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, DOI:10.32604/phyton.2025.075541

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 >

Jiazhou Li^1,2, Mingyu Zhang¹, Xing Li^1,3, Fangbo Cao^1,2, Jiana Chen^1,2, Weiqin Wang^1,2, Huabin Zheng^1,2, Min Huang^1,2,4,*

Phyton-International Journal of Experimental Botany, DOI:10.32604/phyton.2025.075255

Abstract Spikelet filling characteristics in early-season rice in southern China may be distinctive due to its exposure to high temperatures during the ripening period. However, limited information is currently available on these characteristics. This study aimed to characterize spikelet filling in early-season rice and identify the key factors contributing to its improvement. Field experiments were conducted over two years (2021 and 2022) to mainly investigate the proportions of fully-filled, partially-filled, and empty spikelets, along with the biomass-fertilized spikelet ratio and harvest index, in 11 early-season rice varieties. The results revealed significant varietal variation in spikelet filling,… More >

Adolfo Amador Mendoza^1,*, Rosalba Guadalupe Gomez Raymundo², Ana Rosa Ramírez Seañez¹, Hipolito Hernández Hernández¹, Rogelio Enrrique Palacios Torres¹, Nelda Xanath Martínez Galero³, Miguel Ángel García Muñoz³, Saribel Zilli Gutiérrez^4,*

Phyton-International Journal of Experimental Botany, DOI:10.32604/phyton.2025.073856

Abstract The cultivation of Soledad pepper (Capsicum annuum L.) is essential in Oaxaca and Veracruz, but it faces issues with pests and diseases, which affect yield and cause economic losses. To mitigate these impacts, farmers have started using biostimulants such as chitosan and plant growth promoting bacteria instead of agrochemicals due to their environmental and health benefits. This study evaluated the effect of Bacillus subtilis and chitosan, both individually and combined, on the growth, yield, and fruit quality of Soledad pepper under greenhouse conditions. Four treatments were applied at different stages of the crop cycle: Q (Chitosan), BS (Bacillus More >

Fitra Yurid^1,2, Nadiatus Silmi³, Heni Rachmawati^4,5, Nanda Nagara², Riyanti Ekafitri⁶, Athanasia Amanda Septevani^2,7,*

Journal of Renewable Materials, DOI:10.32604/jrm.2025.02025-0118

Abstract This study investigates the potential of starch extracted from underutilized agro-industrial resources as non-food-competing raw materials for the development of flexible bioplastics for food packaging applications. Starch was extracted from three biomass sources: rubber cassava (Manihot glaziovii), banana stem, and banana peel from Ambonese banana (Musa acuminata L.). Rubber cassava starch (S_RC) exhibited the highest starch yield (50.68 ± 0.28%), significantly surpassing banana stem (S_BS, 14.20 ± 0.25%) and banana peel (S_BP, 3.07 ± 0.15%). The amylose contents of S_RC, S_BS, and S_BP were 28.18%, 52.80%, and 56.57%, respectively, while their amylopectin contents were 71.83%, 47.20%, and 43.43%. FTIR spectra… More >

Junmin Tang^1,*, Yi Ding², Juzheng Zhu³, Hongbo Zhong³, Yanliang Long⁴, Shuo Dong⁵

Energy Engineering, DOI:10.32604/ee.2025.074489

Abstract With the rapid growth of the electric vehicle (EV) population and the development of active distribution networks (DN), the optimal scheduling of power systems that incorporate EVs has become increasingly important. electric vehicle battery swap stations (EVBSS), leveraging their substantial battery resources and suitability for centralized scheduling, offer a new approach for enhancing DN flexibility. Accordingly, this paper proposes a two-stage optimal scheduling method for DN that considers low-carbon demand response and the battery life of EVBSS. The method employs dynamic carbon emission factors as penalty components in time-of-use electricity pricing, thereby transmitting carbon signals… More >

Ebtehal Chasseb Jbary^*, Alaa R. Al-Badri

Energy Engineering, DOI:10.32604/ee.2025.074415

Abstract Despite significant advancements in solar collector technology, persistent challenges remain in improving the overall efficiency of solar systems. This paper investigates the use of mini-channel aluminum tubes mounted on the reflective surface as preliminary heating stages to enhance the overall system thermal performance. Experimental assessments were conducted with flow rates ranging from 0.1 to 0.8 LPM and tilt angles of 180° South and 225° Southwest in Al-Kut, Iraq, from 9:00 AM to 2:00 PM. Fluid flows sequentially through five flat aluminum tubes totaling 50 channels, named stage-1, then flows through four aluminum tubes totaling 40… More >

Lihua Zhong¹, Feng Pan¹, Yuyao Yang¹, Lei Feng¹, Jinghe Jiang², Guo Lin², Xiaoshun Zhang^3,*

Energy Engineering, DOI:10.32604/ee.2025.073240

Abstract This paper addresses the challenge of efficiently calculating dynamic carbon emission factors (CEFs) in large-scale power systems. Traditional methods that rely on direct matrix inversion are computationally intensive and become impractical for networks with thousands of nodes. To overcome this limitation, a fast and scalable computational framework is proposed based on the incomplete LU (ILU) preconditioned biconjugate gradient stabilized (BiCGSTAB) iterative solver. The proposed approach formulates the nodal CEF model as a sparse linear system and employs Krylov subspace acceleration with ILU preconditioning to enhance convergence and numerical stability. The method is applied to synthetic… More >

Zhongbin Luo^1,2, Zhaoyang Guan³, Wenxing You², Yunteng Wang², Yanqiu Bi^4,5,*

CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2025.075704

Abstract Gait recognition is a key biometric for long-distance identification, yet its performance is severely degraded by real-world challenges such as varying clothing, carrying conditions, and changing viewpoints. While combining silhouette and skeleton data is a promising direction, effectively fusing these heterogeneous modalities and adaptively weighting their contributions in response to diverse conditions remains a central problem. This paper introduces GaitMAFF, a novel Multi-modal Adaptive Feature Fusion Network, to address this challenge. Our approach first transforms discrete skeleton joints into a dense Skeleton Map representation to align with silhouettes, then employs an attention-based module to dynamically More >

Weimin Shi^1,*, Kuntao Lv¹, Chang Xuan¹, Ji Wu²

CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2025.075203

Abstract The application of deep learning in fabric defect detection has become increasingly widespread. To address false positives and false negatives in fabric roll seam detection, and to improve automation efficiency and product quality, we propose the Multi-scale Context DeepLabV3+ (MSC-DeepLabV3+), a semantic segmentation network designed for fabric roll seam detection, based on DeepLabV3+. The model improvements include enhancing the backbone performance through optimization of the UIB-MobileNetV2 network; designing the Dynamic Atrous and Sliding-window Fusion (DASF) module to improve adaptability to multi-scale seam structures with dynamic dilation rates and a sliding-window mechanism; and utilizing the Progressive… More >

Thi-Xuyen Bui^1,2, Yu-Sheng Lu¹, Yu-Sheng Liao¹, Te-Hua Fang^1,3,*

CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2025.074862

Abstract Context: The mechanical performance of exceedingly soft materials such as Ag is significantly influenced by various working conditions. Therefore, this study systematically investigates the effects of crack geometry, substrate crystal orientation, and indenter shape on crack propagation. The mechanical response of Ag is analyzed using the quasi-continuum (QC) method. A pre-crack with a predefined depth and angle was introduced to initiate fracture behavior. The results show that when the pre-crack height is 50 Å, the crack propagates rapidly as the imprint depth increases from 0 to 7 Å, grows steadily up to 15 Å, and… More >