Tropical cyclone track prediction harnessing deep learning algorithms: A comparative study on the Northern Indian Ocean by Sabbir Rahman, M. Fahim Faisal, Prianka Mondal, Md. Mahfuzur Rahman

“…Utilizing an extensive dataset of historical cyclone tracks and atmospheric parameters, we systematically compare these models across multiple performance metrics, including Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). …”
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Emmetropia deviation in autorefraction compared to subjective refraction result in patients after corneal refractive surgery by Yuexin Wang, Zesong Wang, Yu Zhang, Yifei Yuan, Yan Liu, Shuo Yu, Ziyuan Liu, Chen Yueguo

“…Abstract Background Automatic refraction is commonly applied as a substitute for subjective refraction to evaluate residue refractive error after corneal refractive surgery. Previous research pooled the data from patients of different subgroups to calculate the difference between automatic and subjective refraction, which lacks clinical implications. …”
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TBESO-BP: an improved regression model for predicting subclinical mastitis by Kexin Han, Yongqiang Dai, Huan Liu, Junjie Hu, Leilei Liu, Zhihui Wang, Liping Wei

“…The primary objective is to discern models by exhibiting higher predictive accuracy and lower error values.ResultsThe evaluation of the TBESO-BP model in the test phase reveals a coefficient of determination R2 = 0.94, a Mean Absolute Error (MAE) of 2.07, and a Root Mean Square Error (RMSE) of 5.33. …”
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Differentiating biomarker features and familial characteristics of B-SNIP psychosis Biotypes by David A. Parker, Rebekah L. Trotti, Jennifer E. McDowell, Sarah K. Keedy, Matcheri S. Keshavan, Godfrey D. Pearlson, Elliot S. Gershon, Elena I. Ivleva, Ling-Yu Huang, Kodiak Sauer, S. Kristian Hill, John A. Sweeney, Carol A. Tamminga, Brett A. Clementz

“…First-degree relative data implicate specific bio-factors as familial within idiopathic psychosis which may inform genetic studies.…”
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A Comprehensive Evaluation of Monocular Depth Estimation Methods in Low-Altitude Forest Environment by Jiwen Jia, Junhua Kang, Lin Chen, Xiang Gao, Borui Zhang, Guijun Yang

“…On the Mid-Air dataset, the Transformer-based DepthAnything demonstrates a 54.2% improvement in RMSE for the global error metric compared to the CNN-based Adabins. On the LOBDM dataset, the CNN-based MiDas has the depth edge completeness error of 93.361, while the Transformer-based Metric3D demonstrates the significantly lower error of only 5.494. …”
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Forecasting temperature and rainfall using deep learning for the challenging climates of Northern India by Syed Nisar Hussain Bukhari, Kingsley A. Ogudo

“…The RNN model in MIMO configuration achieved significantly lower mean absolute error (MAE), root mean squared error (RMSE), and mean squared error (MSE) for Jammu, Srinagar, and Ladakh, with respective values of [0.0636, 0.1011, 0.0401] for Jammu, [0.1048, 0.1555, 0.0455] for Srinagar, and [0.0854, 0.1344, 0.0411] for Ladakh. …”
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Data-driven prediction of rate of penetration (ROP) in drilling operations using advanced machine learning models by Guoli Huang, Sarah Kanaan Hamzah, Pinank Patel, T. Ramachandran, Aman Shankhyan, A. Karthikeyan, Dhirendra Nath Thatoi, Deepak Gupta, S. AbdulAmeer, Mariem Alwan, Zahraa Saad Abdulali, Mahmood Jasem Jawad, Hiba Mushtaq, Mohammad Mahtab Alam, Hojjat Abbasi

“…Among the models tested, the Random Forest algorithm demonstrated outstanding performance, achieving an R2 of 0.955, a Mean Squared Error (MSE) of 0.119, and an Average Absolute Relative Error (AARE%) of 7.683, highlighting its reliability and robustness in predicting ROP. …”
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Investigating the biodiversity conservation capability of technological innovation and FinTech by Shayan Khan Kakar, Jing Wang, Noman Arshed, Tran Thi Le Hien, Nazir Muhammad Abdullahi

“…We provide the policy implications of our research.…”
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CXCR4 and CXCR6 dually limit T cell entry into the polyomavirus-infected brain by Kalynn M. Alexander, Elia Afanasiev, Arrienne B. Butic, Ge Jin, Mofida Abdelmageed, Anirban Paul, Jo Anne Stratton, Aron E. Lukacher, Samantha A. Spencer

“…This work demonstrates that CXCR4 and CXCR6 act in a nonredundant fashion to restrict T cell accumulation to the polyomavirus-infected ependyma, with important implications for ongoing efforts to use JCPyV-specific T cell adoptive immunotherapy for PML.…”
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A Comparative Study of Deep Audio Models for Spectrogram- and Waveform-Based SingFake Detection by Minh Nguyen-Duc, Luong Vuong Nguyen, Huy Nguyen-Ho-Nhat, Tri-Hai Nguyen, O-Joun Lee

“…Metrics such as Precision, Recall, F1-score, Equal Error Rate (EER), and Area Under the Curve (AUC) provide insights into the strengths and weaknesses of each approach. …”
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Ecological footprint analysis as a tool for advancing sustainable development goals (SDGs): Evidence from China by Jie Wu, Haozhe Yu, Ning Cao, Jing Zhang, Jawad Khan, David lee

“…Using time series data from 1995 to 2023, the study applies a Vector Error Correction Model (VECM), Autoregressive Distributed Lag (ARDL) analysis, and Fully Modified Ordinary Least Squares (FMOLS) to capture both long-term equilibrium and short-run dynamics. …”
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Implementation of laser-light backscattering imaging for authentication of the geographic origin of Indonesia region citrus by Muhammad Achirul Nanda, S. Rosalinda, Rahmat Budiarto, Inna Novianty, Taufik Ibnu Salim, Pradeka Brilyan Purwandoko, Dimas Firmanda Al Riza

“…The results showed that the proposed technique achieved 96.667 % accuracy and 3.333 % apparent error for authentication of the geographic origin. …”
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Estimation of performance measures in a novel M/M/1 queueing model with reverse balking: A simulation-based approach by Asmita Tamuli, Dhruba Das, V. Deepthi, Amit Choudhury, Dibyajyoti Bora, Bhushita Patowari, Supahi Mahanta

“…The findings offer valuable implications for managing and optimizing service systems where reverse balking is common.…”
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HEALTH CLAIM INSURANCE PREDICTION USING SUPPORT VECTOR MACHINE WITH PARTICLE SWARM OPTIMIZATION by Syaiful Anam, M. Rafael Andika Putra, Zuraidah Fitriah, Indah Yanti, Noor Hidayat, Dwi Mifta Mahanani

“…Prediction of the number of claims could give the significant implications in the profit margins generated by the health insurance company. …”
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Interdependence Between River Aquifer Groundwater Flow and Temperature–Depth Profiles: Type Curves Based on Pi Theorem and Numerical Simulations by José Antonio Jiménez-Valera, Iván Alhama, Carlos Duque, David Labat

“…The interaction between surface water and groundwater has been extensively studied due to its water management implications and the potential environmental impacts arising from it. …”
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Predicting Adjustment of students based on School Culture: the mediating role of Quality of life at School by Seyed Alireza Ghasemi, Hossein Khosravi, Minoo Miri, Hadi Pourshafei, Faezeh Khosravi

“…The goodness-of-fit index of the root of the approximation error is equal to0.076 and the standard root of the residual variance is equal to0.054, which indicates the good fit of the model. …”
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Thermal resistance capacity model for transient simulation of capillary-box heat exchangers by Huili Yu, Yuhao Wang, Guangrui Xv, Di Wu, Songtao Hu

“…The model is verified against experimental data, achieving very good agreement with the mean bias error (MBE) of 7.2 %. A comparison with a three-dimensional computational fluid dynamic (CFD) model indicates that the TRC model's maximum relative error and MBE are 0.7 % and 2.0 % lower than those of the CFD model. …”
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Robotic-assisted vs. traditional medial patellofemoral ligament reconstruction: a comparative study of surgical precision and clinical outcomes by Hongzhi Fang, Zhenghui Shang, Tianli Du

“…The primary endpoints included the error margin between the femoral tunnel entry point, a predefined reference landmark, and the quantity of intraoperative fluoroscopic exposures. …”
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Prediction of Urban Construction Land Carbon Effects (UCLCE) Using BP Neural Network Model: A Case Study of Changxing, Zhejiang Province, China by Qinghua Liao, Xiaoping Zhang, Zixuan Cui, Xunxi Yin

“…These contributions carry significant theoretical and practical implications.…”
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MACRO-ECONOMETRIC ANALYSIS OF INWARD CAPITAL FLOWS: A CASE OF NIGERIA IN TIMES OF SECURITY CHALLENGES by Kingsley Onyekachi Onyele, Eberechi Bernadine Ikwuagwu, Happy Chukwudike Ibe

“… This study used quarterly data for the period of 2014Q1–2021Q2 to investigate the macro-econometric implications of capital flows to Nigeria in the face of security challenges. …”
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