Synthesis and Optical Properties of Triphenylene-Based Donor-Donor and Donor-Acceptor Conjugated Polymers: A Comparative Study by Yong Li, Dung D. Nguyen, Kuldeep Shetye, Zhonghua Peng

“…P2, on the other hand, adopts a random coil conformation in hexane but possibly the helical folding conformation in other good solvents. …”
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Experimental demonstration of 8190-km long-haul semiconductor-laser chaos synchronization induced by digital optical communication signal by Anbang Wang, Junli Wang, Lin Jiang, Longsheng Wang, Yuncai Wang, Lianshan Yan, Yuwen Qin

“…Here, we propose an ultra-long-distance laser synchronization scheme by utilizing random digital optical communication signal as the common drive signal. …”
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Fortifying IoT Infrastructure Using Machine Learning for DDoS Attack within Distributed Computing-based Routing in Networks by Sharaf Aldeen Abdulkadhum Abbas, Abdullahi Abdu Ibrahim

“…Our results indicate that Random Forest outperforms the other models, achieving an accuracy of 99.2%, a false positive rate of 0.8%, and an AUC-ROC of 0.997. …”
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Exploration of transfer learning techniques for the prediction of PM10 by Michael Poelzl, Roman Kern, Simonas Kecorius, Mario Lovrić

“…Common ML models such as Random Forests, Multilayer Perceptrons, Long-Short-Term Memory, and Convolutional Neural Networks are explored to predict particulate matter in both cities. …”
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Cosmic Reionization on Computers: The Evolution of the Ionizing Background and Mean Free Path by Jiawen Fan, Huanqing Chen, Camille Avestruz, Affan Khadir

“…We also compare the MFPs measured in random sightlines. We find that at z  ≈ 5, the MFPs measured in sightlines that start from massive halos are systematically smaller by ≈10% compared with the MFPs measured in random sightlines. …”
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Scoping review of the applications of peptide microarrays on the fight against human infections. by Arthur Vengesai, Maritha Kasambala, Hamlet Mutandadzi, Tariro L Mduluza-Jokonya, Takafira Mduluza, Thajasvarie Naicker

“…Immunosignatures identified by random peptide microarrays were found to be applied in the diagnosis of infections and interrogation of vaccine responses. …”
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Early childhood caries risk prediction using machine learning approaches in Bangladesh by Fardous Hasan, Maha El Tantawi, Farzana Haque, Moréniké Oluwátóyìn Foláyan, Jorma I. Virtanen

“…Recursive Feature Elimination (RFE) and Random Forest (RF) was applied to identify the optimal subsets of features. …”
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Modified Heisenberg Commutation Relations, Free Schrödinger Equations, Tunnel Effect and Its Connections with the Black–Scholes Equation by Mauricio Contreras González, Roberto Ortiz Herrera, José González Suárez

“…Further, because this random geometry is nothing more than gravity at the microscopic level, the Black–Scholes equation becomes a possible simple model for understanding quantum gravity.…”
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IDENTIFIKASI FAKTOR PREFERENSI POSISI RUANG TIDUR ORANG TUA DAN ANAK DI RUMAH TINGGAL by Asta Juliarman Hatta, Hanson E Kusuma, Dara Fitriani

“…Penelitian menggunakan metode kualitatif dengan pendekatan grounded theory yang diperoleh melalui hasil kuesioner daring yang dibagikan secara non-random sampling. Hasil penelitian mengungkapkan terdapat sembilan faktor preferensi responden dalam memilih tiga posisi ruang tidur orang tua dan anak, yaitu aksesibilitas, keinginan, privasi, kenyamanan, kedekatan, interaksi, keamanan, pengawasan, dan tradisi. …”
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Brazilian Dialysis Survey 2023 by Fabiana B. Nerbass, Helbert do Nascimento Lima, Jorge P. Strogoff-de-Matos, Bruno Zawadzki, José A. Moura-Neto, Jocemir Ronaldo Lugon, Ricardo Sesso

“…For estimates of prevalence, incidence, and source of payment for dialysis, data were obtained from a random sample of dialysis centers. Results: A total of 37.5% (n = 332) of the centers voluntarily responded to the online questionnaire, and 124 were randomly selected for specific estimates of prevalence and incidence rates. …”
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Hybridize Machine Learning Methods and Optimization Techniques to Analyze and Repair Welding Defects via Digital Twin of Jidoka Simulator by Ahmed M. Abed, Tamer S. Gaafar

“…We are creating a &#x201C;digital Jidoka twin system&#x201D; (SQ(R/I/E)) with a controller segment programmed with machine learning (ML) algorithms that use the MFEM&#x2019;s huge and uneven data to sort defects and their causes. Hybridising the Random-Forest algorithm with Dingo optimisation and called Regulated Random Forest (RRF) to precisely identify defect clusters and then predict the welding defect growth rate (<inline-formula> <tex-math notation="LaTeX">$\boldsymbol {{R}_{s}}$ </tex-math></inline-formula>) using the Cat-boost optimiser, which is enhanced by a beetle search mechanism called CatBAS. …”
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Physician Perceptions of the Safety and Efficacy of GLP-1 Receptor Agonists: Underestimation of Cardiovascular Risk Reduction and Discrepancies with Clinical Evidence by Srikanth Krishnan, Pratyaksh K. Srivastava, Jayram Attaluri, Rebecca Nayeri, Dhananjay Chatterjee, Jay Patel, Ali Nsair, Matthew Budoff, Arash Nayeri

“…Cardiovascular benefits were perceived by 48.4% of physicians in diabetic patients, consistent with random guessing, and by only 39.3% in nondiabetic patients, significantly below random guessing expectations. …”
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Noninvasive diagnosis of significant liver fibrosis in patients with chronic hepatitis B using nomogram and machine learning models by Chuan Jiang, Zhenyu Xu, Jinqing Liu, Ronghua Li, Keyu Chen, Wenting Peng, Yueming Xiao, Da Cheng, Lei Fu, Shifang Peng

“…A cohort of 259 CHB patients were selected as research subjects. Through random grouping, 182 cases were included in the training set and 77 cases in the validation set. …”
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ANALYSIS OF HIGH RISK FACTORS FOR NON-COMMUNICABLE DISEASE, STROKE IN THE SIDOARJO DISTRICT HEALTH SERVICE by Luluk Widarti, Muhammad Afif Hilmi Masyfahani, Dony Sulystiono, Kusmini Suprihatin, Hotmaida Siagian, Siti Maemonah

“…Conclusions: Based on the research results, the highest risk factors for stroke are cholesterol, random blood sugar, hypertension, and BMI which indicates obesity. …”
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A multi-scale rotated ship targets detection network for remote sensing images in complex scenarios by Siyu Li, Fei Yan, Yunqing Liu, Yuzhuo Shen, Lan Liu, Ke Wang

“…The limited feature information of small-scale targets and their random orientation angles often result in missed and false detections. …”
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Dynamic Analysis of Vehicle Track Coupling Based on Double Beam Track Model by Yayun Qi, Huanyun Dai, Jianjin Yang, Kun Xu

“…Wheel rail vertical force and response of vehicle are calculated by using the model under random irregularity and single harmonic excitation; at the same time, wheel rail force and vertical acceleration response of 3-order, 10-order, and 19-order wheel polygon were calculated. …”
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Multi-Disaster Hazard Analysis, The Case of Elazığ Province by Fethi Ahmet Canpolat

“…The desertification map was obtained from the Ministry of Environment, Urban Planning, and Climate Change. The Random Forest model was used for other disaster hazard maps. …”
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Simulating a travel-related origin of Candida auris in New York–New Jersey by Rita R. Verma, Edward Kiegle, Alexander C. Keyel, Sudha Chaturvedi, Vishnu Chaturvedi

“…We hypothesized C. auris’ introduction to NY-NJ was not a random event but related to travel patterns between South Asia and NY-NJ. …”
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Physics Informed Neural Networks for Modeling Large-Scale Wind Driven Ocean Circulation by Boohyun An, Mohammad Z. Shanti, Chan Yeob Yeun, Ernesto Damiani, Sungmun Lee, Tae-Yeon Kim

“…The effects of different training point distributions, such as uniform, uniform-refined, random, and random-refined, were also examined. The results show that refining the distribution of training points near the western boundary layer can achieve similar accuracy and training performance even with fewer points. …”
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Binding Investigation of Some Important Metal Ions Copper (I), Nickel (II), and Aluminium (III) with Bovine Serum Albumin Using Valid Spectroscopic Techniques by Hassan A. Alhazmi, Md Shamsher Alam, Mohammed Albratty, Asim Najmi, Ahmed A. Abdulhaq, Rym Hassani, Waquar Ahsan, Abdulrahman N. Qramish

“…The change in the BSA secondary structure components such as β-sheet, β-antiparallel, α-helix, β-turn, and random coil were analyzed using second derivative resolution enhancement. …”
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