Erdinç Uslan^1,*, Emin Ulugergerli²

Revue Internationale de Géomatique, Vol.35, pp. 31-51, 2026, DOI:10.32604/rig.2026.075081 - 05 February 2026

Abstract Climate classification systems are essential tools for analyzing regional climatic behavior, assessing long-term aridity patterns, and evaluating the impacts of climate change on water resources and ecosystem resilience. This study introduces a new Climate Classification Method based on uniform and unitless variables, referred to as the U2 Climate Classification (U2CC). The proposed U2 Index was designed to overcome structural limitations of the classical De Martonne (1942) and Erinç (1949) indices, which rely on raw precipitation–temperature ratios and are sensitive to extreme values, particularly subzero temperatures. The U2 methodology consisted of two key steps: (i) normalization… More >

Meng Wang¹, Jinghan Cai¹, Wenzheng Liu¹, Xue Yang¹, Jingjing Zhang¹, Qiangmin Zhou¹, Fanzhen Wang¹, Hang Zhang^1,*, Tonghai Liu^2,*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2025.075541 - 30 January 2026

Abstract Tomato is a major economic crop worldwide, and diseases on tomato leaves can significantly reduce both yield and quality. Traditional manual inspection is inefficient and highly subjective, making it difficult to meet the requirements of early disease identification in complex natural environments. To address this issue, this study proposes an improved YOLO11-based model, YOLO-SPDNet (Scale Sequence Fusion, Position-Channel Attention, and Dual Enhancement Network). The model integrates the SEAM (Self-Ensembling Attention Mechanism) semantic enhancement module, the MLCA (Mixed Local Channel Attention) lightweight attention mechanism, and the SPA (Scale-Position-Detail Awareness) module composed of SSFF (Scale Sequence Feature… More >

Dmytro A. Kiriziy¹, Oksana V. Dubrovna¹, Oksana G. Sokolovska-Sergiienko¹, Alina S. Holoboroda¹, Victor V. Rohach^1,2, Oleg O. Stasik^1,*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2026.075371 - 30 January 2026

Abstract Water scarcity severely constrains the genetic potential of wheat yield worldwide. Proline is among the most versatile stress-related metabolites in plants, and targeting genes involved in proline synthesis and degradation represents a promising strategy for developing drought-tolerant wheat genotypes. This study evaluates the performance of the photosynthetic apparatus in transgenic wheat line with RNAi-mediated suppression of proline dehydrogenase (ProDH) and in the original (wild-type) genotype, under both drought and recovery conditions. Drought was induced at the flowering stage by lowering soil moisture to 30% field capacity for 7 days, compared with 70% field capacity in… More >

Kirti A. Yadav¹, Yachana Jha¹, Haiam O. Elkatry², Heba I. Mohamed^3,*, Ahmed Mahmoud Ismail⁴, Abdelrahman R. Ahmed^2,*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2026.074570 - 30 January 2026

Abstract Phytophthora blight is a devastating disease of pigeon pea (Cajanus cajan) that severely impacts plant growth and productivity. This study investigates the morphological, anatomical, and biochemical responses of a susceptible variety (ICPL 11260) and a resistant variety (IPAC-02) following infection by Phytophthora. Morphological analyses showed that infection caused a drastic reduction in root length, shoot length, leaf number, fresh weight, and dry weight in the susceptible ICPL 11260 variety, with reductions ranging from 0.5- to 2-fold compared to non-infected controls. Anatomical observations revealed pronounced cellular damage and mycelial invasion in infected ICPL 11260 plants by 30… More >

Mohammed Al-Mahbashi^1,2,*, Ali Ahmed³, Abdolraheem Khader^4,*, Shakeel Ahmad³, Mohamed A. Damos⁵, Ahmed Abdu⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.075909 - 29 January 2026

Abstract Reliable detection of traffic signs and lights (TSLs) at long range and under varying illumination is essential for improving the perception and safety of autonomous driving systems (ADS). Traditional object detection models often exhibit significant performance degradation in real-world environments characterized by high dynamic range and complex lighting conditions. To overcome these limitations, this research presents FED-YOLOv10s, an improved and lightweight object detection framework based on You Only look Once v10 (YOLOv10). The proposed model integrates a C2f-Faster block derived from FasterNet to reduce parameters and floating-point operations, an Efficient Multiscale Attention (EMA) mechanism to More >

Nuh Azginoglu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2026.075834 - 29 January 2026

Abstract Breast cancer screening programs rely heavily on mammography for early detection; however, diagnostic performance is strongly affected by inter-reader variability, breast density, and the limitations of conventional computer-aided detection systems. Recent advances in deep learning have enabled more robust and scalable solutions for large-scale screening, yet a systematic comparison of modern object detection architectures on nationally representative datasets remains limited. This study presents a comprehensive quantitative comparison of prominent deep learning–based object detection architectures for Artificial Intelligence-assisted mammography analysis using the MammosighTR dataset, developed within the Turkish National Breast Cancer Screening Program. The dataset comprises… More >

SEUNGIL KIM, GUN-DONG KIM^*

BIOCELL, Vol.50, No.1, 2026, DOI:10.32604/biocell.2025.073781 - 23 January 2026

Abstract Neutrophil extracellular trap (NET) formation or NETosis is a specialized innate immune process in which neutrophils release chromatin fibers decorated with histones and antimicrobial proteins. Although pivotal for pathogen clearance, aberrant NETosis has emerged as a critical modulator of acute and chronic respiratory pathologies, including acute respiratory distress syndrome, asthma, and chronic obstructive pulmonary disease. Dysregulated NET release exacerbates airway inflammation by inducing epithelial injury, mucus hypersecretion, and the recruitment of inflammatory leukocytes, thereby accelerating tissue remodeling and functional decline. Mechanistically, NETosis is governed by peptidyl arginine deiminase 4 (PADI4)-mediated histone citrullination, NADPH oxidase-dependent reactive More >

Mayuri Shukla¹, Soraya Boonmag², Parichart Boontem¹, Piyarat Govitrapong^1,*

BIOCELL, Vol.50, No.1, 2026, DOI:10.32604/biocell.2025.072557 - 23 January 2026

Abstract Ischemic stroke is one of the major causes of long-term disability and mortality worldwide. It results from an interruption in the cerebral blood flow, triggering a cascade of detrimental events like oxidative stress, mitochondrial dysfunction, neuroinflammation, excitotoxicity, and apoptosis, causing neuronal injury and cellular death. Melatonin, a pleiotropic indoleamine produced by the pineal gland, has multifaceted neuroprotective effects on stroke pathophysiology. Interestingly, the serum melatonin levels are associated with peroxidation and antioxidant status, along with mortality score in patients with severe middle cerebral artery infarction. Melatonin exhibits strong antioxidant, anti-inflammatory, and anti-apoptotic properties and preserves More >

Safwan Al-sayed¹, Xi Wang¹, Yijiang Peng^1,*, Esraa Hyarat², Ahmad Ali AlZubi³

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.074068 - 12 January 2026

Abstract In modern construction, Lightweight Aggregate Concrete (LWAC) has been recognized as a vital material of concern because of its unique properties, such as reduced density and improved thermal insulation. Despite the extensive knowledge regarding its macroscopic properties, there is a wide knowledge gap in understanding the influence of microscale parameters like aggregate porosity and volume ratio on the mechanical response of LWAC. This study aims to bridge this knowledge gap, spurred by the need to enhance the predictability and applicability of LWAC in various construction environments. With the help of advanced numerical methods, including the… More >

Xiang Luo¹, Yuxuan Peng², Renghong Xie¹, Peng Li³, Yuwen Qian^3,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073700 - 12 January 2026

Abstract Deep learning has made significant progress in the field of oriented object detection for remote sensing images. However, existing methods still face challenges when dealing with difficult tasks such as multi-scale targets, complex backgrounds, and small objects in remote sensing. Maintaining model lightweight to address resource constraints in remote sensing scenarios while improving task completion for remote sensing tasks remains a research hotspot. Therefore, we propose an enhanced multi-scale feature extraction lightweight network EM-YOLO based on the YOLOv8s architecture, specifically optimized for the characteristics of large target scale variations, diverse orientations, and numerous small objects… More >