Enhancing bending strength in continuous drive friction welding of PEEK polymer cylinders through the innovative progressively increased welding area method by Chil-Chyuan Kuo, Hua-Xhin Liang, Song-Hua Huang, Armaan Farooqui, Shih-Feng Tseng

“…In general, the Taguchi method was used to optimize the process parameters of CDFW of dissimilar PEEK round rods to reduce random efforts by the trial-and-error method. It was found that the proposed PIWA method can definitely enhance the bending strength of rotational friction welded samples due to reduction of voids inside the weld interface. …”
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Modeling pine forest growing stock volume in subtropical regions of China using airborne Lidar data by Zige Lan, Xiandie Jiang, Guiying Li, Yagang Lu, Hongwen Yao, Dengsheng Lu

“…When combining PPF and MXF together to develop GSV models, HBA(Site/Type) with double stratification factors (i.e. typical site and forest type) showed similar performance, with only a minor reduction in RMSE by 0.45 m3/ha for PPF and 0.15 m3/ha for MXF. …”
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Multi-Index Assessment and Machine Learning Integration for Drought Monitoring Using Google Earth Engine by Xulong Duan, Rana Waqar Aslam, Syed Ali Asad Naqvi, Dmitry E. Kucher, Zohaib Afzal, Danish Raza, Rana Muhammad Zulqarnain, Yahia Said

“…The framework’s AI-driven error correction and multisensor synergy provide a scalable model for drought applications, such as ecosystem resilience monitoring (integrating thermal and optical analysis) and hydrological modelling (fusing soil moisture, precipitation, and vegetation datasets). …”
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Physics-Informed Neural Networks: A Review of Methodological Evolution, Theoretical Foundations, and Interdisciplinary Frontiers Toward Next-Generation Scientific Computing by Zhiyuan Ren, Shijie Zhou, Dong Liu, Qihe Liu

“…Third, pioneering cross-domain knowledge transfer through application-specific architectures: TFE-PINN for turbulent flows (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>5.12</mn><mo>±</mo><mn>0.87</mn><mo>%</mo></mrow></semantics></math></inline-formula> error in NASA hypersonic tests), ReconPINN for medical imaging (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>▵</mo><mi>SSIM</mi><mo>=</mo><mo>+</mo><mn>0.18</mn><mo>±</mo><mn>0.04</mn></mrow></semantics></math></inline-formula> on multi-institutional MRI), and SeisPINN for seismic systems (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0.52</mn><mo>±</mo><mn>0.18</mn></mrow></semantics></math></inline-formula> km localization accuracy). …”
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Integrating AI predictive analytics with naturopathic and yoga-based interventions in a data-driven preventive model to improve maternal mental health and pregnancy outcomes by Neha Irfan, Sherin Zafar, Kashish Ara Shakil, Mudasir Ahmad Wani, S. N. Kumar, A. Jaiganesh, K. M. Abubeker

“…In regression tasks, the Random Forest Regressor achieved near-perfect predictions with a Mean Squared Error (MSE) of 4.5767 × 10−8 and an R2 score of 1.000, underscoring its superior predictive capabilities. …”
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CRISPR.BOT an autonomous platform for streamlined genetic engineering and molecular biology applications by Fatmanur Erkek, Rana Kizilkaya, Seyma Baybara, Gamze Gulden, Berranur Sert, Muzeyyen Sena Yazicilar, Menekse Cagla Yilmaz, Sibel Pinar Odabas, Enes Bal, Gamze Yelgen, Tarik Teymur, Yasin Ay, Solen Dogdu, Nilufer Neslihan Tiryaki, Buse Baran, Beste Gelsin, Hasret Araz, Ilayda Cavrar, Cihan Tastan

“…Traditional workflows, laden with laborious and error-prone stages, incur prolonged timelines and escalating costs. …”
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Assessment of predictors and mitigation strategy for therapeutic inertia in the management of hypertension: a quality improvement project by Ananyan Sampath, Shreya Deshpande, Rashmi Verma, Rajnish Joshi

“…When patient adherence was disregarded, TI increased to 49.7%. The total error rate in BP management ranged from 53.29% to 61.5%. …”
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Consistency of the orbital chronologies derived for Vostok and EPICA DC ice cores based on the dependence of ice air content on local insolation by V. A. Khomyakova, N. A. Tebenkova, V. Ya. Lipenkov, D. Raynaud

“…Comparison of the TAC timescales with the optimized chronologies AICC2012 and AICC2023 for the Vostok and EDC cores showed that their discrepancy, as a rule, does not exceed 2 ka, which is consistent with both the standard error of the TAC­based dating method (±2.1 ka) and the standard errors of the AICC2012 (±1.9…4.8 ka) and AICC2023 (±0.8…2.6 ka) reference chronologies themselves. …”
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Three-dimensional visualization of maize roots based on magnetic resonance imaging by Fang Xiaorong, Wang Nanfei, Zhang Jianfeng, Gong Xiangyang, Liu Fei, He Yong

“…Similarly, actual geometric parameters of the samples were measured manually by a vernier caliper and water displacement method.By comparing the reconstruction model of root architecture with the physical object, it was found that the obtained models were well consistent with real samples, showing very good agreement in shape, volume and other morphological parameters, and the errors among them were less than 3%.In sum, the presented methodology can avoid making great efforts in experimental measurements and consequently development of the root architecture models, and decrease the error generated from manual data extraction. …”
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A novel approach for snow depth retrieval in forested areas by integrating horizontal and vertical canopy structures information by Shanna Yue, Liyun Dai, Jie Deng, Yanxing Hu, Lin Xiao, Tao Che

“…Compared to the Chang algorithm and the AMSR-E snow depth product, this study demonstrated higher accuracy in the mid- to high-latitude forested areas of Eurasia, with an R value approximately twice as high and a reduction in the overall root mean square error (RMSE) by 2.3 cm and 7.2 cm, respectively. …”
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The Effects of Presenting AI Uncertainty Information on Pharmacists’ Trust in Automated Pill Recognition Technology: Exploratory Mixed Subjects Study by Jin Yong Kim, Vincent D Marshall, Brigid Rowell, Qiyuan Chen, Yifan Zheng, John D Lee, Raed Al Kontar, Corey Lester, Xi Jessie Yang

“…A pronounced “negativity bias” was observed, where the degree of trust reduction when the AI made an error exceeded the trust gain when the AI made a correct decision (z=–11.30; P<.001). …”
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A novel multimodal image feature fusion mechanism: Application to rabbit liveweight estimation in commercial farms by Daoyi Song, Zhenhao Lai, Shuqi Yang, Dongyu Liu, Jinxia (Fiona) Yao, Hongying Wang, Liangju Wang

“…The network was trained and validated on a dataset of 1,957 overhead images from 300 rabbits collected from a commercial farm, achieving superior performance with an R-Square (R2) of 0.95, Root Mean Square Error (RMSE) of 194.95 g, Mean Absolute Deviation (MAD) of 155.10 g, Mean Absolute Percentage Error (MAPE) of 4.08 %, and Mean Coefficient of Variation (MCV) of 3.03 %. …”
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Synergistic SAPSO-sinusoidal decay empirical formula for ship motion forecasting in waves by Jianwei Wang, Xinyu Han, Jiachen Chai, Wenlei Li, Ze He, Minghua Yue

“…Comparative analysis reveals that SAPSO achieves significant performance enhancements over standard PSO, with mean reductions of 70.8% in Mean Squared Error (MSE) and 40.1% in Root Mean Squared Error (RMSE), indicating substantially improved convergence stability. …”
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Urban Signalized Intersection Traffic State Prediction: A Spatial–Temporal Graph Model Integrating the Cell Transmission Model and Transformer by Anran Li, Zhenlin Xu, Wenhao Li, Yanyan Chen, Yuyan Pan

“…Validation using real traffic data from pNEUMA demonstrates that CeT significantly outperforms baseline models in two-phase signalized intersection scenarios, achieving reductions of 11.47% in Mean Absolute Error (MAE), 13.48% in Root Mean Square Error (RMSE), and an increase of 4.36% in Accuracy (ACC). …”
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Power Assessment and Performance Comparison of Wind Turbines Driven by Multivariate Environmental Factors by Bubin Wang, Bin Zhou, Denghao Zhu, Mingheng Zou, Zhao Rao, Haoxuan Luo, Weihao Ji

“…The proposed method achieves substantial improvements in predictive accuracy, with decreases of 9.39% in mean absolute error (MAE) and 11.75% in root mean square error (RMSE), compared to conventional binning approaches. …”
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Research on Wafer CMP Temperature Online Detection Compensation Algorithm Based on GA-BP Improved Neural Network by Binjie Li, Kuan Shen, Zhilong Song, Binghai Lyu, Wenhong Zhao

“…Experimental results indicate that the mean absolute error (MAE) of the test set has decreased to 0.2381&#x00B0;C, representing reductions of 82% and 68% compared to BP and GA-BP, respectively. …”
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Multi-Level Decomposition and Interpretability-Enhanced Air Conditioning Load Forecasting Study by Xinting Yang, Ling Zhang, Hong Zhao, Wenhua Zhang, Chuan Long, Gang Wu, Junhao Zhao, Xiaodong Shen

“…Results show that the proposed method significantly outperforms the LSTM model without decomposition and other benchmark models in prediction accuracy, with the Root Mean Square Error (RMSE) reductions ranging from 40.26% to 74.18% and the Modified Mean Absolute Percentage Error (MMAPE) reductions from 37.75% to 73.41%. …”
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Implementation of medication reconciliation at admission and discharge in Ministry of Defense Health Services hospitals: a multicentre study by Ahmed Kassem, Noura Alnowaiser, Yasser K Alotaibi, Dalia S Alghamdi, Mohammed Alhrasen, Alaa Alwagdani, Ayla Mohammad Tourkmani, Yasser Al Barakah

“…The medication reconciliation process can significantly lower the incidence of medication errors that may arise from an incomplete or inaccurate medication history as well as reductions in length of hospital stay, patients’ readmissions and lower healthcare costs.The quality improvement collaborative project was conducted as a pilot study in two hospitals, then implemented on a broader scale in 18 hospitals in Saudi Arabia. …”
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Diffuse attenuation coefficient and bathymetry retrieval in shallow water environments by integrating satellite laser altimetry with optical remote sensing by Changda Liu, Huan Xie, Qi Xu, Jie Li, Yuan Sun, Min Ji, Xiaohua Tong

“…The accuracy of the bathymetric maps improved significantly with seafloor classification, as indicated by reductions in root mean square error (RMSE) of 0.12 m and 0.15 m, and in mean absolute percentage error (MAPE) by 2.24 % and 5.87 %, respectively. …”
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Enhancing energy management in battery electric vehicles: A novel approach based on fuzzy Q-learning controller by Salma Ariche, Zakaria Boulghasoul, Abdelhafid El Ouardi, Abdelhadi Elbacha, Abdelouahed Tajer, Stéphane Espié

“…The results show that the FQLC significantly outperforms the FLC, achieving MMAE values as low as 0.01, indicating substantial reductions in error rates. In the performed tests, the FQLC’s ability to manage energy use contributed to range extensions in certain cases, achieving an increase of up to 11 km. …”
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