues to advance, driven by the emergence of sophisticated large language models such as ChatGPT, there has been...
Time series segmentation has attracted more interests in recent years, which aims to segment time series into different segments, each reflects a state...
The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of Vehicles (IoV) technology. The functional...
Software-Defined Networking (SDN) represents a significant paradigm shift in network architecture, separating network logic from the underlying forwarding...
Since the 1950s, when the Turing Test was introduced, there has been notable progress in machine language intelligence. Language modeling, crucial for...
Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item. From ancient times to the present,...
Image steganography is one of the prominent technologies in data hiding standards. Steganographic system performance mostly depends on the embedding strategy....
The tumor microenvironment encompasses not only the tumor cells themselves, but also the surrounding fibroblasts, immunological and inflammatory cells,...
Machine vision detection and intelligent recognition are important research areas in computer vision with wide-ranging applications in manufacturing,...
Object detection and tracking in videos has become an increasingly important area of research due to its potential applications in a variety of domains...
With the progress of science and technology, more and more complex engineering structures are serving in extreme environments. In the service life of...
Extracellular vesicles (EVs) are phospholipid bilayer vesicles released from tumor and non-tumor cells for intercellular communication. EVs contain...
The peridynamics proposed by Silling [1] is a non-local theory of solid mechanics. It redefines the problems by using integral equations rather than partial...
In modern time, experts started to use interdisciplinary properties with the developing of technology and science. Thus, these disciplines provide more...
More than half of the world population is living in cities. It requires extended infrastructure and various services to support the densely concentrated...
Legged robots have always been a focal point of research for scholars domestically and internationally. Compared to other types of robots, quadruped robots...
Response analysis of structures involving non-probabilistic uncertain parameters can be closely related to optimization. This paper provides a review...
The evaporation of micrometer and millimeter liquid drops, involving a liquid-to-vapor phase transition accompanied by mass and energy transfer through...
Resource allocation remains a challenging issue in communication networks, and its complexity is continuously increasing with the densification of the...
Accurate medical diagnosis, which involves identifying diseases based on patient symptoms, is often hindered by uncertainties in data interpretation and...
Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation...
Conventional fault diagnosis systems have constrained the automotive industry to damage vehicle maintenance and component longevity critically. Hence,...
Magneto-electro-elastic (MEE) materials are a specific class of advanced smart materials that simultaneously manifest the coupling behavior under electric,...
The emergence of various technologies such as terahertz communications, Reconfigurable Intelligent Surfaces (RIS), and AI-powered communication services...
As Natural Language Processing (NLP) continues to advance, driven by the emergence of sophisticated large language models such as ChatGPT, there has been...
Time series segmentation has attracted more interests in recent years, which aims to segment time series into different segments, each reflects a state...
The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of Vehicles (IoV) technology. The functional...
Software-Defined Networking (SDN) represents a significant paradigm shift in network architecture, separating network logic from the underlying forwarding...
Since the 1950s, when the Turing Test was introduced, there has been notable progress in machine language intelligence. Language modeling, crucial for...
Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item. From ancient times to the present,...
Image steganography is one of the prominent technologies in data hiding standards. Steganographic system performance mostly depends on the embedding strategy....
The tumor microenvironment encompasses not only the tumor cells themselves, but also the surrounding fibroblasts, immunological and inflammatory cells,...
Machine vision detection and intelligent recognition are important research areas in computer vision with wide-ranging applications in manufacturing,...
Object detection and tracking in videos has become an increasingly important area of research due to its potential applications in a variety of domains...
With the progress of science and technology, more and more complex engineering structures are serving in extreme environments. In the service life of...
Extracellular vesicles (EVs) are phospholipid bilayer vesicles released from tumor and non-tumor cells for intercellular communication. EVs contain...
The peridynamics proposed by Silling [1] is a non-local theory of solid mechanics. It redefines the problems by using integral equations rather than partial...
In modern time, experts started to use interdisciplinary properties with the developing of technology and science. Thus, these disciplines provide more...
More than half of the world population is living in cities. It requires extended infrastructure and various services to support the densely concentrated...
Background: Disaster mental health outcomes of individuals may be affected by the families they inhabit, with effects rippling through the entire family system. Existing research on the experience of children in disasters has typically been limited to examining single individuals or, at most, family dyads. Research is needed to explore interactions within families as a whole, including interactions among multiple family members, as well as with community entities in a broad systems approach with dynamic…
Objectives: Positive family functioning (FF) is critical for adolescent development, yet only a few studies have examined this developmental trajectory pathway. This study aimed to identify different types of FF development trajectories during junior high school students, investigate their influence on social avoidance (SA), and further examine the mediating role of preference for solitude (PS) between them. Methods: A three-wave longitudinal study was used with six-month intervals. Questionnaire data were collected from 436 junior high…
Background: Adverse childhood experiences (ACEs) are a significant issue in adolescent health due to their robust correlation with deficits in executive functions (EF) and health risk behaviors (HRBs). This study aimed to examine the association between ACEs and a range of HRBs, including substance use, sexual risk behavior, suicidal ideation, physical inactivity, and violence. Methods: This cross-sectional study used self-administered questionnaire and cluster sampling in seven junior high schools in Samarinda, Indonesia, with a sample…
Background: The Canadian 24-h movement guidelines (24-HMG) emphasize the holistic consideration of physical activity (PA), sedentary behavior, and sleep in shaping health outcomes. This study aimed to examine the associations between meeting 24-HMG and emotion regulation-related indicators among children and adolescents. Methods: A total of 534 Chinese children and adolescents aged 12.94 ± 1.10 years (49.81% males) participated in this study and completed self-report measures assessing 24-h movement behaviors, emotion regulation strategies, emotion regulation flexibility,…
Background: considering the significant issue of learning burnout among university students, it is essential to investigate the connection between mindfulness and learning burnout. This systematic review and meta-analysis sought to thoroughly examine the direct and indirect relationships between mindfulness and learning burnout. Methods: a comprehensive literature search was conducted in Scopus, Google Scholar, and Web of Science databases until 07 July 2024. A comprehensive literature review analysis of 19 articles was included, which identified three…
Objectives: Social Network Addiction (SNA) is becoming increasingly prevalent among college students; however, there remains a lack of consensus regarding the measurement tools and their optimal cutoff score. This study aims to validate the 21-item Social Network Addiction Scale-Chinese (SNAS-C) in its Chinese version and to determine its optimal cutoff score for identifying potential SNA cases within the college student population. Methods: A cross-sectional survey was conducted, recruiting 3387 college students. Latent profile analysis (LPA)…
Objectives: Emotional exhaustion among healthcare professionals, particularly pharmacists, significantly impacts their well-being and efficacy in patient care. Understanding the psychological mechanisms contributing to emotional exhaustion is essential for developing effective interventions. The present research sought to investigate the potential mediating roles of rumination and coping strategies (adaptive and maladaptive) in the relationship between perceived stress and emotional exhaustion among pharmacists. Methods: A cross-sectional survey was carried out between September 2023 and January 2024 involving 576…
Objectives: College students face increasing mental health challenges. Although Acceptance and Commitment Therapy (ACT) is effective, the efficacy of Internet-based ACT (iACT) needs further exploration. Methods: This study examines the efficacy of iACT on college students’ mental health through a randomized controlled trial. We recruited 90 college students (19.16 ± 1.02 years old) and randomly divided them into the iACT group, face-to-face ACT group, and control group. The effects of the interventions were evaluated using…
The variable salinity in stored reservoirs connected by a long channel attracts the attention of scientists worldwide, having applications in environmental and geophysical engineering. This study explores the impact of Navier slip conditions on exchange flows within a long channel connecting two large reservoirs of differing salinity. These horizontal density gradients drive the flow. We modify the recent one-dimensional theory, developed to avoid runaway stratification, to account for the presence of uniform slip walls. By…
The accelerated global adoption of electric vehicles (EVs) is driving significant expansion and increasing complexity within the EV charging infrastructure, consequently presenting novel and pressing cybersecurity challenges. While considerable effort has focused on preventative cybersecurity measures, a critical deficiency persists in structured methodologies for digital forensic analysis following security incidents, a gap exacerbated by system heterogeneity, distributed digital evidence, and inconsistent logging practices which hinder effective incident reconstruction and attribution. This paper addresses this critical…
As primary load-bearing components extensively utilized in engineering applications, beam structures necessitate the design of their microstructural configurations to achieve lightweight objectives while satisfying diverse mechanical performance requirements. Combining topology optimization with fully coupled homogenization beam theory, we provide a highly efficient design tool to access desirable periodic microstructures for beams. The present optimization framework comprehensively takes into account for key deformation modes, including tension, bending, torsion, and shear deformation, all within a unified formulation.…
Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is a life support intervention for patients with refractory cardiogenic shock or severe cardiopulmonary failure. However, the choice of cannulation strategy remains contentious, partly due to insufficient understanding of hemodynamic characteristics associated with the site of arterial cannulation. In this study, a geometrical multiscale model was built to offer a mathematical tool for addressing the issue. The outflow cannula of ECMO was inserted into the ascending aorta in the case…
Existing power forecasting models struggle to simultaneously handle high-dimensional, noisy load data while capturing long-term dependencies. This critical limitation necessitates an integrated approach combining dimensionality reduction, temporal modeling, and robust prediction, especially for multi-day forecasting. A novel hybrid model, SLHS-TCN-XGBoost, is proposed for power demand forecasting, leveraging SLHS (dimensionality reduction), TCN (temporal feature learning), and XGBoost (ensemble prediction). Applied to the three-year electricity load dataset of Seoul, South Korea, the model’s MAE, RMSE, and MAPE…
Global security threats have motivated organizations to adopt robust and reliable security systems to ensure the safety of individuals and assets. Biometric authentication systems offer a strong solution. However, choosing the best security system requires a structured decision-making framework, especially in complex scenarios involving multiple criteria. To address this problem, we develop a novel quantum spherical fuzzy technique for order preference by similarity to ideal solution (QSF-TOPSIS) methodology, integrating quantum mechanics principles and fuzzy theory.…
The numerical approximation of stochastic partial differential equations (SPDEs), particularly those including q-diffusion, poses considerable challenges due to the requirements for high-order precision, stability amongst random perturbations, and processing efficiency. Because of their simplicity, conventional numerical techniques like the Euler-Maruyama method are frequently employed to solve stochastic differential equations; nonetheless, they may have low-order accuracy and lower stability in stiff or high-resolution situations. This study proposes a novel computational scheme for solving SPDEs arising from…
As vehicular networks grow increasingly complex due to high node mobility and dynamic traffic conditions, efficient clustering mechanisms are vital to ensure stable and scalable communication. Recent studies have emphasized the need for adaptive clustering strategies to improve performance in Intelligent Transportation Systems (ITS). This paper presents the Grasshopper Optimization Algorithm for Vehicular Network Clustering (GOA-VNET) algorithm, an innovative approach to optimal vehicular clustering in Vehicular Ad-Hoc Networks (VANETs), leveraging the Grasshopper Optimization Algorithm (GOA) to…
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