Holy Oghenewona Ovwiurhobo¹, Marius O. Eji², Adil Alshoaibi³, Ndanduleni Lethole⁴, Chawki Awada³, Shumaila Islam³, Nisrin Alnaim³, Fabian I. Ezema^1,4,*

Chalcogenide Letters, Vol.23, No.8, 2026, DOI:10.32604/cl.2026.086712 - 18 September 2026

Abstract Several studies have reported a growing interest in nanomaterials beyond conventional graphite, driven by the rapid global demand for sustainable, high-performance energy storage. Among these materials, two-dimensional (2D) transition metal chalcogenides (TMCs), molybdenum- and tin-based systems such as molybdenum disulfide (MoS₂) and tin (IV) disulfide (SnS₂) in particular, have emerged as promising candidates for next-generation electrochemical energy storage devices (EESDs). This is owing to their unique X-M-X sandwich architectures, tunable electronic properties, and versatile intercalation chemistry. Despite several studies on 2D TMCs and their applications in EESDs, a gap still exists, as there is no comprehensive… More > Graphic Abstract

Kuldashbay Avazov¹, Jasur Sevinov^2,3, Komil Tashev⁴, Jamila Arzieva⁵, Tulkin Botirov⁶, Alpamis Kutlimuratov⁷, Akmalbek Abdusalomov^{2,4,8,9,10,11}, Boburjon Vafoev¹², Young Im Cho^1,*

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.087927 - 15 September 2026

Abstract Wireless sensor networks (WSNs) and Internet of Things (IoT) systems require lightweight cryptographic primitives that provide strong security under strict constraints on area, latency, and timing predictability. Ascon, selected by National Institute of Standards and Technology (NIST) as the standard for lightweight authenticated encryption, is well suited for such environments, yet application-oriented hardware implementations for WSN platforms remain underexplored. This paper presents a comprehensive evaluation of field programmable gate array (FPGA)-based Ascon architectures for secure WSN and IoT deployments, using iterative design with single permutation round and hybrid design with two-round unrolling across two FPGA… More >

Nashat Nawafleh^*, Faris M. Al-Oqla

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.087255 - 15 September 2026

Abstract In order to mimic the thermal properties of various natural fibers, this research presents a novel prediction framework that combines Fuzzy Logic (FL) with Grey Wolf Optimization (GWO). While the GWO technique ensures mathematical correctness by fine-tuning membership function parameters, this research uses a hybrid fuzzy model to outline nonlinear relationships between fiber components and thermal performance, which significantly reduces the need for extensive, trial-and-error laboratory testing. In this study, moisture, cellulose, and hemicellulose levels are predicted to be used to identify the finest natural fibers for biomaterial uses. An optimization methodology is seen by More >

Rui Huang¹, Ziwei Zhang^2,*, Kari Tusongjiang¹, Bowen Zhang³, Ning Yang³, Xiaowei Li¹, Aimudula Maierdan¹

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.086232 - 15 September 2026

Abstract The accuracy of partial discharge (PD) pattern recognition is essential for assessing the insulation condition of gas-insulated switchgear (GIS). However, in practical recognition tasks, phase-resolved partial discharge (PRPD) patterns often exhibit complex feature distributions, and key discharge characteristics may be weakened during feature extraction. This study proposes an improved sparrow search algorithm (ISSA)-optimized attention-enhanced ConvNeXt model for GIS PD pattern recognition. A multi-criterion grayscale evaluation scheme is first employed to select the most suitable grayscale conversion for PRPD patterns, aiming to preserve informative discharge regions and reduce redundant color interference. Subsequently, an attention-enhanced ConvNeXt model… More >

Jianwei Zhang^1,2,*, Ran Shen¹, Qianqi Zhang¹, Yuanxin Li^1,*, Shengchao Chen^3,4,*, Minghao Zhao^2,3, Lubing Shi⁴, Bing Wang⁵

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.084790 - 15 September 2026

Abstract Non-equibiaxial residual stresses are prevalent in engineering components such as welding, additive manufacturing, and surface strengthening, making their accurate detection critical for ensuring structural integrity. This paper proposes a novel method capable of simultaneously identifying two principal stress components (${\sigma }_{\mathrm{x}}^{\mathrm{R}}$, ${\sigma }_{\mathrm{z}}^{\mathrm{R}}$) using only an individual instrumented indentation. First, the normalized total indentation work variation W_norm and the residual indentation ellipticity λ are extracted as sensitive features from the indentation responses through dimensional analysis. Subsequently, a finite element (FE) simulation database comprising 2400 datasets was established to train three types of neural networks: the… More >

Navod Neranjan Thilakarathne^1,*, Madhuka Priyashan Wedisinhage Don², Sharmi Malisha Dilshani³, Jamil Abedalrahim Jamil Alsayaydeh^4,*, Mohd Faizal Bin Yusof⁵, Rostam Affendi Bin Hamzah⁴

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.082189 - 15 September 2026

Abstract With the growing world population and demand for agricultural goods, agriculture requires innovative technologies that make the best use of resource, reduce waste, and increase productivity. So, smart agriculture, which involves the use of innovative digital technologies to enhance the quality and quantity of harvests, has come into play, superseding traditional agriculture. In recent years, the concept of the digital twin has intertwined with smart agriculture to enable precise control of entire farms, facilitating virtual replications. Overall, the digital twin enables continuous monitoring of real-time conditions in the field, providing valuable insights into crop health,… More >

Mohammadreza Nehzati^*

Journal of Intelligent Medicine and Healthcare, Vol.4, pp. 155-177, 2026, DOI:10.32604/jimh.2026.082983 - 14 September 2026

Abstract Background: Exponential growth of diverse clinical data presents challenges for real-time predictive analytics in healthcare. Federated learning offers a paradigm for multi-institutional model training without centralized data sharing, but large-scale deployment across diverse healthcare settings with real-world electronic health record (EHR) integration challenges remains limited. Methods: We implemented Phase 1 of a federated learning network deploying federated histogram-based XGBoost across 47 U.S. healthcare institutions from January to June 2023 as a quality improvement initiative. The system processes clinical data locally, transmitting only gradient and Hessian histograms with differential privacy (ε = 1.0, δ = 10⁻⁵). Primary… More >

Aiyu Ma^1,2,#, Xu Wang^1,2,#, Lu Lu¹, Shuaijie Wang³, Qiuyu Zhao¹, Xuemei Zhang³, Yiping Sun¹, Xuan Meng¹, Yan Zhang¹, Yuzhong Yang¹, Jinhua Zheng^1,2, Xiang Zheng^1,2,*

Oncology Research, Vol.34, No.10, 2026, DOI:10.32604/or.2026.084662 - 14 September 2026

Abstract Objectives: YTH N6-Methyladenosine RNA Binding Protein F2 (YTHDF2) had been implicated in nasopharyngeal carcinoma (NPC) progression. Increasing evidence indicated that numerous circular RNAs (circRNAs) were involved in regulating tumor progression. However, how the regulation of circRNAs by YTHDF2 contributes to NPC progression remains to be uncovered. In this study, we aimed to elucidate the role and mechanism of YTHDF2-mediated circRNA regulation in NPC migration and invasion. Methods: YTHDF2 expression in NPC was assessed using GEO datasets and immunohistochemistry. Functional experiments were performed in HNE1 and 5-8F cells, with migration/invasion evaluated by wound healing and transwell assays,… More >

Songming Liu¹, Siyuan Yin^2,*

Journal of Psychology in Africa, Vol.36, No.4, pp. 701-709, 2026, DOI:10.32604/jpa.2026.079616 - 31 August 2026

Abstract Generative Artificial Intelligence (GenAI) is reshaping language learning, yet research often overlooks how AI-related beliefs foster character strengths. This study investigated the relationship between the perceived usefulness of GenAI and academic engagement, and the mediating role of resilience. Study participants comprised multilingual Mongolian university students (N = 421, female = 57.7%, male = 42.3%; freshmen = 26.1%, sophomores = 21.1%, juniors = 29.9%, seniors = 22.8%; mean age = 20.49, SD = 1.11). Structural equation modeling and bootstrapping procedure results indicated that the perceived usefulness of GenAI was directly associated with higher academic engagement. Furthermore, More >

Kai Luo¹, Yifei Xie¹, Kun Chen¹, Haibing Chen^2,*, Wei Tang^1,*, Shaohua Bi³, Jirong Zhang³, Weifeng He³

Frontiers in Heat and Mass Transfer, Vol.24, No.4, 2026, DOI:10.32604/fhmt.2026.084890 - 31 August 2026

Abstract The internal structure of porous media is strongly correlated with flow and thermal transport characteristics, which further influences the overall heat transfer performance of the entire system. Based on explicit structural representation, a three-dimensional numerical method for coupled flow and heat transfer in multi-layered porous sheet arrays is established, utilizing momentum source terms for porous media and a local thermal equilibrium heat transfer model. The impacts from porosity, inlet velocity, and heating power on the flow and heat transfer characteristics within the segment are systematically investigated, with the porosity range determined based on microstructural observations,… More >