Beatrice Sani^1,2, Alessandro Cignetti², Marta Leporati³, Sara Sommariva⁴, Marco Armenio¹, Valerio Tenace⁵, Arianna Savi², Johanna Umurungi^1,2, Giovanni Fornari^1,2, Simone Busso³, Alessandra Canevaro³, Igor Bisognin³, Silvia Marini¹, Michele Piana⁴, Daniela Cilloni^1,2, Valentina Gaidano^2,*

Oncology Research, Vol.34, No.8, 2026, DOI:10.32604/or.2026.078245 - 16 July 2026

Abstract Objectives: Venetoclax (VEN) is approved for acute myeloid leukemia (AML) in association with azacitidine, in a 28-day schedule at a fixed dosage, which requires reduction if azoles are co-administered. The present study aims to evaluate VEN therapeutic drug monitoring (TDM) in a real-word setting, where the VEN schedule is frequently reduced, investigating: (i) the posaconazole impact, and (ii) whether VEN exposure correlates with safety and efficacy. Methods: We analyzed data from 43 AML patients treated with different VEN-containing regimens, for whom a near-trough VEN plasma concentration (Cmin) was determined at different timepoints (days 5-8-11-15-22-29) across different cycles… More >

Kang-Woo Lee, Dong-Hee Lee^*, Dae-Il Kwon^*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.081667 - 15 June 2026

Abstract Early-life cycle-life prediction for lithium-ion batteries—estimating end-of-life from initial cycles—is valuable for rapid cell screening and battery health management. We investigate whether an explicit correlation-structure descriptor can complement physics-informed ΔQ-based indicators and generic early-cycle statistical features on the Severson 124-cell benchmark. We develop a lightweight hybrid framework that combines ΔQ-based health indicators, data-driven statistical features, and Laplacian Eigenmaps embeddings derived from a Pearson-correlation feature graph, with XGBoost used as the predictor. Across five feature configurations (ΔQ Only, ΔQ + Statistics, Hybrid Append, VIF + Laplacian, and Integrated Laplacian), we evaluate pointwise regression accuracy using RMSE and R² together… More > Graphic Abstract

Miao Ye¹, Ziheng Wang¹, Qiuxiang Jiang¹, Xingsi Xue², Wenxi Liu³, Yu Ning¹, Cheng Zhu^1,4,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.078282 - 15 June 2026

Abstract In recent years, anomaly detection in Wireless Sensor Networks (WSNs) has been widely studied using Graph Neural Networks and Transformer-based methods. However, in multi-node and multi-modal data scenarios, these approaches still face challenges such as insufficient extraction of spatiotemporal correlation features, limited modeling capabilities when relying solely on either time-domain or frequency-domain information, and high computational overhead. To address these issues, this work aims to develop an anomaly detection model that balances detection performance with computational efficiency, enabling effective identification of complex anomaly patterns. Specifically, we propose a time–frequency feature extraction method with topological information… More >

Lingyu Jin^1,2, Rui Wang^1,2, Bo Huang^1,2,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.080050 - 08 May 2026

Abstract Unmanned Aerial Vehicle (UAV) target tracking is one of the key technologies in aerial intelligent perception systems, playing a vital role in applications such as traffic monitoring, border patrol, disaster response, search and rescue, environmental monitoring, and military reconnaissance. Compared with generic object tracking tasks, UAV platforms exhibit significant differences in imaging perspectives, target scales, motion patterns, and onboard computing capabilities, which pose unique challenges for UAV target tracking, including small targets and drastic scale variations, platform motion and motion blur, complex backgrounds and frequent occlusions, low-light conditions at night, as well as real-time and… More >

Yang Liu¹, Yinguo Yang¹, Pingping Xie¹, Qiuyu Lu¹, Yue Chen¹, Zhanpeng Xu^2,*, Zejie Huang²

Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2025.068436 - 27 April 2026

Abstract With the large-scale integration of wind and solar energy into the power grid, the power system is facing uncertainty challenges in multiple links, such as source, grid, and load. How to efficiently dispatch flexible resources, such as energy storage, has become an urgent problem to be solved. To this end, this paper considers the correlation between new energy stations due to natural conditions, uses Vine-Copula theory to describe the correlation characteristics of the output of multiple new energy stations, and proposes a wind solar new energy output scenario generation method based on Vine-Copula theory; Then,… More >

Xiansong Xie^1,*, Xiaoqian Qian²

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.074148 - 31 March 2026

Abstract Correlation function of acceleration responses-based damage identification methods has been developed and employed, while they still face the difficulty in identifying local or minor structural damages. To deal with this issue, a robust structural damage identification method is developed, integrating a modified holistic swarm optimization (MHSO) algorithm with a hybrid objective function. The MHSO is developed by combining Hammersley sequence-based population initialization, chaotic search around the worst solution, and Hooke-Jeeves pattern search around the best solution, thereby improving both global exploration and local exploitation capabilities. A hybrid objective function is constructed by merging acceleration correlation… More >

Jiye Chen^1,*, Min Fu², Sudath Loku-Pathirage³, Bing Leng⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2026.073689 - 30 March 2026

Abstract Slope failures, particularly in railway embankments during intense rainfall, are a major cause of economic damage and humanitarian loss. To forecast how shear cracks develop in slopes under heavy precipitation, we present a novel modeling framework: the Extended Cohesive Damage Element enhanced by soil moisture (SMECDE). The method first translates forecasted rainfall into soil moisture levels via an established correspondence. Then, recognizing that rainfall infiltration lowers soil cohesion—particularly at varying depths—we introduce a Soil Moisture Decoherence Model (SMDM) based on experimental data, which quantifies how cohesion degrades with moisture and how depth affects this process. More >

Adam Dudáš^*

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.076507 - 12 March 2026

Abstract It is known that correlation does not imply causality. Some relationships identified in the analysis of data are coincidental or unknown, and some are produced by real-world causality of the situation, which is problematic, since there is a need to differentiate between these two scenarios. Until recently, the proper−semantic−causality of the relationship could have been determined only by human experts from the area of expertise of the studied data. This has changed with the advance of large language models, which are often utilized as surrogates for such human experts, making the process automated and readily… More >

Dorian Dikov¹, Maria Koleva^2,*, Kiril Simitchiev³, Anelia Bivolarska⁴, Albena Fakirova⁵, Victoria Sarafian^6,7

Canadian Journal of Urology, Vol.33, No.1, pp. 125-134, 2026, DOI:10.32604/cju.2025.068575 - 28 February 2026

Abstract Background: Chronic inflammation is closely associated with the most common and socially significant prostate conditions, including benign prostatic hyperplasia (BPH), prostate cancer (PCa), and prostatitis syndromes. NIH-category IV prostatitis (histologic prostatitis, HP) is defined as asymptomatic chronic inflammation of the prostate. The presence of lymphoid follicles, referred to as tertiary lymphoid structures (TLSs), along with benign lympho-epithelial lesions (BLELs), is among the key histological indicators of immune inflammation and can be assessed relatively easily. This study aimed to quantitatively assess TLSs and BLELs, as well as their relationship with the severity of HP. Methods: We… More >

Shereen S. Jumaa¹, Mohsin H. Challoob², Amjad J. Humaidi^2,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.074752 - 10 February 2026

Abstract Military image encryption plays a vital role in ensuring the secure transmission of sensitive visual information from unauthorized access. This paper proposes a new Tri-independent keying method for encrypting military images. The proposed encryption method is based on multilevel security stages of pixel-level scrambling, bit-level manipulation, and block-level shuffling operations. For having a vast key space, the input password is hashed by the Secure Hash Algorithm 256-bit (SHA-256) for generating independently deterministic keys used in the multilevel stages. A piecewise pixel-level scrambling function is introduced to perform a dual flipping process controlled with an adaptive… More >