Firas Mahmood Younis^1,*, Omar Mohammad Hamdoon², Ayad Younis Abdulla¹

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.073483 - 27 January 2026

Abstract This paper presents an experimental analysis of a solar-assisted powered underfloor heating system, designed primarily to boost energy efficiency and achieve reliable desired steady-state temperature in buildings. We thoroughly tested the system’s thermal and operational features by subjecting it to three distinct scenarios that mimicked diverse solar irradiance and environmental conditions. Our findings reveal a strong correlation between variations in solar input and overall system performance. The Solar Fraction (SF), our key energy efficiency metric, varied significantly across the cases, ranging from 63.1% up to 88.7%. This high reliance on renewables resulted in a substantial… More >

Xinyang Li^1,2,3,#, Luyuan Ma^1,2,3,#, Chuan Shen^1,2,3, Ruolan Gu^1,2,3, Shilong Dong^1,2,3, Mingjie Liu^1,2,3, Ying Xiao^1,2,3, Wenpeng Liu^1,2,3, Yuexia Liu^1,2,3, Caiyan Zhao^1,2,3,*

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.073179 - 19 January 2026

Abstract Background: Hepatocellular carcinoma (HCC) is an aggressive and lethal malignancy. Metabolic reprogramming dynamically remodels the tumor microenvironment (TME) and drives HCC progression. This study investigated the mechanism through which metabolic reprogramming remodels the TME in HCC. Methods: HCC patient transcriptome data were subjected to bioinformatics analysis to identify differentially expressed genes and immune infiltration status. Immunohistochemical analysis was performed to determine the correlation between succinate dehydrogenase complex subunit A (SDHA) expression and M2 macrophage infiltration. SDHA-knockdown or SDHA-overexpressing HCC cells were used for in vitro experiments, including co-culturing, flow cytometry, and enzyme-linked immunosorbent assay. Western blotting… More >

Taehoon Kim, Sehun Lee, Junho Ahn^*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-30, 2026, DOI:10.32604/cmc.2025.071597 - 09 December 2025

Abstract As large, room-scale environments become increasingly common, their spatial complexity increases due to variable, unstructured elements. Consequently, demand for room-scale service robots is surging, yet most technologies remain corridor-centric, and autonomous navigation in expansive rooms becomes unstable even around static obstacles. Existing approaches face several structural limitations. These include the labor-intensive requirement for large-scale object annotation and continual retraining, as well as the vulnerability of vanishing point or line-based methods when geometric cues are insufficient. In addition, the high cost of LiDAR and 3D perception errors caused by limited wall cues and dense interior clutter… More >

Nader Karmous¹, Wadii Jlassi¹, Mohamed Ould-Elhassen Aoueileyine¹, Imen Filali^2,*, Ridha Bouallegue¹

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 4363-4393, 2025, DOI:10.32604/cmes.2025.074178 - 23 December 2025

Abstract This paper introduces a robust Distributed Denial-of-Service attack detection framework tailored for Software-Defined Networking based Internet of Things environments, built upon a novel, synthetic multi-vector dataset generated in a Mininet-Ryu testbed using real-time flow-based labeling. The proposed model is based on the XGBoost algorithm, optimized with Principal Component Analysis for dimensionality reduction, utilizing lightweight flow-level features extracted from OpenFlow statistics to classify attacks across critical IoT protocols including TCP, UDP, HTTP, MQTT, and CoAP. The model employs lightweight flow-level features extracted from OpenFlow statistics to ensure low computational overhead and fast processing. Performance was rigorously… More >

Damodharan Palaniappan¹, Tan Kuan Tak², K. Vijayan³, Balajee Maram⁴, Pravin R Kshirsagar⁵, Naim Ahmad^6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 4107-4127, 2025, DOI:10.32604/cmes.2025.073387 - 23 December 2025

Abstract A phase-aware cross-modal framework is presented that synthesizes UWF_FA from non-invasive UWF_RI for diabetic retinopathy (DR) stratification. A curated cohort of 1198 patients (2915 UWF_RI and 17,854 UWF_FA images) with strict registration quality supports training across three angiographic phases (initial, mid, final). The generator is based on a modified pix2pixHD with an added Gradient Variance Loss to better preserve microvasculature, and is evaluated using MAE, PSNR, SSIM, and MS-SSIM on held-out pairs. Quantitatively, the mid phase achieves the lowest MAE (98.76 ± 42.67), while SSIM remains high across phases. Expert review shows substantial agreement (Cohen’s More >

Mekhled Alharbi^1,*, Khalid Haseeb², Mamoona Humayun^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2601-2616, 2025, DOI:10.32604/cmes.2025.073039 - 26 November 2025

Abstract Emerging technologies and the Internet of Things (IoT) are integrating for the growth and development of heterogeneous networks. These systems are providing real-time devices to end users to deliver dynamic services and improve human lives. Most existing approaches have been proposed to improve energy efficiency and ensure reliable routing; however, trustworthiness and network scalability remain significant research challenges. In this research work, we introduce an AI-enabled Software-Defined Network (SDN)- driven framework to provide secure communication, trusted behavior, and effective route maintenance. By considering multiple parameters in the forwarder selection process, the proposed framework enhances network More >

Başak Müftüoğlu, Sevinç Başay^*

Phyton-International Journal of Experimental Botany, Vol.94, No.10, pp. 3217-3229, 2025, DOI:10.32604/phyton.2025.071755 - 29 October 2025

Abstract Water scarcity is an escalating global challenge that severely threatens productivity and reproductive success in crops, particularly in drought-sensitive species such as Capsicum annuum L. Although deficit irrigation strategies are widely recommended to enhance water use efficiency, knowledge remains limited regarding their interactions with soil amendments such as biochar and the consequent impacts on reproductive traits. This study aimed to evaluate the combined effects of deficit irrigation strategies and biochar application on pollen viability and morphology in Capsicum annuum. The experiment was conducted under full, partial, and deficit irrigation regimes with and without biochar treatment, following a… More >

Rodrigo Rafael da Silva^1,*, Gabriela Carvalho Maia de Queiroz¹, Amanda Cibele da Paz Sousa¹, Antônio Gustavo de Luna Souto¹, Francisco Hélio Alves de Andrade ², Francimar Maik da Silva Morais¹, Rita Magally Oliveira da Silva Marcelino¹, Fagner Nogueira Ferreira¹, Alex Alvares da Silva³, Maria Isabela Batista Clemente¹, Baltazar Cirino Junior¹, Wedson Aleff Oliveira da Silva¹, Mateus de Freitas Almeida dos Santos¹, José Francismar de Medeiros^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.9, pp. 2797-2814, 2025, DOI:10.32604/phyton.2025.068089 - 30 September 2025

Abstract Due to its tolerance to water deficit and salinity, sorghum is considered a suitable crop for cultivation in regions affected by these stress conditions, enabling the efficient use of limited water resources. This study evaluated the resilience of the sweet sorghum cultivar BRS 506 under water deficit and salinity stress, focusing on water relations and yield performance in semiarid conditions. A randomized complete block design was employed in a 3 × 3 factorial arrangement with four replicates. Treatments consisted of three levels of irrigation water salinity (1.50, 3.75, and 6.00 dS m⁻¹) and three irrigation levels… More >

Elyson De La Cruz^*, Hanh Le, Karthik Meduri, Geeta Sandeep Nadella^*, Hari Gonaygunta

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3569-3582, 2025, DOI:10.32604/cmc.2025.068137 - 23 September 2025

Abstract The rapid integration of artificial intelligence (AI) into software development, driven by large language models (LLMs), is reshaping the role of programmers from traditional coders into strategic collaborators within Industry 4.0 ecosystems. This qualitative study employs a hermeneutic phenomenological approach to explore the lived experiences of Information Technology (IT) professionals as they navigate a dynamic technological landscape marked by intelligent automation, shifting professional identities, and emerging ethical concerns. Findings indicate that developers are actively adapting to AI-augmented environments by engaging in continuous upskilling, prompt engineering, interdisciplinary collaboration, and heightened ethical awareness. However, participants also voiced… More >

Zesheng Xi^1,2,#, Chuan He^1,3,#, Yunfan Wang^1,3,#, Bo Zhang^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2545-2565, 2025, DOI:10.32604/cmes.2025.066822 - 31 August 2025

Abstract The increasing reliance on interconnected Internet of Things (IoT) devices has amplified the demand for robust anonymization strategies to protect device identities and ensure secure communication. However, traditional anonymization methods for IoT networks often rely on static identity models, making them vulnerable to inference attacks through long-term observation. Moreover, these methods tend to sacrifice data availability to protect privacy, limiting their practicality in real-world applications. To overcome these limitations, we propose a dynamic device identity anonymization framework using Moving Target Defense (MTD) principles implemented via Software-Defined Networking (SDN). In our model, the SDN controller periodically… More >