Interface and bulk superconductivity in superconducting heterostructures with enhanced critical temperatures

We consider heterostructures obtained by stacking layers of two s-wave superconductors with significantly different coupling strengths, respectively in the weak- and strong-coupling regimes. The weak- and strong-coupling superconductors are chosen with similar critical temperatures for bulk systems. Using dynamical mean-field theory methods, we find an ubiquitous enhancement of the superconducting critical temperature for all the heterostructures where a single layer of one of the two superconductors is alternated with a thicker multilayer of the other. Two distinct physical regimes can be identified as a function of the thickness of the larger layer: (i) an inherently inhomogeneous superconductor characterized by the properties of the two isolated bulk superconductors where the enhancement of the critical temperature is confined to the interface and (ii) a bulk superconductor with an enhanced critical temperature extending to the whole heterostructure. We characterize the crossover between these regimes in terms of the competition between two length scales connected with the proximity effect and the pair coherence.Comment: 7 pages, 4 figure

Mass-driven vortex collisions in flat superfluids

Quantum vortices are often endowed with an effective inertial mass, due, for example, to massive particles in their cores. Such “massive vortices” display new phenomena beyond the standard picture of superfluid vortex dynamics, where mass is neglected. In this work, we demonstrate that massive vortices are allowed to collide, as opposed to their massless counterparts. We propose a scheme to generate controllable, repeatable, deterministic collisional events in pairs of quantum vortices. We demonstrate two mass-driven fundamental processes: (i) the annihilation of two counter-rotating vortices and (ii) the merging of two corotating vortices, thus pointing out new mechanisms supporting incompressible-to-compressible kinetic-energy conversion, as well as doubly quantized vortex stabilization in flat superfluids

Green Approach for Joint Management of Geo-Distributed Data Centers and Interconnection Networks

Every time an Internet user downloads a video, shares a picture, or sends an email, his/her device addresses a data center and often several of them. These complex systems feed the web and all Internet applications with their computing power and information storage, but they are very energy hungry. The energy consumed by Information and Communication Technology (ICT) infrastructures is currently more than 4\% of the worldwide consumption and it is expected to double in the next few years. Data centers and communication networks are responsible for a large portion of the ICT energy consumption and this has stimulated in the last years a research effort to reduce or mitigate their environmental impact. Most of the approaches proposed tackle the problem by separately optimizing the power consumption of the servers in data centers and of the network. However, the Cloud computing infrastructure of most providers, which includes traditional telcos that are extending their offer, is rapidly evolving toward geographically distributed data centers strongly integrated with the network interconnecting them. Distributed data centers do not only bring services closer to users with better quality, but also provide opportunities to improve energy efficiency exploiting the variation of prices in different time zones, the locally generated green energy, and the storage systems that are becoming popular in energy networks. In this paper, we propose an energy aware joint management framework for geo-distributed data centers and their interconnection network. The model is based on virtual machine migration and formulated using mixed integer linear programming. It can be solved using state-of-the art solvers such as CPLEX in reasonable time. The proposed approach covers various aspects of Cloud computing systems. Alongside, it jointly manages the use of green and brown energies using energy storage technologies. The obtained results show that significant energy cost savings can be achieved compared to a baseline strategy, in which data centers do not collaborate to reduce energy and do not use the power coming from renewable resources

Impact of treatment with dimethyl fumarate on sleep quality in patients with relapsing-remitting multiple sclerosis: A multicentre Italian wearable tracker study

BackgroundSleep disorders are common in patients with multiple sclerosis and have a bidirectional interplay with fatigue and depression. ObjectiveTo evaluate the effect of treatment with oral dimethyl fumarate on the quality of sleep in relapsing-remitting multiple sclerosis. MethodsThis was a multicentre observational study with 223 relapsing-remitting multiple sclerosis subjects starting treatment with dimethyl fumarate (n=177) or beta interferon (n=46). All patients underwent subjective (Pittsburgh Sleep Quality Index) and objective (wearable tracker) measurements of quality of sleep. Fatigue, depression, and quality of life were also investigated and physical activity was monitored. ResultsPatients treated with dimethyl fumarate had significant improvement in the quality of sleep as measured with the Pittsburgh Sleep Quality Index (p<0.001). At all-time points, no significant changes in Pittsburgh Sleep Quality Index score were observed in the interferon group. Total and deep sleep measured by wearable tracker decreased at week 12 with both treatments, then remained stable for the total study duration. Depression significantly improved in patients treated with dimethyl fumarate. No significant changes were observed in mobility, fatigue and quality of life. ConclusionIn patients with relapsing-remitting multiple sclerosis, the treatment with dimethyl fumarate was associated with improvements in patient-reported quality of sleep. Further randomised clinical trials are needed to confirm the benefits of long-term treatment with dimethyl fumarate

FIRB "SQUARE" project: nano-structured sensors for the detection of the polluting in engine exhaust gases and for indoor air quality monitoring

The present work is a final dissemination of activities carried out and main results obtained in the national founded project Firb "Square". The project is leaded by Centro Ricerche Fiat and it involves the most qualified national public Research Institutes and Universities active in the fields of nanomaterials synthesis, nanotechnology and gas sensors development

Il farmaco: ricerca, sviluppo e applicazione in terapia

[Italiano]:Il farmaco: ricerca, sviluppo e applicazione in terapia si propone l’obiettivo di offrire una panoramica sul processo di Ricerca e Sviluppo che un farmaco compie a partire dal momento in cui viene progettato fino alla sua pratica utilizzazione. Quando una molecola è ritenuta potenzialmente adatta per creare un medicinale, si attiva un lungo percorso che ha come traguardo la realizzazione di un nuovo mezzo terapeutico e la sua approvazione per l’immissione in commercio. Un percorso scandito dalla rigorosa osservanza di regolamenti e leggi che si sono evoluti nel tempo di pari passo con il progresso scientifico e tecnologico, ma spesso anche a seguito di reazioni avverse o eventi dannosi irreversibili che hanno innescato processi di revisione delle norme e dei protocolli sperimentali. Questo libro parte con una densa ricognizione sulla storia della farmacologia occidentale, al fine di agevolare la comprensione del coacervo di vicende e circostanze che nel tempo hanno fatto da sfondo a tutte quelle dinamiche attraverso cui il processo di Ricerca e Sviluppo si è gradualmente affermato e consolidato. Notevole attenzione è stata poi dedicata ad alcuni risvolti divenuti oramai cruciali all’interno dell’articolato universo normativo in cui il farmaco è collocato, quali le terapie avanzate e i nuovi approcci per la ricerca clinica. Inoltre, gli autori si sono concentrati sulla prescrizione dei cosiddetti off-label e sulle tematiche di farmacoutilizzazione e farmacovigilanza che, nel giro di pochi decenni, sono assurte a sfere di conoscenza sempre più significative e influenti nelle prospettive presenti e future, non solo delle scienze farmaceutiche ma dell’intera società. Lo sforzo compiuto per redigere questo volume trova la sua ragion d’essere proprio nel voler mettere a disposizione dei lettori uno sguardo d’insieme sul farmaco e sulle complesse sfide che ancora lo attendono./ [English]:“The drug: research, development and application in therapy” is an in-depth study on the Research and Development process that a drug performs from the moment it is designed up to its practical use. When a molecule is considered suitable for a medicine, a long process is activated which has as its goal the creation of a new therapeutic tool and its approval for marketing. A path marked by the strict observance of regulations and laws that have evolved over time in step with scientific and technological progress. A path that however has often been determined also by tragic events following damaging adverse reactions that have triggered processes of revision of the norms and experimental protocols. This book starts with a summary on the history of Western pharmacology, written to allow the reader to understand the circumstances that have been the background to those dynamics through which the Research and Development process has gradually consolidated. An important part of the book is dedicated to some aspects that are crucial in the normative universe in which the drug is placed, such as the advanced therapies and new approaches for clinical research. The authors also focused on the prescriptions of off-label drugs and on the issues of pharmacoutilization and pharmacovigilance, two disciplines that, in a few years, have become increasingly influential in the present and future perspectives, not only of the pharmaceutical sciences but of the entire society

Preliminary Assessment of Radiolysis for the Cooling Water System in the Rotating Target of {SORGENTINA}-{RF}

The SORGENTINA-RF project aims at developing a 14 MeV fusion neutron source featuring an emission rate in the order of 5-7 x 10(13) s(-1). The plant relies on a metallic water-cooled rotating target and a deuterium (50%) and tritium (50%) ion beam. Beyond the main focus of medical radioisotope production, the source may represent a multi-purpose neutron facility by implementing a series of neutron-based techniques. Among the different engineering and technological issues to be addressed, the production of incondensable gases and corrosion product into the rotating target deserves a dedicated investigation. In this study, a preliminary analysis is carried out, considering the general layout of the target and the present choice of the target material

Architecture and performance of the KM3NeT front-end firmware

The KM3NeT infrastructure consists of two deep-sea neutrino telescopes being deployed in the Mediterranean Sea. The telescopes will detect extraterrestrial and atmospheric neutrinos by means of the incident photons induced by the passage of relativistic charged particles through the seawater as a consequence of a neutrino interaction. The telescopes are configured in a three-dimensional grid of digital optical modules, each hosting 31 photomultipliers. The photomultiplier signals produced by the incident Cherenkov photons are converted into digital information consisting of the integrated pulse duration and the time at which it surpasses a chosen threshold. The digitization is done by means of time to digital converters (TDCs) embedded in the field programmable gate array of the central logic board. Subsequently, a state machine formats the acquired data for its transmission to shore. We present the architecture and performance of the front-end firmware consisting of the TDCs and the state machine

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches