Multifunctional Lead-Free Halide Perovskite-Based Nanogenerator for Enhanced Energy Harvesting and Information-Encrypted Transmission by Monika Salesh (15306281)

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Design and implementation of DelaySSA. The input data for DelaySSA are reaction information, initial states, parameters and delays. Combining these into the simulation function, th... by Ziyan Jin (21021976)

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Data&Codes.zip by Zer0 Star (20545655)

“…</p><p dir="ltr">To facilitate the widespread use of the proposed framework, we have implemented it as the <b><i>ESLocalIndi</i></b> open-source package in Python, making it easily accessible to geographers. …”

Complex Eigenvalues, Orthogonality, and QR Factorization: Analytical Proofs and Numerical Verification by Umar Tabbsum (22058780)

“…The work includes both analytical proofs and numerical verification to ensure reproducibility and clarity.…”

BSTPP: a python package for Bayesian spatiotemporal point processes by Isaac Manring (20705955)

“…However, they are sometimes neglected due to the difficulty of implementing them. There is a lack of packages with the ability to perform inference for these models, particularly in python. …”

Configurations used in ALAAMs for undirected networks. by Alex Stivala (8356257)

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Type II error rate from estimation of simulated outcomes using the EE algorithm. by Alex Stivala (8356257)

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Comparison of MPNet and ALAAMEE software for ALAAM estimation. by Alex Stivala (8356257)

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Configurations used in ALAAMs for directed networks. by Alex Stivala (8356257)

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Type I error rate from estimation of simulated outcomes using the EE algorithm. by Alex Stivala (8356257)

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Example ALAAMEE output. by Alex Stivala (8356257)

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Type II error rate as the number of runs used for each sample is varied. by Alex Stivala (8356257)

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Parameter estimates and estimated standard errors from the EE algorithm. by Alex Stivala (8356257)

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Network descriptive statistics for the Deezer networks. by Alex Stivala (8356257)

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Example ALAAMEE goodness-of-fit output. by Alex Stivala (8356257)

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ESTRO 2024 Pre-Meeting Course- <b><i>Embracing the AI Revolution: </i></b><b><i>A one-day dive into future-proof implementation</i></b> <b><i>(The Clinician Perspective)</i></b> by Clifton D. Fuller (528030)

“…Fuller for<b><i> </i></b></h2><p dir="ltr"><br></p><h2><i>Embracing the AI Revolution:</i><i> </i><i>A one-day dive into future-proof implementation; The Clinical Perspective.</i></h2><p dir="ltr"><br></p><p dir="ltr">Friday, 3 May 2024 from 08:30-17:00</p><p dir="ltr"><b>Course directors:</b></p><ul><li>Jennifer Dhont, Medical Physicist, Institut Jules Bordet (BE)</li><li>Frank Hoebers, Radiation Oncologist, Maastro Clinic (NL)</li><li>Stine Sofia Korreman, Medical Physicist, Aarhus University (DK)</li></ul><p dir="ltr"><b>Course aim:</b></p><p dir="ltr">To provide an insight into the practical aspects of implementing AI technology into the radiation oncology workflow. …”

Illustration of the text transformation process before and after synonym replacement: The process begins with a sample initial text segment (Sample text before synonym replacement’... by Enock Niyonkuru (21246879)

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Schematic of the approach: This schematic illustrates the entire workflow of the project. by Enock Niyonkuru (21246879)

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Text Transformation Pipeline: An example of the multi-stage text transformation pipeline applied to a sample abstract (PMID: 30609739). by Enock Niyonkuru (21246879)

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Comparative analysis of WordNet replacement impact on data distribution. by Enock Niyonkuru (21246879)

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