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  • Open Access

    ARTICLE

    Interpretable Machine Learning for Compressive and Flexural Strength Prediction of Fly Ash Blended 3D Printed Concrete with Uncertainty Quantification

    Jia Chen1, Zhicheng Liao1, Mengdi Hou2, Jianbo Huang1,3,*

    CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.086222 - 13 August 2026

    Abstract Fly ash (FA) blended 3D printed concrete (3DPC) offers improved sustainability but requires strength prediction models validated at the mix-composition level rather than within familiar formulations. This study applies leave-one-mix-out (LOMO) cross-validation to benchmark eight machine learning algorithms on 126 experimental records spanning seven FA-blended 3DPC compositions (FA 0–15 wt.%, W/B 0.30–0.35, age 1–28 days). ExtraTrees and ElasticNet achieve the highest composition-level generalisation for compressive strength (CS, R2=0.786±0.253) and flexural strength (FS, R2=0.915±0.061, RMSE =0.301 MPa), respectively. SHAP analysis identifies FA replacement percentage as the dominant CS predictor (mean |SHAP|=3.92 MPa, negative… More >

  • Open Access

    ARTICLE

    BroadAttNet: Attention-Driven Micro-Expression Recognition

    Hafiz Khizer bin Talib1, Yanlong Cao2, Muhammad Zaman3,*, Sharifah Sakinah Syed Ahmad4, Nikola Ivkovic5, Mario Konecki5, Adnan Akhunzada6

    CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.078779 - 13 August 2026

    Abstract Micro-expression recognition (MER) is a demanding problem in affective computing because micro-expressions are brief, low-amplitude, involuntary facial movements that often reveal concealed affective states. Their recognition is complicated by weak muscle activation, short temporal duration, inter-subject variability, class imbalance, illumination changes, and the limited scale of publicly available MER datasets. To address these constraints, this paper introduces BroadAttNet, an attention-driven convolutional framework that embeds a Broadbent-inspired selective attention layer into a compact CNN backbone. The proposed layer learns to assign higher importance to discriminative facial regions while suppressing spatially redundant or noisy responses, thereby improving… More >

  • Open Access

    REVIEW

    Targeting the Neuro-Immune Axis in Next-Generation Oncology: Discovery and Validation of β2-Adrenergic Blockade to Reverse Ecosystem-Wide Resistance

    Heng Xu1,#, Jiaan Lu1,#, Zizhang Wang1,#, Jiayu Xu2, Shihui Peng3, Haiqing Chen4, Qiang Cao5,*, Qing Sun6,*, Shangke Huang7,*

    Oncology Research, Vol.34, No.9, 2026, DOI:10.32604/or.2026.083919 - 13 August 2026

    Abstract Despite the potential of current cancer immunotherapies, tumor cells frequently evade immune surveillance by forming an immunosuppressive microenvironment, leading to treatment resistance. Current inquiry positions the sympathetic nervous system (SNS) at the forefront of tumor immunology as a critical driver of this immune evasion. This review delineates the cellular pharmacology of SNS-mediated immune regulation across the tumor ecosystem. Operating predominantly through the cyclic adenosine monophosphate-protein kinase A (cAMP-PKA) signaling axis, the SNS engages in bidirectional regulation with immune cells of the tumor microenvironment (TME). Norepinephrine and epinephrine interact with β2-adrenergic receptors (β2-ARs), triggering G-protein dissociation, adenylyl… More >

  • Open Access

    ARTICLE

    Context-Aware Identity Validation for UAV-Assisted Urban Mobility and Traffic Monitoring Environments

    Kuldashbay Avazov1, Kudratjon Zohirov2, Alpamis Kutlimuratov3, Charos Khidirova4, Jasur Sevinov5,6, Urishev Omadjon7, Adilbek Dauletov8, Akmalbek Abdusalomov4,5,9, Young Im Cho1,*

    CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.083828 - 23 July 2026

    Abstract Unmanned aerial vehicles (UAVs) are becoming a common solution to urban mobility, and traffic monitoring as well, owing to their ability to be deployed flexibly, ability to see a broader area and real-time sensing. However, the reliability of UAV-assisted traffic systems can be compromised through identity spoofing, Sybil attacks, false data injection, and trajectory manipulation. Current authentication techniques primarily verify cryptographic identities but often cannot detect when a claimed identity is inconsistent with physical movement patterns and settings. To overcome this drawback, this paper presents a context-aware identity validation system, CIV-UAV, for UAV-based urban traffic… More >

  • Open Access

    ARTICLE

    Numerical Modeling and Static Contact Analysis for a Bioinspired Rigid-Soft Fingertip

    Jiafeng Liu1,2, Junhao He1, Binbin Deng1, Jie Sun1, Chenyu Shi1,3, Shunhang Liang1, Zicong Zhou1,4, Guangsheng Feng1, Jie Zhang1,*

    CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.083128 - 23 July 2026

    Abstract The ability to achieve sufficient grasping force while maintaining conformal contact with objects is highly attractive for bio-inspired flexible robotic hands and grippers. In this paper, a flexible robotic hand design is developed inspired by the human hand, where the fingers have an embedded rigid phalanx wrapped in soft silicone rubber materials. A rigid-soft numerical model is developed to investigate the static contact behavior of a fingertip with a rigid flat using finite element (FE) analysis. The Ogden constitutive model is adopted to characterize the hyper-elastic behavior of the silicone rubber material and its parameters… More >

  • Open Access

    ARTICLE

    Optimize Sentiment Analysis: Through Machine Learning & Natural Language Processing Techniques

    Naimul Hasan Shadesh*, Zannatul Ferdous, Bipasha Iasmin

    Journal on Artificial Intelligence, Vol.8, pp. 335-357, 2026, DOI:10.32604/jai.2026.078589 - 22 July 2026

    Abstract Sentiment analysis is a core task in Natural Language Processing (NLP) that aims to identify opinions and sentiment polarity expressed in textual data. This study presents a systematic empirical evaluation of classical machine learning–based sentiment analysis methods using a unified experimental framework. Several supervised classifiers, including Decision Trees, Logistic Regression, Support Vector Machines (SVM), Random Forests, Naïve Bayes, and K-Nearest Neighbors (KNN), are evaluated on labeled text datasets collected from multiple domains such as product reviews, customer feedback, hotel reviews, and social media content. The experimental pipeline includes standard NLP preprocessing steps—text normalization, tokenization, stopword More >

  • Open Access

    ARTICLE

    Frequency-Selective Transmission Control of Ultrasonic Guided Waves in T-Shaped Pipes Using Acoustic Metamaterials: Computer Modeling and Experimental Validation

    Weiguo Chen1, Xiaobin Hong1,*, Kai Chen1, Yunyun Deng1, Bin Zhang1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.082376 - 30 June 2026

    Abstract Structural health monitoring (SHM) of ship piping systems is a core component of predictive maintenance strategies for complex marine engineering systems. During the detection of ship T-shaped pipes using ultrasonic guided waves, signal overlap arises from the diffusion of guided wave branches. To address this issue, an intelligent wave-guidance mechanism based on acoustic metamaterials is proposed for dynamic propagation control of ultrasonic guided waves. First, a metamaterial unit composed of a stainless steel substrate and a copper column is designed. The control of bandgap characteristics by lattice constant, column diameter, and column height is systematically… More > Graphic Abstract

    Frequency-Selective Transmission Control of Ultrasonic Guided Waves in T-Shaped Pipes Using Acoustic Metamaterials: Computer Modeling and Experimental Validation

  • Open Access

    ARTICLE

    Expression Analysis and Functional Validation of Lily LoWRKY22

    Ling He, Shun Tao, Qian Wang, Yu-Pei Yin, Xin-Yu He, Shuo Shi, Chun-Yan Wang*

    Phyton-International Journal of Experimental Botany, Vol.95, No.6, 2026, DOI:10.32604/phyton.2026.081349 - 29 June 2026

    Abstract As essential regulatory proteins, WRKY transcription factors participate in the regulation of plant growth, development and stress resistance; however, the functions of LoWRKY22 in the ‘Siberia’ cultivar of Lilium remain uncharacterized. In this study, LoWRKY22 was cloned and subjected to comprehensive functional analyses. Phylogenetic analysis revealed that LoWRKY22 belongs to the WRKY-IIe type subgroup, featuring a conserved WRKY domain and a C2H2-type zinc finger motif, indicating evolutionary conservation with WRKY homologs from Arabidopsis thaliana. Subcellular localization and transactivation assays confirmed its nuclear localization and transcriptional activation activity, supporting its role as a transcriptional regulator. Structural characterization of the LoWRKY22More >

  • Open Access

    ARTICLE

    External validation of the heidenreich criteria for patients with post-chemotherapy residual masses of non-seminomatous germ cell tumor

    Francesco Claps1,2,*, Miguel Ramírez-Backhaus1, Álvaro Gómez-Ferrer1, Juan Manuel Mascarós1, Argimiro Collado Serra1, Augusto Wong1, Ana Calatrava Fons3, Miguel Ángel Climent4, Antonio Amodeo2, Angelo Porreca5, Jose Rubio-Briones1,6

    Canadian Journal of Urology, Vol.33, No.3, pp. 593-602, 2026, DOI:10.32604/cju.2025.070162 - 29 June 2026

    Abstract Objectives: Residual Disease after adjuvant chemotherapy for non-seminomatous germ cell tumor (NSGCT) poses a significant clinical challenge and difficulties in tailored management. This study aimed to externally validate the Heidenreich criteria among patients eligible for unilateral post-chemotherapy retroperitoneal lymph node dissection (PC-RPLND) for residual masses of NSGCT. Methods: For validation, these criteria were retrospectively applied in 23 patients undergoing PC-RPLND for residual masses of NSGCTs. In patients qualified for unilateral-modified PC-RPLND according to the Heidenreich criteria but treated with fully bilateral dissection, pathological reports were evaluated to identify teratoma or active cancer cells inside the… More >

  • Open Access

    ARTICLE

    Prognosis and Immunotherapy Effect of Triple-Negative Breast Cancer by Lactylation-Related Genes and Experimental Validation

    Yang Wang1,2, Ying Xie1, Yiyi Ye1, Youyang Shi1, Feifei Li1, Mengdie Zhu1, Ciyi Hua1, Yuan Xu1, Rui Yang1,3,*, Sheng Liu1,4,*

    Oncology Research, Vol.34, No.7, 2026, DOI:10.32604/or.2026.078051 - 16 June 2026

    Abstract Background Triple-negative breast cancer (TNBC) is an aggressive subtype of breast malignancy characterized by poor clinical outcomes and limited therapeutic options. The identification of reliable biomarkers for predicting prognosis and immunotherapeutic response remains an urgent clinical need. This study aimed to develop an integrative lactylation-related gene signature to simultaneously evaluate prognostic trajectories and immunotherapeutic sensitivity in TNBC. Methods Transcriptomic and clinical data from public TNBC cohorts were systematically analyzed. Lactylation-related gene signatures were used to stratify patients via consensus clustering. A scoring model was constructed based on differentially expressed genes between clusters, and its associations with… More >

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