Amine Batbat^1,2, Khaoula Habbadi², Mohamed Jeddi³, Samiah Hamad Al-Mijalli⁴, Hanae Naceiri Mrabti⁵, Fahad M. Alshabrmi⁶, Naif Hesham Moursi⁷, Hassane Greche¹, Naoufal El Hachlafi^8,*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2026.072398 - 30 January 2026

Abstract Origanum elongatum (OE) is an aromatic, medicinal plant endemic to Morocco that is widely used in traditional medicine due to its biological properties. This study aimed to elucidate the chemical composition of the essential oil (EO) obtained from O. elongatum (OEEO) at three stages of its life cycle, including vegetative stage (OEEO-VS), flowering stage (OEEO-FS), and post-flowering (OEEO-PFS), as well as to evaluate its biological and antiradical characteristics. The chemical analysis of the essential oil was conducted using gas chromatography-mass spectrometry (GC-MS). The antibacterial activity was evaluated in vitro through distinct methodologies, namely, disc diffusion and microatmosphere assay;… More >

Xianrui Lyu, Xiaodan Ren^*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.074388 - 29 January 2026

Abstract Inverse design of advanced materials represents a pivotal challenge in materials science. Leveraging the latent space of Variational Autoencoders (VAEs) for material optimization has emerged as a significant advancement in the field of material inverse design. However, VAEs are inherently prone to generating blurred images, posing challenges for precise inverse design and microstructure manufacturing. While increasing the dimensionality of the VAE latent space can mitigate reconstruction blurriness to some extent, it simultaneously imposes a substantial burden on target optimization due to an excessively high search space. To address these limitations, this study adopts a Variational… More >

TOSHIYUKI HABU^*

BIOCELL, Vol.50, No.1, 2026, DOI:10.32604/biocell.2025.071798 - 23 January 2026

Abstract RING protein 213 (RNF213), the susceptibility gene for Moyamoya disease (MMD), possesses two active AAA+ ATPase (ATPases Associated with diverse cellular Activities) modules, a RING, and RNF213-ZNFX1 finger (RZ finger) domains. Several RNF213 variants have been reported in MMD patients, including the p.R4810K variant (rs112735431), which is a founder polymorphism associated with MMD in East Asia. To elucidate the function of RNF213 and its variant, we investigated the localization of RNF213 and the R4810K variant in this study. RNF213 induced circular hole structures near the nucleus, similar to lipid droplets (LDs), in U-2 OS cells. More >

Naeemah A. Aswad, Ayed N. Saleh^*

Chalcogenide Letters, Vol.22, No.12, pp. 1019-1029, 2025, DOI:10.15251/CL.2025.2212.1019 - 06 December 2025

Abstract The SCAPS-1D software was used to simulate a p–CuI/n–InSe photodetector at 300 K with AM1.5G light. The simulation results showed that, with a quantum efficiency of 97.6% at 800 nm and a responsivity of 0.67 A/W, the ideal absorber layer thickness of 0.8 µm produced the highest overall performance. The specific detectivity was enhanced to 2.5 × 10¹⁵ cm·Hz^1/2 ·W⁻³ and the dark current was decreased by increasing the InSe carrier concentration from 1 × 10¹⁵ cm⁻³ to 3 × 10¹⁵ cm⁻³ . These findings show that the CuI/InSe heterojunction’s broadband response, strong responsivity, and low dark current make More >

Yang Liu¹, Biao Chen¹, Xin Liu², Chenxi Luo², Shihui Xiao^2,*

Frontiers in Heat and Mass Transfer, Vol.23, No.6, pp. 2127-2146, 2025, DOI:10.32604/fhmt.2025.070973 - 31 December 2025

Abstract This study evaluated corn kernel drying performance and quality changes using hot air drying (HAD) and infrared drying (ID) across temperatures ranging from 55°C to 80°C. Optimal drying parameters were determined by using the entropy weight method, with drying time, specific energy consumption, damage rate, fatty acids, starch, polyphenols, and flavonoids as indicators. Results demonstrated that ID significantly outperformed HAD, achieving drying times up to 20% shorter and reducing specific energy consumption and kernel damage by up to 79.3% and 66.7%, respectively, while also better preserving quality attributes. Both methods exhibited drying profiles characterized by More >

Noor Moneer Basher¹, Omar Rafae Alomar^1,*, Omar Mohammed Ali², Diyar Abdullah Ahmed³

Frontiers in Heat and Mass Transfer, Vol.23, No.6, pp. 2001-2024, 2025, DOI:10.32604/fhmt.2025.066997 - 31 December 2025

Abstract The energy consumption of a Split air conditioning unit (ACU) inside a building is extremely large, and efforts to decrease this issue are ongoing. The current work aims to experimentally investigate the thermal performance of ACU using an external cooling-water loop for pre-cooling the condenser to improve the efficiency and to reduce energy consumption by reducing refrigerant temperature before entering the condenser, thereby reducing the coefficient of performance. The experiments are performed on ACU with and without using an external cooling-water loop under different climate conditions. By using the experimental data, the systems’ performances for… More >

Chunyong Yin, Williams Kyei^*

Journal of Cyber Security, Vol.7, pp. 615-635, 2025, DOI:10.32604/jcs.2025.072740 - 24 December 2025

Abstract The evolving sophistication of network threats demands anomaly detection methods that are both robust and adaptive. While autoencoders excel at learning normal traffic patterns, they struggle with complex feature interactions and require manual tuning for different environments. We introduce the Adaptive Robust AutoEncoder (ARAE), a novel framework that dynamically balances reconstruction fidelity with latent space regularization through learnable loss weighting. ARAE incorporates multi-head attention to model feature dependencies and fuses multiple anomaly indicators into an adaptive scoring mechanism. Extensive evaluation on four benchmark datasets demonstrates that ARAE significantly outperforms existing autoencoder variants and classical methods, More >

Siwei Zhang, Xiaozhou Xia^*, Xin Gu, Meilin Zong, Qing Zhang^*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3243-3278, 2025, DOI:10.32604/cmes.2025.073841 - 23 December 2025

Abstract This study presents a coupled thermo-hydro-mechanical-fatigue (THM-F) model, developed based on variational phase-field fatigue theory, to simulate the freeze-thaw (F-T) damage process in concrete. The fracture phase-field model incorporates the F-T fatigue mechanism driven by energy dissipation during the free energy growth stage. Using microscopic inclusion theory, we derive an evolution model of pore size distribution (PSD) for concrete under F-T cycles by treating pore water as columnar inclusions. Drawing upon pore ice crystal theory, calculation models that account for concrete PSD characteristics are established to determine ice saturation, permeability coefficient, and pore pressure. To… More >

Maysaa Al-Qurashi¹, Ayesha Siddiqa², Shazia Karim³, Yu-Ming Chu^4,5,*, Saima Rashid^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2057-2129, 2025, DOI:10.32604/cmes.2025.071629 - 26 November 2025

Abstract Chikungunya is a mosquito-borne viral infection caused by the chikungunya virus (CHIKV). It is characterized by acute onset of high fever, severe polyarthralgia, myalgia, headache, and maculopapular rash. The virus is rapidly spreading and may establish in new regions where competent mosquito vectors are present. This research analyzes the regulatory dynamics of a stochastic differential equation (SDE) model describing the transmission of the CHIKV, incorporating seasonal variations, immunization efforts, and environmental fluctuations modeled through Poisson random measure noise under demographic heterogeneity. The model guarantees the existence of a global positive solution and demonstrates periodic dynamics… More >

Binu Sudhakaran Pillai¹, Raghavendra Kulkarni², Venkata Satya Suresh kumar Kondeti², Surendran Rajendran^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 1141-1166, 2025, DOI:10.32604/cmes.2025.070348 - 30 October 2025

Abstract Future 6G communications will open up opportunities for innovative applications, including Cyber-Physical Systems, edge computing, supporting Industry 5.0, and digital agriculture. While automation is creating efficiencies, it can also create new cyber threats, such as vulnerabilities in trust and malicious node injection. Denial-of-Service (DoS) attacks can stop many forms of operations by overwhelming networks and systems with data noise. Current anomaly detection methods require extensive software changes and only detect static threats. Data collection is important for being accurate, but it is often a slow, tedious, and sometimes inefficient process. This paper proposes a new… More >