Shujie Yin¹, Zong Li¹, Wen-Bin Ou^1,2,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.069049 - 30 December 2025

Abstract Ferroptosis is an iron-dependent, excessive lipid peroxidation-driven form of regulated cell death. The core mechanisms of ferroptosis include lipid peroxidation cascade, System X_c⁻-glutathioneglutathione peroxidase 4 axis, iron and lipid metabolism chaos, the NAD(P)Hferroptosis suppressor protein 1—ubiquinone axis, and GTP cyclohydrolase 1 tetrahydrobiopterin-dihydrofolate reductase axis. Cuproptosis is triggered by copper ions and involves ferredoxin 1-mediated aggregation of lipoylated proteins, differing fundamentally from ferroptosis. Both ferroptosis and cuproptosis exhibit dual roles (promote or inhibit) in cancers. And the sensitivity of different cancer types to ferroptosis varies, which may depend on special metabolic signatures (e.g., E-cadherin loss causes epithelial–mesenchymal More > Graphic Abstract

Jinqian Li¹, Jianhong Wu^2,*

International Journal of Mental Health Promotion, Vol.27, No.12, pp. 1883-1896, 2025, DOI:10.32604/ijmhp.2025.071306 - 31 December 2025

Abstract Background: Platform algorithms driving content presentation are profoundly shaping the experience of younger users. While prior research has examined anxiety stemming from young adults’ social media usage, the link between upward social comparison and anxiety remains unclear. This study aims to investigate the mediating role of upward social comparison in this relationship and determine the moderating role of psychological resilience. Methods: A cross-sectional survey was conducted among 562 young Chinese adults aged 18–35 (53% female). Data were collected via an online questionnaire employing validated measurement instruments, including scales for social media usage patterns, upward comparator behaviour… More >

Jeongsu Park¹, Moohong Min^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3913-3948, 2025, DOI:10.32604/cmes.2025.072261 - 23 December 2025

Abstract Time series anomaly detection is critical in domains such as manufacturing, finance, and cybersecurity. Recent generative AI models, particularly Transformer- and Autoencoder-based architectures, show strong accuracy but their robustness under noisy conditions is less understood. This study evaluates three representative models—AnomalyTransformer, TranAD, and USAD—on the Server Machine Dataset (SMD) and cross-domain benchmarks including the Soil Moisture Active Passive (SMAP) dataset, the Mars Science Laboratory (MSL) dataset, and the Secure Water Treatment (SWaT) testbed. Seven noise settings (five canonical, two mixed) at multiple intensities are tested under fixed clean-data training, with variations in window, stride, and More > Graphic Abstract

Miah A. Robinson, Abdulghani M. Abdulghani, Mokhles M. Abdulghani, Khalid H. Abed^*

Journal on Artificial Intelligence, Vol.7, pp. 615-632, 2025, DOI:10.32604/jai.2025.073535 - 01 December 2025

Abstract Ensuring the safety of Artificial Intelligence (AI) is essential for providing dependable services, especially in various sectors such as the military, education, healthcare, and automotive industries. A highly effective method to boost the precision and performance of an AI agent involves multi-configuration training, followed by thorough evaluation in a specific setting to gauge performance outcomes. This research thoroughly investigates the design of three AI agents, each configured with a different number of hidden units. The first agent is equipped with 128 hidden units, the second with 256, and the third with 512, all utilizing the… More >

Ke Li¹, Bendong Liu¹, Yulong Han², Yafeng Zhang³, Chunqi Yang¹, Dawei Yin², Yazhou Zhang³, Wantao Ding^4,*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.11, pp. 2779-2793, 2025, DOI:10.32604/fdmp.2025.072671 - 01 December 2025

Abstract Traditional cement-based slurries are often constrained by excessive cement consumption, prolonged setting times, and limited controllability, which hinder their broader engineering applications. To overcome these challenges, this study focuses on optimizing ordinary cement-based slurry through the incorporation of targeted additives and rational adjustment of mix proportions, with the aim of developing a rapid-setting, early-strength cementitious system. In particular, a series of comparative and orthogonal experiments were conducted to systematically examine the evolution of the slurry’s macroscopic properties. In addition, the response surface methodology (RSM) was introduced to reveal the interaction mechanisms among key parameters, thereby… More >

Ricardo Dominico Da Silva^1,2, Jangkung Raharjo^1,3,*, Sudarmono Sasmono^1,3

Energy Engineering, Vol.122, No.12, pp. 5073-5090, 2025, DOI:10.32604/ee.2025.071545 - 27 November 2025

Abstract The rapid development of technology has led to an ever-increasing demand for electrical energy. In the context of Timor-Leste, which still relies on fossil energy sources with high operational costs and significant environmental impacts, electricity load forecasting is a strategic measure to support the energy transition towards the Net Zero Emission (NZE) target by 2050. This study aims to utilize historical electricity load data for the period 2013–2024, as well as data on external factors affecting electricity consumption, to forecast electricity load in Timor-Leste in the next 10 years (2025–2035). The forecasting results are expected… More >

Apoorav Sharma¹, Ayush Dogra^2,*, Bhawna Goyal³, Archana Saini², Vinay Kukreja²

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 367-481, 2025, DOI:10.32604/cmc.2025.066481 - 29 August 2025

Abstract To enable proper diagnosis of a patient, medical images must demonstrate no presence of noise and artifacts. The major hurdle lies in acquiring these images in such a manner that extraneous variables, causing distortions in the form of noise and artifacts, are kept to a bare minimum. The unexpected change realized during the acquisition process specifically attacks the integrity of the image’s quality, while indirectly attacking the effectiveness of the diagnostic process. It is thus crucial that this is attended to with maximum efficiency at the level of pertinent expertise. The solution to these challenges… More >

Muhammad Osama¹, Sarwar Shah Khan^2,*, Sajid Khan², Muzammil Khan³, Mian Muhammad Danyal⁴, Reshma Khan¹

Digital Engineering and Digital Twin, Vol.3, pp. 17-34, 2025, DOI:10.32604/dedt.2025.066344 - 19 August 2025

Abstract Image fusion is a technique used to combine essential information from two or more source images into a single, more informative output image. The resulting fused image contains more meaningful details than any individual source image. This study focuses on multi-focus image fusion, a crucial area in image processing. Due to the limited depth of field of optical lenses, it is often challenging to capture an image where all areas are in focus simultaneously. As a result, multi-focus image fusion plays a key role in integrating and extracting the necessary details from different focal regions.… More >

Alex Ximenes Naves¹, Gladys Maquera², Assed Haddad¹, Dieter Boer^3,*

Energy Engineering, Vol.122, No.7, pp. 2611-2636, 2025, DOI:10.32604/ee.2025.061971 - 27 June 2025

Abstract The growing concern for energy efficiency and the increasing deployment of intermittent renewable energies has led to the development of technologies for capturing, storing, and discharging energy. Supercapacitors can be considered where batteries do not meet the requirements. However, supercapacitors in systems with a slower charge/discharge cycle, such as photovoltaic systems (PVS), present other obstacles that make replacing batteries more challenging. An extensive literature review unveils a knowledge gap regarding a methodological comparison of batteries and supercapacitors. In this study, we address the technological feasibility of intermittent renewable energy generation systems, focusing on storage solutions… More > Graphic Abstract

Mostafa Ahmed Arafa^1,2, Karim Hamda Farhat^1,*, Nesma Lotfy³, Farrukh Kamel Khan¹, Alaa Mokhtar⁴, Abdulaziz Mohammed Althunayan¹, Waleed Al-Taweel⁴, Sultan Saud Al-Khateeb⁴, Sami Azhari^1,5, Danny Munther Rabah^1,4

Canadian Journal of Urology, Vol.32, No.3, pp. 173-180, 2025, DOI:10.32604/cju.2025.066016 - 27 June 2025

Abstract Background: Transrectal (TR) and transperineal (TP) biopsies are commonly used methods for diagnosing prostate cancer. However, their comparative effectiveness in conjunction with machine learning (ML) techniques remains underexplored. This study aimed to evaluate the predictive accuracy of ML algorithms in detecting prostate cancer using data derived from TR and TP biopsies. Methods: The clinical records of patients who underwent prostate biopsy at King Saud University Medical City and King Faisal Specialist Hospital and Research Centerin Riyadh, Saudi Arabia, between 2018 and 2025 were analyzed. Data were used to train and test ML models, including eXtreme… More >