Jingru Lv¹, Jianpeng Hu^1,*, Jin Zhao², Yonghao Luo¹

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.073212 - 10 February 2026

Abstract Chinese abbreviations improve communicative efficiency by extracting key components from longer expressions. They are widely used in both daily communication and professional domains. However, existing abbreviation generation methods still face two major challenges. First, sequence-labeling-based approaches often neglect contextual meaning by making binary decisions at the character level, leading to abbreviations that fail to capture semantic completeness. Second, generation-based methods rely heavily on a single decoding process, which frequently produces correct abbreviations but ranks them lower due to inadequate semantic evaluation. To address these limitations, we propose a novel two-stage framework with Generation–Iterative Optimization for More >

Zhongfan Sun, Kan Guo, Yongli Hu^*, Yong Zhang

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.072903 - 10 February 2026

Abstract Knowledge-based Visual Question Answering (VQA) requires the integration of visual information with external knowledge reasoning. Existing approaches typically retrieve information from external corpora and rely on pretrained language models for reasoning. However, their performance is often hindered by the limited capabilities of retrievers and the constrained size of knowledge bases. Moreover, relying on image captions to bridge the modal gap between visual and language modalities can lead to the omission of critical visual details. To address these limitations, we propose the Reflective Chain-of-Thought (ReCoT) method, a simple yet effective framework inspired by metacognition theory. ReCoT effectively activates… More >

Cosmin Dumitru, Emanuel Pantelimon, Alexandru Guzu, Georgian Nicolae^*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.072749 - 10 February 2026

Abstract Unmanned aerial vehicles (UAVs), especially quadcopters, have become indispensable in numerous industrial and scientific applications due to their flexibility, low cost, and capability to operate in dynamic environments. This paper presents a complete design and implementation of a compact autonomous quadcopter capable of trajectory tracking, object detection, precision landing, and real-time telemetry via long-range communication protocols. The system integrates an onboard flight controller running real-time sensor fusion algorithms, a vision-based detection system on a companion single-board computer, and a telemetry unit using Long Range (LoRa) communication. Extensive flight tests were conducted to validate the system’s More >

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 >