Matthew Rubinstein^1,*, Madeline Lauren Hong¹, Rishi Kumar Nanda¹, Daniel Thomas Jones¹, Hazem Aboaid², Yin Mon Myat³, Kyaw Zin Thein⁴

Oncology Research, Vol.33, No.11, pp. 3161-3183, 2025, DOI:10.32604/or.2025.067791 - 22 October 2025

Abstract The ever-expanding development of tissue-agnostic therapies which target malignancies based on specific mutations rather than tissue origin have transformed the landscape of oncology. The purpose of this review is to explore the impact, safety, and challenges of tissue-agnostic therapies including pembrolizumab, dostarlimab, larotrectinib, entrectinib, repotrectinib, dabrafenib plus trametinib, selpercatinib, and trastuzumab deruxtecan. As the therapeutic arsenal continues to grow, it is crucial to understand how these therapies truly benefit patients and to address the barriers that stand in the way of making them more widely available. Although these therapies have shown effectiveness across multiple cancer More >

Takeshi Toyozumi^1,*, Hideaki Shimada², Hisahiro Matsubara¹

Oncology Research, Vol.33, No.11, pp. 3185-3206, 2025, DOI:10.32604/or.2025.065818 - 22 October 2025

Abstract Cancer immunotherapy has long been established as an important treatment option for cancers. In particular, Immune Checkpoint Inhibitor (ICI) has been reported to be effective against various gastrointestinal cancers (esophageal cancer, gastric cancer, colorectal cancer); however, the treatment phase in which ICI should be used and how it should be incorporated into the treatment strategy vary depending on the cancer type being treated. Multiple clinical trials and basic research on ICIs are currently underway, and new insights from these results will continue to change the clinical treatment strategy of gastrointestinal cancers. While it is desirable… More >

Ahmad Faldo¹, Labanta Marbun¹, Hezekiah Lemuel Putra Zebua¹, Fateha Fateha², Rossy Choerun Nissa², Yurin Karunia Apsha Albaina Iasya³, Riri Uswatun Annifah³, Amrul Amrul¹, Yeyen Nurhamiyah^2,*

Journal of Polymer Materials, Vol.42, No.3, pp. 743-755, 2025, DOI:10.32604/jpm.2025.069981 - 30 September 2025

Abstract Conventional bioplastic production from seaweed often relies on extraction processes that are costly, time-consuming, and yield limited product. This study presents a direct fabrication method using Gracilaria sp., a red seaweed rich in polysaccharides, to produce bioplastic films without the need for extraction. Sorbitol was incorporated as a plasticizer at concentrations of 0%–10% (w/w) to modify film characteristics. Thermal analysis revealed improved stability at moderate sorbitol levels (5%–7%), while excessive plasticizer slightly reduced thermal resistance. Mechanical testing showed that sorbitol increased film flexibility and elongation at break, though tensile strength and stiffness declined. Tear strength followed More >

Qiji Dai¹, Jikai Li^2,*, Bohui Ning¹, Yutao Xu¹, Chang Liu², Xuan Zhang¹

Energy Engineering, Vol.122, No.10, pp. 4061-4080, 2025, DOI:10.32604/ee.2025.067304 - 30 September 2025

Abstract Aiming at the challenge of complex load balancing coordination for a three-phase four-leg (3P4L) based multi-ended low voltage flexible DC distribution system (M-LVDC) considering unbalanced power compensation, this paper proposes a phase-split power decoupling unbalanced compensation strategy based load balancing strategy for 3P4L based M-LVDC. Firstly, the topology and operation principle of the 3P4L-based M-LVDC system is introduced, and quasi-proportional resonant (QPR) based phase-split power current control for the 3P4L converter is proposed. Secondly, a load-balancing control strategy considering unbalanced compensation for 3P4L-based M-LVDC is presented, in which the control diagrams for each 3P4L-based converter… More >

Weibing Xu¹, Bo Yao^2,*, Xiangjun Quan³, Xunyou Zhang¹, Ning Zou², Shuo Liu², Jia Wang⁴, Jiansuo Zhang⁴

Energy Engineering, Vol.122, No.10, pp. 4225-4243, 2025, DOI:10.32604/ee.2025.066738 - 30 September 2025

Abstract The integration of large-scale new energy and high-capacity DC transmission leads to a reduction in system inertia. Grid-forming renewable energy sources (GF-RES) has a significant improvement effect on system inertia. Commutation failure faults may cause a short-term reactive power surplus at the sending end and trigger transient overvoltage, threatening the safe and stable operation of the power grid. However, there is a lack of research on the calculation method of transient overvoltage caused by commutation failure in high-voltage DC transmission systems with grid-forming renewable energy sources integration. Based on the existing equivalent model of high-voltage… More >

Hoang-Dieu Vu^1,2, Duc-Nghia Tran³, Quang-Tu Pham¹, Ngoc-Linh Nguyen^4,*, Duc-Tan Tran^1,*

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 2819-2835, 2025, DOI:10.32604/cmc.2025.068355 - 23 September 2025

Abstract This study presents CGB-Net, a novel deep learning architecture specifically developed for classifying twelve distinct sleep positions using a single abdominal accelerometer, with direct applicability to gastroesophageal reflux disease (GERD) monitoring. Unlike conventional approaches limited to four basic postures, CGB-Net enables fine-grained classification of twelve clinically relevant sleep positions, providing enhanced resolution for personalized health assessment. The architecture introduces a unique integration of three complementary components: 1D Convolutional Neural Networks (1D-CNN) for efficient local spatial feature extraction, Gated Recurrent Units (GRU) to capture short-term temporal dependencies with reduced computational complexity, and Bidirectional Long Short-Term Memory… More >

Zhenhui Cai, Kaiqing Zhou^*, Zhouhua Liao

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 2255-2303, 2025, DOI:10.32604/cmc.2025.067994 - 23 September 2025

Abstract The YOLO (You Only Look Once) series, a leading single-stage object detection framework, has gained significant prominence in medical-image analysis due to its real-time efficiency and robust performance. Recent iterations of YOLO have further enhanced its accuracy and reliability in critical clinical tasks such as tumor detection, lesion segmentation, and microscopic image analysis, thereby accelerating the development of clinical decision support systems. This paper systematically reviews advances in YOLO-based medical object detection from 2018 to 2024. It compares YOLO’s performance with other models (e.g., Faster R-CNN, RetinaNet) in medical contexts, summarizes standard evaluation metrics (e.g.,… More >

Jun Li^#,*, Kai Xu^#,*, Baozhu Chen, Xiaohan Yang, Mengting Sun, Guojun Li, HaoJie Du

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3349-3368, 2025, DOI:10.32604/cmc.2025.067316 - 23 September 2025

Abstract Pedestrian trajectory prediction is pivotal and challenging in applications such as autonomous driving, social robotics, and intelligent surveillance systems. Pedestrian trajectory is governed not only by individual intent but also by interactions with surrounding agents. These interactions are critical to trajectory prediction accuracy. While prior studies have employed Convolutional Neural Networks (CNNs) and Graph Convolutional Networks (GCNs) to model such interactions, these methods fail to distinguish varying influence levels among neighboring pedestrians. To address this, we propose a novel model based on a bidirectional graph attention network and spatio-temporal graphs to capture dynamic interactions. Specifically,… More >

Ghadah Aldehim, Shakila Basheer, Ala Saleh Alluhaidan, Sapiah Sakri^*

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3599-3619, 2025, DOI:10.32604/cmc.2025.065643 - 23 September 2025

Abstract Although digital changes in power systems have added more ways to monitor and control them, these changes have also led to new cyber-attack risks, mainly from False Data Injection (FDI) attacks. If this happens, the sensors and operations are compromised, which can lead to big problems, disruptions, failures and blackouts. In response to this challenge, this paper presents a reliable and innovative detection framework that leverages Bidirectional Long Short-Term Memory (Bi-LSTM) networks and employs explanatory methods from Artificial Intelligence (AI). Not only does the suggested architecture detect potential fraud with high accuracy, but it also… More >

He Huang, Jin Zhu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 1717-1748, 2025, DOI:10.32604/cmes.2025.068384 - 31 August 2025

Abstract Automated guided vehicles (AGVs) are key equipment in automated container terminals (ACTs), and their operational efficiency can be impacted by conflicts and battery swapping. Additionally, AGVs have bidirectional transportation capabilities, allowing them to move in the opposite direction without turning around, which helps reduce transportation time. This paper aims at the problem of AGV scheduling and bidirectional conflict-free routing with battery swapping in automated terminals. A bi-level mixed integer programming (MIP) model is proposed, taking into account task assignment, bidirectional conflict-free routing, and battery swapping. The upper model focuses on container task assignment and AGV… More >