Xing-Guo Li^1,2,3,#, Lu-Kai Wang^4,#, Fu-Ming Tsai⁵, Hsueh-Chun Wang^1,*

BIOCELL, Vol.50, No.6, 2026, DOI:10.32604/biocell.2026.075492 - 09 June 2026

Abstract Itaconate, produced by aconitate decarboxylase 1 (ACOD1, also known as IRG1), acts as a key immunometabolite that inhibits succinate dehydrogenase (SDH) and can engage reduction-oxidation (redox)-sensitive signaling programs. This review summarizes the emerging, context-dependent roles of the ACOD1-itaconate axis in cancer, while critically distinguishing between the effects of endogenous itaconate and its cell-permeable derivatives. In tumor cells, endogenous ACOD1 expression or uptake via solute carrier family 13 member 3 (SLC13A3) alters oxidative phosphorylation and glycolysis. In the tumor microenvironment, myeloid-derived itaconate contributes to immune tolerance by reducing dendritic-cell cross-priming and limiting CD8⁺ T-cell metabolic activity. Moreover, More >

Bernard P. Zeigler^*

Digital Engineering and Digital Twin, Vol.4, pp. 1-26, 2026, DOI:10.32604/dedt.2026.082492 - 02 June 2026

Abstract As Digital Twin (DT) applications expand into complex, dynamic environments, a formal methodology is lacking to ensure that the embedded digital models remain adequate for specific stakeholder goals over time. This article introduces the Experimental Frame–System Under Test (EFSUT) methodology, providing a principled foundation for linking high-level stakeholder questions to the specific models capable of answering them. EFSUT organizes the digital engineering process around three core constructs: stakeholder questions, experimental frames that formalize observational requirements, and models related through morphisms. This structure allows developers to reason about model choice, reduction, and adequacy with technical rigor… More >

Hamed Saber¹, Antonio Zippo^1,2, Farhad S. Samani³, Francesco Pellicano^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.079313 - 27 May 2026

Abstract Lightweight bridges are increasingly used in modern infrastructure due to their structural efficiency; however, their relatively low stiffness and damping lead to a high sensitivity to vibration excitation induced by moving loads such as pedestrians and vehicles. Conventional vibration mitigation strategies are often insufficient to suppress low-frequency responses, which has caused the development of advanced nonlinear isolation mechanisms. This paper investigates the effectiveness of nonlinear quasi-zero stiffness supports (QZSS) in suppressing vertical vibrations of lightweight bridges. Such structures are highly susceptible to vibrations induced by moving loads because of low stiffness and dissipation, with consequent… More > Graphic Abstract

Anh-Vu Nguyen¹, Tien-Chuong Vu¹, Ba-Duan Nguyen¹, Hoang-Anh Pham^1,*, Ravipudi Venkata Rao²

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.080453 - 27 April 2026

Abstract Structural optimization is essential for finding optimal designs in practical engineering tasks. Metaheuristic algorithms have been widely applied in structural optimization problems in recent years, especially when dealing with discrete design variables, the nonlinearity of the objective function and constraints. Unlike gradient-based algorithms, which rely on the slope variation of a function, metaheuristic algorithms do not require derivative calculations and thus avoid being trapped in local optimum. However, metaheuristic algorithms often require numerous function evaluations, involving costly structural analyses, thus increasing computational load considerably. This paper investigates a method to reduce computational load, specifically by… More >

Junwei Zhang¹, Pei Liu¹, Huihang Li¹, Guokang Huang¹, Bozheng Yuan¹, Wenjing Wei¹, Xiaoshun Zhang^2,*

Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2025.072462 - 27 April 2026

Abstract Addressing global climate challenges necessitates urgent low carbon transitions in high energy consuming enterprises (HECEs). This study proposes a comprehensive framework to assess their carbon reduction potential (CRP) by integrating electricity usage behavior analysis and dynamic carbon emission factor (DCEF) prediction. HECEs are classified into “electricity reduction” and “electricity transfer” categories based on load characteristics, enabling tailored optimization strategies. The framework employs machine learning to predict DCEFs, capturing real time variations in grid carbon intensity. A low carbon optimization model is then formulated to minimize emissions while adhering to production requirements and grid constraints, solved… More > Graphic Abstract

Thatsamaphon Boonchuntuk¹, Thanyapisit Buaprakhong¹, Varintorn Sithisint¹, Awirut Phusaensaart¹, Sinthon Wilke¹, Thittaporn Ganokratanaa^1,*, Mahasak Ketcham²

Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2026.069005 - 27 April 2026

Abstract Urban traffic congestion directly contributes to excessive energy consumption and urban air pollution, requiring adaptive traffic signal control strategies that incorporate sustainability objectives alongside mobility performance. This study proposes a Large Language Model (LLM) driven traffic signal optimization framework that transforms detailed intersection-level traffic states into structured natural-language prompts, enabling the LLM to reason over congestion patterns, queue asymmetry, phase history, and estimated energy emission impacts. Unlike reinforcement learning (RL) based controllers, the LLM requires no task-specific training and operates in a zero-shot manner through carefully designed structured prompts that encode traffic states, phase history,… More >

Luigi Coltelli^1,2,#, Paola Orlandi^3,#, Chiara Finale^1,4,#, Gianna Musettini^1,4,#, Luna Chiara Masini^1,4, Marco Scalese⁵, Giulia Soria^1,4, Elena Sartori^1,4, Ylenia Nodari^1,4, Giada Arrighi^1,2, Arianna Bandini³, Marta Banchi³, Costanza Tacchi³, Donghao Tang³, Barbara Salvadori⁶, Lucia Tanganelli^1,7, Simona Giovannelli^1,8, Mirco Pistelli⁹, Samanta Cupini^1,4, Maurizio Lucchesi^1,10, Alessandro Cosimi¹¹, Giulia Lorenzini^1,7, Elisa Biasco^1,4, Chiara Caparello^1,4, Giulia Acconci^1,4,6, Eloise Fontana^1,4, Eleonora Bona^1,4, Azzurra Farnesi^1,4, Antonio Pellino^1,4, Andrea Marini^1,4, Ermelinda De Maio^1,4, Irene Stasi^1,4, Cecilia Barbara^1,4, Enrico Sammarco^1,4, Javier Rosada^12,13, Giacomo Allegrini^1,4,*, Guido Bocci^3,*

Oncology Research, Vol.34, No.5, 2026, DOI:10.32604/or.2026.073799 - 22 April 2026

Abstract Background: The treatment of advanced hormone receptor-positive (HR+) breast cancer has seen relevant changes in last years. However, bevacizumab remains an option when combined with paclitaxel, but no certified pharmacogenetic profiles are now usable for the prediction of its response in breast cancer patients. This study aimed to explore the pharmacogenetic interactions among single nucleotide polymorphisms (SNPs) of genes involved in the angiogenic process and their impact on progression-free survival (PFS) and overall survival (OS) in hormone receptor-positive (HR+) metastatic breast cancer subjects administered with bevacizumab plus paclitaxel, or with paclitaxel alone (clinicaltrial.gov… More >

Heming Xu¹, Haichao Zhou^1,*, Wei Zhang¹, Wenxuan He¹, Lin Bo²

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.3, 2026, DOI:10.32604/fdmp.2026.075610 - 31 March 2026

Abstract This review addresses four key themes in automotive aerodynamics: flow instability in the wheel region, the aerodynamic characteristics of rims, the aerodynamic behavior of tires, and drag reduction strategies based on flow control around the wheels. The wheel region, comprising the tire, rim, and adjacent aerodynamic components, typically represents the major source of vehicle drag owing to the inherently complex flow generated by wheel rotation, tread geometry, and rim design, which gives rise to flow separation, vortex shedding, and turbulence. Drawing on a broad body of experimental and numerical research, this review elucidates the mechanisms More >

Yan Shi^1,2, Xin Wang³, Yi Wang³, Bingfeng Zhao⁴, Shang Ren⁴, Xufang Zhang^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2026.076624 - 30 March 2026

Abstract This paper introduces a computationally efficient global sensitivity analysis method for quantifying the influence of uncertain clamp support conditions on the natural frequencies of aero-engine pipe systems. The dynamic model is based on a three-dimensional Timoshenko beam finite element formulation, with clamps represented as distributed spring elements possessing anisotropic stiffness. To overcome the prohibitive cost of traditional Monte Carlo simulation, the multiplicative dimensional reduction method (M-DRM) is integrated with variance decomposition theory. This approach approximates the high-dimensional frequency response function as a product of univariate components, enabling rapid computation of Sobol’ sensitivity indices with a More >

Saira Ali Bhatti¹, Maqbool Khan^2,*, Arshad Ahmad³, Muhammad Shahid Anwar⁴, Leila Jamel⁵, Aisha M. Mashraqi⁶, Wadee Alhalabi^7,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2026.074688 - 30 March 2026

Abstract Medical imaging is essential in modern health care, allowing accurate diagnosis and effective treatment planning. These images, however, often demonstrate low contrast, noise, and brightness distortion that reduce their diagnostic reliability. This review presents a structured and comprehensive analysis of advanced histogram equalization (HE)-based techniques for medical image enhancement. Our review methodology encompasses: (1) classical HE approaches and related limitations in medical domains; (2) adaptive schemes like Adaptive Histogram Equalization (AHE) and Contrast Limited Adaptive Histogrma Equalization (CLAHE) and their advance variants; (3) brightness-preserving schemes like BBHE and MMBEBHE and related algorithms; (4) dynamic and More > Graphic Abstract