Olive fruit ripening characterisation based on electrical capacitance measurements by Daniel Argüello, Miguel Noguera, Andrés Mejías, Juan Manuel Enrique, Arturo Aquino

“…These samples were also subjected to chemical analysis for reference. The analysis of this data revealed high intra-sample variability, consistent with recent studies. …”
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Computational Modeling and Molecular dynamics Simulations of Thiazolino 2-pyridone amide analog compounds as Chlamydia trachomatis inhibitor by Emmanuel Edache, Adamu Uzairu, Paul Mamza, Gideon Shallangwa

“…Between the experimental and predicted pIC50 value, the overall standard deviation error of prediction (SDEP) was 0.2448, showing strong 2D-QSAR model predictability. …”
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Performance prediction of radio frequency based negative ion source using fusion neural network model by Yu Gu, Chundong Hu, Yang Li, Yuwen Yang, Yahong Xie, Qinglong Cui, Yuanzhe Zhao

“…The model leverages the setting parameters and diagnostic data from RF-NIS to train multiple specific neural network models, thereby establishing the fusion neural network architecture. …”
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Genome-Wide Association Study and Phenotype Prediction of Reproductive Traits in Large White Pigs by Hao Zhang, Shiqian Bao, Xiaona Zhao, Yangfan Bai, Yangcheng Lv, Pengfei Gao, Fuzhong Li, Wuping Zhang

“…In the combined-parity analysis, candidate genes, such as <i>BLVRA</i>, <i>STK17A</i>, <i>PSMA2</i>, and <i>C7orf25</i>, were identified. …”
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AutoGEEval: A Multimodal and Automated Evaluation Framework for Geospatial Code Generation on GEE with Large Language Models by Huayi Wu, Zhangxiao Shen, Shuyang Hou, Jianyuan Liang, Haoyue Jiao, Yaxian Qing, Xiaopu Zhang, Xu Li, Zhipeng Gui, Xuefeng Guan, Longgang Xiang

“…AutoGEEval supports multidimensional quantitative analysis of model outputs in terms of accuracy, resource consumption, execution efficiency, and error types. …”
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Groundwater flow system of the Abijata-Langano-Ziway lakes basin, Ethiopia by Debele Abera, Behailu Berehanu, Tenalem Ayenew

“…Statistical measures indicated a strong correlation (R2 = 0.98) and high efficiency (NSE = 0.97) in replicating the observed data. Additionally, the Mean Error (ME) of −8.3 m suggests minimal bias in the simulations. …”
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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

“…The models were evaluated using comprehensive performance metrics and validated through statistical analysis. Results demonstrate that the CNN-LSTM-BMO achieves superior performance with the lowest Root Mean Square Error (RMSE) of 0.5523 and highest R² value of 0.9435, showing statistically significant improvements over other optimization methods as confirmed by paired t-tests (P < 0.05). …”
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Multi-scale computational modeling towards efficacy in radiopharmaceutical therapies while minimizing side effects: Modeling of amino acid infusion. by Aryan Golzaryan, Mohammad Souri, Farshad M Kashkooli, Arman Rahmim, M Soltani

“…Our findings revealed a relative error (RE) of 9.6% ± 2.2% (mean ± SD) in total tumor absorbed dose calculation between PBPK and CDR equations, attributable to the consideration of IFP. …”
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E-learning success evaluation in Lebanon during wartime: An extension of Delone and McLean IS success model [version 1; peer review: 2 approved] by Elie Yammine, Layal Rabih

“…Methods A quantitative approach was employed using a structured questionnaire distributed to 429 students and academic staff within higher education institutions in Lebanon. Sampling and data analysis were conducted through structural equation modelling to test hypothesized relationships of the proposed model in SPSS 27.0 using the path analysis. …”
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Investigation of the performance of activated carbon derived from ripe plantain peels for CO2 capture: Modelling and optimisation using response surface methodology by Emmanuel Rieborue Khama, Emmanuel Zeneboebi Loyibo, Wilfred Okologume, Stanley Toochukwu Ekwueme, Chukwudi Victor Okafor, Nnaemeka Princewill Ohia

“…The Response Surface Methodology (RSM) conducted gave 2FI model as the most representative of the design data and showed high accuracy (R2=0.9973) and low error metrics (MSE=0.01697, RMSE=0.130269, MAE=0.109, MAPE=2.7244). …”
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Innovative Approach Integrating Machine Learning Models for Coiled Tubing Fatigue Modeling by Khalil Moulay Brahim, Ahmed Hadjadj, Aissa Abidi Saad, Elfakeur Abidi Saad, Hichem Horra

“…A detailed machine learning model is presented, emphasizing the capability to handle complex data and improve prediction under diverse operational conditions. …”
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Validation of Gait Kinematics With Ramp and Stair Ascent and Descent Revealed by Markerless Motion Capture in Simulated Living Space: Test-Retest Reliability Study by Daiki Shimotori, Kenji Kato, Tatsuya Yoshimi, Izumi Kondo

“…The absolute reliability of day-to-day reproducibility was assessed using full-curve analysis (root mean square difference [RMSD]) and discrete point analysis of gait events using the standard error of measurement (SEM). …”
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Predictive value of vaginal lactic acid bacteria changes on occurrence of HR-HPV-infected cervical intraepithelial neoplasia and construction and validation of nomogram model by Ying Huang, Yuliang Shen, Xuemei Wei, Jie Feng, Lin Zhu

“…Results There was no significant difference in the incidence of CIN, baseline data and vaginal lactic acid bacteria parameters between the training set and the verification set (P > 0.05). …”
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Lake Water Storage and Long-Term Variation of Nganga Rinco on the Tibetan Plateau Revealed by ICESat-2 and Satellite Imagery by Yunmei Li, Qianqian Chen, Shiqiang Zhang, Yuanzheng Cui, Chang Huang

“…Bathymetry in dynamic regions offers higher spatial resolution and more precise elevation data compared to the SRTM DEM. When compared to <italic>in situ</italic> bathymetry, the derived bathymetry showed an average error of 3.64 m, with errors concentrated in deeper regions. …”
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Artificial Neural Network and Response Surface Methodology-Driven Optimization of Cu–Al₂O₃/Water Hybrid Nanofluid Flow in a Wavy Enclosure with Inclined Perio... by Tarikul Islam, Sílvio Gama, Marco Martins Afonso

“…Furthermore, the ANN model demonstrates high accuracy with a mean squared error (MSE) of 0.00018, making it a strong alternative to RSM analysis. …”
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Quantifying degradation in animal acoustic signals with the R package baRulho by Marcelo Araya‐Salas, Erin E. Grabarczyk, Marcos Quiroz‐Oliva, Adrián García‐Rodríguez, Alejandro Rico‐Guevara

“…Moreover, the package minimizes the potential for user error through automated test file annotation and verification procedures. …”
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On the parametric analytics to investigate hole quality characteristics during helical milling of carbon fiber reinforced plastics stacks by Mehdi Tlija, Nimra Naeem, Mohammad Pervez Mughal, Kiran Mughal, Saad Ullah, Muhammad Sana, Anamta Khan

“…Tool eccentricity, cutting speed, and tangential feed were input machining parameters while pitch was kept constant at 2 mm/rev. Analysis of variance is used to study the impact of input variables on the hole quality aspects that include delamination damage, length of uncut fiber, circularity error, and surface roughness by using the Taguchi design of experiment. …”
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Assessment of a patient safety culture: a nationwide cross-sectional study comparing public and private hospitals in Kuwait by Fatemah M. Alsaleh, Shaikha Albraikan, Hadeel Alzoubi, Eman A. Abahussain, Hossam Elamir

“…The questionnaire was distributed among clinical staff in public general and private hospitals. Data analysis using Microsoft Excel and SPSS 23 (α level = 0.05) provided an overview of participant characteristics and patient safety culture scores. …”
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ACO-NM hybrid optimization calculation method for transit time of oxygen activation logging in CO2 injection profile by WANG Zhengyan, CHEN Meng, YANG Guofeng, LIU Guoquan, PEI Yang, CHEN Qiang

“…Compared with the traditional methods involving manual peak boundary determination combined with weighted average or Gaussian function fitting methods, this approach offered higher fitting efficiency, reduced human intervention, and lower calculation error.Through a comparative analysis of pulse neutron oxygen activation data processing and interpretation in well X (CO2 injection well) of the M oilfield, the established ACO-NM optimization model could effectively realize the bimodal separation of overlapping peaks in tubing and casing spaces. …”
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Perinatal artificial intelligence in ultrasound (PAIR) study: predicting delivery timing by Neil Patel, John O’Brien, Robert Bunn, Brandon Schanbacher, John Bauer, Garrett K. Lam

“…Delivery outcomes for this subgroup were blinded from the AI by an independent third-party data monitor. Unique predictions were made for each patient after each ultrasound exam, and the AI’s performance was evaluated against the actual delivery date using metrics such as R2 values and mean absolute error (MAE) compared to actual days until delivery. …”
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