Lijun Yang¹, Qiuwei Yang^2,*

CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.083976 - 23 July 2026

Abstract This study proposes a Multi-Stage Sparrow Search Algorithm (MS-SSA) for precise structural damage identification. Initially, the structural static displacement sensitivity formulation is derived via the Sherman-Morrison-Woodbury formula, and an objective function is constructed by integrating the sensitivity equations with the L2-norm penalty. Subsequently, MS-SSA is implemented to sequentially achieve preliminary damage localization and accurate quantification. In the localization phase, a constrained narrow-bound search space is predefined to identify potential damage regions. Leveraging this feedback, the sensitivity equations are condensed, and the search boundaries are adaptively refined for the quantification phase, where SSA is reapplied to… More >

Byeongjeong Kim, Jeonghyun Park, Joonho Yang, Hwanhee Lee^*

CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.082460 - 23 July 2026

Abstract Long-context question answering over narrative documents remains challenging because many questions require reconstructing event sequences while preserving local contextual flow under limited context budgets. Existing retrieval-augmented generation (RAG) methods typically retrieve document snippets independently, which can fragment narratives and harm temporal dependencies. We propose ChronoRAG, a retrieval framework for narrative question answering that first converts sequential document chunks into concise relation descriptions and then retrieves relevant units together with their adjacent chronological context. This design preserves retrieval precision while providing the generator with coherent local narrative structure. Experiments on NarrativeQA and GutenQA show that ChronoRAG More >

Qiya Wang^1,2, Jia Liu^1,2,*, Yuwei Lu^1,2, Yujie Liu^1,2, Peng Luo^1,2

CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.081589 - 23 July 2026

Abstract Implicit Neural Representation (INR) is a technique that models continuous signals using neural networks, replacing traditional discrete grid representations with a coordinate-to-value mapping function. As a data carrier, INR is gradually being adopted as the target for steganographic processing. However, existing INR-based steganographic schemes typically require modifying network structures (e.g., weights, nodes) and retraining to obtain stego INRs, leading to high time consumption and the need for re-training when replacing cover images. To address this issue, this paper proposes StegaMIR (Steganography via Modulated Implicit Representations), an image steganographic scheme based on modulated implicit representations. It… More >

Shasha Tian^1,2, Zhengyang Chen^1,3, Kai Ren^1,2, Na Li^1,2, Chongwei Ruan⁴, Zhijia Cui^1,3, Mian Wu^4,*

CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.081556 - 23 July 2026

Abstract To address the issues of low exploration efficiency and “geometric myopia” caused by the lack of high-level environmental structure modeling for mobile robots in complex indoor environments, this paper proposes an active SLAM object navigation method based on Situational Semantic Augmented Graph (SSAG). Unlike methods that learn policies solely on pixel-level semantic maps or exploit only object-level relations for implicit association, this work elevates local observations online into a room-level topological graph and performs explicit semantic reasoning over unobserved regions. First, an online room segmentation algorithm is employed to transform unstructured sensory data into a… More >

Xiaolan Li^1,2,*, Jinyu Shen^1,2, Jinhuang Liang^1,2, Yanting Wang^1,2

Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.076521 - 18 June 2026

Abstract The intrinsic volatility and stochasticity of large-scale wind power generation pose significant challenges to grid stability. To address the limitations of conventional models in capturing strong non-stationarity, this study proposes a novel Multi-Stage Adaptive Forecasting Network (MSAF-Net). The framework features a hierarchical signal refinement strategy coupled with an intelligently optimized hybrid predictor. Initially, input redundancy is minimized via Pearson Correlation Coefficient (PCC) analysis to isolate significant meteorological variables. A two-phase decomposition-reconstruction mechanism is then implemented: the wind power series is first decomposed using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN). To optimize the… More >

Xiaoshan Wang¹, Qiang Cui¹, Lei Pu^2,*

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.5, 2026, DOI:10.32604/fdmp.2026.081184 - 27 May 2026

Abstract The passability (transport behavior) of while-drilling lost circulation materials (LCMs) through directional tools is strongly influenced by material composition and particle characteristics. In this study, a coupled computational fluid dynamics–discrete element method (CFD–DEM) model is developed to systematically evaluate the effects of particle size distribution, concentration, morphology, and fiber inclusion on LCM transport behavior. Visualization experiments conducted using a transparent screen section demonstrate good agreement with the simulated pressure-drop evolution, supporting the validity of the model. The results reveal that increasing particle size from 1.2–1.6 mm to above 2.8 mm shifts the system from a More > Graphic Abstract

Xinyu Yue¹, Zhenhua Li^1,2,*, Zhenxing Li¹, Tao Zhang¹, Yanchun Xu¹, Xiaozhen Zhao³

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2026.077395 - 27 May 2026

Abstract Winding deformation is a predominant cause of transformer failures and critically compromises the safe, reliable, and economic operation of power systems. To overcome the inadequacy of the conventional three-dimensional (3D) Lissajous curve method in discriminating among various types of winding faults, this paper proposes an online monitoring method for transformer winding deformation based on 3D Lissajous curves. In the proposed method, the primary current di1(t)/dt, the derivative of the primary current di1(t)/dt, and the voltage difference between the primary and secondary sides Δu(t) are adopted as the coordinate axes to construct 3D Lissajous… More >

Huan Song^1,2, Yuan Zhao³, Chenglin He^2,4,*

Journal of Psychology in Africa, Vol.36, No.2, pp. 249-255, 2026, DOI:10.32604/jpa.2026.069347 - 29 April 2026

Abstract This study aimed to explore the mediating roles of body dissatisfaction and self-esteem on the relationship between body mass index (BMI) and among female college students. Using a cross-sectional study design, 669 Chinese female college students completed the Body Mass Index, the Body Image States Scale, the Self-Esteem Scale, and the Social Avoidance and Distress Scale. The results showed that body dissatisfaction partially mediated the relationship between BMI and social avoidance. Additionally, body dissatisfaction and self-esteem together formed a serial mediation pathway between BMI and social avoidance. In other words, BMI shows a direct association More >

Munro Matthew James^1,*, López Vásquez Clara Elena^1,2, Wickremesekera Agadha³, Chan Alex Ho Chuen¹, Gray Clint Lee^1,4,5,*

Oncology Research, Vol.34, No.5, 2026, DOI:10.32604/or.2026.074958 - 22 April 2026

Abstract Objective: Meningioma is the most common primary brain tumour. Invasion into the brain is a diagnostic feature of grade II meningiomas and is associated with recurrence and poor prognosis. Mebendazole is a microtubule inhibitor typically prescribed as an anthelmintic. However, it has the potential to be repurposed for cancer treatment. Here, we aimed to assess the ability of mebendazole to inhibit meningioma cell invasion. Methods: Primary patient-derived meningioma cell lines were cultured as 3D spheroids and embedded in an extracellular matrix-like matrix as an in vitro model of invasion. Mebendazole-treated and untreated control spheroids were analysed… More >

İbrahim Üntan^1,*, Nuh Aldemir²

Canadian Journal of Urology, Vol.33, No.2, pp. 239-248, 2026, DOI:10.32604/cju.2026.076805 - 20 April 2026

Abstract Background: Ureteral stones are a common cause of acute renal colic, and while most small stones pass spontaneously, reliable predictors of passage are needed to optimize patient selection for conservative management. This study aims to evaluate the role of radiologic, clinical and laboratory parameters—particularly the proximal/distal (P/D) ureteral diameter ratio—in predicting spontaneous passage of <10 mm ureteral stones. Materials and Methods: This retrospective cohort study included 277 patients diagnosed with ureteral calculi <10 mm on non-contrast computed tomography between September 2022 and September 2025. Pregnant patients, solitary kidney cases, congenital anomalies, active urinary infection, and incomplete… More > Graphic Abstract