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  • Open Access

    ARTICLE

    Influence of Phenological Stage on the Volatile Content and Biological Properties of Origanum elongatum Essential Oil

    Amine Batbat1,2, Khaoula Habbadi2, Mohamed Jeddi3, Samiah Hamad Al-Mijalli4, Hanae Naceiri Mrabti5, Fahad M. Alshabrmi6, Naif Hesham Moursi7, Hassane Greche1, Naoufal El Hachlafi8,*

    Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2026.072398 - 30 January 2026

    Abstract Origanum elongatum (OE) is an aromatic, medicinal plant endemic to Morocco that is widely used in traditional medicine due to its biological properties. This study aimed to elucidate the chemical composition of the essential oil (EO) obtained from O. elongatum (OEEO) at three stages of its life cycle, including vegetative stage (OEEO-VS), flowering stage (OEEO-FS), and post-flowering (OEEO-PFS), as well as to evaluate its biological and antiradical characteristics. The chemical analysis of the essential oil was conducted using gas chromatography-mass spectrometry (GC-MS). The antibacterial activity was evaluated in vitro through distinct methodologies, namely, disc diffusion and microatmosphere assay;… More >

  • Open Access

    ARTICLE

    Low-Carbon Economic Dispatch of an Integrated Energy System with Multi-Device Coupling under Ladder-Type Carbon Trading

    Chenxuan Zhang, Yongqing Qi*, Ximin Cao, Yanchi Zhang

    Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.069878 - 27 January 2026

    Abstract To enhance the low-carbon economic efficiency and increase the utilization of renewable energy within integrated energy systems (IES), this paper proposes a low-carbon dispatch model integrating power-to-gas (P2G), carbon capture and storage (CCS), hydrogen fuel cell (HFC), and combined heat and power (CHP). The P2G process is refined into a two-stage structure, and HFC is introduced to enhance hydrogen utilization. Together with CCS and CHP, these devices form a multi-energy conversion system coupling electricity, heat, cooling, and gas. A ladder-type carbon trading approach is adopted to flexibly manage carbon output by leveraging marginal cost adjustments.… More >

  • Open Access

    ARTICLE

    A Retrospective Real-World Study: The Efficacy and Safety of Immune Checkpoint Inhibitors Combined with Chemoradiotherapy in Limited-Stage Small Cell Lung Cancer

    Ruoxue Cai1,#, Shuyi Hu2,#, Feiyang Li2, Huanhuan Sha3,*, Guoren Zhou2,*, Ying Fang3

    Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.070893 - 19 January 2026

    Abstract Objective: To determine whether immunotherapy can bring new hope for patients with limited-stage small-cell lung cancer (LS-SCLC). We conducted this retrospective study to evaluate whether immunotherapy can achieve better efficacy in LS-SCLC patients. Methods: We evaluated 122 LS-SCLC patients who received concurrent chemoradiotherapy (CCRT) or sequential chemoradiotherapy (SCRT) (Group A) and immunotherapy combined with CCRT/SCRT followed by immunotherapy (Group B), to assess the objective response rate (ORR), disease control rate (DCR), and progression-free survival (PFS). Factors affecting prognosis were also explored using Cox analysis. The prognosis of patients with type 2 diabetes and patients with… More >

  • Open Access

    ARTICLE

    Two-Stage LightGBM Framework for Cost-Sensitive Prediction of Impending Failures of Component X in Scania Trucks

    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 >

  • Open Access

    ARTICLE

    A Real Time YOLO Based Container Grapple Slot Detection and Classification System

    Chen-Chiung Hsieh1,*, Chun-An Chen1, Wei-Hsin Huang2

    CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072514 - 12 January 2026

    Abstract Container transportation is pivotal in global trade due to its efficiency, safety, and cost-effectiveness. However, structural defects—particularly in grapple slots—can result in cargo damage, financial loss, and elevated safety risks, including container drops during lifting operations. Timely and accurate inspection before and after transit is therefore essential. Traditional inspection methods rely heavily on manual observation of internal and external surfaces, which are time-consuming, resource-intensive, and prone to subjective errors. Container roofs pose additional challenges due to limited visibility, while grapple slots are especially vulnerable to wear from frequent use. This study proposes a two-stage automated… More >

  • Open Access

    ARTICLE

    From Budget-Aware Preferences to Optimal Composition: A Dual-Stage Framework for Wireless Energy Service Optimization

    Haotian Zhang, Jing Li*, Ming Zhu, Zhiyong Zhao, Hongli Su, Liming Sun

    CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072381 - 12 January 2026

    Abstract In the wireless energy transmission service composition optimization problem, a key challenge is accurately capturing users’ preferences for service criteria under complex influencing factors, and optimally selecting a composition solution under their budget constraints. Existing studies typically evaluate satisfaction solely based on energy transmission capacity, while overlooking critical factors such as price and trustworthiness of the provider, leading to a mismatch between optimization outcomes and user needs. To address this gap, we construct a user satisfaction evaluation model for multi-user and multi-provider scenarios, systematically incorporating service price, transmission capacity, and trustworthiness into the satisfaction assessment… More >

  • Open Access

    ARTICLE

    H/V Spectral Ratio Reveals Seismic Response of Base-Isolated Large-Span High-Rise in Beijing

    Zhangdi Xie1,2,*, Cantao Zhuang1, Yong Wu1, Linghui Niu1, Jianming Zhao3

    Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.070531 - 08 January 2026

    Abstract This study employed tri-component continuous monitoring data from 10 measurement points on both sides of a base isolation layer in the basement of a large-span high-rise building in Beijing, as well as from a free-field station and roof frame, during a Mw 5.5 magnitude earthquake in Pingyuan, Shandong, in 2023. The H/V spectral ratio method was used to evaluate the structural dynamic response characteristics of the building and analyze the regulatory effect of the base-isolation layer on seismic waves. The results indicate that during the earthquake, the peak frequency of the free-field and the measurement points… More >

  • Open Access

    ARTICLE

    A Multi-Stage Pipeline for Date Fruit Processing: Integrating YOLOv11 Detection, Classification, and Automated Counting

    Ali S. Alzaharani, Abid Iqbal*

    CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-27, 2026, DOI:10.32604/cmc.2025.070410 - 10 November 2025

    Abstract In this study, an automated multimodal system for detecting, classifying, and dating fruit was developed using a two-stage YOLOv11 pipeline. In the first stage, the YOLOv11 detection model locates individual date fruits in real time by drawing bounding boxes around them. These bounding boxes are subsequently passed to a YOLOv11 classification model, which analyzes cropped images and assigns class labels. An additional counting module automatically tallies the detected fruits, offering a near-instantaneous estimation of quantity. The experimental results suggest high precision and recall for detection, high classification accuracy (across 15 classes), and near-perfect counting in More >

  • Open Access

    ARTICLE

    A Dynamic IPR Framework for Predicting Shale Oil Well Productivity in the Spontaneous Flow Stage

    Sheng Lei1,2,3, Guanglong Sheng1,2,3,*, Hui Zhao1,2,3

    FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.12, pp. 3011-3031, 2025, DOI:10.32604/fdmp.2025.073802 - 31 December 2025

    Abstract This study investigates the unsteady flow characteristics of shale oil reservoirs during the depletion development process, with a particular focus on production behavior following fracturing and shut-in stages. Shale reservoirs exhibit distinctive production patterns that differ from traditional oil reservoirs, as their inflow performance does not conform to the classic steady-state relationship. Instead, production is governed by unsteady-state flow behavior, and the combined effects of the wellbore and choke cause the inflow performance curve to evolve dynamically over time. To address these challenges, this study introduces the concept of a “Dynamic IPR curve” and develops… More >

  • Open Access

    ARTICLE

    A Generative Sky Image-Based Two-Stage Framework for Probabilistic Photovoltaic Power Forecasting

    Chen Pan, ChangGyoon Lim*

    CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3747-3781, 2025, DOI:10.32604/cmes.2025.073389 - 23 December 2025

    Abstract Solar forecasting using ground-based sky image offers a promising approach to reduce uncertainty in photovoltaic (PV) power generation. However, existing methods often rely on deterministic predictions that lack diversity, making it difficult to capture the inherently stochastic nature of cloud movement. To address this limitation, we propose a new two-stage probabilistic forecasting framework. In the first stage, we introduce I-GPT, a multiscale physics-constrained generative model for stochastic sky image prediction. Given a sequence of past sky images, I-GPT uses a Transformer-based VQ-VAE. It also incorporates multi-scale physics-informed recurrent units (Multi-scale PhyCell) and dynamically weighted fuses… More >

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