Huo Ye¹, Jiantong Li², Lingna Xu^3,*

Chalcogenide Letters, Vol.23, No.8, 2026, DOI:10.32604/cl.2026.087654 - 18 September 2026

Abstract SF₆ is the primary insulating and arc extinction medium in gas-insulated switchgear (GIS). Sulfur hexafluoride (SF₆) decomposes to create diagnostic markers, such as sulfur dioxide (SO₂), thionyl fluoride (SOF₂), and hydrogen sulfide (H₂S) when electrical problems occur, such as partial discharge and local overheating. Accurate quantification of these fault-marker gases is important for the early identification of insulation defects and the condition assessment of SF₆-insulated equipment. Molybdenum disulfide (MoS₂) is a well-known and atomically thin van der Waals semiconductor that has attracted considerable attention as a platform for gas-sensing applications. This is due to its large accessible surface area,… More >

Fen Liu^1,*, Jinghua Zhang², Weijie Tan³

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.086571 - 15 September 2026

Abstract Multi-modal information fusion integrates data from various sensors, distinct sources, or different modalities, such as audio, images, and text, to achieve a more comprehensive and accurate understanding and analysis. This paper proposes a Semi-Tensor Product-based Block Term Decomposition of Multilinear (STP-BTDM) pooling method and applies it to sentiment analysis and emotion recognition. Unlike prior factorized multilinear approaches, STP-BTDM introduces block-term decomposition with a block-diagonal core tensor, yielding a globally sparse yet locally dense structure and enabling modality-specific independent subspace learning. The technique first introduces the Semi-Tensor Product-based Block Term Decomposition (STP-BTD) model to obtain globally… More >

Haipeng Hu¹, Tao Hong², Junjie Zhu³, Xinjie Yao^4,*, Zhoupeng Guo^5,*, Dahai Xia^6,*

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.086475 - 15 September 2026

Abstract Cold-start alloy-design campaigns often have too few labeled compositions to reliably locate phase boundaries for tree-structured composition-space Gaussian process regression (TCGPR). We study a controlled way to incorporate external CALPHAD-like boundary information into this partitioning step. The proposed MP-TCGPR method adds a Gaussian MAP penalty centered on a thermodynamic boundary estimate and uses an adaptive width ${\sigma }_j(N)={\sigma }_0\sqrt{1+N/N_{\mathrm{c}\mathrm{r}\mathrm{o}\mathrm{s}\mathrm{s}}}$ to reduce prior influence as node-level data accumulate. The revised theory distinguishes asymptotic convergence from convergence rate: a fixed-width prior is also asymptotically negligible under local regularity, whereas the adaptive schedule accelerates finite-sample prior More >

Yalong Liang¹, Xiaohui Yuan¹, Yuning Han², Pei Li^3,*

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.086403 - 15 September 2026

Abstract NBT-based lead-free piezoceramics are promising alternatives to Pb-containing materials, yet their functional properties arise from complex and coupled composition–processing–structure–property relationships. Here, we develop a structure-informed machine learning framework to predict and interpret the piezoelectric coefficient d₃₃, depolarization temperature T_d, and relative dielectric permittivity ε_r. A database of 214 records from 34 publications was compiled, including 204 records for model development and 10 records for independent literature validation. The correlation analysis involved 38 variables, including 35 candidate input descriptors and three target properties. After Pearson correlation-based redundancy filtering, 30 nonredundant input descriptors were retained for model development. To… More >

Anxiang Shen¹, Xinxin Ren², Tao Wang¹, Jianqiu Zhou^1,2,*

Frontiers in Heat and Mass Transfer, Vol.24, No.4, 2026, DOI:10.32604/fhmt.2026.082573 - 31 August 2026

Abstract To address the growing number of variable-composition ejector refrigeration cycles, this study proposes analyzing the matching performance between working fluids and cycles through 3D (Temperature-Entropy-Mass fraction) Thermodynamic Diagrams. The ejector refrigeration cycle is decoupled into a driving module and a refrigeration module, and a theoretical upper-bound model (COP_limiting) that depends only on working-fluid properties is derived from the T-s diagram. Graph-theoretic analysis yields an explicit relation between COP_limiting and fluid-specific parameters such as Δs_b-b^′/Δs_a-b^′ and Δs_e-e^′/Δs_d-e^′. Definition of k₁ (ΔT_4–7/Δs_e-e^′) and k₂ (ΔT_3–4/Δs_b-b^′) reveals that wet fluids favour the refrigeration module, whereas dry fluids favour the driving module. The influence… More >

Xianyan Wang^1,#, Yan Guo^1,#, Nan Yang¹, Shengnan Ouyang¹, Honglang Duan¹, Jie Wang¹, Qiqiang Guo¹, Liehua Tie^1,2,3,*, Guijie Ding¹

Phyton-International Journal of Experimental Botany, Vol.95, No.8, 2026, DOI:10.32604/phyton.2026.084022 - 28 August 2026

Abstract Understory vegetation-mediated forest litter decomposition and nutrient release processes are critical for biogeochemical cycles and ecosystem sustainability. Drought-dominated global change significantly affects relevant processes, but its impact on metal element release from mixed litters of overstory trees and understory vegetation remains unclear. Here, we conducted an 18-month in situ decomposition experiment in a Pinus massoniana–Camellia oleifera mixed forest under three precipitation regimes: control (CK), low-intensity reduction (R30), and high-intensity reduction (R60). Both R30 and R60 treatments significantly inhibited P. massoniana litter mass loss by 4.85% and 6.22%, respectively. Only R60 treatment significantly reduced the mass loss in C. oleifera and… More >

Yongning Zhang¹, Dongxue Li^1,2,*, Cen Yang³, Yongwang Gui⁴

Structural Durability & Health Monitoring, Vol.20, No.5, 2026, DOI:10.32604/sdhm.2026.081767 - 24 August 2026

Abstract To address the challenge that the baseline state of FE models for operational highly statically indeterminate bridges is difficult to evaluate accurately, this paper proposes an intelligent multi-parameter inversion and updating framework driven by measured dynamic strains and a LSTM neural network. First, to tackle the complex environmental interferences coupled within short-term monitoring strain signals, a moving-window baseline detrending and refined thermal effect decoupling algorithm is employed. This successfully strips away long-term dead loads and temperature drift, extracting pure mechanical strain sequences with a high signal-to-noise ratio. Second, to overcome the mode omission issue caused… More >

David Hason Rudd^1,*, Cesar Sanin², Md Rafiqul Islam³, Xianzhi Wang¹, Huan Huo¹

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084015 - 13 August 2026

Abstract The accurate classification of human emotions from speech remains a formidable challenge due to the dynamic, non-stationary properties of audio signals and pervasive background noise. Traditional single-domain extraction methods frequently fail to capture overlapping acoustic phenomena, resulting in high misclassification rates among acoustically similar emotions. To overcome this, we propose the Dual-Decomposition Ensemble (DDE-SER), an architecture that synergizes 1D adaptive frequency filtering with 2D spatial spectrogram separation. The framework operates through two distinct pipelines: an adaptive time-domain branch that leverages VGG-optiVMD to autonomously extract Intrinsic Mode Functions (IMFs), and a structural spectrogram branch that applies… More >

Sugeng Rifqi Mubaroq^1,*, Rolly Maulana Awangga², Tegar Ditya Pragama¹, Sidiq Fathummubin³, Ali Yusuf Abdulhaq¹

Intelligent Automation & Soft Computing, Vol.41, pp. 27-46, 2026, DOI:10.32604/iasc.2026.088039 - 11 August 2026

Abstract Decoding cognitive workload from electroencephalography (EEG) underpins passive brain–computer interfaces and adaptive learning technology, yet practical decoders share two weaknesses: they rely on a single family of features, and their accuracy collapses on recordings from an unfamiliar device, montage, or task. We address both. We first build a multi-specialist stacking decoder that fuses complementary spectral, Riemannian, and spatial views through a meta-learner. Evaluated across two public corpora under the leave-one-subject-out MOABB benchmarking protocol, it outperforms the best single specialist on the binary workload contrasts, and the strongest of these effects survives family-wide false-discovery-rate correction. The… More >

Bilal Taher^*

Chalcogenide Letters, Vol.23, No.7, 2026, DOI:10.32604/cl.2026.085371 - 07 August 2026

Abstract Nanopowder copper sulphide CuS has been synthesised successfully via the chemical bath deposition method. Two samples of precipitated CuS nanopowder were prepared at molar concentration of 0.5 M from [CuSO₄·5H₂O and Na₂S₂O₃·5H₂O] and 0.05 M from [Na₂EDTA·2H₂O]. Both samples were annealed at 150°C for one hour in air. The effects of washing and nonwashing on the structural, morphological, and compositional properties were studied. The X-ray diffraction (XRD) patterns showed that both samples have a CuS hexagonal structure with lattice constants (a = 3.773 Å , c = 16.398 Å ), and (a =… More >