Machine learning framework for oxytetracycline removal using nanostructured cupric oxide supported on magnetic chitosan alginate biocomposite by Hassan Rasoulzadeh, Hossein Azarpira, Mojtaba Pourakbar, Amir Sheikhmohammadi, Alieh Rezagholizade-shirvan

“…The PSO allowed us not only to identify these optimal values but also to analyze the relationships between the variables. …”
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A Novel Method for Eliminating Glint in Water-Leaving Radiance from UAV Multispectral Imagery by Jong-Seok Lee, Sin-Young Kim, Young-Heon Jo

“…Unmanned Aerial Vehicle (UAV) high-resolution remote sensing imagery has been used for unprecedented coastal environment monitoring with ground sampling distance and time intervals of a few centimeters and seconds, respectively. …”
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Enhancing Campus Mobility: Simulated Multi-Objective Optimization of Electric Vehicle Sharing Systems Within an Intelligent Transportation System Frameworks by Omar S. Aba Hussen, Shaiful J. Hashim, Nasri Sulaiman Member, S.A.R. Alhaddad, Bassam Y. Ribbfors, Masanobu Umeda, Keiichi Katamine

“…In addition to conventional decision variables, dynamic dual relocation thresholds and charge levels are introduced as decision variables to enhance optimization. …”
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Multi-scale convolutional transformer network for motor imagery brain-computer interface by Wei Zhao, Baocan Zhang, Haifeng Zhou, Dezhi Wei, Chenxi Huang, Quan Lan

“…However, traditional CNN-based methods face challenges such as individual variability in EEG signals and the limited receptive fields of CNNs. …”
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Shedding Light on the Antioxidant Activity of Bee Venom Using a 2,2-Diphenyl-1-Picrylhydrazyl Assay in a Detergent-Based Buffer by Alessandro Orrù, Barbara Pittau, Francesca Pettinau

“…In this study, we aim to address the source of this variability by investigating the antioxidant activity of HBV in a detergent-based buffer across a range of pH values (from 3 to 7.5). …”
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XGBoost based enhanced predictive model for handling missing input parameters: A case study on gas turbine by Nagoor Basha Shaik, Kittiphong Jongkittinarukorn, Kishore Bingi

“…The proposed research establishes the framework for real-time integration of the developed XGBoost model with gas turbine control systems.…”
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Does Cultural Communication Strategy in Metaverse affect International Students’ Mental Health? Moderating effects of Cyberchondria and Healthcare Disparity by Muhammad Nouman Shafiq

“…In order to measure the variables using measurement scales, questionnaires are created using various items from the variables. …”
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Using Response Surface Methodology to Optimize Edible Coating Formulations to Delay Ripening and Preserve Postharvest Quality of Tomatoes by Robin Tsague Donjio, Jean Aghofack Nguemezi, Mariette Anoumaa, Eugene Tafre Phounzong, Justine Odelonne Kenfack, Théophile Fonkou

“…Under these conditions, predicted values of response variables are as follows: ripening rate (RR) 40.75, chlorophyll a (Chl a) 8.11, firmness (Fir) 4.00, total flavonoid content (TFC) 43.51, and titratable acidity (TA) 0.30. …”
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Machine learning-based predictive tools and nomogram for in-hospital mortality in critically ill cancer patients: development and external validation using retrospective cohorts by Kaier Gu, Saisai Lu

“…This model can assist physicians in clinical decision-making and timely intervention. Clinical trial number Not applicable.…”
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Features of daily blood pressure fluctuations in patients with obstructive sleep apnea syndrome and obesity by O. I. Tokarenko, Ya. O. Andreeva

“…Patients of all three groups more frequently showed significantly increased of SBP and DBP daytime and night time variability than the patients of control group. …”
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Mean Platelet Volume in Patients with Obstructive Sleep Apnea and Its Relationship with Simpler Heart Rate Derivatives by Aydın Akyüz, Dursun Çayan Akkoyun, Mustafa Oran, Hasan Değirmenci, Recep Alp

“…/HR mean] (P > 0.05 for all variables). In multivariate analysis, platelet count and percentages of recording time spent at arterial oxygen saturation < 90% significant variables are associated with MPV (β±SE: −0.004 ± 0.002, 95% CI, −0.008 to −0.001; P = 0.034) and (β±SE: 2.93 ± 1.93, 95% CI, 0.167 to 5.69; P = 0.038). …”
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Study of ethnoveterinary medicine practices in a global hotspot of India using ecological modelling: why and where? by Kaushalendra Kumar Jha, Radhika Jha

“…Model validity was ascertained using common evaluator AUC (0.700 to 0.847) and model-specific (presence-only) evaluator CBI (0.495 to 0.945) values. The three vital variables for different species contributing to habitat prediction were bio17 (precipitation of driest quarter), bio4 (temperature seasonality), and bio2 (mean diurnal range) in this region. …”
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Factors influencing clinical breast cancer screening: A cross-sectional study among Islamic women in Kumasi Metropolis of Ghana. by Abdul-Karim Abubakari, Janet Gross, Emmanuel Adusei-Poku

“…Binary logistic regression was employed to determine the relationships between variables. Outcome variables with P-values < 0.05 were considered statistically significant. …”
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Investigation of Peanut Leaf Spot Detection Using Superpixel Unmixing Technology for Hyperspectral UAV Images by Qiang Guan, Shicheng Qiao, Shuai Feng, Wen Du

“…By optimizing threshold values, a better balance between completeness and the internal variability of crop regions was achieved, allowing for the precise extraction of crop regions. …”
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A Hybrid Regression–Kriging–Machine Learning Framework for Imputing Missing TROPOMI NO₂ Data over Taiwan by Alyssa Valerio, Yi-Chun Chen, Chian-Yi Liu, Yi-Ying Chen, Chuan-Yao Lin

“…Model performance was evaluated using the coefficient of determination (<i>r</i>²), computed against observed TROPOMI NO₂ column values filtered by quality assurance criteria. GBR achieved the highest validation <i>r</i>² values of 0.83 for January and February, while RF yielded 0.82 and 0.79 in January and December, respectively. …”
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Machine learning models integrating dietary data predict all-cause mortality in U.S. NAFLD patients: an NHANES-based study by Pinchu Chen, Yao Li, Chenfenglin Yang, Qifan Zhang

“…SHAP values were employed for model interpretability. Results LASSO-Cox regression identified 13 significant variables, including age, household income, blood glucose, sedentary behavior, dietary fiber intake and so on. …”
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Differences in Strength, Muscle Work, and Hamstring/Quadriceps Ratio in Professional and Junior Elite Basketball Players According to Sex by Raúl Coto Martín, Néstor Pérez Mallada, María Jesús Martínez Beltrán, Lucía Cuéllar Marín, Pablo José Borrás Luján, Oscar Otín Arroyo, María Ana Sáenz-Nuño, Juan Manuel Arribas-Marín

“…Concentric knee flexion and extension strength variables were measured in Newtons, the strength ratio between flexors and extensors in H/Q ratio, and muscle work (product of force times displacement) in Joules. …”
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Performance evaluation of a medium axial field-of-view sparse PET system based on flat panels of monolithic LYSO detectors: a simulation study by Maya Abi-Akl, Jens Maebe, Boris Vervenne, Othmane Bouhali, Christian Vanhove, Stefaan Vandenberghe

“…Results The SpM-FP showed 4–5 times lower sensitivity than the L-FP, requiring an acquisition time of 2–3 min to match the image quality achieved by the L-FP in 30 s. …”
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A storage model with random release rate for modeling exposure to food contaminants by Patrice Bertail, Stéphan Clémençon, Jessica Tressou

“…Via embedded chain analysis,ergodic properties of this extension of the standard compound Poisson damwith (deterministic) linear release rate are investigated, the latter being of crucialimportance in describing the long-term behavior of the exposure process(Xt)t≥0 and assessing values such as the proportion of time the contaminantbody burden is over a certain threshold. …”
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Circadian rhythm and epilepsy: a nationally representative cross-sectional study based on actigraphy data by Tianyou Tang, YuDong Zhou, Xuan Zhai, Xuan Zhai

“…The investigation focused on the comparative analysis of seven nonparametric indices associated with circadian rhythms (Interdaily Stability (IS), Intradaily Variability (IV), Relative Amplitude (RA), L5, M10, L5 start time, and M10 start time) between the overall population and patients with epilepsy. …”
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