Science Advances

These data correspond to the results reported in J. Borge-Holthoefer, Nicola Perra, Bruno Gonçalves, Sandra González-Bailón, Alex Arenas, Yamir Moreno and Alessandro Vespignani. The dynamic of information-driven coordination phenomena: a transfer entropy analysis. Science Advances 2(4) e1501158 (2016) doi: 10.1126/sciadv.1501158 (open access) Check the readme.txt file in the tar.gz for further information.

Biomedical implants, such as brain stimulators, have significantly enhanced the quality of life for many individuals. Recently, the emergence of photonic implants has opened new avenues for innovative treatment methods and high-resolution neuronal stimulation through a technique known as optogenetics. However, classical photonic implants, such as optical fibres tether the subject to an external light source. Wireless light sources, which combine an energy receiver for wireless power transfer with an integrated light source in a compact volume, are revolutionizing treatment methods and propel optogenetic research forward. Nevertheless, current electromagnetic field based wireless stimulators are still bulky or require high frequency fields to operate, which are strongly absorbed by opaque watery environments such as tissue. The composite magnetoelectric (ME) effect, which enables the conversion of magnetic fields to electric fields via mechanical oscillations, has the potential to overcome limitations related to miniaturization, power supply, and low-frequency device operation. In this work, we explore the combination of composite ME materials and organic light-emitting diodes (OLEDs) to create a compact light source that operates at frequencies below one megahertz. We present the first sub-cubic millimetre, low frequency wireless light source by directly manufacturing a specifically tailored OLED stack onto an ME transducer. The device demonstrates robust performance with no signs of degradation over hours of continuous operation and can be operated deep inside a tissue phantom. We show that the light output is sufficient to trigger an optogenetic response in Drosophila melanogaster fruit fly larvae and outline efforts towards mammalian animal models. To provide enough power for the OLED, ME transducers must be operated at their mechanical resonance frequency. We exploit his property to demonstrate the clustered activation of multiple devices located in the same magnetic field. A computational optimization strategy allows guided resonance frequency tuning by changing the shape of the device. Our work lays the foundations for a novel type of tiny, wireless light source operable centimetres deep inside tissue. The data files are embargoed until 17/05/2026

Extent of perennially shadowed regions (PSRs) obtained by applying ray-tracing to LOLA shape models with various values of the maximum solar declination. See README.TXT for a technical description of the data files.

Supplementary data for "A combined molecular dynamics and experimental study of two-step process enabling low-temperature formation of phase-pure α-FAPbI3: 10.1126/sciadv.abe3326"

This repository contains sharable datasets for the publication below. The related codes are in a different github repository: https://github.com/benmarhnia-lab/synergistic_effect_wildfire_extremeheat_ca. Chen C, Schwarz L, Rosenthal N, Marlier ME, Benmarhnia T. Exploring spatial heterogeneity in synergistic effects of compound climate hazards: Extreme heat and wildfire smoke on cardiorespiratory hospitalizations in California. Sci Adv. 2024;10(5):eadj7264. doi:10.1126/sciadv.adj7264 Here is a list of the datasets included: "zcta_list_eh85_wf15_binary_1772zcta.csv" contains a list of California zctas with exposure and health data available for our analyses. "census_2010_pop.csv" contains zcta centroids and popualtion (2010 census). "zip_selected_hpi3_hpi_wt_041823_clean.csv" contains zcta-specific Healthy Places Index data after cleaning. "eh85_wf15_binary_1772zcta_0619.rds" contains exposure time-series data.

Dynamic sparse X-ray nanotomography reveals ionomer hydration mechanism in polymer electrolyte fuel-cell catalyst: Raw data and reconstruction software Dataset structure: - Dynamic_PEFC_data.h5 # Raw projection data for dynamic tomography imaging of PEFC catalyst hydration. - /sinogram # Sinogram of all projections, 3-dimensional array with axes (Nangle,X axis,Y axis). - /tomo_angle # Tomography rotation angle for each projection, 1D array with axis (Nangle). - /humidity_readout # Relative humidity value at the time each projection is measured, 1D array with axis (Nangle). - /Deform_X # X/Y/Z components for the deformation vector field which characterize nonrigid deformation of the sample. - /Deform_Y - /Deform_Z - liquid_simulation.h5 # Numerical simulation of dynamic liquid filling process. - /sinogram # Sinogram of all projections, 3-dimensional array with axes (Nangle,X axis,Y axis). - /tomo_angle # Tomography rotation angle for each projection, 1D array with axis (Nangle). - /groundtruth_tomograms # Ground truth of the simulated tomograms, 4-dimensional array with axes (Timeframe,Y axis, Z axis, X axis). - phasetran_simulation.h5 # Numerical simulation of gradual linear density change process. - /sinogram # Sinogram of all projections, 3-dimensional array with axes (Nangle,X axis,Y axis). - /tomo_angle # Tomography rotation angle for each projection, 1D array with axis (Nangle). - /groundtruth_tomograms # Ground truth of the simulated tomograms, 4-dimensional array with axes (Timeframe,Y axis, Z axis, X axis). Reconstruction codes: - astra_nonrigid.zip # Compressed python package of modified version of astra-toolbox with nonrigid computed tomography implementation. - /astra # Python package folder, need to be added to Python import search path (sys.path). # If the pre-compiled version doesn't work, source code of the pacakge can be downloaded: # https://github.com/zr-gao/astra-toolbox-nonrigid # Follow the instructions and requirements on the website to compile and install the package. - reconstruction_PEFC.py # Python script for sparse dynamic tomography of the PEFC dataset. # Need to be in the same folder with Dynamic_PEFC_data.h5 to load data. # Follow the instructions in the code to set reconstruction parameters and export results. # Requirements: cupy, numpy, astra(with nonrigid)*, h5py # * !!! Nonrigid computed tomography is used for the reconstruction, therefore the astra package with nonrigid implementation (in astra_nonrigid.zip) is required. - reconstruction_simulation.py # Python script for sparse dynamic tomography of numerical simulations. # Need to be in the same folder with liquid_simulation.h5 or phasetran_simulation.h5, loaded filename is selected in the code. # Follow the instructions in the code to set reconstruction parameters and export results. # Requirements: cupy, numpy, astra**, h5py # ** Reconstruction of numerical simulations does not use nonrigid computed tomography, therefore both the astra_nonrigid.zip and the official astra-toolbox package will work. # To download and install the official astra-toolbox refer to the repository: # https://github.com/astra-toolbox/astra-toolbox

Scripts, simulation results and visualizations for the manuscript: "Poaching pressure on African rhinos is still at all-time high". It constitutes movement simulations of a poacher in a reserve with varying rhino densities. These simulations provide validation data with varying parameter combinations for the mathematical model as presented in the manuscript, in order to derive the relationship between rhino density and poacher search distance.

Extent of perennially shadowed regions (PSRs) obtained by applying ray-tracing to LOLA shape models with various values of the maximum solar declination. See README.TXT for a technical description of the data files.

Scripts, simulation results and visualizations for the manuscript: "Poaching pressure on African rhinos is still at all-time high". It constitutes movement simulations of a poacher in a reserve with varying rhino densities. These simulations provide validation data with varying parameter combinations for the mathematical model as presented in the manuscript, in order to derive the relationship between rhino density and poacher search distance.