Mathematical Modelling of Acetaminophen Release in HPC/PAAm Hydrogel: Synthesis and Application by Abigail M. Díaz-Guerrero, Claudia A. Castillo-Miranda, Carlos F. Castro-Guerrero, Hernán Peraza-Vázquez, Ana B. Morales-Cepeda, Adrián F. Peña-Delgado

“…In order to describe the release of acetaminophen in HPC/PAAm gel, a genetic programming algorithm was used to accomplish Multigene Symbolic Regression (MSR). …”
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Astronomaly Protege: Discovery through Human-machine Collaboration by Michelle Lochner, Lawrence Rudnick

“…We train PROTEGE on images from the MeerKAT Galaxy Cluster Legacy Survey, leveraging the self-supervised deep learning algorithm Bootstrap Your Own Latent to find a low-dimensional representation of the radio galaxy cutouts. …”
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Modeling Canopy Height of Forest–Savanna Mosaics in Togo Using ICESat-2 and GEDI Spaceborne LiDAR and Multisource Satellite Data by Arifou Kombate, Guy Armel Fotso Kamga, Kalifa Goïta

“…We tested four methods: Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost) and Deep Neural Network (DNN). The RF algorithm obtained the best predictions using 98% relative height (RH98). …”
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Enhanced dry SO₂ capture estimation using Python-driven computational frameworks with hyperparameter tuning and data augmentation by Robert Makomere, Hilary Rutto, Alfayo Alugongo, Lawrence Koech, Evans Suter, Itumeleng Kohitlhetse

“…In addition, it was the least convoluted algorithm according to Akaike information criterion and Bayesian information criterion assessments. …”
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Trust Region Policy Learning for Adaptive Drug Infusion with Communication Networks in Hypertensive Patients by Mai The Vu, Seong Han Kim, Ha Le Nhu Ngoc Thanh, Majid Roohi, Tuan Hai Nguyen

“…Secondly, a model-free deep reinforcement learning (MF-DRL) algorithm is integrated into the NBC to adjust dynamically the coefficients of the controller. …”
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Aircraft hybrid-electric environment for analysis and design (AHEAD) applied on a fixed-wing drone by Manuel A. Rendón, Patrícia H. Hallak, Yipsy Roque Benito, Marcelo Assato, Camila de Oliveira Cunha, Daniel Miranda Esther, Rafael Grande Pancini Delmonte, Denys Pinto Gonçalves

“…The aircraft is modeled in SUAVE and OpenVSP [1], propeller in QBlade [2], ICE in Diesel-RK [3], electrical components in MATLAB®/SIMULINK®, and the method algorithm is programmed in Python. By employing this method, it is possible to analyze the viability of substituting actual propulsion by hybrid.…”
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Discovering Large-scale Structure at 2 < z < 5 in the C3VO Survey by Denise Hung, Brian C. Lemaux, Olga Cucciati, Ben Forrest, Ekta A. Shah, Roy R. Gal, Finn Giddings, Derek Sikorski, Emmet Golden-Marx, Lori M. Lubin, Nimish Hathi, Giovanni Zamorani, Lu Shen, Sandro Bardelli, Letizia P. Cassarà, Gabriella De Lucia, Fabio Fontanot, Bianca Garilli, Lucia Guaita, Michaela Monika Hirschmann, Kyoung-Soo Lee, Andrew B. Newman, Vandana Ramakrishnan, Daniela Vergani, Lizhi Xie, Elena Zucca

“…We also apply the same technique to mock observations of simulated galaxies with properties derived from the GAlaxy Evolution and Assembly semianalytic model in order to judge the effectiveness of our search algorithm as a function of redshift, total mass, and fraction of spectroscopic redshifts. …”
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A prediction model of liver fat fraction and presence of non-alcoholic fatty liver disease (NAFLD) among patients with overweight or obesity by Jie Chen, Jiang Yue, Jingjing Fu, Shengyun He, Qianjing Liu, Minglan Yang, Wang Zhang, Hua Xu, Qing Lu, Jing Ma

“…Through univariate analysis, we have identified potential factors, and the definitive elements in the prediction model were selected utilizing the forward stepwise regression algorithm. The Shang Hai Steatosis Index (SHSI) incorporates alanine aminotransferase (ALT), aspartate aminotransferase (AST), fasting insulin, and 1-h postload glycaemic levels, thereby furnishing the capability to predict NAFLD with an area under the receiver operator characteristic (AUROC) of 0.87. …”
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Diagnostics and treatment of peptic ulcer: clinical guidelines of the Russian gastroenterological Association by V. T. Ivashkin, A. A. Sheptulin, I. V. Mayev, Ye. K. Baranskaya, A. S. Trukhmanov, T. L. Lapina, S. G. Burkov, A. V. Kalinin, A. V. Tkachev

“…Strict conformance of diagnostic algorithm for this category of patients as well as the eradication therapy protocol allows to decrease considerably the risk of recurrence of PUD and its complications.…”
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Multi-objective optimization of custom implant abutment design for enhanced bone remodeling in single-crown implants using 3D finite element analysis by Pongsakorn Poovarodom, Chaiy Rungsiyakull, Jarupol Suriyawanakul, Qing Li, Keiichi Sasaki, Nobuhiro Yoda, Pimduen Rungsiyakull

“…A 12-month bone remodeling algorithm subroutine in finite element analysis to optimize three parameters: implant placement depth, abutment taper degree, and gingival height of the titanium base abutment. …”
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A Semi-Automated Usability Evaluation Framework for Interactive Image Segmentation Systems by Mario Amrehn, Stefan Steidl, Reinier Kortekaas, Maddalena Strumia, Markus Weingarten, Markus Kowarschik, Andreas Maier

“…It is demonstrated that even when the underlying segmentation algorithm is the same throughout interactive prototypes, their user experience may vary substantially. …”
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Location Information-Based Routing Protocol for Energy Harvesting Cognitive Radio Wireless Sensor Network by Mohamad-Rida Mortada, Abbass Nasser, Alaaeddine Ramadan, Koffi-Clement Yao, Ali Mansour

“…LIBRO has been recently proposed as an efficient routing algorithm for traditional WSN networks. In this paper, we extend its application to EH-CWSNs, in which the WSN nodes act as Secondary Users (SUs). …”
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Adaptive Resource Allocation and Mode Switching for D2D Networks With Imperfect CSI in AGV-Based Factory Automation by Safiu A. Gbadamosi, Gerhard P. Hancke, Adnan M. Abu-Mahfouz

“…The ARAMS scheme integrates mode switching (MS), channel-quality factor (CQF), and power control (PC) within a bi-phasic resource-sharing (RS) algorithm to lower the computational complexity. In the initial phase, the operational mode for each D2D user (DU) per cell is adaptively selected based on the channel gain ratio (CGR). …”
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Ensemble Deep Learning Object Detection Fusion for Cell Tracking, Mitosis, and Lineage by Imad Eddine Toubal, Noor Al-Shakarji, D. D. W. Cornelison, Kannappan Palaniappan

“…EDNet detections are used in our M2Track multiobject tracking algorithm for tracking cells, detecting cell mitosis (cell division) events, and cell lineage graphs. …”
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Knowledge-driven semantic converting method of multimodal models toward a geospatial perspective by Jianbo Lai, Jun Zhu, Pei Dang, Jianlin Wu, Yukun Guo, Xinyu Yang, Na Li

“…Subsequently, a structural matching template based on knowledge reuse was established, and a knowledge-guided algorithm for multimodal model transformation was designed. …”
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Stability Control of the Agricultural Tractor-Trailer System in Saline Alkali Land: A Collaborative Trajectory Planning Approach by Guannan Lei, Shilong Zhou, Penghui Zhang, Fei Xie, Zihang Gao, Li Shuang, Yanyun Xue, Enjie Fan, Zhenbo Xin

“…Based on the intrinsic property of the lateral deviation of the TTS, a collaborative trajectory prediction algorithm that satisfies the time domain and system constraints is proposed. …”
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Comparison between Hyperspectral Imaging and Chemical Analysis of Polyphenol Oxidase Activity on Fresh-Cut Apple Slices by Luna Shrestha, Boris Kulig, Roberto Moscetti, Riccardo Massantini, Elke Pawelzik, Oliver Hensel, Barbara Sturm

“…Golden Delicious and Elstar) were used to build a robust detection algorithm, which is independent of cultivars and applied treatments. …”
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Application of Machine Learning to Background Rejection in Very-high-energy Gamma-Ray Observation by Jie Li, Hongkui Lv, Yang Liu, Jiajun Huang, Yu Wang, Wenbin Lin

“…Machine learning (ML) models, including logistic regression, support vector machines, decision trees, random forests, XGBoost, CatBoost, and deep neural networks (DNN) were constructed and trained using data sets of four energy bands ranging from 10 ^12 to 10 ^16 eV, and finally fused using the stacking ensemble algorithm. To comprehensively assess the classification ability of each model, the accuracy, F1 score, precision, recall, and area under the curve value of the receiver operating characteristic curve were used. …”
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Fine-tuning a local LLaMA-3 large language model for automated privacy-preserving physician letter generation in radiation oncology by Yihao Hou, Yihao Hou, Christoph Bert, Christoph Bert, Christoph Bert, Ahmed Gomaa, Ahmed Gomaa, Ahmed Gomaa, Godehard Lahmer, Godehard Lahmer, Godehard Lahmer, Daniel Höfler, Daniel Höfler, Daniel Höfler, Thomas Weissmann, Thomas Weissmann, Thomas Weissmann, Raphaela Voigt, Raphaela Voigt, Raphaela Voigt, Philipp Schubert, Philipp Schubert, Philipp Schubert, Charlotte Schmitter, Charlotte Schmitter, Charlotte Schmitter, Alina Depardon, Alina Depardon, Alina Depardon, Sabine Semrau, Sabine Semrau, Sabine Semrau, Andreas Maier, Rainer Fietkau, Rainer Fietkau, Rainer Fietkau, Yixing Huang, Yixing Huang, Florian Putz, Florian Putz, Florian Putz

“…IntroductionGenerating physician letters is a time-consuming task in daily clinical practice.MethodsThis study investigates local fine-tuning of large language models (LLMs), specifically LLaMA models, for physician letter generation in a privacy-preserving manner within the field of radiation oncology.ResultsOur findings demonstrate that base LLaMA models, without fine-tuning, are inadequate for effectively generating physician letters. The QLoRA algorithm provides an efficient method for local intra-institutional fine-tuning of LLMs with limited computational resources (i.e., a single 48 GB GPU workstation within the hospital). …”
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Heat shock protein-related diagnostic signature and molecular subtypes in ankylosing spondylitis: new pathogenesis insights by Geqiang Wang, Yongji Li, Jiaxing Liu, Qian Zhang, Weixin Cai, Xiaodong Li

“…To assess the immunological landscape, we employed the xCell algorithm. Through logistic regression analysis, the four core HRGs (CCT2, HSPA6, DNAJB14, and DNAJC5) were confirmed as potential biomarkers for AS. …”
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