Multidomain, Automated Photopatterning of DNA-functionalized Hydrogels (MAPDH). by Moshe Rubanov (7289156)

“…<b>B)</b> Pseudocode for MAPDH in Python. The algorithm takes as input the vials that will be flowed through the patterning chamber. …”

Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish) by Daniel Pérez Palau (11097348)

“…</a></p><p dir="ltr">More information:</p><ul><li><a href="https://www.hatemedia.es/" rel="nofollow" target="_blank">https://www.hatemedia.es/</a> or contact: <a href="mailto:elias.said@unir.net" target="_blank">elias.said@unir.net</a></li><li>This algorithm is related to the hate/non-hate classification algorithm, also developed by the authors: <a href="https://github.com/esaidh266/Algorithm-for-detection-of-hate-speech-in-Spanish" target="_blank">https://github.com/esaidh266/Algorithm-for-detection-of-hate-speech-in-Spanish</a></li><li>This algorithm is related to the algorithm for classifying hate expressions by intensities in Spanish, also developed by the authors: <a href="https://github.com/esaidh266/Algorithm-for-classifying-hate-expressions-by-intensities-in-Spanish" target="_blank">https://github.com/esaidh266/Algorithm-for-classifying-hate-expressions-by-intensities-in-Spanish</a></li></ul><p></p>…”

Integration of Morphoscanner with MDAnalysis, NGLview and Networkx. by Federico Fontana (533670)

Spatiotemporal parameters for patients clusters (before and one year after surgery) and control group. by Xavier Gasparutto (8374578)

Characteristics and patients reported outcomes for patient clusters before and one year after surgery compared to the control group. by Xavier Gasparutto (8374578)

Where to Handle an Exception? Recommending Exception Handling Locations from a Global Perspective by Xiangyang Jia (10026932)

IJGIS-code&data.rar by Sancheng Zhu (8801357)

Human expert pattern recognition. by Robin Dirk (17296179)

Antibody challenge outcomes. by Andrea Blasco (7439102)

“…Also shown is the benchmark algorithm implemented in Python (A1) and C++ (A2); note that benchmark algorithms A1 and A2 have perfect accuracy (<i>ACC</i> equal to unity). …”

Artifact and instructions to generate experimental results for Euro-Par 2019 paper "A Comparison of Random Task Graph Generation Methods for Scheduling Problems" by Louis-Claude Canon (569406)

Bespoke software controls the sorter GUI and reports on instrument status to the user. by Diane M. Wiener (1956583)

Traditional Mach-Zehnder DHM system with an imaging system composed of an infinity-corrected microscope objective (MO) lens and a tube lens (TL) operating in non-telecentric regime... by Brian Bogue-Jimenez (16954568)

Silencing of <i>MeASLBD47</i> in cassava plants using a cassava common mosaic virus (Cscmv)-based Virus-induced gene silencing (VIGS) system. by Yiming Mao (6059345)

Graphical representation of the community of <i>Dehalobacter</i> sp. CF and <i>Bacteroidales</i> sp. CF50 after the application of the community gap-filling method. by Dafni Giannari (11632200)

Fig 12 - by Nisha Yadav (366131)

Data_Sheet_1_Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri).docx by Niklas Pallast (6796196)

“…Following a modular structure developed in Python scripting language, the pipeline integrates established and newly developed algorithms. …”

Data_Sheet_2_Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri).pdf by Niklas Pallast (6796196)

“…Following a modular structure developed in Python scripting language, the pipeline integrates established and newly developed algorithms. …”

metropolis_hastings.py;postprocessing.py;folkman_a_b_c_time.py;figures_Inverse_Proliferation.R;README.md from Bayesian inference of a non-local proliferation model by Zuzanna Szymańska (11679819)

“…;Auxiliary R (version 3.6.2) code to generate figures presenting the results of the random walk Metropolis-Hastings algorithm for the Bayesian inference of a non-local proliferation function.…”

Data-Driven Design of High-Performance Graphene-Based Seawater Desalination Membranes by Kun Meng (141278)

“…A high-throughput screening involving density functional theory–machine learning (DFT-ML) framework is considered to be an essential avenue to tackle this dilemma. …”

Data-Driven Design of High-Performance Graphene-Based Seawater Desalination Membranes by Kun Meng (141278)

“…A high-throughput screening involving density functional theory–machine learning (DFT-ML) framework is considered to be an essential avenue to tackle this dilemma. …”