Saif Ullah^1,2, Izhar Ali^1,2,*

Phyton-International Journal of Experimental Botany, DOI:10.32604/phyton.2025.064608

Abstract Nitrogen (N) assimilation is crucial for the growth and development of C₃ plants, as it converts inorganic N into organic forms, important for protein synthesis, nucleic acids and other vital biomolecules. However, abiotic stressors such as drought, salinity, extreme temperatures and others significantly impact N uptake and utilization, thereby hindering plant growth and development. Recent advances in molecular biology have illuminated the complex networks that govern N assimilation under these stressful conditions, emphasizing the role of transcription factors, regulatory genes, and stress-responsive pathways. This review provides an integrated perspective on the latest research in nitrogen metabolism… More >

Mohsen Ali Alawami¹, Dahyun Jung², Yewon Park², Yoonseo Ku², Gyeonghwan Choi², Ki-Woong Park^2,*

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.063819

Abstract To date, many previous studies have been proposed for driver authentication; however, these solutions have many shortcomings and are still far from practical for real-world applications. In this paper, we tackle the shortcomings of the existing solutions and reach toward proposing a lightweight and practical authentication system, dubbed DriveMe, for identifying drivers on cars. Our novelty aspects are ① Lightweight scheme that depends only on a single sensor data (i.e., pressure readings) attached to the driver’s seat and belt. ② Practical evaluation in which one-class authentication models are trained from only the owner users and tested using… More >

Qingyu Tan, Yan Li, Byeong-Seok Shin^*

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.063811

Abstract Federated Learning (FL), a practical solution that leverages distributed data across devices without the need for centralized data storage, which enables multiple participants to jointly train models while preserving data privacy and avoiding direct data sharing. Despite its privacy-preserving advantages, FL remains vulnerable to backdoor attacks, where malicious participants introduce backdoors into local models that are then propagated to the global model through the aggregation process. While existing differential privacy defenses have demonstrated effectiveness against backdoor attacks in FL, they often incur a significant degradation in the performance of the aggregated models on benign tasks.… More >

Sirawit Makaew, Yupaporn Areepong^*, Saowanit Sukparungsee

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.063459

Abstract This study aims to examine the explicit solution for calculating the Average Run Length (ARL) on the triple exponentially weighted moving average (TEWMA) control chart applied to autoregressive model (AR(p)), where AR(p) is an autoregressive model of order p, representing a time series with dependencies on its p previous values. Additionally, the study evaluates the accuracy of both explicit and numerical integral equation (NIE) solutions for AR(p) using the TEWMA control chart, focusing on the absolute percentage relative error. The results indicate that the explicit and approximate solutions are in close agreement. Furthermore, the study More >

Trong Hieu Luu¹, Phan Nguyen Ky Phuc², Quang Hieu Ngo^1,*, Thanh Tam Nguyen³, Huu Cuong Nguyen¹

CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2025.064007

Abstract This study presents a drone-based aerial imaging method for automated rice seedling detection and counting in paddy fields. Utilizing a drone equipped with a high-resolution camera, images are captured 14 days post-sowing at a consistent altitude of six meters, employing autonomous flight for uniform data acquisition. The approach effectively addresses the distinct growth patterns of both single and clustered rice seedlings at this early stage. The methodology follows a two-step process: first, the GoogleNet deep learning network identifies the location and center points of rice plants. Then, the U-Net deep learning network performs classification and… More >

Chen Wang^1,2, Tiezheng Guo¹, Qingwen Yang¹, Yanyi Liu¹, Jiawei Tang¹, Yingyou Wen^1,2,*

CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2025.063676

Abstract Primary light chain amyloidosis is a rare hematologic disease with multi-organ involvement. Nearly one-third of patients with amyloidosis experience five or more consultations before diagnosis, which may lead to a poor prognosis due to delayed diagnosis. Early risk prediction based on artificial intelligence is valuable for clinical diagnosis and treatment of amyloidosis. For this disease, we propose an Evolutionary Neural Architecture Searching (ENAS) based risk prediction model, which achieves high-precision early risk prediction using physical examination data as a reference factor. To further enhance the value of clinic application, we designed a natural language-based interpretable… More >

Rahim Khan¹, Ihsan Rabbi¹, Umar Farooq¹, Jawad Khan^2,*, Fahad Alturise^3,*

CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2025.063303

Abstract Leaf disease identification is one of the most promising applications of convolutional neural networks (CNNs). This method represents a significant step towards revolutionizing agriculture by enabling the quick and accurate assessment of plant health. In this study, a CNN model was specifically designed and tested to detect and categorize diseases on fig tree leaves. The researchers utilized a dataset of 3422 images, divided into four classes: healthy, fig rust, fig mosaic, and anthracnose. These diseases can significantly reduce the yield and quality of fig tree fruit. The objective of this research is to develop a… More >

Dang Hung Tran, Van Tinh Nguyen^*

CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2025.063228

Abstract It is known that long non-coding RNAs (lncRNAs) play vital roles in biological processes and contribute to the progression, development, and treatment of various diseases. Obviously, understanding associations between diseases and lncRNAs significantly enhances our ability to interpret disease mechanisms. Nevertheless, the process of determining lncRNA-disease associations is costly, labor-intensive, and time-consuming. Hence, it is expected to foster computational strategies to uncover lncRNA-disease relationships for further verification to save time and resources. In this study, a collaborative filtering and graph attention network-based LncRNA-Disease Association (CFGANLDA) method was nominated to expose potential lncRNA-disease associations. First, it… More >

Thien-Tan Cao, Huu-Thanh Duong, Viet-Tuan Le, Hau Nguyen Trung, Vinh Truong Hoang, Kiet Tran-Trung^*

CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2025.061583

Abstract Kinship verification is a key biometric recognition task that determines biological relationships based on physical features. Traditional methods predominantly use facial recognition, leveraging established techniques and extensive datasets. However, recent research has highlighted ear recognition as a promising alternative, offering advantages in robustness against variations in facial expressions, aging, and occlusions. Despite its potential, a significant challenge in ear-based kinship verification is the lack of large-scale datasets necessary for training deep learning models effectively. To address this challenge, we introduce the EarKinshipVN dataset, a novel and extensive collection of ear images designed specifically for kinship… More >

MARíA BELéN ROCCO, CLARA REQUENA D’ALESSIO, VALERIA GISELLE SáNCHEZ, HORACIO EDUARDO ROMEO, MARíA LAURA BARREIRO ARCOS^*

BIOCELL, DOI:10.32604/biocell.2025.062525

Abstract Introduction: Hyperthyroidism is known to affect various physiological systems, including the immune system. Thyroid hormones (THs) play a crucial role in regulating immune function, and alterations in THs levels can lead to immune dysregulation. Objective: Currently, we aimed to elucidate the effects of hyperthyroidism on immune function in BALB/c mice, with a focus on anatomical and histological changes in lymphoid organs, the immune response to mitogenic stimulation, mitochondrial dynamics, and reactive oxygen species (ROS) production. Methods: Hyperthyroidism was induced in BALB/c mice by administering thyroxine (T4; 14 mg/L) in their drinking water for 30 days. Thyroid… More >