Ping Wu¹, Jie Zou², Wangxin Li^1,*, Yidong Xu¹

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.070873 - 08 January 2026

Abstract The existing 2D settlement monitoring systems for utility tunnels are heavily reliant on manual interpretation of deformation data and empirical prediction models. Consequently, early anomalies (e.g., minor cracks) are often misjudged, and warnings lag by about 24 h without automated spatial localization. This study establishes a technical framework for requirements analysis, architectural design, and data-integration protocols. Revit parametric modelling is used to build a 3D tunnel model with structural elements, pipelines and 18 monitoring points (for displacement and joint width). Custom Revit API code integrated real-time sensor data into the BIM platform via an automated… More >

Abdulrahman K. Sinno¹, Aisha Mustapha¹, Navya Nair¹, Simona Zaami², Lina De Paola², Valentina Billone³, Eleonora Conti³, Giuseppe Gullo^3,*, Pasquale Patrizio⁴

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.072176 - 30 December 2025

Abstract Cervical cancer related to human papillomavirus (HPV) is a leading cause of cancer-related mortality among women worldwide. Cancer cells release fragments of their DNA, known as circulating tumor DNA (ctDNA), which can be detected in bodily fluids. A PubMed search using the terms “ctHPV” or “circulating tumor DNA” and “cervical cancer”, limited to the past ten years, identified 104 articles, complemented by hand-searching for literature addressing medico-legal implications. Studies were evaluated for relevance and methodological quality. Detection and characterization of circulating tumor HPV DNA (ctHPV DNA) have emerged as promising tools for assessing prognosis and More >

Mingoo Kwon, Kyeongmin Kim, Minseok Song^*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 519-537, 2025, DOI:10.32604/cmc.2025.066754 - 29 August 2025

Abstract Efficient edge caching is essential for maximizing utility in video streaming systems, especially under constraints such as limited storage capacity and dynamically fluctuating content popularity. Utility, defined as the benefit obtained per unit of cache bandwidth usage, degrades when static or greedy caching strategies fail to adapt to changing demand patterns. To address this, we propose a deep reinforcement learning (DRL)-based caching framework built upon the proximal policy optimization (PPO) algorithm. Our approach formulates edge caching as a sequential decision-making problem and introduces a reward model that balances cache hit performance and utility by prioritizing More >

Tatsuhito Hasegawa^#,*, Kyosuke Fujino^#

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2429-2454, 2025, DOI:10.32604/cmc.2025.066270 - 03 July 2025

Abstract Recent advances in wearable devices have enabled large-scale collection of sensor data across healthcare, sports, and other domains but this has also raised critical privacy concerns, especially under tightening regulations such as the General Data Protection Regulation (GDPR), which explicitly restrict the processing of data that can re-identify individuals. Although existing anonymization approaches such as the Anonymizing AutoEncoder (AAE) can reduce the risk of re-identification, they often introduce substantial waveform distortions and fail to preserve information beyond a single classification task (e.g., human activity recognition). This study proposes a novel sensor data anonymization method based… More >

Xiaoni Sun¹, Jiming Li², Zhiqiang Zhao², Guodong Jing², Baojun Chen², Jinrong Hu³, Fei Wang², Yong Zhang^1,*

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2121-2149, 2025, DOI:10.32604/cmc.2025.063373 - 03 July 2025

Abstract Weather forecasting is crucial for agriculture, transportation, and industry. Deep Learning (DL) has greatly improved the prediction accuracy. Among them, Graph Neural Networks (GNNs) excel at processing weather data by establishing connections between regions. This allows them to understand complex patterns that traditional methods might miss. As a result, achieving more accurate predictions becomes possible. The paper reviews the role of GNNs in short-to medium-range weather forecasting. The methods are classified into three categories based on dataset differences. The paper also further identifies five promising research frontiers. These areas aim to boost forecasting precision and More >

Rupa Das¹, Roseline Mostafa², Bhaskaran Gopalakrishnan^2,*

Energy Engineering, Vol.122, No.7, pp. 2931-2956, 2025, DOI:10.32604/ee.2025.064887 - 27 June 2025

Abstract Highly energy-efficient buildings have generated remarkable interest over the last few years. There is a need for simulation based effective control systems for efficient usage of electrical and fossil fuel driven devices, as they contribute to energy-efficient buildings and assist in gaining flexibility for the human occupancy-based energy loads. In this context, the integrated energy profile of a building can be ascertained by effective research approaches, as this knowledge would be beneficial to understand the demographics with respect to human occupancy and activities, as well as estimate varying energy consumption over time. Utility data from… More > Graphic Abstract

Ting-Yu Lin¹, Kuo-Chen Hung^2,*, Josef Jablonsky³, Kuo-Ping Lin¹

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1901-1927, 2025, DOI:10.32604/cmc.2025.063543 - 16 April 2025

Abstract VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) has been developed and applied for over twenty-five years, gaining recognition as a prominent multi-criteria decision-making (MCDM) method. Over this period, numerous studies have explored its applications, conducted comparative analyses, integrated it with other methods, and proposed various modifications to enhance its performance. This paper aims to delve into the fundamental principles and objectives of VIKOR, which aim to maximize group utility and minimize individual regret simultaneously. However, this study identifies a significant limitation in the VIKOR methodology: its process amplifies the weight of individual regret, and the calculated… More >

Jie Zou^1,2, Ping Wu^2,*, Jianwei Chen³, Weijie Fan², Yidong Xu²

Structural Durability & Health Monitoring, Vol.19, No.3, pp. 441-471, 2025, DOI:10.32604/sdhm.2024.058864 - 03 April 2025

Abstract As an essential part of the urban infrastructure, underground utility tunnels have a long service life, complex structural performance evolution and dynamic changes both inside and outside the tunnel. These combined factors result in a wide variety of disaster risks during the operation and maintenance phase, which make risk management and control particularly challenging. This work first reviews three common representative disaster factors during the operation and maintenance period: settlement, earthquakes, and explosions. It summarizes the causes of disasters, key technologies, and research methods. Then, it delves into the research on the intelligent operation and More >

Guodong Yuan^1,*, Jin Xie²

Journal on Artificial Intelligence, Vol.7, pp. 1-16, 2025, DOI:10.32604/jai.2025.061437 - 14 March 2025

Abstract This paper addresses the problem of access efficiency in multi-robot systems to the monitoring area. A distributed algorithm for multi-robot continuous monitoring, based on the uncertainty of target points, is used to minimize the uncertainty and instantaneous idle time of all target points in the task domain, while maintaining a certain access frequency to the entire task domain at regular time intervals. During monitoring, the robot uses shared information to evaluate the cumulative uncertainty and idle time of the target points, and combines the update list collected from adjacent target points with a utility function More >

BELARDINILLI FRANCESCA^1,#, MICHELA DE MEO^1,#, FRANCESCO DEL GIUDICE², CARLO MARIA SCORNAJENGHI², PAOLA GAZZANIGA¹, ETTORE DE BERARDINIS², LUCA MARINO³, FABIO MASSIMO MAGLIOCCA⁴, BENJAMIN INBEH CHUNG⁵, JAN ŁASZKIEWICZ⁶, VALENTINA MAGRI⁴, GIUSEPPE GIANNINI^1,7, CHIARA NICOLAZZO^1,*

Oncology Research, Vol.33, No.3, pp. 723-731, 2025, DOI:10.32604/or.2024.056282 - 28 February 2025

Abstract Objectives: Intravesical Bacillus Calmette-Guérin (BCG) therapy is a gold standard for patients with high-risk non-muscle invasive bladder cancer (NMIBC). Although a long-lasting therapeutic response is observed in most patients, BCG failure occurs in 30%–50% of patients and a progression to muscle-invasive disease is found in 10%–15%. Therefore, predicting high-risk patients who might not benefit from BCG treatment is critical. The purpose of this study was to identify, whether the presence of specific oncogenic mutations might be indicative of BCG treatment response. Methods: Nineteen high-grade NMIBC patients who received intravesical BCG were retrospectively enrolled and divided… More > Graphic Abstract