Results 81 to 90 of about 88,482 (262)

Numba-MPI v1.0: Enabling MPI communication within Numba/LLVM JIT-compiled Python code

SoftwareX
The numba-mpi package offers access to the Message Passing Interface (MPI) routines from Python code that uses the Numba just-in-time (JIT) compiler. As a result, high-performance and multi-threaded Python code may utilize MPI communication facilities ...
Kacper Derlatka, Maciej Manna, Oleksii Bulenok, David Zwicker, Sylwester Arabas   +4 more
doaj   +1 more source

Selectivity Filter Dynamics Define Ion Conductance and Selectivity Differences in CNG and HCN Channels

Advanced Science, EarlyView.
Cyclic nucleotide‐gated (CNG) and hyperpolarization‐activated cyclic nucleotide‐gated (HCN) channels share substantial sequence and structural similarity but differ markedly in ion conductance and K+ selectivity. Microsecond‐scale atomistic MD simulations qualitatively reproduced the conductance differences observed in single‐channel recordings and ...
Haoran Liu, Klaus Benndorf, Yessenbek K. Aldakul, Han Sun   +3 more
wiley   +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

Endoplasmic Reticulum Geometry Dictates Neuronal Bursting via Calcium Store Refill Rates and Exposes Selective Neuronal Vulnerability

Advanced Science, EarlyView.
The ER's continuous tubular network is maintained by ER‐shaping proteins whose mutation or dysregulation contributes to neurodegenerative diseases. Here, we show that ER morphology sets the speed of Ca2+ store replenishment between firing events. Disrupting ER continuity slows intra‐ER Ca2+ redistribution from extracellular refill (SOCE) sites, driving
Valentina Davi, Pierre Parutto, Yuyi Zhang, Tasuku Konno, Cecile Crapart, Raquel Pereira, John P. Franklin, Mosab Ali Awadelkareem, Daniel C Maddison, Michael J. Devine, Edgar R. Gomes, Joseph Chambers, Elena Koslover, Edward Avezov   +13 more
wiley   +1 more source

Rapid Proteome‐Wide Discovery of Protein–Protein Interactions With ppIRIS

Advanced Science, EarlyView.
ppIRIS is a lightweight deep learning framework for proteome‐wide protein–protein interaction prediction directly from sequence. By fusing evolutionary and structural embeddings with a regularized Siamese architecture, ppIRIS achieves state‐of‐the‐art accuracy across species, enables minute‐scale screening, and reveals biologically validated bacterial ...
Luiz Felipe Piochi, Di Tang, Johan Malmström, Yasaman Karami, Hamed Khakzad   +4 more
wiley   +1 more source

Deciphering the Evolution Pattern of Structural Variations Overlapped With Repetitive Sequence During Cattle Evolution

Advanced Science, EarlyView.
The authors complement bovine pan‐SV with massive novel structural variations (SVs) identified through long‐read sequencing of 83 globally distributed cattle breeds. Repetitive sequence‐mediated SVs (rep‐SV) exhibit distinct dynamic patterns throughout cattle sub‐speciation and/or domestication processes, including uneven distribution between chr‐X and
Zhifan Guo, Jinxiu Li, Adeniyi C. Adeola, Xueyan Jiang, Juntao Ma, Jian Xiao, Dexiang Hu, Kaixing Qu, Haihong Wu, Junren Chen, Zhanxing He, Tingting Yin, Ali Esmailizadeh, Jing Luo, Olivier Hanotte, Ya‐Ping Zhang, Yan Li   +16 more
wiley   +1 more source

Freeware solutions for spectropolarimetric data reduction

, 2007
Most of the solar physicists use very expensive software for data reduction and visualization. We present hereafter a reliable freeware solution based on the Python language.
Leger, L., Paletou, F., Rezaei, R.
core   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Process Monitoring and Control in Dermatological Diagnosis: A Deep Learning Approach Using Python, NumPy, Pandas, Keras, and TensorFlow

Proceedings
This paper delves into integrating machine learning techniques into dermatological diagnostics, specifically focusing on identifying and evaluating skin diseases [...]
Neelamadhab Padhy, T. Bhubaneswari, Sushree Sangita Das, Meetali Sinha   +3 more
doaj   +1 more source

Discovering Interpretable Semantics from Radio Signals for Contactless Cardiac Monitoring

Advanced Science, EarlyView.
This study presents a semantic representation framework for clinically interpretable cardiac monitoring from contactless radio signals. It formulates radio semantic learning as an information‐bottleneck problem and approximates the objective via intra‐modal compression and cross‐modal alignment, structuring radio measurements into meaningful semantic ...
Jinbo Chen, Haoyu Wang, Guixin Xu, Yuqin Yuan, Xinmeng Cai, Zhengwu Wei, Dongheng Zhang, Qibin Sun, Tianwei Zhang, Cuntai Guan, Yan Chen   +10 more
wiley   +1 more source