A multiple time-scale computational model of a tumor and its micro environment by Christopher DuBois, Jesse Farnham, Eric Aaron, Ami Radunskaya

“…The diffusion of these nutrientsis modeled using a novel variation of random-walk techniques.Furthermore, we detail the effects of three boundary updateruleson simulations, describing their effects on computationalefficiency and biological realism. …”
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Synthetic Peptides as Potential Antigens for Cutaneous Leishmaniosis Diagnosis by Juliana Seger Link, Silvana Maria Alban, Carlos Ricardo Soccol, Gilberto Vinicius Melo Pereira, Vanete Thomaz Soccol

“…In order to reach the goal, we used random peptide phage display libraries screened using antibodies from Leishmania braziliensis patients. …”
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Segmenting tourism in rural area by emphasizing on motivational factors: Case study of Kolan river catchment area by Nasser Bayat, Seyed Ali Badri

“…By the method of Simple random sampling we collected a total of 200 questionnaires of tourists in the study area. …”
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Evaluating the M6 learning model and realistic mathematics education (RME) approach in enhancing critical thinking skills in mathematics: A focus on students’ logical-mathematical... by Ardi Dwi Susandi, Sudirman Sudirman, Binti Khoiriyah

“…Method: A quasi-experimental design was employed with a sample of 318 seventh-grade students from State Middle Schools in Cirebon Regency in the 2023/2024 academic year. Stratified cluster random sampling produced three groups: 107 students in the first experimental group, 105 in the second, and 106 in the control group. …”
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LASSO-mCGA: Machine Learning and Modified Compact Genetic Algorithm-Based Biomarker Selection for Breast Cancer Subtype Classification by Nimisha Ghosh, Sankar Kumar Mridha, Rourab Paul

“…To identify such biomarkers, initially LASSO in association with four machine learning models such as Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbours (KNN) and Naive Bayes (NB) are applied on the dataset to find the initial reduced set of genes as well as the best learning model based on classification accuracy; SVM in this case. …”
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RELASI KEKUASAAN DAN PENGETAHUAN PADA ARSITEKTUR GEREJA CANDI GANJURAN by Prisca Bicawasti Budi Sutanty

“…Metode penelitian menggunakan kualitatif deskriptif dengan random probability sampling. Penelitian ini mengungkapkan adanya relasi pengetahuan dan kekuasaan yang dimiliki oleh arsitek yang akan mempengaruhi arsitektur Gereja Candi Ganjuran dan menjelaskan diskursus pada pengguna. …”
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Frequency, Prevalence, Interaction, and Gender Differences of Six Psychosocial Factors in Patients Presenting to a Psychiatric Emergency Service by James C. Patterson II, Ovais Khalid, Sarah E. Wakefield, Justin K. Liegmann, Saima Maqsood, Rajeev Srivastava, Elizabeth Allen

“… # METHODS We completed a retrospective chart review of 160 patients selected at random who utilized the PES during 2009-2010. We looked for historical presence of a broken family, abuse or neglect, substance abuse, legal problems, violence, or incomplete education. …”
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Efficacy of yoga for chronic back pain: A comprehensive meta-analysis of clinical trials by M. D. Sangeetha, B. N. Sharath, P. Seema, P. K. Sreenath Menon, M. Shashi Kumar, M. Sathiabalan, R. Nandhini

“…A total of six randomized controlled trials met the inclusion criteria and were included in the meta-analysis. …”
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An efficient smart phone application for wheat crop diseases detection using advanced machine learning. by Awais Amir Niaz, Rehan Ashraf, Toqeer Mahmood, C M Nadeem Faisal, Muhammad Mobeen Abid

“…The application utilizes sophisticated machine learning techniques, including Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and AdaBoost, combined with feature extraction methods such as Count Vectorization (CV) and Term Frequency-Inverse Document Frequency (TF-IDF). …”
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Characterization of the C-terminal tail of the Arc protein. by Melissa Boldridge, Jody Shimabukuro, Keith Nakamatsu, Christian Won, Chad Jansen, Helen Turner, Lei Wang

“…Chemical shift analysis based on solution NMR spectra confirmed that the C-terminal tail has a random coil (disordered) structure, and the tail starts from the residue D357. …”
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Classification and Regression Trees analysis identifies patients at high risk for kidney function decline following hospitalization. by Weihao Wang, Wei Zhu, Janos Hajagos, Laura Fochtmann, Farrukh M Koraishy

“…We conducted a retrospective cohort study on patients hospitalized at Stony Brook University Hospital in 2020 who were followed for 36 months post discharge. Random Forest (RF) identified the top ten features associated with fast eGFR decline. …”
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A dataset of gridded precipitation intensity-duration-frequency curves in Qinghai-Tibet Plateau by Zhihui Ren, Yan-Fang Sang, Peng Cui, Fei Chen, Deliang Chen

“…The generalized extreme value distribution is chosen to fit the annual maximum precipitation samples at 203 weather stations, based on which the at-site IDF curves are estimated; then, principal component analysis is done to identify the southeast-northwest spatial pattern of at-site IDF curves, and its first principal component gives a 96% explained variance; finally, spatial interpolation is done to estimate gridded IDF curves by using the random forest model with geographical and climatic variables as predictors. …”
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Utilization of Institutional Maternal Delivery and Associated Factors among Rural Women: A Case Study of High Priority District of Himachal Pradesh by Mandeep Kaur

“…Data collection was done by multistage random sampling through an interview method using a structured questionnaire. …”
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Risk assessment of water inrush from coal floor based on enhanced samples with class distribution by Shiwei Liu, Jiaxin Zhao, Hao Yu, Jiaqi Chen

“…Abstract In the risk assessment of water inrush from coal floors, the amount of measured data obtained through on-site testing is small and random, which limits the prediction accuracy and generalizability of a model based on measured data. …”
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Optimizing Subchannel Assignment and Power Allocation for Network Slicing in High-Density NOMA Networks: A Q-Learning Approach by Suhare Solaiman

“…Extensive simulations demonstrate that the proposed algorithm is flexible and scalable in dynamic scenarios, outperforming random and exhaustive search algorithms in high-density NOMA networks in terms of sum rates. …”
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Wheat Futures Prices Prediction in China: A Hybrid Approach by Yunpeng Sun, Jin Guo, Shan Shan, Yousaf Ali Khan

“…Furthermore, the statistical significance of our point estimation was further tested through the Mariano and Diebold test. Considering random walk forecast as the bench mark, we used a number of economic indicators, trader’s expectation towards futures prices, and lagged value of futures price of wheat in order to forecast the evaluation of wheat futures price. …”
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Ovine Eimeria infection, OPG and determinants in and around Gondar town, Ethiopia by Senait Belay, Desie Sheferaw

“…A total of 422 sheep were selected by systematic random sampling technique, and from these animals, faecal samples were collected and examined for Eimeria oocysts. …”
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Identifikasi Permasalahan Mahasiswa Evaluasi Semester Program Akademik dan Vokasi di Institut Teknologi Sepuluh Nopember Surabaya by Yuli Purwanto, Setiawan Setiawan, Sunawi Sunawi, Fatkhul Iman Nurdjati, Siti Machmudah

“…The population consists of 422 active students, with a sample of 252 students selected through Proportioned Stratified Random Sampling. Data was collected via questionnaires and interviews. …”
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Forecasting Travel Speed in the Rainfall Days to Develop Suitable Variable Speed Limits Control Strategy for Less Driving Risk by Ping Wang, Yajie Zhang, Saisai Wang, Li Li, Xiaohui Li

“…However, it is hard to develop suitable VSL aligning with travel speed of mainstream that it affected by the traffic flow, rainfall intensity, individual travel speed, peak hours, working days, random events, and so on. In this paper, the average travel speed and traffic flow of each road section are calculated from the toll collection data of Xi’an Ring Road from May to July in 2018 in Shaanxi Province, China. …”
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External low energy electromagnetic fields affect heart dynamics: surrogate for system synchronization, chaos control and cancer patient’s health by Frederico P. Costa, Jack Tuszynski, Antonio F. Iemma, Willian A. Trevizan, Bertram Wiedenmann, Eckehard Schöll

“…Cancer reduces physiological variability, implying a systemic disconnection that desynchronizes bodily systems and their inherent random processes. The dynamics of heart rate, in this context, could reflect global physiological network instability in the sense of entrainment. …”
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