Lijia Li, Shu Liu, Xiaoliang Huang^*, Zhilin Qi

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.1, 2026, DOI:10.32604/fdmp.2026.073294 - 06 February 2026

Abstract Identifying geohazards such as landslides and methane leakage is crucial during gas extraction from natural gas hydrate (NGH) reservoirs, and understanding reservoir settlement behavior is central to this assessment. Horizontal wells can enlarge the pressure relief zone within the formation, improving single-well productivity, and are therefore considered a promising approach for NGH development. This study examines the settlement response of hydrate-bearing sediments during depressurization using horizontal wells. A fully coupled thermal, hydraulic, mechanical, and chemical (THMC) model with representative reservoir properties (Shenhu region in the South China Sea) is presented accordingly. The simulations show that More >

Bárbara Polo-Martín^*

Revue Internationale de Géomatique, Vol.35, pp. 53-78, 2026, DOI:10.32604/rig.2026.071069 - 05 February 2026

Abstract The expansion of transportation networks, including railways and ports, has been a major force driving urban growth, mobility, and socio-economic transformations since the Industrial Revolution. This study utilizes Historical Geographic Information Systems to examine the global evolution of transportation infrastructure, focusing on railways and ports, from 1880 to 2020. The dataset enables a multidimensional analysis of how transportation systems have shaped cities, influenced regional development, and helped to make possible sustainability efforts. By offering insights into transport accessibility, land-use changes, and economic connectivity, the study provides a robust empirical foundation for understanding long-term infrastructure dynamics. More >

Nuh Azginoglu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2026.075834 - 29 January 2026

Abstract Breast cancer screening programs rely heavily on mammography for early detection; however, diagnostic performance is strongly affected by inter-reader variability, breast density, and the limitations of conventional computer-aided detection systems. Recent advances in deep learning have enabled more robust and scalable solutions for large-scale screening, yet a systematic comparison of modern object detection architectures on nationally representative datasets remains limited. This study presents a comprehensive quantitative comparison of prominent deep learning–based object detection architectures for Artificial Intelligence-assisted mammography analysis using the MammosighTR dataset, developed within the Turkish National Breast Cancer Screening Program. The dataset comprises… More >

Van-Viet Nguyen¹, Huu-Khanh Nguyen², Kim-Son Nguyen¹, Thi Minh-Hue Luong¹, Duc-Quang Vu¹, Trung-Nghia Phung³, The-Vinh Nguyen^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.075442 - 29 January 2026

Abstract It remains difficult to automate the creation and validation of Unified Modeling Language (UML) diagrams due to unstructured requirements, limited automated pipelines, and the lack of reliable evaluation methods. This study introduces a cohesive architecture that amalgamates requirement development, UML synthesis, and multimodal validation. First, LLaMA-3.2-1B-Instruct was utilized to generate user-focused requirements. Then, DeepSeek-R1-Distill-Qwen-32B applies its reasoning skills to transform these requirements into PlantUML code. Using this dual-LLM pipeline, we constructed a synthetic dataset of 11,997 UML diagrams spanning six major diagram families. Rendering analysis showed that 89.5% of the generated diagrams compile correctly, while… More >

Huda Talib Najm^1,2, Ahmed Sabah Al-Araji³, Nur Syazreen Ahmad^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.071837 - 29 January 2026

Abstract Mobile service robots (MSRs) in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions, including model uncertainties and external disturbances. This study presents a cognitive control strategy that integrates a Numerical Feedforward Inverse Dynamic Controller (NFIDC) with a Feedback Radial Basis Function Neural Network (FRBFNN). The robot’s mechanical structure was designed in SolidWorks 2022 SP2.0 and validated under operational loads using finite element analysis in ANSYS 2022 R1. The NFIDC-FRBFNN framework merges proactive inverse dynamic compensation with adaptive neural learning to achieve smooth torque responses and accurate motion control.… More >

Sha Hu^1,2,#, Wenjing Wang^1,#, Qianfang Hu^3,#, Rujuan Zheng^1,2, Qinghe Huang^1,2, Hui Shi^1,2, Xinyuan Ding^3,*, Wenjuan Wang^1,2,*, Zengyan Zhu^1,2,*

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.068967 - 19 January 2026

Abstract Objectives: Acquired resistance to paclitaxel represents a critical barrier to the effective chemotherapy of non-small cell lung cancer (NSCLC). The present study aimed to elucidate the molecular and pharmacological mechanisms promoting paclitaxel resistance in NSCLC and to explore potential strategies for overcoming this resistance. Methods: Here, we report an integrated pharmacological and analytical approach to quantify paclitaxel disposition and overcome resistance in a A549/TAX cell model (paclitaxel-resistant A549 cells). Results: Cell counting kit-8 (CCK-8) assay, colony formation, and apoptosis assays confirmed that A549/TAX cells exhibited marked resistance to paclitaxel relative to parental A549 cells. Based on… More >

Si-Woo Kim, Yong Soo Kim^*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073492 - 12 January 2026

Abstract Predictive maintenance (PdM) is vital for ensuring the reliability, safety, and cost efficiency of heavy-duty vehicle fleets. However, real-world sensor data are often highly imbalanced, noisy, and temporally irregular, posing significant challenges to model robustness and deployment. Using multivariate time-series data from Scania trucks, this study proposes a novel PdM framework that integrates efficient feature summarization with cost-sensitive hierarchical classification. First, the proposed last_k_summary method transforms recent operational records into compact statistical and trend-based descriptors while preserving missingness, allowing LightGBM to leverage its inherent split rules without ad-hoc imputation. Then, a two-stage LightGBM framework is developed… More >

Hang Wen^1,2, Kai Zeng^1,2,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072909 - 12 January 2026

Abstract Federated learning often experiences slow and unstable convergence due to edge-side data heterogeneity. This problem becomes more severe when edge participation rate is low, as the information collected from different edge devices varies significantly. As a result, communication overhead increases, which further slows down the convergence process. To address this challenge, we propose a simple yet effective federated learning framework that improves consistency among edge devices. The core idea is clusters the lookahead gradients collected from edge devices on the cloud server to obtain personalized momentum for steering local updates. In parallel, a global momentum… More > Graphic Abstract

Pham Huy Thong¹, Hoang Thi Canh^2,3,*, Nguyen Tuan Huy⁴, Nguyen Long Giang^1,*, Luong Thi Hong Lan⁴

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071776 - 12 January 2026

Abstract Satellite image segmentation plays a crucial role in remote sensing, supporting applications such as environmental monitoring, land use analysis, and disaster management. However, traditional segmentation methods often rely on large amounts of labeled data, which are costly and time-consuming to obtain, especially in large-scale or dynamic environments. To address this challenge, we propose the Semi-Supervised Multi-View Picture Fuzzy Clustering (SS-MPFC) algorithm, which improves segmentation accuracy and robustness, particularly in complex and uncertain remote sensing scenarios. SS-MPFC unifies three paradigms: semi-supervised learning, multi-view clustering, and picture fuzzy set theory. This integration allows the model to effectively… More >

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 >