High availability using virtualization - 3RC

High availability has always been one of the main problems for a data center. Till now high availability was achieved by host per host redundancy, a highly expensive method in terms of hardware and human costs. A new approach to the problem can be offered by virtualization. Using virtualization, it is possible to achieve a redundancy system for all the services running on a data center. This new approach to high availability allows the running virtual machines to be distributed over a small number of servers, by exploiting the features of the virtualization layer: start, stop and move virtual machines between physical hosts. The 3RC system is based on a finite state machine, providing the possibility to restart each virtual machine over any physical host, or reinstall it from scratch. A complete infrastructure has been developed to install operating system and middleware in a few minutes. To virtualize the main servers of a data center, a new procedure has been developed to migrate physical to virtual hosts. The whole Grid data center SNS-PISA is running at the moment in virtual environment under the high availability system.Comment: 10 page

Raising awareness on gender issues: A path through physics, outreach and diversity.

When and where it is convenient to start working on raising awareness on gender issues? Our answer is that high school is definitely a good start, mainly if we think that outreach activities can have a role in the transition to an environment for learning, teaching and researching in physics that is equally attractive and supportive to all genders, at each stage of their education and career path. As researchers of INFN and CNR we promoted a school competition devoted to consider the role of women in science and particularly in Physics. Outreach activities can have the role of raising awareness, knowledge through an active involvement of students for changing the culture and removing stereotypes. In these years we organized 3 contests, with 226 videos, more than 100 high schools and a thousand of students involved. The idea was to try to understand the thinking and knowledge of young people on present and past gender issues connected to women and science, to know how they imagine the society of the future, to understand if they are unaware "carriers" of stereotypes and prejudices and if the cultural change can start from/with them. The students have been asked to produce a video on subjects regarding these questions. The article describes the contests, the evaluation process, the results of first analysis. The work started inside the EU-funded GENERA project, to which both research groups belong, and continues inside the GENERA Network. The collaboration among physicists and sociologists has been, and still is, fundamental in these years

ARIANNA: A research environment for neuroimaging studies in autism spectrum disorders

The complexity and heterogeneity of Autism Spectrum Disorders (ASD) require the implementation of dedicated analysis techniques to obtain the maximum from the interrelationship among many variables that describe affected individuals, spanning from clinical phenotypic characterization and genetic profile to structural and functional brain images. The ARIANNA project has developed a collaborative interdisciplinary research environment that is easily accessible to the community of researchers working on ASD (https://arianna.pi.infn.it). The main goals of the project are: to analyze neuroimaging data acquired in multiple sites with multivariate approaches based on machine learning; to detect structural and functional brain characteristics that allow the distinguishing of individuals with ASD from control subjects; to identify neuroimaging-based criteria to stratify the population with ASD to support the future development of personalized treatments. Secure data handling and storage are guaranteed within the project, as well as the access to fast grid/cloud-based computational resources. This paper outlines the web-based architecture, the computing infrastructure and the collaborative analysis workflows at the basis of the ARIANNA interdisciplinary working environment. It also demonstrates the full functionality of the research platform. The availability of this innovative working environment for analyzing clinical and neuroimaging information of individuals with ASD is expected to support researchers in disentangling complex data thus facilitating their interpretation

Preserving access to ALEPH computing environment via virtual machines

The ALEPH Collaboration [1] took data at the LEP (CERN) electron-positron collider in the period 1989-2000, producing more than 300 scientific papers. While most of the Collaboration activities stopped in the last years, the data collected still has physics potential, with new theoretical models emerging, which ask checks with data at the Z and WW production energies. An attempt to revive and preserve the ALEPH Computing Environment is presented, the aim is not only the preservation of the data files (usually called bit preservation), but of the full environment a physicist would need to perform brand new analyses. Technically, a Virtual Machine approach has been chosen, using the VirtualBox platform. Concerning simulated events, the full chain from event generators to physics plots is possible, and reprocessing of data events is also functioning. Interactive tools like the DALI event display can be used on both data and simulated events. The Virtual Machine approach is suited for both interactive usage, and for massive computing using Cloud like approaches

Ethanol-induced oxidative stress: basic knowledge

After a general introduction, the main pathways of ethanol metabolism (alcohol dehydrogenase, catalase, coupling of catalase with NADPH oxidase and microsomal ethanol-oxidizing system) are shortly reviewed. The cytochrome P450 isoform (CYP2E1) specifically involved in ethanol oxidation is discussed. The acetaldehyde metabolism and the shift of the NAD/NADH ratio in the cellular environment (reductive stress) are stressed. The toxic effects of acetaldehyde are mentioned. The ethanol-induced oxidative stress: the increased MDA formation by incubated liver preparations, the absorption of conjugated dienes in mitochondrial and microsomal lipids and the decrease in the most unsaturated fatty acids in liver cell membranes are discussed. The formation of carbon-centered (1-hydroxyethyl) and oxygen-centered (hydroxyl) radicals during the metabolism of ethanol is considered: the generation of hydroxyethyl radicals, which occurs likely during the process of univalent reduction of dioxygen, is highlighted and is carried out by ferric cytochrome P450 oxy-complex (P450–Fe3+O2·−) formed during the reduction of heme-oxygen. The ethanol-induced lipid peroxidation has been evaluated, and it has been shown that plasma F2-isoprostanes are increased in ethanol toxicity

ARIANNA: un Ambiente di Ricerca Interdisciplinare per l’Analisi di Neuroimmagini Nell’Autismo

I Disturbi dello Spettro Autistico (DSA) comprendono un gruppo eterogeneo di disturbi del neurosviluppo caratterizzati da alterazioni nelle abilità sociali e comunicative e dalla presenza di comportamenti e interessi ristretti e ripetitivi. Recenti studi epidemiologici hanno riportato una prevalenza di un caso ogni 68 nati negli Stati Uniti, molto più elevata rispetto alle precedenti stime, riconducibile ad un generale aumento di riconoscimento dei DSA, all’inclusione di forme più lievi e alla possibile influenza di fattori non-genetici. Nonostante i bambini con DSA abbiano mostrato di ottenere notevoli benefici da interventi precoci, quando la plasticità cerebrale è massima e l’influenza dell’ambiente può avere i maggiori benefici, la diagnosi precoce è ancora estremamente complessa. Infatti, sebbene alcuni aspetti comuni definiscano la condizione di DSA, i soggetti mostrano un’estrema eterogeneità nella severità dei sintomi, nelle funzioni adattive, cognitive e nelle abilità di linguaggio, oltre alla compresenza di ulteriori patologie medico/psichiatriche. Inoltre, una serie di altri disturbi del neurosviluppo possono manifestarsi con sintomi parzialmente sovrapponibili a quelli dei DSA e quindi devono essere presi in considerazione per la diagnosi differenziale. In questo complesso scenario i ricercatori stanno cercando di identificare dei biomarcatori in grado di favorire il riconoscimento precoce delle sue manifestazioni patologiche dei DSA, facilitarne la diagnosi precoce e gettare nuove luci sui meccanismi neurobiologici di questi disturbi. Le neuroimmagini, nonostante abbiano ancora una limitata utilità diagnostica, hanno già rivelato un ruolo fondamentale nella caratterizzazione dei DSA attraverso l’osservazione in vivo del coinvolgimento cerebrale in tali disturbi. Grazie al fatto che si tratta di tecniche non invasive, le immagini di risonanza magnetica cerebrale sono state usate in molti studi per rivelare anomalie nella volumetria di determinate aree del cervello (attraverso la risonanza magnetica di tipo strutturale), per identificare modelli ricorrenti di attività funzionale e di connettività tra diverse aree (attraverso la risonanza magnetica funzionale) e di connettività strutturale (attraverso le tecniche di risonanza magnetica pesate in diffusione). La complessità del problema impone la necessità di lavorare su ampie basi di dati, ben caratterizzati dal punto di vista clinico e dei dati di imaging. Pertanto sono essenziali studi collaborativi multicentrici, dal momento che la condivisione dei dati riduce la difficoltà di raccoglierne sufficienti quantità tali da permettere risposte statisticamente supportate ai vari quesiti scientifici. Tuttavia lavorare con ampie basi di dati esige corrispondenti approcci sufficientemente potenti dal punto di vista computazionale e la necessità di sviluppare algoritmi innovativi in grado di analizzare dati provenienti da diversi centri e di diversa tipologia. Infatti i dati multicentrici richiedono un processo di armonizzazione e strategie innovative per estrarre anche informazioni e relazioni nascoste, ma significative, tra i dati. Per affrontare queste sfide, il progetto ARIANNA (Ambiente di Ricerca Interdisciplinare per l’Analisi di Neuroimmagini Nell’Autismo) si propone di sviluppare un nuovo ambiente di ricerca dedicato allo studio delle neuroimmagini nell’ambito dei DSA. L’approccio innovativo di ARIANNA consiste nel separare durante uno studio di ricerca clinica le fasi di progettazione e acquisizione dei dati dall’analisi di questi ultimi. Le prime due fasi verranno condotte dai neuropsichiatri e dal personale esperto di acquisizione di immagini di risonanza magnetica, mentre la fase di analisi dei dati verrà affidata ad un gruppo dedicato. In particolare, il team di analisti dati ha sia le competenze nell’ambito delle tecniche più innovative di elaborazione di dati multicentrici e multi-modali sia l’accesso a risorse computazionali adeguate a gestire grandi quantità di dati. L’obbiettivo finale di ARIANNA è pertanto quello di rendere disponibile alla comunità scientifica dei neuroscienziati un sistema informatico, accessibile tramite web, in grado di raccogliere dati di imaging cerebrale con le relative informazioni cliniche e di offrire un servizio di analisi avanzato

The ASIMOV Prize for scientific publishing - HEP researchers trigger young people toward science

This work presents the ASIMOV Prize for scientific publishing, which was launched in Italy in 2016. The prize aims to bring the young generations closer to scientific culture, through the critical reading of popular science books. The books are selected by a committee that includes scientists, professors, Ph.D. and Ph.D. students, writers, journalists and friends of culture, and most importantly, over 800 school teachers. Students are actively involved in the prize, according to the best practices of public engagement: they read, review the books and vote for them, choosing the winner. The experience is quite successful: 12,000 students from 270 schools all over Italy participated in the last edition. The possibility of replicating this experience in other countries is indicated, as was done in Brazil in 2020 with more than encouraging results

Description and performance of track and primary-vertex reconstruction with the CMS tracker

A description is provided of the software algorithms developed for the CMS tracker both for reconstructing charged-particle trajectories in proton-proton interactions and for using the resulting tracks to estimate the positions of the LHC luminous region and individual primary-interaction vertices. Despite the very hostile environment at the LHC, the performance obtained with these algorithms is found to be excellent. For tbar t events under typical 2011 pileup conditions, the average track-reconstruction efficiency for promptly-produced charged particles with transverse momenta of p(T) > 0.9GeV is 94% for pseudorapidities of |η| < 0.9 and 85% for 0.9 < |η| < 2.5. The inefficiency is caused mainly by hadrons that undergo nuclear interactions in the tracker material. For isolated muons, the corresponding efficiencies are essentially 100%. For isolated muons of p(T) = 100GeV emitted at |η| < 1.4, the resolutions are approximately 2.8% in p(T), and respectively, 10μm and 30μm in the transverse and longitudinal impact parameters. The position resolution achieved for reconstructed primary vertices that correspond to interesting pp collisions is 10–12μm in each of the three spatial dimensions. The tracking and vertexing software is fast and flexible, and easily adaptable to other functions, such as fast tracking for the trigger, or dedicated tracking for electrons that takes into account bremsstrahlung