University of Milano-Bicocca Showcase

The dataset contains frequency-domain and time-domain measurements acquired from a microwave single-photon source and power-sensor device based on a superconducting transmon qubit, as reported in D. Labranca et al., “Reconstruction of single-photon emission with a self-calibrated wQED device based on a transmon qubit,” New Journal of Physics 27 (2025) 073001, https://doi.org/10.1088/1367-2630/ade736. The files are from frequency domain measurements (VNA and Spectrum Analyzer) and time domain measurements (digitizer) of a microwave single-photon source and power sensor device (superconducting transmon qubit). Both files can be read as python dictonaries of arrays (or matrices) and they feature explanatory key names. - ReflectionMeasurement.mat : Contains data for the reflection measurement at the emission port of the qubit. Two matrices are included: one with the qubit detuned by several GHz ("offRes" flag) and one with the qubit at the center of the bandwidth analyzed ("onRes" flag) - SpectrumAnalyzerMeasurement.mat: Contains the SA traces measured for a VNA tone with power "Pvna_corrected". - RabiOscillations.mat: Contains mode matched Rabi emission of the single-photon source and it is used to calibrate the qubit drive pulses. - QuadratureDistribution.mat: Contains the mode-matched emission of the source after preparing the ground, excited and superposition states of the qubit.

Final scoring sheet for the cases enrolled in the study

Time lapse video of brown band disease (BrB) progression.

Dataset archives

This dataset was generated as a result of the experiement described in the paper "Spillover effects of cooperative behaviour when switching tasks: the role of gender"

These data are relative to the paper "Neural Signatures of Hyper-Realistic AI-Generated Faces: Dissociating Behavioral Indistinguishability from Implicit Neural Evaluation". The present study aimed to determine whether the human brain preserves sensitivity to the artificial origin of hyper-realistic AI-generated faces even when explicit, behavioral discrimination from real faces fails. By integrating behavioral validation with high-density EEG recordings, we sought to characterize the temporal dynamics and neural substrates underlying the processing of real versus GAN-generated faces across perceptual, evaluative, and familiarity-related stages. Specifically, the study investigated whether implicit neural markers reveal systematic differences in the processing of artificial faces that are behaviorally indistinguishable from real ones, thereby dissociating overt recognition performance from covert neural evaluation.

Dataset relative to the study reported in the article "When remembering items is easier than remembering order". The study aimed at investigating whether remembering a series of items and their order are separate operations. The dataset reports the results of an immediate serial recall task performed with two conditions of cognitive load (high and low) and three conditions of aspect of the series to remember (items, order and both). All the scores recorded in the dataset are expresses as a proportion of correct responses.

Here a section of a human papillary thyroid carcinoma, analysed with MALDI-MSI and H&E stained. The dataset includes: -H&E stained WSI (ptc_core_tma_q3.tif); -ROIs (geojson); SCiLS exchange format ROIs (SEF.zip); -imzML of the differnt ROIs (imzML.zip). The ROIs were obtained using the workflow presented in "Improving the annotation for Spatial Proteomics: A computational approach to enhance molecular characterization of Thyroid Nodules" . A detailed description and scripts can be found at https://github.com/Vsc0/msi-enhanced .

Normal human lymph nodes and tonsils, multiplexed with the MILAN technique, analyzed with BRAQUE.