Optically Referenced Microwave Generator with Attosecond-Level Timing Noise by Lulu Yan, Jun Ruan, Pan Zhang, Bingjie Rao, Mingkun Li, Zhijing Du, Shougang Zhang

“…The microwave regeneration method employs an optical-to-microwave phase detector based on a fiber-based Sagnac loop to produce the error signal between a 9.6 GHz dielectric resonator oscillator (DRO) and the OFC. …”
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A study on predicting the risk of coronary artery disease in OSAHS patients based on a four-variable screening tool potential predictive model and its correlation with the severity... by Yanli Yao, Yu Li, Yulan Chen, Xuan Qiu, Gulimire Aimaiti, Ayiguzaili Maimaitimin

“…The Hosmer-Lemeshow test, calibration curve, and DCA results indicate that potential predictive model based on the 4 V possesses significant clinical applicability in predicting OSAHS in conjunction with CAD. …”
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Robust Higher-Order Nonsingular Terminal Sliding Mode Control of Unknown Nonlinear Dynamic Systems by Quanmin Zhu, Jianhua Zhang, Zhen Liu, Shuanghe Yu

“…Three simulated bench test examples, in which two of them have representatively numerical challenges and the other is a two-link rigid robotic manipulator with two input and two output (TITO) operational mode as a typical multi-degree interconnected nonlinear dynamics tool, are studied to demonstrate the effectiveness of the MFTSMC and employed to show the user-transparent procedure to facilitate the potential applications. The major MFTSMC performance includes (1) finite time (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>2.5</mn><mo>±</mo><mn>0.05</mn></mrow></semantics></math></inline-formula> s) dynamic stabilization to equilibria in dealing with total physical model uncertainty and disturbance, (2) effective dynamic tracking and small steady state error <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0</mn><mo>±</mo><mn>0.002</mn></mrow></semantics></math></inline-formula>, (3) robustness (zero sensitivity at state output against the unknown bounded internal uncertainty and external disturbance), (4) no singularity issue in the neighborhood of TSM <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>σ</mi><mo>=</mo><mn>0</mn></mrow></semantics></math></inline-formula>, (5) stable chattering with low amplitude (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>±</mo><mn>0.01</mn></mrow></semantics></math></inline-formula>) at frequency 50 mHz due to high gain used against disturbance <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>d</mi><mo stretchy="false">(</mo><mi>t</mi><mo stretchy="false">)</mo><mo>=</mo><mn>100</mn><mo>+</mo><mn>30</mn><mi>sin</mi><mo stretchy="false">(</mo><mn>2</mn><mi>π</mi><mi>t</mi><mo stretchy="false">)</mo></mrow></semantics></math></inline-formula>). …”
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Detecting Anomalies in Attributed Networks Through Sparse Canonical Correlation Analysis Combined With Random Masking and Padding by Wasim Khan, Mohammad Ishrat, Ahmad Neyaz Khan, Mohammad Arif, Anwar Ahamed Shaikh, Mousa Mohammed Khubrani, Shadab Alam, Mohammed Shuaib, Rajan John

“…The empirical evaluation across multiple benchmark datasets validates the potential of the proposed approach as a pivotal tool in advancing anomaly detection research and applications.…”
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Adversarial denoising of EEG signals: a comparative analysis of standard GAN and WGAN-GP approaches by Imad Eddine Tibermacine, Samuele Russo, Francesco Citeroni, Giuseppe Mancini, Abdelaziz Rabehi, Amal H. Alharbi, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy, Christian Napoli, Christian Napoli, Christian Napoli

“…The demonstrated improvements in signal quality underscore the promise of adversarially trained models for applications ranging from basic neuroscience research to real-time brain–computer interfaces (BCIs) in clinical or consumer-grade settings. …”
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Correction of TRMM 3B43 Monthly Precipitation Data Using Quantile Regression Model in the Urmia Lake Basin by Sima Kazempour Choursi, Mahdi Erfanian, Hirad Abghari, Mirhassan Miryaghoobzadeh, khadijeh Javan

“…Furthermore, the Mean Absolute Error (MAE) significantly decreased after quantile regression correction, demonstrating a closer alignment between TRMM data and observed rainfall. …”
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Nanoscale Organic Contaminant Detection at the Surface Using Nonlinear Bond Model by Hendradi Hardhienata, Muhammad Ahyad, Fasya Nabilah, Husin Alatas, Faridah Handayasari, Agus Kartono, Tony Sumaryada, Muhammad D. Birowosuto

“…This approach offers valuable applications in environmental monitoring, combining the sensitivity of SHG with the adsorption properties of GO for nanoscale detection.…”
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Development and Validation of a Brain Aging Biomarker in Middle-Aged and Older Adults: Deep Learning Approach by Zihan Li, Jun Li, Jiahui Li, Mengying Wang, Andi Xu, Yushu Huang, Qi Yu, Lingzhi Zhang, Yingjun Li, Zilin Li, Xifeng Wu, Jiajun Bu, Wenyuan Li

“…Model performance was evaluated using mean absolute error (MAE) against benchmark models, while generalization capability was further validated on an external UK Biobank dataset. …”
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Modeling the compressive strength behavior of concrete reinforced with basalt fiber by Kennedy C. Onyelowe, Ahmed M. Ebid, Shadi Hanandeh, Viroon Kamchoom, Paul Awoyera, Siva Avudaiappan

“…Abstract This research investigates the compressive strength behavior of basalt fiber-reinforced concrete (BFRC) using machine learning models to optimize predictions and enhance its practical applications. The study incorporates various modeling techniques, including Artificial Neural Networks (ANN), k-Nearest Neighbors (KNN), Support Vector Machines (SVM), Decision Trees, and Random Forest (RF), to evaluate their predictive capabilities. …”
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Evaluating Degenerative Lumbar Disease with Markerless 3D Motion Capture: Reliability and Validity in Sit-to-Stand Test by Yi-Ting Huang, Szu-Hua Chen, Chao-Ying Chen, Shiu-Min Wang, Pei-Yuan Wu, Dar-Ming Lai, Wei-Li Hsu

“…Markerless motion capture offers a portable alternative, yet its functional assessment applications in DLD remain underexplored. Thus, the aim of this study is to evaluate the reliability and validity of markerless motion capture for assessing functional tests in DLD patients. …”
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Research on Hybrid Architecture Neural Networks for Time Series Prediction by Fujin Zhuang, Xiao Chen, Punyaphol Horata, Khamron Sunat

“…Although MAE was slightly higher, the overall error control remained within an acceptable range, validating the model&#x2019;s stability and effectiveness. …”
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A 3&#x00D7;3 Antenna Beamforming Network Based on Waveguide Nolen Matrix for Ka-Bands by Hatem Oday Hanoosh, Mohamad Kamal A. Rahim, Noor Asniza Murad, Yaqdhan Mahmood Hussein

“…Therefore, this beamforming has a greater impact on the mm wave beamforming networks and applications.…”
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Nonlinear Dynamical Model and Analysis of Emotional Propagation Based on Caputo Derivative by Liang Hong, Lipu Zhang

“…This framework advances the mechanistic understanding of co-evolutionary dynamics in emotion-modulated social networks, supporting applications in clinical intervention design, collective sentiment modeling, and psychophysiological coupling research.…”
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On the hydrostatic approximation in rotating stratified flow by A. Wirth

“…</p> <p>Calculating the difference of the two projection-evolution operators, the expression of the error, scaling and prefactors done by the hydrostatic approximation is obtained. …”
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Inverse Dynamic Parameter Identification for Remote Sensing of Soil Moisture From SMAP Satellite Observations by Runze Zhang, Adam Watts, Mohamad Alipour

“…The results demonstrated that the incorporation of dynamic <italic>h</italic> and &#x03C9; parameters, derived on a daily scale, markedly enhanced the soil moisture retrieval performance with an average unbiased root-mean-square error (ubRMSE) of 0.01 (0.02) m³&#x002F;m³ and Pearson correlation (<italic>R</italic>) of 0.95 (0.90) for the SCA (RDCA) algorithms, indicating that dynamic parameterization holds significant promise for improving retrieval accuracy. …”
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Fitts’ law-based identification of motor development stages for the upper limb: proof of concept in three age groups by Cristina Sanchez, Eloy Urendes, Alejandra Aceves, María Martínez-Olagüe, Rafael Raya

“…From an Information Theory perspective, throughput (TP) reflects processing speed in reaching tasks, while error rate (ER) quantifies incorrect selections. …”
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Effect of grinding wheel type and cooling method on grinding quality of SiCf/SiC ceramic matrix composites by Ben WANG, Jiajie TANG, Hongdi CHU, Qi ZHANG

“…Therefore, in practical applications, the grinding wheels and cooling methods should be reasonably selected based on different processing requirements to improve the processing quality and the efficiency of SiCf/SiC composites. …”
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TanSat-2: a new satellite for mapping solar-induced chlorophyll fluorescence at both red and far-red bands with high spatiotemporal resolution by D. Zhao, D. Zhao, D. Zhao, S. Du, S. Du, C. Zou, C. Zou, C. Zou, L. Tian, M. Fan, M. Fan, Y. Du, Y. Du, Y. Du, L. Liu, L. Liu, L. Liu

“…However, accurate mapping of dual-band (red and far-red) SIF with daily temporal resolution and kilometer-level spatial resolution remains a critical gap, despite its significance for various applications. The Chinese next-generation greenhouse gas monitoring satellite, TanSat-2, is set to succeed the original TanSat satellite, aiming to record the fraction of greenhouse gases, pollutants, and SIF measurements from space. …”
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Evaluating snow depth retrievals from Sentinel-1 volume scattering over NASA SnowEx sites by Z. Hoppinen, Z. Hoppinen, R. T. Palomaki, G. Brencher, D. Dunmire, D. Dunmire, E. Gagliano, A. Marziliano, J. Tarricone, J. Tarricone, H.-P. Marshall

“…Our findings provide an open-source framework for future investigations, along with insight into the applicability of C-band SAR for snow depth retrievals and directions for future C-band snow depth retrieval algorithm development. …”
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Comprehensive Evaluation of Operation Safety of Earth-rock Dams Based on Weight Optimization-cloud Model by ZHANG Jianwei, WU Weitao, HOU Ge, HUANG Jinlin, WANG Bingpeng, LIU Hongze, HU Zixu

“…It combines with the cloud model to evaluate the operation state of earth and rock dams from both quantitative and qualitative perspectives, which more realistically and effectively reflects the safety condition of the dams and provides a reference for the safety evaluation of the dam.ConclusionsThe results indicated that this method is applicable to the comprehensive evaluation of the operational safety of earth and rock dams. …”
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