José Luis Rodríguez-Lorenzo¹, José Javier Martín-Gómez², Ángel Anocibar Beloqui³, Félix Cabello Sáenz de Santamaría⁴, Gregorio Muñoz Organero⁴, Ángel Tocino⁵, Emilio Cervantes^2,*

Phyton-International Journal of Experimental Botany, Vol.95, No.6, 2026, DOI:10.32604/phyton.2026.080612 - 29 June 2026

Abstract Background: The transition from wild Vitis vinifera subsp. sylvestris to cultivated grapes led to major changes in seed shape, known as the “domestication syndrome.” While traditional measurements distinguish these groups, high-resolution geometric analysis provides a more precise way to track domestication and variety stability. Objective: This study uses a multi-parametric approach—combining Fourier descriptors, curvature analysis, and the J-Index—to quantify seed shape variation across 121 Vitis populations. Methods: We analysed 48 varieties, including wild species and three major cultivated lineages (Iberian, Central European, and Muscat). Results: Principal Component Analysis (PCA) successfully separated wild and cultivated groups. The first three components explained… More >

Sravani Parvathareddy^1,*, Abid Yahya¹, Lilian Amuhaya¹, Ravi Samikannu¹, Raymond S. Suglo²

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2026.079449 - 27 May 2026

Abstract This paper presents a novel framework for the development of a real-time energy management system for mining microgrids, which integrates the benefits of a long short-term memory (LSTM) network and a feedforward neural network (FNN) for the prediction of the load and solar power, and the optimization of the dispatch, respectively, while ensuring the safety of the microgrid through the application of a convex safety filter. In the proposed framework, the LSTM provides probabilistic multi-step forecasts of load and photovoltaic generation, capturing the high volatility characteristic of mining operations with ramp rates up to 5… More > Graphic Abstract

Awais Ahmad¹, Fakhri Alam Khan^2,3, Awais Ahmad⁴, Gautam Srivastava^5,6,7, Syed Atif Moqurrab^8,*, Abdul Razaque⁹, Dina S. M. Hassan^10,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.076104 - 09 April 2026

Abstract Collision avoidance is recognized as a critical challenge in Vehicular Ad-Hoc Networks (VANETs), which demand real-time decision-making. It plays a vital role in ensuring road safety and traffic efficiency. Traditional approaches like rule-based systems and heuristic methods fail to provide optimal solutions in dynamic and unpredictable traffic scenarios. They cannot balance multiple objectives like minimizing collision risk, ensuring passenger comfort, and optimizing fuel efficiency, leading to suboptimal performance in real-world conditions. To tackle collision avoidance, this paper introduces a novel approach by defining the issue as an optimal control problem and solving it using the… More >

Jianfeng Lu¹, Tao Huang¹, Yuanai Xie^2,*, Shuqin Cao¹, Bing Li³

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 619-634, 2025, DOI:10.32604/cmc.2025.060094 - 26 March 2025

Abstract The proliferation of deep learning (DL) has amplified the demand for processing large and complex datasets for tasks such as modeling, classification, and identification. However, traditional DL methods compromise client privacy by collecting sensitive data, underscoring the necessity for privacy-preserving solutions like Federated Learning (FL). FL effectively addresses escalating privacy concerns by facilitating collaborative model training without necessitating the sharing of raw data. Given that FL clients autonomously manage training data, encouraging client engagement is pivotal for successful model training. To overcome challenges like unreliable communication and budget constraints, we present ENTIRE, a contract-based dynamic… More >

Yuan Ping^1,2,*, Huina Li¹, Chun Guo³, Bin Hao⁴

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4949-4976, 2025, DOI:10.32604/cmc.2025.057693 - 06 March 2025

Abstract Towards optimal k-prototype discovery, k-means-like algorithms give us inspirations of central samples collection, yet the unstable seed samples selection, the hypothesis of a circle-like pattern, and the unknown K are still challenges, particularly for non-predetermined data patterns. We propose an adaptive k-prototype clustering method (kProtoClust) which launches cluster exploration with a sketchy division of K clusters and finds evidence for splitting and merging. On behalf of a group of data samples, support vectors and outliers from the perspective of support vector data description are not the appropriate candidates for prototypes, while inner samples become the first candidates for… More >

Xincong Shi^1,2, Yuze Ji^3,*, Xinrui Wang³, Ruimin Tian³, Chao Zhang²

Energy Engineering, Vol.122, No.3, pp. 1199-1220, 2025, DOI:10.32604/ee.2025.061586 - 07 March 2025

Abstract With the development of integrated power and gas distribution systems (IPGS) incorporating renewable energy sources (RESs), coordinating the restoration processes of the power distribution system (PS) and the gas distribution system (GS) by utilizing the benefits of RESs enhances service restoration. In this context, this paper proposes a coordinated service restoration framework that considers the uncertainty in RESs and the bi-directional restoration interactions between the PS and GS. Additionally, a coordinated service restoration model is developed considering the two systems’ interdependency and the GS’s dynamic characteristics. The objective is to maximize the system resilience index… More >

Zeyu Deng¹, Yuan Liang^1,*, Gengdong Cheng¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.012504

Abstract Compared to single-material optimization, topology optimization of multi-material structures offers a larger design space. It also requires efficient material selection methods to provide guidance for designers. The predominant methods are based on interpolation schemes, which introduce order-dependence issues during the optimization process. This means the sequence in which materials are arranged can significantly impact the optimization outcomes and may lead to notable issues with material gradation. This paper identifies the mathematical essence of multi-material topology optimization as a nonlinear multi-valued integer programming problem. In this paper, we propose a novel stochastic discrete steepest descent multi-valued More >

Bo Hui^1,2,*, Shengneng Zhu², Sijun Su², Wenjuan Li²

Frontiers in Heat and Mass Transfer, Vol.22, No.3, pp. 855-868, 2024, DOI:10.32604/fhmt.2024.051387 - 11 July 2024

Abstract The structure of the concave-convex plates has proven to be crucial in optimizing the internal flow characteristics of the electrolyzer for hydrogen production. This paper investigates the impact of the gradual expansion angle of the inlet channel on the internal flow field of alkaline electrolyzers. The flow distribution characteristics of concave-convex plates with different inlet angle structures in the electrolytic cell is discussed. Besides, the system with internal heat source is studied. The results indicate that a moderate gradual expansion angle is beneficial for enhancing fluid uniformity. However, an excessively large gradual expansion angle may More > Graphic Abstract

Penghui Liu^1,2,*, Yaning Zhang¹, Yuxing Dai², Yanzhou Sun^1,3

Energy Engineering, Vol.121, No.7, pp. 1883-1901, 2024, DOI:10.32604/ee.2024.049318 - 11 June 2024

Abstract Arc grounding faults occur frequently in the power grid with small resistance grounding neutral points. The existing arc fault identification technology only uses the fault line signal characteristics to set the identification index, which leads to detection failure when the arc zero-off characteristic is short. To solve this problem, this paper presents an arc fault identification method by utilizing integrated signal characteristics of both the fault line and sound lines. Firstly, the waveform characteristics of the fault line and sound lines under an arc grounding fault are studied. After that, the convex hull, gradient product,… More >

Fangyi Li^*, Dachang Zhu^*, Huimin Shi

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1981-1999, 2024, DOI:10.32604/cmes.2023.031332 - 29 January 2024

Abstract In time-variant reliability problems, there are a lot of uncertain variables from different sources. Therefore, it is important to consider these uncertainties in engineering. In addition, time-variant reliability problems typically involve a complex multilevel nested optimization problem, which can result in an enormous amount of computation. To this end, this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model. In this method, the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a time-independent reliability More >