Lower extremity functional performance tests and their measurement properties in athletes: a systematic review and narrative synthesis by Alison Rushton, Nicola R Heneghan, Lee Herrington, James Martin, Rosalyn Cooke, Andy Soundy

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Prediction of Carbon Dioxide Concentrations in Strawberry Greenhouse by Using Time Series Models by Seung Hyun Shin, Nibas Chandra Deb, Elanchezhian Arulmozhi, Niraj Tamrakar, Oluwasegun Moses Ogundele, Junghoo Kook, Dae Hyun Kim, Hyeon Tae Kim

“…The time-series data were analyzed using the autoregressive integrated moving average (ARIMA) and the Prophet Forecasting Model (PFM), with performance assessed through root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R²). …”
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Performance Evaluation of Inherent Optical Property Algorithms and Identification of Potential Water Quality Indicators Using GCOM-C Data in Eutrophic Lake Kasumigaura, Japan by Misganaw Choto, Hiroto Higa, Salem Ibrahim Salem, Eko Siswanto, Takayuki Suzuki, Martin Mäll

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Deterministic Neutronics Calculation Method of Small Lead-cooled Reactor Based on Venus-Ⅱ Criticality Experimental Facility and Its Verification by YANG Yichen1, ZHENG Youqi1, ZHU Qingfu2, ZHOU Qi2, NING Tong2

“…Small reactors with complexity and flexibility are now the focus of research in many countries. Small lead-cooled reactor (SLR) is an important direction for the future development of small reactors. …”
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The Efficacy of Conversational AI in Rectifying the Theory-of-Mind and Autonomy Biases: Comparative Analysis by Marcin Rządeczka, Anna Sterna, Julia Stolińska, Paulina Kaczyńska, Marcin Moskalewicz

“…The findings reveal the need for improved simulated emotional intelligence in chatbot design to provide adaptive, personalized responses that reduce overreliance and encourage independent coping skills. Future research should focus on enhancing affective response mechanisms and addressing ethical concerns such as bias mitigation and data privacy to ensure safe, effective AI-based mental health support.…”
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New Insights Into the Population Structure of Hector's Dolphin (Cephalorhynchus hectori) Revealed Using Environmental DNA by S. M. Bennington, S. D. Bourke, S. P. Wilkinson, N. Englebert, D. M. Bond, G.‐J. Jeunen, S. Dawson, E. Slooten, P. W. Dillingham, W. J. Rayment, A. Alexander

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Analyzing infant cry to detect birth asphyxia using a hybrid CNN and feature extraction approach by Samrat Kumar Dey, Khandaker Mohammad Mohi Uddin, Arpita Howlader, Md. Mahbubur Rahman, Hafiz Md. Hasan Babu, Nitish Biswas, Umme Raihan Siddiqi, Badhan Mazumder

“…The performance of different ML and DL models is evaluated, with Logistic Regression (LR) achieving an accuracy of 99.16% and a 0.008% error rate. In comparison, ANN1 outperforms other DL models with an accuracy of 98.20% and a 0.018% error rate. …”
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Real‐Climatic Microcontroller‐in‐the‐Loop (RCMIL) Framework: A Novel, Rapid, and Cost‐Effective Approach for Verifying Photovoltaic Control Systems by Ambe Harrison, Idriss Dagal, Wulfran Fendzi Mbasso, Fritz Nguemo Kemdoum, Reagan Jean Jacques Molu, Hamid Belghiti, Pradeep Jangir

“…By pushing the frontiers of PV system research, this paper provides a vital resource that speeds up the transition from simulation to real‐world applications.…”
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Optimized irrigation and fertilization for spring maize under warming and wetting climate in a semi-arid region of China by Hongjuan Zhang, Rui Zhang, Lina Sun, Haolin Li, Yanling Xue, Xia Zhao, Jiahui Liu, Chao Yuan

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Topography-Enhanced Multilevel Residual Attention U-Net Model for Sea Ice Concentration Spatial Super-Resolution Prediction by Jianxin He, Yuxin Zhao, Shuo Yang, Haoyu Wang, Xiong Deng

“…High-resolution (HR) sea ice concentration (SIC) is essential for polar ocean monitoring and Arctic research. Super-resolution (SR) techniques improve the spatial resolution of SIC data, but existing methods often fail to capture fine-scale structures, perform poorly at ice edges, and lack accuracy near sea–land boundaries. …”
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Modeling the compressive strength of concrete at different curing regimes using machine learning by Kennedy C. Onyelowe, Ahmed M. Ebid, Rosa Belén Ramos Jiménez, Angel Geovanny Lozano Guamán, Diego Ramiro Ñacato Estrella, Juan Carlos Cayán Martínez, Eduardo Francisco García Cabezas, Paul Awoyera

“…Generally, it can be deduced that the ANN maintains the decisive model with the lowest error in computation and the least outliers from the ± 25% accuracy envelop. …”
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Comparison of amblyopia in schoolchildren in Ireland and Northern Ireland: a population-based observational cross-sectional analysis of a treatable childhood visual deficit by Veronica O'Dwyer, Kathryn Saunders, Siofra Harrington, Karen Breslin

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Estimation of Canopy Chlorophyll Content of Apple Trees Based on UAV Multispectral Remote Sensing Images by Juxia Wang, Yu Zhang, Fei Han, Zhenpeng Shi, Fu Zhao, Fengzi Zhang, Weizheng Pan, Zhiyong Zhang, Qingliang Cui

“…Additionally, the model performance was assessed by selecting the coefficient of determination (R²), root mean square error (RMSE) and mean absolute error (MAE). The results show that the SPAD estimation results vary from stage to stage, where the best estimation model for the flower-falling stage, fruit-setting stage and fruit-maturing stage is RF and those for the fruit expansion stage and fruit-coloring stage are PLSR and MLR, respectively. …”
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Prediction of coalbed methane productivity based on neural network models by JIN Yi, ZHENG Chenhui, SONG Huibo, MA Jiaheng, YANG Yunhang, LIU Shunxi, ZHANG Kun, NI Xiaoming

“…Clarifying the influence mechanism of these factors on the productivity of coalbed methane wells is the basis for achieving fine reservoir reconstruction and increasing production of coalbed methane wells.MethodsTherefore， this paper takes Shizhuang South Block in Qinshui Basin as the research object， and comprehensively considers the geological background， reservoir physical properties and dynamic drainage data， uses neural network algorithm to carry out CBM productivity prediction. …”
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Imputation and Missing Indicators for Handling Missing Longitudinal Data: Data Simulation Analysis Based on Electronic Health Record Data by Molly Ehrig, Garrett S Bullock, Xiaoyan Iris Leng, Nicholas M Pajewski, Jaime Lynn Speiser

“…We evaluated imputation quality using normalized root-mean-square error for continuous variables and percent falsely classified for categorical variables. …”
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MeloDI: An Internet of Things Architecture to Evaluate Melon Quality by Means of Machine Learning Using Sensors Data and Drone Images by Angel Luis Perales Gomez, Juan Jesus Losada del Olmo, Pedro E. Lopez-de-Teruel, Alberto Ruiz, Felix J. Garcia Clemente, Andres Conesa Bueno

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Evaluasi Kinerja MLLIB APACHE SPARK pada Klasifikasi Berita Palsu dalam Bahasa Indonesia by Antonius Angga Kurniawan, Metty Mustikasari

“…Evaluasi dilakukan berdasarkan accuracy, test error, f1-score, confusion matrix, dan running time. …”
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Time Series Modelling of the Caspian Kutum (Rutilus frisii) Catch Using SARIMA Model by Fateh Moezzi, Hadi Poorbagher, Soheil Eagderi, Jahangir Feghhi

“…The performance and predictive ability of the models were assessed using aset of indices, including Akaike’s information criteria (AIC), Bayesian information criterion(BIC), root mean squared error (RMSE), normalized root mean squared error (nRMSE), meanabsolute error (MAE), normalized mean absolute error (nMAE) and the Pearson correlationcoefficient (r). …”
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Accurate Prediction of 327 Rice Variety Growth Period Based on Unmanned Aerial Vehicle Multispectral Remote Sensing by Zixuan Qiu, Hao Liu, Lu Wang, Shuaibo Shao, Can Chen, Zijia Liu, Song Liang, Cai Wang, Bing Cao

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Detection Technology for Catenary Stagger Value Based on Acceleration Signals by CHEN Hongming, ZHOU Ning, LU Wenwei, YANG Zixian, CHENG Yao, WANG Dong, ZHANG Weihua

“…［Objective］ To address the inefficiency and high operational requirements of existing detection methods for catenary stagger value in electrified railways, special research on catenary stagger value detection method is conducted. …”
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