Perception and Reality of Robotic Microsurgery: A Cross-sectional Comparative User and Nonuser Survey Study by Maximilian Mayrhofer-Schmid, MD, Martin Aman, MD, PhD, Floris V. Raasveld, MD, Wen-Chih Liu, MD, Felix Struebing, MD, Ulrich Kneser, MD, Kyle R. Eberlin, MD, Leila Harhaus, MD, Arne Hendrik Boecker, MD

“…Results showed that users appreciated tremor reduction and improved anastomotic quality as advantages, which were significantly underestimated by nonusers. …”
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Based on the N2N-SAMP for sparse underwater acoustic channel estimation by Zhen Wang, Zhen Wang, Maofa Wang, Yangzhen Wang, Yangzhen Wang, Zhenjing Zhu, Zhenjing Zhu, Guangtao Shang, Guangtao Shang, Jiabao Zhao, Jiabao Zhao, Ning Hu, Ning Hu

“…Notably, in low SNR environments, the N2N-SAMP algorithm significantly outperforms the traditional SAMP algorithm in terms of Mean Squared Error (MSE) and Bit Error Rate (BER). Specifically, at SNR levels of 0 dB, 10 dB, and 20 dB, the MSE of channel estimation is reduced by 58.95%, 76.08%, and 19.42%, respectively, compared to the SAMP algorithm that selects the optimal threshold based on noise power. …”
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An Improved Tropospheric Tomographic Model Based on Artificial Neural Network by Minghao Zhang, Kefei Zhang, Suqin Wu, Longjiang Li, Dantong Zhu, Moufeng Wan, Peng Sun, Jiaqi Shi, Shangyi Liu, Andong Hu

“…Statistical results show that the root mean square error (RMSE) of slant water vapor reconstructed from the improved model is reduced to 1.35 from 2.85 mm of the traditional model. …”
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FEN-MRMGCN: A Frontend-Enhanced Network Based on Multi-Relational Modeling GCN for Bus Arrival Time Prediction by Ting Qiu, Chan-Tong Lam, Bowie Liu, Benjamin K. Ng, Xiaochen Yuan, Sio Kei Im

“…Experimental results demonstrate that our frontend-enhanced network achieves a reduction in the Mean Absolute Percentage Error (MAPE) by 15.36%, 13.44%, and 19.07% compared to traditional time series forecasting models like CNN, LSTM, and Transformer, respectively. …”
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Emerging role of generative AI in renewable energy forecasting and system optimization by Erdiwansyah, Rizalman Mamat, Syafrizal, Mohd Fairusham Ghazali, Firdaus Basrawi, S.M. Rosdi

“…Results indicate that GAN-based models reduce root mean square error (RMSE) by 15–20 % in solar irradiance forecasting and significantly enhance spatial-temporal wind simulations. …”
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Harnessing solar drying for starter cultures: A novel approach to backslopping fermentation by Marcel Houngbédji, Donan Bangbadé, D. Sylvain Dabadé, Schadrac D. Agossevi, B. Pélagie Agbobatinkpo, S. Wilfrid Padonou, Joseph Dossou, Paulin Azokpota, D. Joseph Hounhouigan

“…The drying kinetic patterns showed consistent fit with Midili-Kucuk model with high reliable predictivity (R2 = 0.998) and least bias (Root Mean Square Error = 0.016), demonstrating the suitability of solar drying for small-scale production of starter culture. …”
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Harnessing Lactiplantibacillus plantarum EP21 and its membrane vesicles to inhibit myopia development by Chi-Fong Lin, Yu-An Hsu, Yung-Lan Chou, Ying-Chi Chen, En-Shyh Lin, Peng-Tai Tien, Jamie jiin-Yi Chen, Ming-Yen Wu, Chia-Hung Lin, Hui-Ju Lin, Lei Wan

“…The MVs exhibited anti-myopic properties, indicated by a reduction in axial length elongation and a corresponding upregulation of refractive error. …”
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Drug-Resistant Tuberculosis Hotspots in Oliver Reginald Tambo District Municipality, Eastern Cape, South Africa by Lindiwe Modest Faye, Mojisola Clara Hosu, Teke Apalata

“…The Linear Regression model predicts a continued decline to zero cases by 2026, with an R² = 0.865, a mean squared error (MSE) of 507.175, and a mean absolute error (MAE) of 18.65. …”
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Vector Decimation Harmonic Mean-Based Algorithm for Online Acoustic Feedback Active Noise Control by Suman Turpati, Ajay Roy, Tathababu Addepalli, Mohammed Alkahtani, Abdullatif Hakami, Ahmad Faiz Minai, Abdallah Hammad

“…The proposed method has superior noise reduction effectiveness compared to other algorithms, which indiscriminately attenuate the control filter across all frequencies. …”
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Revolutionizing Clear-Sky Humidity Profile Retrieval with Multi-Angle-Aware Networks for Ground-Based Microwave Radiometers by Yinshan Yang, Zhanqing Li, Jianping Guo, Yuying Wang, Hao Wu, Yi Shang, Ye Wang, Langfeng Zhu, Xing Yan

“…Based on the 7-year (2018–2024) in situ measurements from Beijing, Nanjing, and Shanghai, validation results reveal that AngleNet achieves substantial improvements, with an average R2 of 0.71 and a root mean square error (RMSE) of 10.39%, surpassing conventional models such as LGBM (light gradient boosting machine) and RF (random forest) by over 10% in both metrics, and demonstrating a remarkable 41% increase in R2 and a 10% reduction in RMSE compared to the previous BRNN method (batch normalization and robust neural network). …”
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Deep Learning for Opportunistic Rain Estimation via Satellite Microwave Links by Giovanni Scognamiglio, Andrea Rucci, Attilio Vaccaro, Elisa Adirosi, Fabiola Sapienza, Filippo Giannetti, Giacomo Bacci, Sabina Angeloni, Luca Baldini, Giacomo Roversi, Alberto Ortolani, Andrea Antonini, Samantha Melani

“…Compared to the state-of-the-art power-law-based models applied to similar datasets reported in the literature, our ML models achieve a <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>46</mn><mo>%</mo></mrow></semantics></math></inline-formula> reduction in the root mean squared error (RMSE) for event-based cumulative precipitation predictions.…”
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Research on non-destructive testing method for radial defect of anchor bolt based on longitudinal guided wave by Deying TANG, Weimin TANG, Zhiyi ZENG, Qing TIAN, Ailing LI, Yaling GUO, Erdi A’BI, Tongyu WU, Yibo WU

“…The radial defects of anchor bolt caused by long-term corrosion lead to the reduction of its bearing capacity, which led to a large number of engineering accidents. …”
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Modeling drug retention as memory effects in obese patients using fractional and augmented models by Amani R. Ynineb, Erhan Yumuk, Dana Copot, Bora Ayvaz, Bouchra Khoumeri, Ghada Ben Othman, Marcian D. Mihai, Isabela R. Birs, Cristina I. Muresan, Clara M. Ionescu

“…During the awakening phase, both the augmented and fractional-order models reduce BIS prediction error compared to the classical model. The augmented model lowers RMSE by 22.5% (from 10.38 to 8.04), while the fractional model achieves a 21.4% reduction (to 8.16) (based on one obese patient case). …”
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Dynamic Shock-Transmission Mechanism Between U.S. Trade Policy Uncertainty and Sharia-Compliant Stock Market Volatility of GCC Economies by Mosab I. Tabash, Suzan Sameer Issa, Marwan Mansour, Mohammed W. A. Saleh, Maha Rahrouh, Kholoud AlQeisi, Mujeeb Saif Mohsen Al-Absy

“…Conversely, Qatar and Kuwait show the least transmission of error variance from TPU during higher-volatility conditions (<i>τ</i> = 0.95). …”
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High-precision large-aperture single-frame interferometric surface profile measurement method based on deep learning by Liang Tang, Mingzhi Han, Shuai Yang, Ye Sun, Lirong Qiu, Weiqian Zhao

“…In particular, a significant reduction in the measurement time (reduced by a factor of 48) is achieved compared with that of the traditional phase-shifting method. …”
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Individualized Estimation of Baseline Retinal Nerve Fiber Layer Thickness Using Conditional Variational Autoencoder by Ou Tan, PhD, Keke Liu, MD, Aiyin Chen, MD, Dongseok Choi, PhD, Jonathan C.H. Chan, MD, Bonnie N.K. Choy, MD, Kendrick C. Shih, MD, Jasper K.W. Wong, MD, Alex L.K. Ng, MD, Janice J.C. Cheung, MD, Michael Y. Ni, MD, Jimmy S.M. Lai, MD, Gabriel M. Leung, MD, Ian Y.H. Wong, MD, David Huang, MD, PhD

“…The reductions in prediction errors for NFLT profile and overall NFLT value were independently validated using the CEI data. …”
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A comprehensive IoT cloud-based wind station ready for real-time measurements and artificial intelligence integration by Décio Alves, Fábio Mendonça, Sheikh Shanawaz Mostafa, Fernando Morgado-Dias

“…Calibration procedures reduced the maximum mean error of the ultrasonic wind sensors from 0.7 m/s to 0.2 m/s, achieving a 71% improvement in measurement accuracy. …”
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Patient-specific fluid–structure simulations of anomalous aortic origin of right coronary arteriesCentral MessagePerspective by Michael X. Jiang, MD, MEng, Muhammad O. Khan, PhD, Joanna Ghobrial, MD, Ian S. Rogers, MD, Gosta B. Pettersson, MD, PhD, Eugene H. Blackstone, MD, Alison L. Marsden, PhD

“…Conclusions: Patient-specific FSI modeling of AAORCA is a promising, noninvasive method to assess the iFR reduction caused by intramural geometries and inform surgical intervention. …”
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Comparative evaluation of accuracy, precision, and radiation dose between mindways and low-dose iCare QCT for lumbar spine BMD using the European spine phantom by Yujie Li, Yujie Li, Tiantian Yin, Tiantian Yin, Qiushi Yang, Heli Han, Zeguo Wang, Wanjiang Yu

“…Accuracy was evaluated using relative measurement error (RME), and precision was assessed via relative standard deviation (RSD). …”
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Mechanical Anastomotic Coupling Device versus Hand-sewn Venous Anastomosis in Head and Neck Reconstruction—An Analysis of 1694 Venous Anastomoses by Rajan Arora, Kripa Shanker Mishra, Hemant T. Bhoye, Ajay Kumar Dewan, Ravi K. Singh, Ravikiran Naalla

“…The venous anastomosis is a critical step in free-tissue transfer. The margin of error is less and the outcome depends on the surgeon’s skill and technique. …”
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