University of Milano-Bicocca Showcase

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.

Final scoring sheet for the cases enrolled in the study

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.

Supplementary data and underlying data supporting the finding described in "Production and carbon footprint of microbial oil from waste lemon peel extract". Abstract Background The agricultural sector is one of the leading producers of agro-industrial solid organic waste. This waste is mainly disposed of by incineration or landfilled, representing a huge loss of potential resources, which could be used for the production of high-value chemicals. In this study, a fermentation process for the production of microbial oil from waste lemon extract (LE), an aqueous side stream deriving from waste lemon peel and pulp processing, was developed and assessed for impacts. Microbial oil can have many and diverse applications, from plasticisers in plastic and rubber compounds to moisturizers in cosmetic formulation. Methods and results Characterization of LE revealed that its autoclaving process is effective for increasing the concentration of readily available glucose and fructose, reaching 28.77 ± 0.08 g L-1 and 25.68 ± 0.27 g L-1. Nitrogen content was measured too, revealing a C/N ratio of 85, optimal for triggering lipid accumulation in the selected microbial cell factory. Therefore, the oleaginous yeast Cutaneotrichosporon oleaginosum was cultivated in an unmodified LE-based medium in 2 L bioreactors, resulting in a lipid accumulation of 0.47 ± 0.08 goil gCDW-1. Finally, a new lipid extraction method using green solvents was developed, which allowed to extract and purify 11.29 g of oils, corresponding to 35% of the cell dry weight. The carbon footprint of this laboratory-scale production was estimated to be 71 - 434 kgCO2eq kg-1 microbial oil, with electricity consumption of the fermentation step as the main factor. Simulation of the process in a 300L fermenter suggests that the electricity consumption, and therefore the overall impact, can be drastically reduced with scale-up. Conclusions The proposed process is promising in terms of production and has the advantage of not being in competition with edible resources and land use. However, the microbial oil yield and the extraction process must be optimized to make the process sustainable.

PhD Thesis Supplementary Files to the Chapter 3 (Version 1). Supplementary File 1: Metadata of all the samples collected, including day and time of sampling, day/night distribution, season, geographic coordinates, distribution among macro-zones and micro-zones. Supplementary File 2: List of annotated bony fish and elasmobranch taxa detected in the dataset. Supplementary File 3: List of annotated invertebrate taxa for the nine selected phyla, namely: Annelida, Arthropoda, Bryozoa, Cnidaria, Ctenophora, Echinodermata, Mollusca, Chlorophyta, Haptophyta.

Supporting_Video for PhD thesis entitled: Analysis of shark aggregations and ecology in the maldives. Assessing a protocol for the survey of the species by the use of non invasive methods. From Parmegiani Andrea PhD student XXXVIII cycle in Terrestrial and Marine Environmental Sciences, University of Milano Bicocca, 2025.

Raw data of the study

The stimulus set was used in the ERP paper "Decoding Motivational States and Craving through Electrical Markers for Neural 'Mind Reading’ by Proverbio AM & Zanetti A (2025). The aim of this study was to identify electrical neuromarkers of 12 different motivational and physiological states (such as visceral craves, affective and somatosensory states, and secondary needs) in LIS, coma, or minimally conscious state patients. Auditory stimuli were designed by combining a human expressive voice with a background sound to evoke a context related to the targeted needs. The stimuli included: primary or visceral needs (hunger, thirst, and sleep), homeostatic or somatosensory sensations (cold, heat, and pain), emotional or affective states (sadness, joy, and fear), and secondary needs (desire for music, movement, and play). 17 audio clips were recorded for each micro-category, each replicated twice: once with a male voice and once with a female voice, totaling 408 stimuli. Audacity software was used to combining the vocal track with a background context coherent with the verbal content. Human voices were recorded using Microphone 202 K38 by Hompower (SNR = 80 dB). The semantic content, the prosodic intonation and the emotional tone of all voices were coherent and appropriately matched. Some of the background sounds were recorded using the same microphone, while others were sourced from the publicly accessible BBC Sound Effects library for scientific purposes (https://sound-effects.bbcrewind.co.uk/search). Research was funded by ATE – Fondo di Ateneo No. 31159-2019-ATE-0064, University of Milano-Bicocca. The research project, entitled “Auditory imagery in BCI mental reconstruction” was preapproved by the Research Assessment Committee of the Department of Psychology (CRIP) for minimal risk projects, under the aegis of the Ethical committee of University of Milano-Bicocca, on February 9th, 2024, protocol n: RM-2024-775).