Results 71 to 80 of about 87,048 (263)

flow-models 2.2: Efficient and parallel elephant flow modeling with machine learning

SoftwareX
This article introduces the latest version of the flow-models framework for IP network flow analysis. Key improvements include support for Dask to enable parallel computing, dataset reduction techniques for efficient training, and new modules for entropy
Piotr Jurkiewicz
doaj   +1 more source

The Python ARM Radar Toolkit (Py-ART), a Library for Working with Weather Radar Data in the Python Programming Language

Journal of Open Research Software, 2016
The Python ARM Radar Toolkit is a package for reading, visualizing, correcting and analysing data from weather radars. Development began to meet the needs of the Atmospheric Radiation Measurement Climate Research Facility and has since expanded to ...
Jonathan J Helmus, Scott M Collis
doaj   +1 more source

AI‐Driven Acceleration of Fluorescence Probe Discovery

Advanced Science, EarlyView.
We present PROBY, an AI model trained on large‐scale datasets to predict key photophysical properties and accelerate the discovery of target‐specific fluorescent probes. By screening a target‐annotated library, PROBY identifies candidate probes for diverse targets and could guide probe optimization, enabling a range of in vitro and in vivo imaging ...
Xuefeng Jiang, Yanbo Li, Xue Tian, Sen Yang, Ruina Luo, Cenxing Zhou, Yuxuan Liu, Jingying Hu, Sen Feng, Lu Gan, Chongzhao Ran, Kun‐Hsing Yu, Junhan Zhao, Xiao Han, Xuan Zhai, Yuntao Jia, Jiapei Dai, Xiyue Wang, Biyue Zhu   +18 more
wiley   +1 more source

Cohort‐Scale Spatial Autocorrelation for Tumor Prediction in Mid‐Infrared Pathology and Spatial Biomarker Discovery Using MALDI Imaging Lipidomics

Advanced Science, EarlyView.
Computational annotation of various tissue types in heterogeneous samples such as colorectal cancer liver metastasis (CRLM) using spatial autocorrelation analysis on non‐destructive mid‐infrared (MIR) imaging data enabled correlative multimodal mass spectrometry imaging (MSI) for spatial investigation of lipid tumor marker candidates. The method can be
Miriam F. Rittel, Nikolas Ebert, Denis Abu Sammour, Sebastian Graf, Björn C. Fröhlich, Emrullah Birgin, Shad A. Mohammed, Nuh N. Rahbari, Axel Wellmann, Oliver Wasenmüller, Cleo‐Aron Weis, Stefan Schmidt, Carsten Hopf   +12 more
wiley   +1 more source

Opfunu: An Open-source Python Library for Optimization Benchmark Functions

Journal of Open Research Software
Opfunu is a Python library designed to address the need for a comprehensive suite of benchmark functions for numerical optimization algorithms. It offers a rich collection of functions, including all those used in the Congress on Evolutionary Computation
Nguyen Van Thieu
doaj   +1 more source

Polyglot Jet Finding [PDF]

EPJ Web of Conferences
The evaluation of new computing languages for a large community, like HEP, involves comparison of many aspects of the languages’ behaviour, ecosystem and interactions with other languages.
Stewart Graeme Andrew, Gras Philippe, Hegner Benedikt, Krasnopolski Atell   +3 more
doaj   +1 more source

A Scalable Method for Cavity‐Enhanced Solid‐State Quantum Sensors

Advanced Science, EarlyView.
Photoluminescent color centres in diamond and hexagon boron nitride are powerful nanoscale solid‐state quantum sensors. Methods for integrating them into macroscopic structures that improve their sensitivity are highly sought after. This study demonstrates a low‐cost and scalable method for the fabrication of quantum sensor‐doped thin‐film cavities ...
Daniel J. Tibben, Roy Styles, David A. Broadway, Jean‐Philippe Tetienne, Daniel E. Gómez, Philipp Reineck   +5 more
wiley   +1 more source

COFFEE -- An MPI-parallelized Python package for the numerical evolution of differential equations [PDF]

, 2019
COFFEE (ConFormal Field Equation Evolver) is a Python package primarily developed to numerically evolve systems of partial differential equations over time using the method of lines.
Doulis, Georgios, Frauendiener, Jörg, Stevens, Chris, Whale, Ben   +3 more
core   +2 more sources

Multi‐View Biomedical Foundation Models for Molecule‐Target and Property Prediction

Advanced Science, EarlyView.
Molecular foundation models can provide accurate predictions for a large set of downstream tasks. We develop MMELON, an approach that integrates pre‐trained graph, image, and text foundation models and validate our multi‐view model on over 120 tasks, including GPCR binding.
Parthasarathy Suryanarayanan, Yunguang Qiu, Shreyans Sethi, Diwakar Mahajan, Hongyang Li, Yuxin Yang, Elif Eyigoz, Aldo Guzmán‐Sáenz, Daniel E. Platt, Timothy H. Rumbell, Kenney Ng, Sanjoy Dey, Myson Burch, Bum Chul Kwon, Pablo Meyer, Feixiong Cheng, Jianying Hu, Joseph A. Morrone   +17 more
wiley   +1 more source

Resolvent4py: A parallel Python package for analysis, model reduction and control of large-scale linear systems

SoftwareX
In this paper, we present resolvent4py, a parallel Python package for the analysis, model reduction and control of large-scale linear systems with millions or billions of degrees of freedom.
Alberto Padovan, Vishal Anantharaman, Clarence W. Rowley, Blaine Vollmer, Tim Colonius, Daniel J. Bodony   +5 more
doaj   +1 more source