Use of Population-Based Compartmental Modeling and Retinol Isotope Dilution to Study Vitamin A Kinetics and Total Body Stores among Ghanaian Women of Reproductive Age by Michael H Green, Veronica Lopez-Teros, Joanne Balmer Green, Georg Lietz, Sika M Kumordzie, Anthony Oxley, Ahmed D Fuseini, K Winifred Nyaaba, Emily Becher, Jennie N Davis, K Ryan Wessells, Seth Adu-Afarwuah, Reina Engle-Stone, Marjorie J Haskell

“…Methods: Women (n = 89) ingested a dose of [2H6]retinyl acetate and blood samples (3/woman) were collected from 6 h to 91 d, with all participants sampled at 14 d, about half at either 21 or 28 d, and each at one other time. Composite data (plasma retinol fraction of dose; FDp) were analyzed using Simulation, Analysis and Modeling software to obtain kinetic parameters, TBS, and other state variables as well as model-derived values for the RID composite coefficient FaS. …”
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Integrating biomarkers for hemostatic disorders into computational models of blood clot formation: A systematic review by Mohamad Al Bannoud, Tiago Dias Martins, Silmara Aparecida de Lima Montalvão, Joyce Maria Annichino-Bizzacchi, Rubens Maciel Filho, Maria Regina Wolf Maciel

“…A systematic review was conducted following the PRISMA protocol, focusing on ten clinically significant biomarkers associated with hemostatic disorders: D-dimer, fibrinogen, Von Willebrand factor, factor Ⅷ, P-selectin, prothrombin time (PT), activated partial thromboplastin time (APTT), antithrombin Ⅲ, protein C, and protein S. …”
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Optimal Placement of Wind Power System Using Machine Learning by Abdul Karim, Muhammad Amir Raza, Darakhshan Ara, Muhammad Shahid, Shakir Ali Soomro

“…Because SARIMAX captures long-term dependencies, it is particularly suitable for time series data where past events have a large impact on future values. …”
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Research on Forecasting Sales of Pure Electric Vehicles in China Based on the Seasonal Autoregressive Integrated Moving Average–Gray Relational Analysis–Support Vector Regression M... by Ru Yu, Xiaoli Wang, Xiaojun Xu, Zhiwen Zhang

“…Aiming to address the complexity and challenges of predicting pure electric vehicle (EV) sales, this paper integrates a time series model, support vector machine and combined model to forecast EV sales in China. …”
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Biodiesel production from soybean oil using ionic liquid as a catalyst in a microreactor by F. Mohammadi, M. Rahimi, A. Parvareh, M. Feyzi

“…The proximity of the experimental results and predicted values showed that the regression model issignificant. …”
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Short-Term Wind Speed Prediction Using EEMD-LSSVM Model by Aiqing Kang, Qingxiong Tan, Xiaohui Yuan, Xiaohui Lei, Yanbin Yuan

“…Finally, the superposition principle is employed to sum the predicted values of every subseries as the final wind speed prediction. …”
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Deep Learning Method for Breakdown Voltage and Forward <i>I-V</i> Characteristic Prediction of Silicon Carbide Schottky Barrier Diodes by Hao Zhou, Xiang Wang, Shulong Wang, Chenyu Liu, Dongliang Chen, Jiarui Li, Lan Ma, Guohao Zhang

“…Although the model requires a certain amount of time to establish itself, it supports linear variations in related variables once developed. …”
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Research Tests of Drill Seeder with Control and Monitoring Unit of Seed Metering Device for Differentiated Dosing of Seeds and Mineral Fertilisers in Precision Agriculture by Zolotukhin Yevgeniy, Nukeshev Sayakhat, Amantayev Maxat, Rustembayev Arman, Kakabayev Nurbol, Kravchenko Ruslan

“…It was revealed that the seeder allows for smooth adjustment, reduces time, and increases the range of seeding rate and dosing of seeding material. …”
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Exploring the Impact of Cervical Multifidus Muscle Morphology on Postural Balance in Post-Stroke Patients: A pilot study by Vanesa Abuín-Porras, Paolo Pedersini, Almudena Paret-Fernández, Carlos Romero-Morales, Paula García-Bermejo, Isabel Rodríguez-Costa, Jorge Villafañe

“…No significant differences in the ultrasound values between affected and unaffected sides in post-stroke patients were found. …”
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Optimization of robotic spray painting trajectories using machine learning for improved surface quality by Ritesh Bhat, M. Karuppasamy, M. Maragatharajan, Anandakumar Haldorai, E. Nirmala, Nithesh Naik

“…The study offers clear guidelines for practitioners to enhance their processes to produce high-quality products and time efficiency.…”
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The relationship between individualised speed thresholds and changes in aerobic fitness in elite professional youth soccer players. A case study by Ronan KAVANAGH, Kevin McDAID, David RHODES, Jill ALEXANDER, Damian HARPER, Rafael OLIVEIRA, Kieran BERRY, Mark CONNOR, Piotr ZMIJEWSKI, Ryland MORGANS

“…Conclusions: ASR-based training load variables displayed the highest correlations with Bronco results. …”
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Use of the visual analog scale of craving in addiction medicine: advantages and limitations of the method by Evgeny M. Krupitsky, Elvina A. Akhmetova, Svetlana G. Klimanova

“…In addition to the inherent constraints of self-report methods, such as reliance on self-reflection, the VAS requires a clear definition of the construct being measured, lacks norms or thresholds, and maybe affected by the variability of how the respondents interpret maximum and intermediate scale values. …”
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Circadian rhythm abnormalities and autonomic dysfunction in patients with Chronic Fatigue Syndrome/Myalgic Encephalomyelitis. by Trinitat Cambras, Jesús Castro-Marrero, Maria Cleofé Zaragoza, Antoni Díez-Noguera, José Alegre

“…The circadian variables and the spectral analysis of the rhythms were calculated. …”
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Diagnostic framework to validate clinical machine learning models locally on temporally stamped data by Maximilian Schuessler, Scott Fleming, Shannon Meyer, Tina Seto, Tina Hernandez-Boussard

“…When applied to predicting ACU in cancer patients, the framework highlights fluctuations in features, labels, and data values over time. Conclusions The work in this study emphasizes the importance of data timeliness and relevance. …”
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Assessment of meteorological and socioeconomic drought conditions in the Tekeze watershed, northern Ethiopia by Yonas Tesfay Tela, Simachew Bantigegn Wassie, Mehrete Belay Ferede

“…The drought conditions in the area were exacerbating from time to time with a drought reoccurrence period of 2 years. …”
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Investigation of Possibility of Measuring the Albedo of Earth's Surface in Visible and Near Infrared Bands in Conditions of Aerosol Pollution of Atmosphere Using Unmanned Aerial Ve... by H. H. Asadov, A. J. Alieva, M. G. Ashrafov

“…These factors leading to changes in the earth's albedo lead to the need for periodic measurements of regional values of the albedo of the earth's surface. There are a number of problems related to measuring the albedo of the earth, related to the spatial and temporal variability of this indicator. …”
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Efficient adsorption of methylene blue (MB) by an eco-friendly chitosan derivative adsorbent: An RSM and ANN modeling study by E. Igberase, I.G. Mkhize

“…One neuron was employed as the output layer, which corresponds to the removal efficiency of MB, and variables, including adsorbent dosage, pH, contact time, and MB concentration, were taken into consideration as the input layer feed data. …”
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Underwater synthetic image generation for multi-temporal monitoring of crustose coralline algae by A. Calantropio, A. Giaquinto, S. Del Pizzo, F. Menna, E. Nocerino

“…Results demonstrate the ability to detect chromatic alterations over time, with SSIM values indicating consistency and &Delta;E metrics revealing widespread perceptual changes. …”
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Differential Positioning with Bluetooth Low Energy (BLE) Beacons for UAS Indoor Operations: Analysis and Results by Salvatore Ponte, Gennaro Ariante, Alberto Greco, Giuseppe Del Core

“…Distance information from measured <i>RSSI</i> values can be degraded by multipath, reflection, and fading that cause unpredictable variability of the <i>RSSI</i> and may lead to poor-quality measurements. …”
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The impacts of specific place visitations on theft patterns: a case study in Greater London, UK by Tongxin Chen, Kate Bowers, Tao Cheng

“…An explainable machine learning approach was applied to analyse the impacts of place visitations on theft levels: the ‘XGBoost’ algorithm trained a high-performance regression model and ‘SHapley Additive exPlanations’ (SHAP) values were measured to identify the contributions of different visitation variables to theft levels at specific spatial and temporal scales. …”
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