E. V. Macias-Melo¹, P. R. Torres-Hernández², K. M. Aguilar-Castro¹, I. Hernández-Pérez¹, P. García-Alamilla³, C. E. Torres-Aguilar¹, M. I. Hernández-López⁴, S. Medina García⁴, J. Serrano-Arellano^4,*

Frontiers in Heat and Mass Transfer, Vol.24, No.1, 2026, DOI:10.32604/fhmt.2025.074900 - 28 February 2026

Abstract This study presents the design, construction, and thermal evaluation of a solar-powered cocoa roaster based on a Parabolic Cylinder Collector (PCC) with dual-axis solar tracking. The system integrates three functional subsystems: the cylindrical-parabolic reflecting surface, the stainless-steel absorber tube, and a microcontroller-based tracking mechanism. The prototype enables continuous acquisition of key thermal variables (solar irradiance, ambient temperature, absorber surface temperature, and bean temperature), allowing a detailed characterization of heat transfer processes during roasting. Roasting experiments were conducted at controlled durations of 40, 55, and 70 min between 10:00 and 14:00 h. Maximum roasting temperatures of… More >

Hui Zhang¹, Yingchun He¹, Min Hong², Yang Wang³, Mingzhang Li¹, Qiguo Zhuang¹, Kui Du¹, Yue Xie^1,*

Phyton-International Journal of Experimental Botany, Vol.95, No.2, 2026, DOI:10.32604/phyton.2026.074974 - 28 February 2026

Abstract The genus Actinidia is primarily functionally dioecious, and early sex identification plays a crucial role in improving breeding efficiency and reducing production costs. In this study, the accuracy of three sex-linked molecular markers (SyGI [Shy Girl], FrBy [Friendly Boy], and SmY1) in sex identification was evaluated in various Actinidia species. The selected marker products were subsequently cloned and sequenced in six wild Actinidia species. Ninety-six wild A. chinensis chinensis accessions and 74 A. chinensis deliciosa accessions, most of which were wild, with only one cultivated, were used for comprehensive primer validation. Thirty-three juvenile A. chinensis chinensis hybrid seedlings were used for practical application… More >

Christian Pérez-Chablé¹, Daisy Pérez-Brito^1,*, Anuar Magaña-Alvarez¹, Jairo Cristóbal-Alejo², Irma L. Medina-Baizabal¹, Marcela Gamboa-Angulo^1,*

Phyton-International Journal of Experimental Botany, Vol.95, No.2, 2026, DOI:10.32604/phyton.2026.072668 - 28 February 2026

Abstract Acalypha gaumeri (Euphorbiaceae) is the only endemic species of the genus in the Yucatan Peninsula. It is dioecious and has antifungal properties against various phytopathogens. In the present study, molecular identification of A. gaumeri was performed using the rbcL region, confirming its belonging to the Acalypha genus. Its genetic diversity was evaluated using 10 SPAR markers (ISSR and DAMD) from 60 individuals collected from female and male plants of the Kiuic, Tinum and Yaxcaba ex-situ populations. The results showed a high level of genetic polymorphism (PIC = 0.980) and significant differences among the populations. Ethanol and aqueous extracts from… More >

Liqiu Suo¹, Lin Xia¹, Yoona Chung¹, Eunchan Kim^1,2,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.076329 - 10 February 2026

Abstract Accurate purchase prediction in e-commerce critically depends on the quality of behavioral features. This paper proposes a layered and interpretable feature engineering framework that organizes user signals into three layers: Basic, Conversion & Stability (efficiency and volatility across actions), and Advanced Interactions & Activity (cross-behavior synergies and intensity). Using real Taobao (Alibaba’s primary e-commerce platform) logs (57,976 records for 10,203 users; 25 November–03 December 2017), we conducted a hierarchical, layer-wise evaluation that holds data splits and hyperparameters fixed while varying only the feature set to quantify each layer’s marginal contribution. Across logistic regression (LR), decision… More >

Zhendong Du^*, Hanliu Wang, Kenji Hashimoto

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.074520 - 10 February 2026

Abstract Planning in lexical-prior-free environments presents a fundamental challenge for evaluating whether large language models (LLMs) possess genuine structural reasoning capabilities beyond lexical memorization. When predicates and action names are replaced with semantically irrelevant random symbols while preserving logical structures, existing direct generation approaches exhibit severe performance degradation. This paper proposes a symbol-agnostic closed-loop planning pipeline that enables models to construct executable plans through systematic validation and iterative refinement. The system implements a complete generate-verify-repair cycle through six core processing components: semantic comprehension extracts structural constraints, language planner generates text plans, symbol translator performs structure-preserving mapping,… More >

Tongcheng Geng^1,#, Zhiyuan Xu^2,#, Yubin Qu^3,*, W. Eric Wong⁴

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.074081 - 10 February 2026

Abstract Large language models (LLMs) have revolutionized AI applications across diverse domains. However, their widespread deployment has introduced critical security vulnerabilities, particularly prompt injection attacks that manipulate model behavior through malicious instructions. Following Kitchenham’s guidelines, this systematic review synthesizes 128 peer-reviewed studies from 2022 to 2025 to provide a unified understanding of this rapidly evolving threat landscape. Our findings reveal a swift progression from simple direct injections to sophisticated multimodal attacks, achieving over 90% success rates against unprotected systems. In response, defense mechanisms show varying effectiveness: input preprocessing achieves 60%–80% detection rates and advanced architectural defenses More >

Jinzheng Yu¹, Yang Xu², Haozhen Li², Junqi Li³, Ligu Zhu¹, Hao Shen^1,*, Lei Shi^1,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.073771 - 10 February 2026

Abstract Online Public Opinion Reports consolidate news and social media for timely crisis management by governments and enterprises. While large language models (LLMs) enable automated report generation, this specific domain lacks formal task definitions and corresponding benchmarks. To bridge this gap, we define the Automated Online Public Opinion Report Generation (OPOR-Gen) task and construct OPOR-Bench, an event-centric dataset with 463 crisis events across 108 countries (comprising 8.8 K news articles and 185 K tweets). To evaluate report quality, we propose OPOR-Eval, a novel agent-based framework that simulates human expert evaluation. Validation experiments show OPOR-Eval achieves a More >

Jian Huang¹, Mingwei Li¹, Yulong Tian¹, Yi Yao², Hao Han^1,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.073201 - 10 February 2026

Abstract With the popularization of new technologies, telephone fraud has become the main means of stealing money and personal identity information. Taking inspiration from the website authentication mechanism, we propose an end-to-end data modem scheme that transmits the caller’s digital certificates through a voice channel for the recipient to verify the caller’s identity. Encoding useful information through voice channels is very difficult without the assistance of telecommunications providers. For example, speech activity detection may quickly classify encoded signals as non-speech signals and reject input waveforms. To address this issue, we propose a novel modulation method based… More >

Sooyong Jeong^1,#, Cheolhee Park^2,#, Dowon Hong^3,*, Changho Seo⁴

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.072561 - 10 February 2026

Abstract With the growing complexity and decentralization of network systems, the attack surface has expanded, which has led to greater concerns over network threats. In this context, artificial intelligence (AI)-based network intrusion detection systems (NIDS) have been extensively studied, and recent efforts have shifted toward integrating distributed learning to enable intelligent and scalable detection mechanisms. However, most existing works focus on individual distributed learning frameworks, and there is a lack of systematic evaluations that compare different algorithms under consistent conditions. In this paper, we present a comprehensive evaluation of representative distributed learning frameworks—Federated Learning (FL), Split… More >

Fankun Meng^1,2,3, Yuyang Liu^1,2,*, Xiaohua Liu⁴, Chenlong Duan^1,2, Yuhui Zhou^1,2,3

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.1, 2026, DOI:10.32604/fdmp.2026.075865 - 06 February 2026

Abstract Carbonate gas reservoirs are often characterized by strong heterogeneity, complex inter-well connectivity, extensive edge or bottom water, and unbalanced production, challenges that are also common in many heterogeneous gas reservoirs with intricate storage and flow behavior. To address these issues within a unified, data-driven framework, this study develops a multi-block material balance model that accounts for inter-block flow and aquifer influx, and is applicable to a wide range of reservoir types. The model incorporates inter-well and well-group conductive connectivity together with pseudo–steady-state aquifer support. The governing equations are solved using a Newton–Raphson scheme, while particle More > Graphic Abstract