Array programming with NumPy

Harris, C. R.; Millman, K. Jarrod; Walt, Stéfan J. van der; Gommers, Ralf; Virtanen, Pauli; Cournapeau, David; Wieser, Eric; Taylor, Julian; Berg, Sebastian; Smith, Nathaniel J.; Kern, Robert; Picus, Matti; Hoyer, Stephan; Kerkwijk, M. H. van; Brett, Matthew; Haldane, Allan; Río, Jaime Fernández del; Wiebe, Mark; Peterson, Pearu; Gerard-Marchant, P; Sheppard, Kevin; Reddy, Tyler; Weckesser, Warren; Abbasi, Hameer; Gohlke, Christoph; Oliphant, Travis E.

doi:10.1038/s41586-020-2649-2

Cited by 14,643 publications

(8,536 citation statements)

References 80 publications

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“…The algorithms and functions implemented in this study were written in Python (van Rossum and Drake, 2009), using the packages Numpy (Oliphant, 2006;van der Walt et al, 2011;Harris et al, 2020), Scipy (SciPy 1.0 Contributors et al, 2020), and Matplotlib (Hunter, 2007). All code and data published with this paper is available under the BSD 3-clause license, and all figures generated in this paper are available under the CC-BY 4.0 license.…”

Section: License and Reusabilitymentioning

confidence: 99%

Natural Stings: Selling Distrust About Vaccines on Brazilian YouTube

2020

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In this study, we investigate misinformation and disinformation (M&D) about vaccines using a case study approach to understand how M&D about vaccines circulate on YouTube in Portuguese, and who are the channels creating and disseminating this kind of content. The World Health Organization considered vaccine hesitation as one of the greatest threats to global health in 2019. Researchers associated this hesitation to a strengthening of the anti-vaccination movements, suggesting that social media is currently the main spreader of this position. YouTube increasingly becomes a matter of concern, since its recommendation system is identified as a promoter of misinformation and extreme content. Despite YouTube's statements, M&D about vaccines continue to be disseminated in videos in Portuguese, reaching a large audience. We found 52 videos containing M&D about vaccines. The main M&D were the claim of dangerous ingredients in vaccines, the defense of self-direction-freedom of choice, independent research-, the promotion of alternative health services, the myth that vaccines cause diseases, conspiracy theories, and the allegation of vaccine's severe collateral effects. We identified 39 brands advertising on 13 videos of our M&D sample. Although the YouTube Partner Program is an important source of income, the channels use different economic strategies, such as the selling of courses, and therapies and the use of fundraising platforms. We also found that alternative health channels spread distrust about traditional institutions to promote themselves as trusted sources for the audience and thereby profit with alternative health services.

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Section: License and Reusabilitymentioning

confidence: 99%

Natural Stings: Selling Distrust About Vaccines on Brazilian YouTube

2020

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“…The final time for each simulation is 2000 seconds. The model was implemented in Python 3.7, using the NumPy [75], Joblib, scikit-learn [76], statsmodels, pandas [77], Matplotlib [78] and SciPy [79] packages. All scripts are available at https://github.com/vrcarva/WNMM_probing.…”

Section: Methodsmentioning

confidence: 99%

Active probing to highlight approaching transitions to ictal states in coupled neural mass models

Carvalho

Moraes

Cash

et al. 2020

Preprint

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The extraction of electrophysiological features that reliably forecast the occurrence of seizures is one of the most challenging goals in epilepsy research. Among possible approaches to tackle this problem is the use of active probing paradigms in which responses to stimuli are used to detect underlying system changes leading up to seizures. This work evaluates the theoretical and mechanistic underpinnings of this strategy using a well-studied seizure-generating neural mass model with two coupled populations. Different simulations are done by shifting parameters (excitability, slow inhibition, and coupling gains) towards ictal states while low-frequency probing stimuli are applied to either one or both populations. The correlation between the extracted features and the shifted parameter indicates if the impending transition to the ictal state may be identified in advance. Results show that not only can the response to the probing stimuli forecast seizures but this is true regardless of the altered ictogenic parameter. That is, similar feature changes are highlighted by probing stimuli responses in advance of the seizure including: increased response variance and lag-1 autocorrelation, decreased skewness, and increased mutual information between the outputs of both model subsets. These changes were restricted to the stimulated population, showing a local effect of this perturbational approach. The transition latencies from normal activity to sustained discharges of spikes were not affected, suggesting that stimuli had no pro-ictal effects. However, stimuli were found to elicit interictal-like spikes just before the transition to the ictal state. Furthermore, the observed feature changes highlighted by probing the neuronal populations may reflect the phenomenon of critical slowing down, where increased recovery times from perturbations may signal the loss of a systems’ resilience and are common hallmarks of an impending critical transition. These results provide more evidence that active probing approaches highlight information about underlying system changes involved in ictogenesis and may be able to play a role in assisting seizure forecasting methods which can be incorporated into early-warning systems that ultimately enable closing the loop for targeted seizure-controlling interventions.Author summaryEpilepsy is characterized by spontaneous and recurrent seizures. Developing a method to forecast the occurrence of these events would ease part of the burden to patients by providing warning systems and identifying critical periods for closed-loop seizure suppressing methods. However, this task is far from trivial and doing this in a clinical setting has been a challenge that is not yet solved. A possible way to achieve this is by using active probing paradigms, in which stimuli are used to highlight otherwise hidden changes in brain dynamics that may lead to seizures. In this work, this approach is tested in a computational model with two coupled neuronal populations. Active probing responses highlighted underlying model parameter changes that led neuronal activity closer to seizures, something that was not detected with the passive observation in most evaluated model settings. Observed feature changes revealed higher excitability, longer recovery times from stimuli, and increased synchrony between populations as the threshold to seizure-like activity approached. This indicates that low frequency stimuli may be used to reveal early-warning signs and assist in seizure forecasting methods.

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“…Scientific libraries in Python language were used to for reading, processing and evaluation of the AC data. Numerical processing was performed with Numpy [54] and Pandas [55], and plotting was done using Matplotlib [56]. Custom functions were written for reading and processing the raw data, automatic quantile-based color mapping, and generation of transmittograms.…”

Section: Evaluation Of Transmittogram and Stability Trajectorymentioning

confidence: 99%

On the State and Stability of Fuel Cell Catalyst Inks

Bapat

Giehl²,

Kohsakowski³

et al. 2021

Preprint

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Catalyst layers (CL) as an active component of the catalyst coated membrane (CCM) form the heart of proton electrolyte membrane fuel cells (PEMFC). For optimum performance of the fuel cell, obtaining suitable structural and functional characteristics for the CL is crucial. Direct tuning of the microstructure and morphology of the CL is non-trivial; hence catalyst inks as catalyst layer precursors need to be modulated, which are then applied onto a membrane, to form the CCM. Obtaining favorable dispersion characteristics forms an important prerequisite in engineering catalyst inks for large scale manufacturing. In order to facilitate a knowledge-based approach for developing fuel cell inks, this work introduces new tools and methods to study both the dispersion state and stability characteristics, simultaneously. Catalyst inks were prepared using different processing methods which include stirring and ultrasonication. The proposed tools are used to characterize and elucidate the effects of the processing method. Structural characterization of the dispersed particles and their assemblages was carried out by means of transmission electron microscopy. Analytical centrifugation (AC) was used to study the state and stability of inks. Herein, we introduce new concepts, S score and stability trajectory, for a time-resolved assessment of inks in their native state using AC. The findings were validated and rationalized using transmittograms as a direct visualization technique. The flowability of inks was investigated by rheological measurements. It was found that probe sonication only up to an optimum amplitude leads to a highly stable colloidal ink.

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Array programming with NumPy

Cited by 14,643 publications

References 80 publications

Natural Stings: Selling Distrust About Vaccines on Brazilian YouTube

Natural Stings: Selling Distrust About Vaccines on Brazilian YouTube

Active probing to highlight approaching transitions to ictal states in coupled neural mass models

On the State and Stability of Fuel Cell Catalyst Inks

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