Intelligent Motion Control under Industry 4.E IMOCO4.E

Progetto di ricerca internazionale-H2020, ECSEL-JU (Electronic Components and Systems for European Leadership)

Abstract:

Durata: 2021-2024

Finanziamento: € 497.500,00

Principal Investigator: Marko Bertogna

Componenti gruppo di ricerca (UniMoRe): Riccardo Lancellotti, Riccardo Martoglia, Luigi Rovati

Partners:

Automotive Intelligence for/at Connected Shared Mobility AI4CSM

Progetto di ricerca internazionale-H2020, ECSEL-JU (Electronic Components and Systems for European Leadership)

Abstract:

Durata: 2021-2024    

Finanziamento: € 469.375,00

Principal Investigator: Andrea Marongiu

Componenti gruppo di ricerca (UniMoRe): Paolo Valente

Partners:

Machine Learning for Quantum ML4Q

Progetto di ricerca internazionale-HORIZON-MCSA-DN-2021

Abstract

The Marie Skłodowska-Curie Doctoral Network "ML4Q - Machine Learning for Quantum" provides high-level interdisciplinary,intersectoral and international training to 10 doctoral researchers who will explore how machine learning and quantum science technology can be combined to (i) extend quantum and classical machine learning based prediction of materials and matterproperties and to strongly-correlated regimes, and (ii) accelerate the development of quantum technologies through machinelearning, thus enabling new approaches to solving outstanding problems currently out of reach of classical computers. This has the potential to address some of the world's most pressing challenges, such as developing tools for discovering more environmentally friendly chemical processes and efficient materials, or accelerating the development of quantum technologies which will give Europe an edge in the global tech race. ML4Q fellows will realize this vision will through their individual projects and interdisciplinary collaborations reinforced by a comprehensive training program which combines cutting-edge research with a focus on networking, career development for academic and non-academic career paths, open science and responsible research and innovation for society, that will enable them to shape emerging technologies and the next digital transformation in Europe. The consortium consists of 5 academic and 5 non-academic research partners (including 2 leading Eu QT startups) and 11 principal investigators who bring together all the necessary expertise computer science, AI and machine learning, quantum technology, and chemistry and materials science, as well as their interfaces. Together we will prepare the next generation of strong, resilient, flexible, and creative quantum and computer scientists with the combination of skills needed to meet the future needs of the rapidly evolving innovative materials, quantum technologies industries, as well as other knowledge based sectors.

Durata: 2024-2028

Finanziamento: € 518.875,20

Principal Investigator: Guido Goldoni

Componenti gruppo di ricerca (UniMoRe): Marco Gibertini, Federico Grasselli

Partners: Universite de Strasbourg, Karlsruher Institut fur Technologie, Università degli Studi di Padua, Wigner Research Centre for Physics, CNR-NANO, Ericsson Magyarorszag Kommunikacios Rendszerek KFT.

Integration and Harmonization of Logistics Operations

Progetto di ricerca Internazionale- Horizon EU-TRACE

Abstract 

Durata: 2023-2026

Finanziamento: 491.875,00

Principal Investigator: Marko Bertogna     

Componenti gruppo di ricerca (UniMoRe): 

Partners:

Materials design at the Exascale-MaX

Progetto di ricerca Internazionale- Horizon-EuroHPC-JU-2021-Coe-01

Abstract

Understanding, predicting, and discovering the properties and performance of materials is key to delivering the technologies that power our economy and provide a sustainable development to our society. For this reason, materials simulations have become one of the most intensive and fast-growing domains for high-performance computing worldwide, with a recognized European leadership in developing and innovating the ecosystem of quantum simulation codes. MaX will target these lighthouse codes to address the challenges and leverage the opportunities arising from future exascale and post-exascale architectures, and to offer powerful paths to discovery and innovation serving both scientific and industrial applications.

MaX includes (1) the core developing teams of the European lighthouse codes; (2) the HPC centres designing and hosting pre-exascale and exascale systems; (3) the main European companies engaged in the development of exascale technologies; and it brings (4) a sustained record in training and educating the community, and (5) in disseminating its resources under an extensive open-source model that includes codes, workflows, and FAIR data.

These synergies will underpin the objectives of the present proposal, that aims to upscale the MaX codes and their performance to multiple heterogeneous exascale architectures; to endow these codes with innovative capabilities enabled by such architectures; to co-design the hardware and software in collaboration with the relevant European stakeholders; to enable turn-key simulation capabilities that meet the power of exascale resources and deliver the resilience needed; to disseminate the entire ecosystem of codes, workflows, and data; and to train and engage developers and users in fully leveraging such powerful instruments for discovery and innovation.

Durata: 2022-2026

Finanziamento: 118.750,00

Principal Investigator: Elisa Molinari

Componenti gruppo di ricerca (UniMoRe): Marco Gibertini, Alice Ruini

Partners: CNR, SISSA Trieste, CINECA, E4, Leonardo SpA, ICN2 Barcelona, BSC, FZ-JSC Juelich, Uni Bremen, CEA Paris, ATOS, SiPearl, IT4I, JStefanInstitute.

White-label shop for digital intelligence assistance and human-AI collaboration in manufacturing-WASABI

Progetto di ricerca Internazionale- Horizon EU

Abstract

Durata: 2023-2027

Finanziamento: 288.750,00

Principal Investigator: Federica Mandreoli

Componenti gruppo di ricerca (UniMoRe): 

Partners:

EUMaster4HPC-EU Master in High Performance Computing

Progetto di ricerca Internazionale- H2020-JTI-EuroHPC-2020-03

Abstract

Advancing education and training in High Performance Computing (HPC), High Performance Data Analytics (HPDA), and Artificial Intelligence (AI) is essential for strengthening the world-class European HPC ecosystem. It is of primary importance to ensure the digital transformation and the sustainability of high-priority economic sectors. There is a significant potential for creating socioeconomic value with HPC; however, missing educated and skilled professionals in HPC/HPDA/AI could prevent Europe from achieving this potential. The lack of a well-trained workforce in HPC system design and development, deployment and operation, as well as HPC applications and hardware-software codesign, is a known problem that needs to be tackled from various directions. Today, many of the members of the European Technology Platform (ETP) have difficulties finding suitably educated staff. All this has an even broader economic impact causing the limitation on growth and delays in development because of the necessity for additional training, often over an extended period after hiring. In this context, the HERCULES (Hpc EuRopean ConsortiUm Leading Education activitieS) project aims at defining and developing a new and innovative European Master programme focusing on high performance solutions. This master programme will equip students with the competencies and knowledge in HPC/HPDA/AI required by academia and industry. Furthermore, it will enable them to develop their sense of innovation. Moreover, this master's programme will tackle various aspects of the HPC ecosystem and its applications to different scientific and industrial domains.

Durata: 2023-2027

Finanziamento: 85.905,00

Principal Investigator: Elisa Molinari

Componenti gruppo di ricerca (UniMoRe): Alice Ruini

Partners: Université du Luxembourg, Universitat Politècnica de Catalunya, Politecnico di Milano, Friedrich-Alexander-Universität Erlangen-Nürnberg,  Sorbonne Université, Sofia University St. Kliment Ohridski, European Technology Platform for High Performance Computing, Università della Svizzera Italiana, Kungliga Tekniska Hoegskolan, Cineca Consorzio Interuniversitario, Technische Universitaet Wien, VSB - Technical University of Ostrava, AGH Krakow University of Science and Technology, Univerza V Ljubljani, Pannon Egyetem, National Technical University of Athens, Consorzio Interuniversitario Nazionale per L'informatica, Barcelona Supercomputing Centre-Centro Nacional De Supercomputacion,  Université de Reims Champagne-Ardennne, Middle East Technical University.

A network of excellence for ditributed, trustworthy, efficient and scalable AI at the Edge-dAIEDGE

Progetto di ricerca Internazionale- Horizon -RIA

Abstract

Durata: 2023-2026

Finanziamento: 165.668,75

Principal Investigator: Andrea Marongiu 

Componenti gruppo di ricerca (UniMoRe): 

Partners:

Biodegradable thin film electronics for massively deployable and sustainable internet of Things applications

Progetto di rilevante interesse nazionale (PRIN)2022

Abstract

In 2019, the world generated 53.6Mt of electronic waste (e-waste), of which less than 20% are documented to be recycled. This e-waste is expected to increase with a rate of 6.5% yearly. In parallel, the energy-intensive fabrication of the Integrated Circuit (IC) industry is responsible for a dramatic increase of resource consumption (x5 water in the last decade) and of CO2 emission (about x2 from 2019). This picture is further being exacerbated by the Internet of Things (IoT) scenario that foresee the deployment of trillions of interconnected electronic devices. Sustainable electronics is a new concept that accounts for the environmental, social, and economic impact of electronic devices through the entire life cycle to reduce natural resources and CO2 footprint. The implementation of such new concept articulates along four main pathways: (i) eco-design that incorporates environmental requirements into the specifications; (ii) research of new sustainable materials; (iii) efficient manufacturing (net-zero production); (iv) efficient recycling. Within this context, and for certain applications biodegradable thin-film transistor (TFT) technology has emerged as a viable alternative to the resource-intensive manufacturing by simplifying the processes and to the uncontrolled increase of e-waste by ensuring efficient recycling. Among the TFT technologies, the one based on amorphous oxide semiconductor (a-IGZO), which is the backbone of active matrix displays, has been recently proposed by IMEC, TNO, ARM, PragmatIC, and academic research groups, with contributions from the PI and co-PI, for the realization of sustainable Radiofrequency (RF) circuits, e.g., RF identification tags. Its simplified manufacturing process requires a 100x lower energy and water consumption and results in a 1000x lower CO2 equivalent footprint (per area) with respect to silicon CMOS technology. Moreover, today TFTs operate above hundreds of MHz with long-term operational stability, prospecting large-scale integrated circuits. Such improvements in the manufacturing and device engineering have not yet been paired by progress in revising the constituent materials, that remain non-biodegradable. One critical example is polyimide (used as substrate and encapsulant), whose degradation in the environment requires centuries. The proposed research targets three main objectives: (i) study the biocompatibility and biodegradation of a-IGZO, selected 2D semiconductors, and biofilms derived from the upcycling of fish waste; (ii) develop models and simulation tools to support material selection, device optimization, and performance prediction for biodegradable circuits; (iii) fabricate fully biodegradable TFTs and basic digital/analog circuits. The project promises to set the foundations of the next leap in thin film electronics for biodegradable RFID tags and sustainable IoT.

Durata: 2023-2025

Finanziamento: 54.031,00

Principal Investigator: Alice Ruini

Componenti gruppo di ricerca (UniMoRe): Giuseppe Cantarella

Partners: Università "Ca' Foscari" VENEZIA, Libera Università di Bolzano.

AI-TEM Artificial Intelligence enhanced Transmission Electron Microscopy for advanced imaging

Progetto di rilevante interesse nazionale (PRIN)2022

Abstract

Durata: 2023-2025

Finanziamento: 77.209,00

Principal Investigator: Marco Beleggia

Componenti gruppo di ricerca (UniMoRe): 

Partners:

TUNing the Electronic Structure of graphene from low to high electron doping (TUNES)

Progetto di rilevante interesse nazionale (PRIN)2022

Abstract

Durata: 2023-2025

Finanziamento: 77.059,00

Principal Investigator: Valentina De Renzi

Componenti gruppo di ricerca (UniMoRe): 

Partners: 

Simultaneous electrical control of spin and valley polarization in van der Waals magnetic materials (SECSY)

Progetto di rilevante interesse nazionale (PRIN)2022

Abstract

The ever-increasing demand for high-speed, high-density, and low-power electronic components has stimulated the scientific community to identify new paradigms to achieve information processing and communication. Interesting scenarios have emerged from operating on degrees of freedom of the electrons in materials other than their charge, leading to spintronics, and, more recently, to valleytronics. In the latter, it is the momentum of one of the equivalent pockets (so-called valleys) in the Brillouin zone to which the electron/hole belongs that plays the role of a pseudospin variable. Although early investigations date back to the 1970s, the field has only recently been revolutionized by the discovery of two-dimensional (2D) materials, which offer unprecedented opportunities to control and manipulate valleys. Much of this success arises from spin-valley locking, by which different valleys are endowed with a specific spin polarization, enhancing both spin and valley coherence times. Three recent major breakthroughs have the potential to further expand the range of spin-valleytronic phenomena enabled by 2D materials: the isolation of 2D magnets, the identification of an extensive portfolio of novel monolayers from computational exfoliation, and the combinatorially vast opportunities offered by stacking 2D materials into van der Waals (vdW) heterostructures. 

SECSY aims at capitalizing on these developments by combining the internationally recognized expertise of the partners in materials design, theoretical modeling, high-throughput calculations, and efficient device simulations towards the identification of promising materials platforms for spin-valleytronics, addressing in particular the pressing need to achieve a fully electrical control of the locked spin and valley degrees of freedom. Two classes of systems will be investigated: single layer antiferromagnets and magnet-semiconductor-magnet vdW heterostructures. In the first case, spin-valley locking arises either from spin-orbit coupling or from a recently discovered subtle interplay between exchange interactions and crystal fields. We will extend the design principles to identify such altermagnets also in 2D, and explore materials’ databases through accurate first-principles simulations to find viable materials realizations. In the second case, spin and valley are coupled through a valley-Zeeman effect in the semiconductor, further affected by the proximity to the magnetic layers. Materials combinations will be identified by data-mining and high-throughput calculations, eventually validated against many-body effects. In both cases, we envision realistic pathways to tune the spin-valley polarization through a vertical, gate-induced, electric field. The range of possible applications of these materials platforms will be investigated by multiscale device simulations that we plan to accelerate by developing an innovative formulation based on hybrid Wannier functions.

Durata: 2023-2025

Finanziamento: 79.634,00

Principal Investigator: Marco Gibertini

Componenti gruppo di ricerca (UniMoRe): 

Partners: Università di Trieste, Università di Pisa.

Tribo-Electricity: a New Route for Tribology (TRIEL)

Progetto di rilevante interesse nazionale (PRIN)2022

Abstract

We propose to employ a synergistic mixture of state-of-the-art methods consisting in ab-initio and semi-classical simulations, atomic-force microscopy, and meso-/macro-scopic experimental apparatuses, to investigate tribo-electricity (TE), one of the most relevant frictional phenomenon connected to electronic effects. While recent experiments reported a very large impact of electron kinetic and excitations on the measured friction, in some caseseven dominant, there is presently a dramatic lacking of understanding about the physical mechanisms therein involved. This is due to the past limited methodologies and limited computational resources, which have prevented so far the possibility to study such phenomena at the appropriate lenght scales and timescales. We want to tackle this problem by a parallel of theoretical and experimental studies on a set of TE-relevant interfaces, in order to provide a model for the induced tribo-current as a function of working conditions such as interfacial pressure and sliding speed. From a theoretical point of view, such research is timely and necessary in order to advance from a mechanical to a quantum-mechanical description of friction. The theoretical methods established in TRIEL will permit to describe a multitude of quantum-tribological phenomena, and to quantify their contribution to the total friction. Experimentally, the project is conceived in order to bridge the gap between the single-contact TE response obtained by nano-probes and the multi-contact one originating from macroscopic interfaces in ambient conditions. Such strategy will permit the mutual validation of theoretical and experimental approaches, each providing a different layer of information about the TE process. In this respect, one envisaged result of the project will be the establishment of a predictive framework for the sake of an improved efficiency and lifetime of TE devices. The here proposed research line is directed to a vast amount of practical applications: the possibility of efficiently producing green energy from friction could be employed to realize truly self-powered devices such as micro sensors and actuators. Moreover, the knowledge and experience attained with TRIEL could trigger future research to tackle the many open questions emerging from the new field of ‘Quantum Tribology’.

Durata: 2023-2025

Finanziamento: 93.634,00

Principal Investigator: Alberto Rota

Componenti gruppo di ricerca (UniMoRe): Enrico Gualtieri, Antonio Ballestrazzi

Partners: Università di Milano, CNR.

Understanding Quantum Field Theory through its Deformations

Progetto di rilevante interesse nazionale (PRIN)2022

Abstract

The laws describing the natural world's most fundamental features are based on the paradigm of Quantum Field Theory (QFT). Yet, our understanding of QFT itself is mostly limited to free theories and to small deformations around those. In particular, the presence in a QFT of an operator which is irrelevant (in the sense of the renormalisation group) is usually not good news for the high-energy physics of the model. Perturbing a field theory with irrelevant operators can drastically affect the model's ultraviolet properties and introduce new fundamental degrees of freedom at high energy.

A class of exactly-solvable irrelevant deformations known as T-Tbar-type deformations was recently introduced. It allows to fully characterise an infinite-dimensional space of quantum field theories with specific symmetries, at least in a particular low-dimensional setup.

T-Tbar-type perturbations are solvable: physical observables of interest, such as the S-matrix and the finite-volume spectrum, can be easily found in terms of the corresponding undeformed quantities. For these perturbations, we can reverse the renormalisation group trajectory and gain exact information about ultraviolet physics. The outcome is stunning: while the low-energy physics resembles a conventional local quantum field theory, at high-energy the density of states on a cylinder shows Hagedorn growth similar to that of a string theory.

Over the last five years, these initial observations stimulated considerable activity in conformal and integrable QFTs, string theory and quantum gravity, leading to hundreds of scientific publications and a series of international conferences in Israel, the United States, Italy, and South Korea.

The aim of this project is to study the properties of this family of irrelevant perturbations of classical and quantum field theories and their connections with gravity, strings and AdS/CFT to gain insight on fundamental features of quantum field theory and quantum gravity.

Durata: 2023-2025

Finanziamento: 65.600,00

Principal Investigator: Rouven Frassek

Componenti gruppo di ricerca (UniMoRe): -

Partners: University of Parma, University of Turin.

Inverse Problems in the Imaging Science (IPIS)

Progetto di rilevante interesse nazionale (PRIN) 2022

Abstract

IPIS proposes to gather five research groups of applied mathematicians with two strategic objectives:

• In the short term, to push forward the state-of-the-art of imaging sciences, with specific focus on approaches inspired by inverse problems (IPs) theory.

• In the medium term, to make the IPIS network as a first embryo for a computational imaging center, diffused across Italy and open to contributions from all mathematicians interested in imaging applications.

Mathematical approaches to imaging sciences are currently of two kinds: data-driven machine learning (ML) searches for hidden correlations among data, exploiting highly populated historical databases; model-driven inverse problems theory explicitly accounts for the mathematical model of signal formation and is particularly reliable in applications where large training sets are not available. IPIS aims at integrating these two paradigms by exploiting physical forward models to describe data generation, and prior models to identify data descriptors and decrease the conditioning of the numerical problem.

Besides representing a framework for the development of basic research in mathematical imaging, IPIS is also an application-oriented proposal, where the computational techniques of the methodological WPs will be mainstreamed into an application WP devoted to four imaging modalities: linear and non-linear tomographies, optical imaging, Fourier-based imaging, and parametric imaging. Further, two specific WPs will work at the implementation and validation of software tools, and at their showcasing across the scientific community, via a dissemination campaign based on an open-source, open-data strategy.

Durata: 2023-2025

Finanziamento: 40.650,00

Principal Investigator: Silvia Bonettini

Componenti gruppo di ricerca (UniMoRe): Daniele Funaro, Danilo Pezzi

Partners: Università di Genova, Università dell’Insubria, Università di Bologna, Università di Cagliari.

Emergence of condensation-like phenomena in interacting particle systems: kinetic and lattice models

Progetto di rilevante interesse nazionale (PRIN)2022

Abstract

Durata: 2023-2025

Finanziamento: 96.945,00

Principal Investigator: Gioia Carinci

Componenti gruppo di ricerca (UniMoRe): 

Partners:

STILE: Sustainable Tomographic Imaging with Learning and rEgularization

Progetto di rilevante interesse nazionale (PRIN) 2022

Abstract

Modern medical practice crucially relies on biomedical imaging, of which Computerized Tomography (CT) is a central pillar. Traditional CT uses a series of X-ray projections, post-processed by computer algorithms, to produce cross sectional illustrations of the inside of the body. While the results are very effective, the main drawback of X-ray CT is the harmful effect of radiations on the human body. The present project focuses on a main path of innovation in CT: reduction of patient exposure to radiation. Specifically, we will investigate mathematical and computational themes arising from the emerging technologies of: a) low-dose Computed Tomography (LD-CT), based on a reduced radiation dose per projection and/or a reduced number of projections; b) zero-dose CT, based on non-ionizing investigating signals such as light in Diffuse Optical Tomography (DOT). In both cases, the reduced ionizing exposure comes at the price of a much noisier/subsampled signal, so that the associated reconstruction problems are severely ill-posed and require advanced mathematical and numerical techniques for adequate treatment.

Durata: 2023-2025

Finanziamento: 76.421,00

Principal Investigator: Marco Prato

Componenti gruppo di ricerca (UniMoRe): Mauro Leoncini, Roberto Cavicchioli, Danilo Pezzi

Partners: Università di Milano, Università di Bologna.

Boltzmann Machines beyond the “independent identically distributed” Paradigm: a Mathematical Physics Approach

Progetto di rilevante interesse nazionale (PRIN) 2022

Abstract: 

The project plans to go beyond the paradigm of independent identically distributed(i.i.d.) disorder that the theory of complex systems has followed so far. From itsbirth in the mid seventies, to the Parisi theory of the spin glass, up to the recentrigorous mathematical results, such theory has been mostly developed with thehypothesis of i.i.d. random variables appearing in the Hamiltonian function. Whilesuch a framework represents a natural and physically motivated starting point toinvestigate magnetic alloys, nowadays the most striking applications of disorderedsystems, such as those coming from machine learning and inference, require to gobeyond. Machine learning indeed, or more generally a high dimensional statisticalinference task, can be interpreted as the solution of a statistical mechanics systemof interacting particles with random parameters, usually called Boltzmann Machine.The data, represented by a suitable distribution, is in fact mapped into a distributionof those parameters that in general have no reason to be neither independent noridentically distributed.

Durata: 2023-2025

Finanziamento: 100.030,00

Principal Investigator: Cecilia Vernia

Componenti gruppo di ricerca (UniMoRe): Dott. Francesco Casini, Prof. Claudio Giberti.

Partners: Università di Bologna.

Numerical Optimization with Adaptive Accuracy and Applications to Machine Learning

Progetto di rilevante interesse nazionale (PRIN)2022

Abstract

A large variety of real-life problems can be modeled as continuous optimization problems. Moreover, the technological advances of recent years have highlighted not only the need of storing huge amounts of data, but also of analyzing them to extract useful information. Thus, continuous numerical optimization plays a fundamental role in the solution of large-scale problems arising in many fields, such as machine learning, in all the applications of everyday life.

The high dimensionality of the problems requires ad-hoc numerical methods, able to deal with huge datasets and based either on approximation techniques, such as inexact evaluations or regularizations of functions in a deterministic framework , or on stochastic models, exploiting data redundancy and integral or flow-based representations. These methods share the idea that inexact solvers must be used to tackle difficulties such as high dimensionality, uncertainty, ill posedness, ill conditioning, multiple scales, sparsity, and thus they include deterministic and stochastic methods, hybrid methods (combining deterministic, stochastic and heuristic approaches), multiscale methods, etc., all using adaptive accuracy.

The project has the ambition of proposing, in a unifying framework, numerical optimization algorithms with adaptive accuracy for efficiently solving a variety of problems in the curse of dimensionality, non-convexity and/or non-smoothness, which share the aforementioned difficulties.

Durata: 2023-2025

Finanziamento: 55.009,00

Principal Investigator: Luca Zanni

Componenti gruppo di ricerca (UniMoRe): Federica Porta, Andrea Magnani, Elisabetta Benedetti

Partners: Università degli Studi di Napoli Federico II, Università degli Studi della Campania "Luigi Vanvitelli", Università degli Studi di Firenze.

Simplifying Predictable and energy-efficient Acceleration from Cloud to Edge (SPACE)

Progetto di rilevante interesse nazionale (PRIN)2022

Abstract

Durata: 2023-2025

Finanziamento: 154.209,00

Principal Investigator: Andrea Marongiu

Componenti gruppo di ricerca (UniMoRe): 

Partners:

Tight control of treatment efficacy with tElemedicine for an improved Management of Patients with hemOphilia

Progetto di rilevante interesse nazionale (PRIN)2022

Abstract

Hemophilia A and B are rare bleeding disorders due to coagulation factor VIII (FVIII) and FIX deficiency, respectively. Repeated joint bleeding (hemarthrosis) leads to chronic arthropathy, disability, and early prosthetic surgery. Indeed, bleeding can be prevented by regular prophylactic treatment, although adherence is often suboptimal, in particular in young adults. Annual bleeding rate (ABR) has been traditionally used as an outcome measure of treatment efficacy, although it is a patient-reported outcome and there is evidence that patients often report as bleeding events also joint pain episodes due to chronic arthropathy. In addition, bleeding may even occur in asymptomatic joints. Therefore, a definite diagnosis of hemarthrosis is pivotal and a personalized management is warranted to avoid overtreatment or undertreatment. To date, a definite diagnosis of hemarthrosis can be confirmed by ultrasound or arthrocentesis at the Hemophilia Treatment Center (HTC).

On this background, we will develop a home-based integrated system for patient adherence to treatment by active assistance with reminders and collection of data on spontaneous and post-traumatic bleeding events, quality of life, productivity and pain through the use of a mobile application and wearable sensors to monitor physical activity. In a subgroup of patients, an exploratory study will be conducted with a portable wireless ultrasound probe compatible with smartphones and tablets. A user-friendly mobile app will guide the patient in the collection of images that will be transferred to the HTC. A computer-assisted diagnosis (CAD) tool prototyped by our research team will support physicians in providing the patient a quick response. Aim of the TEMPO study is to investigate the feasibility, acceptability and sustainability of such telemedicine system and to evaluate its efficacy in improving adherence to treatment; to explore the feasibility of integrating patient-based joint ultrasound assessment; and to pave the way for a personalized management in contrast with a “one-size-fits all” model. The ultimate goal is to improve patients’ quality of life, while also reducing disease burden. Moreover, we will explore beyond state of the art approaches to further improve the efficacy of at home sensors and devices in tackling spontaneous or traumatic bleeding.

Durata: 2023-2025

Finanziamento: 97.379,00

Principal Investigator: Luca Bedogni

Componenti gruppo di ricerca (UniMoRe): Luca Bedogni, Francesco Franco

Partners: Università di Milano, Centro Nazionale delle Ricerche.

Binders with high iONIc Conductivity for fully sustainable Li-ion cells (BIONIC)

Progetto di rilevante interesse nazionale (PRIN)2022

Abstract

Durata: 2023-2025

Finanziamento: 92.861,00

Principal Investigator: Rita Magri

Componenti gruppo di ricerca (UniMoRe): 

Partners:

Molecular networks and cell biophysical properties influencing gene expression leading to tumor cell proliferation and invasion: role of DDB2 and PCNA

Progetto di rilevante interesse nazionale (PRIN)2022

Abstract

Among the typical hallmarks of cancer cells, the high proliferative rate, the genome instability and the acquisition of metastastic properties, contribute significantly to the progression of the disease. However, due to the complexity and variety of cancer types, the molecular mechanisms determining tumor progression and invasive potential are still not completely understood. The DNA Damage Binding 2 (DDB2) is a protein participating in Nucleotide Excision Repair (NER), by forming with DDB1 a heterodimeric complex involved in the recognition of UV-induced DNA lesions (1,2,3). Mutations in DDB2 gene determine the genetic disease Xeroderma pigmentosum of group E (XP-E) (1), which is characterized by NER deficiency and a high risk to develop malignant skin tumors (4). Consistently, DDB2-deficient mice frequently develop spontaneous malignant tumors (4, 5). DDB2 is a multifunctional protein also involved in the regulation of the cell cycle inhibitor p21(CDKN1A), thereby inducing apoptosis after DNA damage (6). In addition, DDB2 interacts with the transcriptional co-activators CBP/p300, and with STAGA complex (7,8), and is a co-factor of the transcription factor E2F1 (9). DDB2 plays a tumor suppressor function by repressing key factors of the epithelial-to-mesenchimal transition (EMT), and probably also by modulating cell adhesion mechanical properties (10, 11). However, DDB2 overexpression has been found in tumors, such as head and neck, renal, melanoma and cervical cancers (Protein Atlas), suggesting that this protein may promote cancer progression with a not well-defined mechanism. We have recently discovered that DDB2 interacts with PCNA, a master regulator of several processes, including DNA replication, repair, transcription, as well as cell cycle and survival. Interestingly, a DDB2 mutant unable to interact with PCNA (DDB2/PCNA-) is NER deficient, confers a proliferative advantage and promotes cell motility (12). However, the contribution of PCNA to DDB2 activity in tumors, and the relevance of its failure, are still unclear. The goal of this project is to identify new molecular network comprising DDB2 and PCNA, which may help dissecting gene expression pathways leading to increased cell proliferation and acquisition of invasion ability in these tumors. In particular, specific aims are: i) to define the DDB2 interactome, and the role of PCNA in this network; ii) to analyze the whole exome of cells expressing the DDB2(PCNA-) mutant form, and investigate whether DDB2 may influence gene expression through PCNA interaction; iii) to assess biophysical properties of cells expressing DDB2wt and DDB2(PCNA-) forms, in order to understand how mechanical aspects may influence the gene expression profile, DNA damage response and migration properties of these cells. This study will be important to identify new pathways of tumor formation involving DDB2 and PCNA, and to find new chemotherapy approaches to counteract this activity.

Durata: 2023-2025

Finanziamento: 64.893,00

Principal Investigator: Andrea Alessandrini

Componenti gruppo di ricerca (UniMoRe): Andrea Alessandrini

Partners:  Dipartimento di Medicina molecolare, Unità di Immunologia e Patologia generale, Università di Pavia; Istituto di Genetica Molecolare “Luigi Luca Cavalli-Sforza”,
Consiglio Nazionale delle Ricerche, Pavia.

Protein function from disorder. Insight from single molecule optical tweezers, physical models, and computation

Progetto di rilevante interesse nazionale (PRIN)2022

Abstract

Durata: 2023-2025

Finanziamento: 111.291,00

Principal Investigator: Ciro Cecconi

Componenti gruppo di ricerca (UniMoRe): 

Partners:

Chiral quantum walks for enhanced energy storage, transport and routing (QWEST)

Progetto di rilevante interesse nazionale (PRIN)2022 PNRR

Abstract

Quantum technology is a rapidly expanding field of physics and engineering, encompassing technologies that rely on genuine quantum properties of radiation and matters to realize protocols to process information more effectively than their classical counterparts. Quantum features of physical systems may also be exploited to improve the production, transport, storage and conversion of energy in large scale networks. This project aims to systematically investigate the conditions in which quantum features represent a resource to build an affordable, reliable, sustainable, and modern energy ecosystem. In order to provide general results, we exploit the paradigm of quantum walks to model quantum energy networks, and address the use of quantum superpositions, interference, and chirality to design schemes for enhanced energy transmission, routing, storage, and conversion and to assess whether situations exist where noise actually enhances energy management without losing quantum advantages.

Durata: 2023-2025

Finanziamento: 72.000,00

Principal Investigator: Paolo Bordone

Componenti gruppo di ricerca (UniMoRe): Paolo Bordone, Simone Cavazzoni, Gaia Forghieri, Giovanni Ragazzi.

Partners: Università degli Studi di Milano.

Advanced optimization METhods for automated central veIn Sign detection in multiple sclerosis from magneTic resonAnce imaging (AMETISTA)

Progetto di rilevante interesse nazionale (PRIN)2022 PNRR

Abstract

Durata: 2023-2025

Finanziamento: 112.322,00

Principal Investigator: Federica Porta

Componenti gruppo di ricerca (UniMoRe): 

Partners:

Metal clusters decoration of Borophene nanostructures with enhanced Hydrogen adsorption and release properties (HYBORON)

Progetto di rilevante interesse nazionale (PRIN)2022 PNRR

Abstract

The present proposal titled “Metal clusters decoration of Borophene nanostructures with enhanced Hydrogen adsorption and release properties”, hereafter referred as HYBORON will aim at the synthesis of Borophene (BPH) and decoration with metallic nanoparticles. BPH will be fabricated in different nanostructures from mono to multilayer and from nanotubes to clusters, and will be combined with metallic clusters and thin films deposited on Si wafers. On these systems we shall perform microscopy (STM and TEM) and spectroscopy studies (electrons, raman) also at synchrotron radiation laboratories. Spectroscopic measurements will be cross-checked to ab-initio calculations of density of states close to the Fermi Edge of the as-grown materials. The aim will be to prove the predicted outperforming BPH -Ti physisorption action able to adsorb H2 molecules through the exposure to surfaces of well defined crystallographic orientation by a fraction larger than 10%, while few tens of meV binding energy will guarantee such molecules to be released under heating at ambient pressure. From such a system the hydrogen storage applications will greatly benefit surpassing the targets envisaged by United States Dept. of Energy on gravimetric density (4.5 wt% ) and volumetric capacity (30g/L) in automotive applications. The project will be conveniently divided in 5 workpackages (WP) : 1) CVD borophene will be deposited on substrates coated with Al or other metal films and decorated by Ti nanostructures. 2) Reversely, functionalized substrates by deposition of metallic clusters will be coated by BPH few layers deposited on the differently oriented crystalline facets. 3) The third WP will be dedicated to the variable temperature STM microscopy with the aim to achieve, especially in the case of the 2D single layer-BPH the atomic resolution and fundamental interaction of B with metal atoms, in close connection with High resolution TEM at the UNIMORE laboratory. 4) Fourth WP will be dedicated to spectroscopy in-situ study of H2 dosed as-grown nanocluster samples and will include spectro-microscopy characterization making use of synchrotron radiation facilities. 5) The fifth WP will be in charge of the close comparison between photoemission, Auger and Raman experimental results with the calculations of the formation energy values obtainable from structural chemistry simulation, using density functional methods. Furthermore, the calculations will confirm the structural model obtained from the microscopy studies. The results will be able to confirm the physisorption/chemisorption action of the material, the diffusion coefficients and binding energies of the system before and after H uptake and put it in relation with the calculated density of states.

Durata: 2023-2025

Finanziamento: 75.000,00

Principal Investigator: Sergio D’Addato

Componenti gruppo di ricerca (UniMoRe): Sergio D’Addato

Partners: UniCAM, UniTOV.

Opto-mechanical effects in spin-defects for quantum technologies

Progetto di rilevante interesse nazionale (PRIN)2022 PNRR

Abstract

Durata: 2023-2025

Finanziamento: 149.277,00

Principal Investigator: Marco Govoni

Componenti gruppo di ricerca (UniMoRe): 

Partners:

Integrable spin chains: Fundamentals, stochastic processes and supersymmetric gauge theories

FAR interdisciplinare 2023

Abstract

This scientific project concerns the study of the fundamental structures of integrable spin chains, their relations to supersymmetric gauge theories and stochastic particle processes. The major research theme concerns the development of the theory of non-compact spin chains and Baxter Q-operators for the Yangian of simple Lie algebras, their supersymmetric extensions and q-deformations. The proposed research finds its application in two seemingly unrelated scientific-disciplinary fields in the domain of theoretical physics which surprisingly share some common mathematical structures: the AdS/CFT correspondence and non-equilibrium statistical mechanics. More precisely, within the first field, we will provide a derivation of the fundamental structures (QQ-system) underlying the Fishnet CFT and N=6 super Chern-Simons theory (ABJM) that may ultimately lead to the non-perturbative formulation of the supersymmetric gauge theories. Within the second field, we will define a novel family of integrable stochastic particle process that naturally extend the key examples of the Symmetric Simple Exclusion Process (SSEP) and Asymmetric Simple Exclusion Process (ASEP) with reservoirs by allowing for an unbounded number of particles and species at each site. We plan to solve these models using integrability methods by relating them to the corresponding process in equilibrium. This will yield the steady state and the full spectrum of the non-equilibrium systems.

Durata: 2023-2025

Finanziamento: 79.346,00

Principal Investigator: Rouven Frassek

Componenti gruppo di ricerca (UniMoRe): Cristian Giardina, Diego Trancanelli

Partners: -