Determination of 5-fluorouracil anticancer drug solubility in supercritical CO 2 using semi-empirical and machine learning models by Gholamhossein Sodeifian, Ratna Surya Alwi, Reza Derakhsheshpour, Nedasadat Saadati Ardestani

“…Whereas, a crossover point has been seen. Three models with different approaches were applied to correlate and model the experimental data set: (i) seven density-based models, (ii) PR equations of state (vdW2 mixing rule), and (iii) machine learning-based models, namely non-linear regressions, Random Forest, Gradient Boosting, Decision Tree, and Kernel Ridge. …”
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Robust methoxy-based covalent organic frameworks membranes enable efficient near-molecular-weight selectivity by Yanqing Xu, Jiaqi Xiong, Chenfei Lin, Yixiang Yu, Qite Qiu, Junbin Liao, Huimin Ruan, Arcadio Sotto, Jiangnan Shen

“…The TFB-OMe-TAPA COFs membrane demonstrated sharp rejection profiles, separating solutes of different molecular sizes. A three-stage cascade process was used to fractionate binary molecules with varying charges, achieving a separation factor of 26.7 for heterogeneous charge molecules. …”
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The Role of Marketing Mix on Voluntary Tax Compliance: Small Taxpayers’ Experience in Dodoma City by Allen Mrindoko, Eunice Nyange

“…The quantitative data were collected from small business managers/owners who were selected using systematic random sampling technique, while qualitative data were collected from three TRA officers selected purposively. …”
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Cultivating a thriving agricultural sector: Unveiling the drivers of farmer participation in agricultural development interventions in Ghana by Magdalene Aidoo, Stephen Prah, Irene Serwaa Asante, Charles Kwame Sackey, Bright Owusu Asante

“…We utilized three models – binary probit, multivariate probit and generalized Poisson to achieve the objectives of this paper. …”
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URM: A Unified RAM Management Scheme for NAND Flash Storage Devices by A. Xiaochang Li, B. Jichen Chen, C. Zhengjun Zhai, D. Mingchen Feng, E. Xin Ye

“…Our multivariate classification is transformed into multiple binary classifications (logistic regressions). Finally, we extensively evaluate URM using various realistic workloads, and the experimental results show that, compared with three data buffer management schemes, CFLRU, BPLRU, and VBBMS, URM can improve the hit ratio of data buffer and save response time by an average to 32% and 18%, respectively.…”
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An Interpretable Machine Learning Framework for Athlete Motor Profiling Using Multi-Domain Field Assessments: A Proof-of-Concept Study by Bartosz Wilczyński, Maciej Biały, Katarzyna Zorena

“…Early detection of modifiable motor deficits is essential for safe, long-term athletic development, yet most field screens provide only binary risk scores. We therefore designed a practical and interpretable profiling system that classifies youth athletes into one of four functional categories—Functionally Weak, Strength-Deficient, Stability-Deficient, or No Clear Dysfunction—using three common assessments: Functional Movement Screen, hand-held dynamometry, and Y-Balance Test. …”
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Forecasting the Unseen: Enhancing Tsunami Occurrence Predictions with Machine-Learning-Driven Analytics by Snehal Satish, Hari Gonaygunta, Akhila Reddy Yadulla, Deepak Kumar, Mohan Harish Maturi, Karthik Meduri, Elyson De La Cruz, Geeta Sandeep Nadella, Guna Sekhar Sajja

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ELECTRONIC BAND STRUCTURE OF THE ORDERED Zn0.5Cd0.5Se ALLOY CALCULATED BY THE SEMI-EMPIRICAL TIGHT-BINDING METHOD CONSIDERING SECOND-NEAREST NEIGHBOR by Juan Carlos Salcedo-Reyes

“…Usually, semiconductor ternary alloys are studied via a pseudo-binary approach in which the semiconductoris described like a crystalline array were the cation/anion sub-lattice consist of a random distribution of thecationic/anionic atoms. …”
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Supervised machine learning applied in nursing notes for identifying the need of childhood cancer patients for psychosocial support by Akseli Reunamo, Hans Moen, Sanna Salanterä, Sanna Salanterä, Päivi M. Lähteenmäki

“…Patients with the latter label were identified by having an outpatient appointment reservation in a mental health–related care unit at least 1 year after their primary diagnosis.ResultsThe random forest classification model trained on both cancer and diabetes patients performed best for the cancer patient population in three-times repeated nested cross-validation with 0.798 mean area under the receiver operating characteristics curve and was better with 99% probability (credibility interval −0.2840 to −0.0422) than the neural network–based model using only cancer patients in training when comparing all classifiers pairwise by using the Bayesian correlated t-test.ConclusionsUsing machine learning to predict childhood cancer patients needing psychosocial support was possible using nursing notes with a good area under the receiver operating characteristics curve. …”
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Comparison of Various Feature Extractors and Classifiers in Wood Defect Detection by Kenan Kiliç, Kazım Kiliç, İbrahim Alper Doğru, Uğur Özcan

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Pseudo chaotic pulse position modulation in UWB communications by XIANG Xin1, WANG Jie-ling2, ZENG Zhi-bin2, YI Ke-chu2, CHEN Shun-fang3

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Nutritional and prenatal care factors associated with low birth weight among full-term infants in public hospitals of Addis Ababa, Ethiopia by Berhanu Teshome Woldeamanuel, Merga Abdissa Aga

“…To account for hospital-level variability, a multilevel binary logistic regression model was employed, treating hospitals as random effects, to identify maternal, nutritional and prenatal care factors associated with LBW.Results The prevalence of LBW was 12%. …”
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Genome characterization through dichotomic classes: An analysis of the whole chromosome 1 of A. thaliana by Enrico Properzi, Simone Giannerini, Diego Luis Gonzalez, Rodolfo Rosa

“…In this article we show how dichotomic classes, binary variables naturally derived from a new mathematical model of the genetic code, can be used in order to characterize different parts of the genome. …”
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Evaluating Coastal Wetland Mapping Accuracy with High-Resolution Multi-spectral Imagery and LiDAR Remote Sensing Data by M. Anokye, L. Hashemi-Beni

“…The study also addresses binary classification for wetland and non-wetland classification and a multi-classification for different wetland classes, leveraging on the Random Forest algorithm which significantly improved the overall accuracy of wetland mapping. …”
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Effective breastfeeding practices among mothers exclusively breastfeeding infants in Ethiopia by Yonas Abebe, Beriso Dadi

“…In the multivariable binary logistic analysis, postpartum counselling (AOR = 2.61; 95 % CI 1.27, 5.39), breastfeeding experience (AOR = 6.08; 95 % CI 1.34, 27.39), postpartum breastfeeding demonstration (AOR = 4.14; 95 % CI 1.13, 15.2) and attending four or more antenatal care visits (AOR = 4.41; 95 % CI 2.3, 8.35) were factors significantly associated with effective breastfeeding practice. …”
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Recognition Method of Corn and Rice Crop Growth State Based on Computer Image Processing Technology by Li Tian, Chun Wang, Hailiang Li, Haitian Sun

“…The time to extract features by the proposed method is 1.4 seconds, whereas comparative methods such as random forest (RF) take 3.8 s and other traditional techniques take 4.9 s. …”
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A cross-national analysis of childhood predictors of daily smoking in adulthood by Sung Joon Jang, Pedro A. de la Rosa, R. Noah Padgett, Matt Bradshaw, Tyler J. VanderWeele, Byron R. Johnson

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Central obesity is an independent risk factor of poor glycaemic control at Dr George Mukhari Academic Hospital by Tsakani Stanford Mashele, Motetelo Alfred Mogale, Olakunle Adewunmi Towobola, Mmampenani Florence Moshesh

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Shape Penalized Decision Forests for Imbalanced Data Classification by Rahul Goswami, Aindrila Garai, Payel Sadhukhan, Palash Ghosh, Tanujit Chakraborty

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A Mathematical Approach for Computing the Linear Equivalence of a Periodic Key-Stream Sequence Using Fourier Transform by Baghdad Science Journal

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