EEGManyPipelines: A Large-scale, Grassroots Multi-analyst Study of Electroencephalography Analysis Practices in the Wild

The ongoing reproducibility crisis in psychology and cognitive neuroscience has sparked increasing calls to re-evaluate and reshape scientific culture and practices. Heeding those calls, we have recently launched the EEGManyPipelines project as a means to assess the robustness of EEG research in naturalistic conditions and experiment with an alternative model of conducting scientific research.

Towards a digital twin for personalized diabetes prevention: the PRAESIIDIUM project

This contribution outlines current research aimed at developing models for personalized type 2 diabetes mellitus (T2D) prevention in the framework of the European project PRAESIIDIUM (Physics Informed Machine Learn-ing-Based Prediction and Reversion of Impaired Fasting Glucose Management) aimed at building a digital twin for preventing T2D in patients at risk.

Segment Routing v6 - Security Issues and Experimental Results

SRv6 can provide hybrid cooperation between a centralized network controller and network nodes. IPv6 routers maintain multi-hop ECMP-aware segments, whereas the controller establishes a source-routed path through the network. Since the state of the flow is defined at the ingress to the network and then is contained in a specific packet header, called Segment Routing Header (SRH), the importance of such a header itself is vital. Motivated by the need to study and investigate this technology, this paper discusses some security-related issues of Segment Routing.

Some Results on Colored Network Contraction

Networks are pervasive in computer science and in real world applications. It is often useful to leverage distinctive node features to regroup such data in clusters, by making use of a single representative node per cluster. Such contracted graphs can help identify features of the original networks that were not visible before. As an example, we can identify contiguous nodes having the same discrete property in a social network. Contracting a graph allows a more scalable analysis of the interactions and structure of the network nodes.

Numerical simulation of a compressible gas flow in porous media bioremendiation

In a subsoil bioremediation intervention air or oxygen is injected in the polluted region and then a model for unsaturated porous media it is required, based on the theory of the dynamics of multiphase fluids in porous media. In order to optmize the costs of the intervention it is useful to consider the gas as compressible and this fact introduces nonlinearity in the mathematical model. The physical problem is described by a system of equations and the unknowns are: pollutant; bacteria concentration; oxygen saturation and oxygen pressure.

Highly automated dipole estimation (HADES)

Automatic estimation of current dipoles from biomagnetic data is still a problematic task. This is due not only to the ill-posedness of the inverse problem but also to two intrinsic difficulties introduced by the dipolar model: the unknown number of sources and the nonlinear relationship between the source locations and the data. Recently, we have developed a new Bayesian approach, particle filtering, based on dynamical tracking of the dipole constellation.

Quantitative Multidimensional Central Limit Theorems for Means of the Dirichlet-Ferguson Measure

The Dirichlet-Ferguson measure is a cornerstone in nonparametric Bayesian statistics and the study of distributional properties of expectations with respect to such measure is an important line of research. In this paper we provide explicit upper bounds for the d2, the d3 and the convex distance between vectors whose components are means of the Dirichlet-Ferguson measure and a Gaussian random vector.

Aperto un bando per un assegno di ricerca sui fondi PRIN 2022

PRIN2022 carissimo

Scade il 12 gennaio la selezione per un assegno di ricerca sul programma 2022T7XP29 “Decoding and leveraging the molecular determinants of myogenic fate through integrative genomics and cell engineering”, finanziato dal PRIN 2022.

La tematica riguarda lo sviluppo di metodi statistici per l’analisi e l’integrazione di dati omici”, sotto la responsabilità scientifica della dott.ssa Annamaria Carissimo. 

Requisiti sono:

Genomica
analisi statistica

Sulla CNR Web TV il video della giornata "Ma a che serve la matematica?"

cnrwebtv

Pubblicato sulla CNR Web TV il servizio sulla giornata del 24 ottobre "Ma a che serve la matematica?" svoltasi a Roma, al Salone Margherita, in collaborazione con il Museo della moneta di Banca d'Italia.

Sul palco, ricercatori dell'IAC e di Banca d'Italia, hanno raccontato agli studenti delle scuole superiori le varie applicazioni della matematica nella vita quotidiana. 

Un'occasione per festeggiare i 100 anni del CNR.

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