RL-ADN: A high-performance Deep Reinforcement Learning environment for optimal Energy Storage Systems dispatch in active distribution networks by Shengren Hou, Shuyi Gao, Weijie Xia, Edgar Mauricio Salazar Duque, Peter Palensky, Pedro P. Vergara

“…This paper introduces RL-ADN, an innovative open-source library specifically designed for solving the optimal ESSs dispatch in active distribution networks. …”
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Análisis del patrón gol en la competición del fútbol femenino: primera y segunda división by Norberto Pascual Verdú, Pascual Villena Rodas, José Antonio Mártinez Carbonell

“…Para ello, se elaboró un panel de codificación en el software de LongoMatch Open Source, que permitió registrar las acciones ocurridas según 6 variables: momento, superficie de golpeo, tipo de jugada, zona de juego, posición y titularidad o suplencia de las jugadoras. …”
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Development and validation of the Michigan Chronic Disease Simulation Model (MICROSIM). by James F Burke, Luciana L Copeland, Jeremy B Sussman, Rodney A Hayward, Alden L Gross, Emily M Briceño, Rachael Whitney, Bruno J Giordani, Mitchell S V Elkind, Jennifer J Manly, Rebecca F Gottesman, Darrell J Gaskin, Stephen Sidney, Kristine Yaffe, Ralph L Sacco, Susan R Heckbert, Timothy M Hughes, Andrzej T Galecki, Deborah A Levine

“…MICROSIM is an extensible, open-source framework designed to estimate the population-level impact of different BP management strategies and reproduces US population-level estimates of BP and other vascular risk factors levels, their change over time, and incident all-cause dementia, stroke, myocardial infarction, and mortality.…”
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Enhanced STag Marker System: Materials and Methods for Flexible Robot Localisation by James R. Heselden, Dimitris Paparas, Robert L. Stevenson, Gautham P. Das

“…As a part of this contribution, the associated software for marker set generation/detection, physical marker fabrication, and end-to-end localisation has been released as an open source distribution.…”
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Three-dimensional numerical study of a local scour downstream of a submerged sluice gate using two hydro-morphodynamic models, SedFoam and FLOW-3D by Ghzayel, Alaa, Beaudoin, Anthony

“…SedFoam is a multiphase flow model based on the open-source tool-box OpenFOAM and uses a coupling method between the fluid and particles phases in the RANS equations through the dense granular rheology, while FLOW-3D is an CFD software that uses a sediment scour model to perform sediment transport through bedload and suspended load transport equations without direct coupling with the fluid phase. …”
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Tracing the Winds: A Uniform Interpretation of Helium Escape in Exoplanets from Archival Spectroscopic Observations by Patrick McCreery, Leonardo A. Dos Santos, Néstor Espinoza, Romain Allart, James Kirk

“…In this study, we employ the open-source atmospheric escape model p-winds to systematically analyze all publicly available helium triplet spectroscopic detections related to exoplanetary atmospheric escape. …”
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Deep Ensemble Learning for Human Action Recognition in Still Images by Xiangchun Yu, Zhe Zhang, Lei Wu, Wei Pang, Hechang Chen, Zhezhou Yu, Bin Li

“…We conduct experiments in Li’s action dataset, uncropped and 1.5x cropped Willow action datasets, and the results have validated the effectiveness and robustness of our proposed models in terms of mitigating overfitting issues in small datasets. Finally, we open source our code for the model in GitHub (https://github.com/yxchspring/deep_ensemble_learning) in order to share our model with the community.…”
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DockCADD: A streamlined in silico pipeline for the identification of potent ribosomal S6 Kinase 2 (RSK2) inhibitors by El Mehdi Karim, Meriem Khedraoui, Abdelkbir Errougui, Yasir S. Raouf, Abdelouahid Samadi, Samir Chtita

“…Herein, we developed an open-source computational pipeline, identified as DockCADD (available at https://github.com/mehdikariim/DockCADD), which enables the identification of potent RSK2 inhibitors by automated virtual screening, ADME-Tox profiling, and molecular dynamics (MD) simulations. …”
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Rating pome fruit quality traits using deep learning and image processing by Nhan H. Nguyen, Joseph Michaud, Rene Mogollon, Huiting Zhang, Heidi Hargarten, Rachel Leisso, Carolina A. Torres, Loren Honaas, Stephen Ficklin

“…Integrative analyses enhanced by Granny's improved resolution and reduced bias, such as linking fruit outcomes to global scale ‐omics data, environmental changes, and other quantitative fruit quality metrics like soluble solids content and flesh firmness, will further enrich our understanding of fruit quality dynamics. Lastly, Granny is open‐source and freely available.…”
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A case study in statistical software development for advanced evidence synthesis: the combined value of analysts and research software engineers by Naomi Bradbury, Tom Morris, Clareece Nevill, Janion Nevill, Ryan Field, Suzanne Freeman, Nicola Cooper, Alex Sutton

“…Aim Here, we present our experience of developing production grade web-apps from the point-of-view of individuals trained primarily as statisticians rather than software developers in the hopes of encouraging and inspiring other groups to develop valuable open-source statistical software whilst also learning from our experiences. …”
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Infrared dim tiny-sized target detection based on feature fusion by Peng Zhang, Yaman Jing, Guodong Liu, Ziyang Chen, Xiaoyan Wu, Osami Sasaki, Jixiong Pu

“…The comparison of the proposed network with other algorithms are performed on open-source dataset and experimentally generated infrared images. …”
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An Ontology for Digital Medicine Outcomes: Development of the Digital Medicine Outcomes Value Set (DOVeS) by Benjamin Rosner, Matthew Horridge, Guillen Austria, Tiffany Lee, Andrew Auerbach

“…MethodsFrom a starting point of a 4-generation–deep hierarchical taxonomy developed by ADviCE, we developed DOVeS using the Web Ontology Language through the open-source ontology editor Protégé, and data from 185 vendors who had submitted structured product information to ADviCE. …”
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Development and biomechanical evaluation of a 3D printed analogue of the human lumbar spine by Siril Teja Dukkipati, Mark Driscoll

“…The vertebrae and the IVDs were derived from an open-source 3D MRI anatomography database, while the ligaments were modeled based on literature incorporating mounting points on the spinous and transverse processes. …”
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Pan-Cancer Analysis of Disulfidptosis-Related Genes Affecting Prognosis and Tumor Microenvironment by Jingyang SUN, Rongxuan JIANG, Liren HOU, Huanhuan DONG, Yihan LIN, Niuniu DONG, Guangjian ZHANG, Yanpeng ZHANG

“…MethodsPan-cancer RNA-seq data, mutation profiles, clinical information, TMB, MSI, stemness scores, and tumor and immune microenvironment data contained in TCGA and various open-source online databases, and multi-group R-language algorithms were used for comprehensive analysis. …”
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SEAHORS: Spatial Exploration of ArcHaeological Objects in R Shiny by Royer, Aurélien, Discamps, Emmanuel, Plutniak, Sébastien, Thomas, Marc

“…This paper presents SEAHORS, an R shiny application available as an R package, dedicated to the intra-site spatial analysis of piece-plotted archaeological remains. This open-source script generates 2D and 3D scatter and density plots for archaeological objects located with cartesian coordinates. …”
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Targeted generative data augmentation for automatic metastases detection from free-text radiology reports by Maede Ashofteh Barabadi, Xiaodan Zhu, Wai Yip Chan, Amber L. Simpson, Richard K. G. Do

“…Specifically, we prompt Llama3, an open-source instruction-tuned large language model, to generate synthetic training data to expand our limited labeled data and adapt BERT, a small pretrained language model, to the task. …”
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Large language models generating synthetic clinical datasets: a feasibility and comparative analysis with real-world perioperative data by Austin A. Barr, Joshua Quan, Eddie Guo, Emre Sezgin, Emre Sezgin

“…Recent advances in large language models (LLMs) provide an opportunity to generate synthetic data with reduced reliance on domain expertise, computational resources, and pre-training.ObjectiveThis study aims to assess the feasibility of generating realistic tabular clinical data with OpenAI’s GPT-4o using zero-shot prompting, and evaluate the fidelity of LLM-generated data by comparing its statistical properties to the Vital Signs DataBase (VitalDB), a real-world open-source perioperative dataset.MethodsIn Phase 1, GPT-4o was prompted to generate a dataset with qualitative descriptions of 13 clinical parameters. …”
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Advancements, Trends and Future Prospects of Lower Limb Prosthesis by Muhammad Asif, Mohsin Islam Tiwana, Umar Shahbaz Khan, Waqar Shahid Qureshi, Javaid Iqbal, Nasir Rashid, Noman Naseer

“…We have also developed an open-source database “FAKH-50” for patents to emphasize the design trends and advancements in lower limb prostheses from 1970 to 2020. …”
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A physically-based formulation for texture evolution during dynamic recrystallization. A case study of ice by Chauve, Thomas, Montagnat, Maurine, Dansereau, Véronique, Saramito, Pierre, Fourteau, Kévin, Tommasi, Andréa

“…This set of equations, which is the core of the R$^{3}$iCe model is solved by a finite-element method with a semi-implicit scheme coded using the Rheolef library. The resulting open-source software R$^{3}$iCe is validated by comparison with laboratory creep data for ice polycrystals under uniaxial compression, simple shear, and uniaxial tension. …”
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msiFlow: automated workflows for reproducible and scalable multimodal mass spectrometry imaging and microscopy data analysis by Philippa Spangenberg, Sebastian Bessler, Lars Widera, Jenny Bottek, Mathis Richter, Stephanie Thiebes, Devon Siemes, Sascha D. Krauß, Lukasz G. Migas, Siva Swapna Kasarla, Prasad Phapale, Jens Kleesiek, Dagmar Führer, Lars C. Moeller, Heike Heuer, Raf Van de Plas, Matthias Gunzer, Oliver Soehnlein, Jens Soltwisch, Olga Shevchuk, Klaus Dreisewerd, Daniel R. Engel

“…Here, we present msiFlow, an accessible open-source, platform-independent and vendor-neutral software for end-to-end, high-throughput, transparent and reproducible analysis of multimodal imaging data. msiFlow integrates all necessary steps from raw data import to analytical visualisation along with state-of-the-art and self-developed algorithms into automated workflows. …”
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