A Process Calculus for Expressing Finite Place/Transition Petri Nets

We introduce the process calculus Multi-CCS, which extends conservatively CCS with an operator of strong prefixing able to model atomic sequences of actions as well as multiparty synchronization. Multi-CCS is equipped with a labeled transition system semantics, which makes use of a minimal structural congruence. Multi-CCS is also equipped with an unsafe P/T Petri net semantics by means of a novel technique. This is the first rich process calculus, including CCS as a subcalculus, which receives a semantics in terms of unsafe, labeled P/T nets. The main result of the paper is that a class of Multi-CCS processes, called finite-net processes, is able to represent all finite (reduced) P/T nets.Comment: In Proceedings EXPRESS'10, arXiv:1011.601

Characterisation of Colour Components and Polymeric Pigments of Commercial Red Wines by Using Selected UV-Vis Spectrophotometric Methods

The composition of the colour components of commercial red wines from Italy was analysed in terms of total colour,co-pigmentation, SO2-resistant pigments, small and large polymeric pigments, and tannins. A total of 128 wines,including Sangiovese, Cabernet Sauvignon, Nero d’Avola, Merlot, Marzemino, Negroamaro, Aglianico, Cannonauand Rossese di dolceacqua from five vintages (1999 to 2003) were analysed. The composition of the wines showedsignificant differences in terms of total colour and co-pigmentation. Total colour at 520 nm was highest inMarzemino (7.50±1.5 AU, absorbance units), and then in Aglianico (7.10±2.8 AU) and Cabernet Sauvignon(5.01±2.50 AU). The level of large and small polymeric pigments in Sangiovese wines showed a range from 0.05 to0.40 and 0.10 to 0.27 AU 520 nm respectively. The variation in the level of polymeric pigments is affected by anumber of factors, including vintage, grape composition, fermentation and storage conditions

Search for a diffuse flux of cosmic neutrinos in the shower channel with the ANTARES telescope

ANTARES è il più grande telescopio di neutrini sottomarino in funzione al momento. Si trova nel Mar Mediterraneo, 40 km a largo di Tolone, Francia, ed è composto da 885 fotomoltiplicatori disposti lungo linee verticali ancorate sul fondo marino a 2475 m di profondità. L’obiettivo principale di ANTARES è l’osservazione di neutrini di alta energia di origine astrofisica. Il telescopio di neutrini IceCube, situato al Polo Sud, ha misurato negli ultimi anni un eccesso di neutrini di altissima energia (> TeV) rispetto al fondo atteso. Questo flusso proviene da sorgenti sconosciute e non risolvibili come sorgenti individuali. ANTARES può investigare questo eccesso sfruttando la complementarietà del suo campo di vista e le ottime capacità di ricostruzione direzionale ed energetica del rivelatore. Una ricerca di flussi diffusi di neutrini cosmici su tutto il cielo è presentata in questa tesi. In particolare si sfruttano gli eventi di tipo sciame per cui è possibile ottenere un’ottima risoluzione energetica, che permette di rigettare in maniera precisa il fondo dato da eventi atmosferici. Una catena di tagli per la selezione di un campione di eventi sufficientemente puro è definita nell’analisi. L’intero campione di dati raccolti da ANTARES tra il 2007 ed il 2013 è stato analizzato per questa analisi, producendo un osservazione di 7 eventi su un fondo atteso di 5±2

Round-Hashing for Data Storage: Distributed Servers and External-Memory Tables

This paper proposes round-hashing, which is suitable for data storage on distributed servers and for implementing external-memory tables in which each lookup retrieves at most one single block of external memory, using a stash. For data storage, round-hashing is like consistent hashing as it avoids a full rehashing of the keys when new servers are added. Experiments show that the speed to serve requests is tenfold or more than the state of the art. In distributed data storage, this guarantees better throughput for serving requests and, moreover, greatly reduces decision times for which data should move to new servers as rescanning data is much faster

Oii-web: An interactive online programming contest training system

In this paper we report our experience, related to the online training for the Italian and International Olympiads in Informatics. We developed an interactive online system, based on CMS, the grading system used in several major programming contests including the International Olympiads in Informatics (IOI), and used it in three distinct context: training students for the Italian Olympiads in Informatics (OII), training teachers in order to be able to assist students for the OII, and training the Italian team for the IOI. The system, that is freely available, proved to be a game changer for the whole italian olympiads in informatics ecosystem: in one year, we almost doubled the participation to OII, from 13k to 21k secondary school students. The system is developed basing on the Contest Management System (CMS, http://cms- dev.github.io/), so it is highly available to extensions supporting, for instance, the pro- duction of feedback on problems solutions submitted by trainees. The system is also freely available, with the idea of allowing for support to alternative necessities and developmen

Rendere sociali le imprese. Impatto sociale, confini dell\u2019impresa e rete di stakeholder

E\u2019 possibile ampliare il concetto di impresa sociale fino a comprendere imprese for profit posizionate fuori dai confini fissati dalla definizione ex lege? La risposta a questa domanda necessita di un cambio di punti di vista: la gestione dell\u2019eventuale surplus non pu\uf2 pi\uf9 essere una discriminante di ci\uf2 che viene inteso come impresa sociale. E\u2019 necessario muovere l\u2019attenzione verso i processi che invece permettono di realizzare l\u2019impatto sociale a prescindere da ci\uf2 che accade dal lato degli eventuali profitti. Fatto ci\uf2, \ue8 quindi importante capire quale determinante di questi processi pu\uf2 essere posta alla base della creazione di impatto sociale anche in presenza di soggetti che perseguano fini for profit. In particolare, l\u2019impresa for profit dovr\ue0 essere vista nel contesto del pi\uf9 ampio network di stakeholder che deve essere mobilitato per raggiungere i fini sociali. La mobilitazione degli stakeholder ha il ruolo fondamentale di \u201cfar quadrare il cerchio\u201d, cio\ue8 di permettere ad attori for profit di raggiugere fini sociali, e di poter quindi essere assimilati concettualmente all\u2019idea di imprese sociali. Questo tuttavia non pu\uf2 avvenire lasciando invariate le organizzazioni che decidono di intraprendere questa strada (non ancora riconosciuta, e forse difficilmente catturabile, dalla legge). Appare evidente, infatti, come la mobilitazione degli stakeholder a fini sociali influenzi profondamente i confini dell\u2019impresa: quando gli attori operano sulla base di valori condivisi finalizzati a raggiungere un certo impatto sociale, le imprese parte del network devono optare per comportamenti trasparenti, rendendo ulteriormente permeabili i propri confini. Per rendere evidente questo processo, andremo ad analizzare un network di organizzazioni costituito da piccole imprese manifatturiere, organizzazioni non profit e gruppi di acquisto solidale che, senza rinunciare ognuno alla propria vocazione, hanno sviluppato un modello virtuoso di produzione finalizzata sia al raggiungimento di un impatto sociale che alla sostenibilit\ue0 economica delle imprese partecipanti. In questo caso vedremo che le imprese for profit possono mobilitare una rete di stakeholder a fini sociali a patto di gestire la propria filiera attraverso quella che chiameremo global openness, intesa non solo come trasparenza dei processi interni all\u2019impresa ma anche come necessit\ue0 di rendere trasparente l\u2019intera catena del valore, ben oltre i propri confini e quelli dei propri partner diretti

Made in Carcere: Scaling a Social Enterprise Business Model

"Officina Creativa" (Creative Workshop) is a social enterprise giving female convicts a second change: to produce fashion accessories branded as \u201cMade in Carcere\u201d (Made in Jail). The case deals with the struggles and the challenges that the founder of the company had to deal with as the business started to flourish and gaining social legitimation. Some questions were crowding her mind: Was it really possible to further scale up the organization\u2019s operations and impact? And if so, how? And why growing was so difficult for the organization

Self-mentoring: a new deep learning pipeline to train a self-supervised U-net for few-shot learning of bio-artificial capsule segmentation

Background: Accurate segmentation of microscopic structures such as bio-artificial capsules in microscopy imaging is a prerequisite to the computer-aided understanding of important biomechanical phenomenons. State-of-the-art segmentation performances are achieved by deep neural networks and related data-driven approaches. Training these networks from only a few annotated examples is challenging while producing manually annotated images that provide supervision is tedious. Method: Recently, self-supervision, i.e. designing a neural pipeline providing synthetic or indirect supervision, has proved to significantly increase generalization performances of models trained on few shots. The objective of this paper is to introduce one such neural pipeline in the context of micro-capsule image segmentation. Our method leverages the rather simple content of these images so that a trainee network can be mentored by a referee network which has been previously trained on synthetically generated pairs of corrupted/correct region masks. Results: Challenging experimental setups are investigated. They involve from only 3 to 10 annotated images along with moderately large amounts of unannotated images. In a bio-artificial capsule dataset, our approach consistently and drastically improves accuracy. We also show that the learnt referee network is transferable to another Glioblastoma cell dataset and that it can be efficiently coupled with data augmentation strategies. Conclusions: Experimental results show that very significant accuracy increments are obtained by the proposed pipeline, leading to the conclusion that the self-supervision mechanism introduced in this paper has the potential to replace human annotations

Computing Difference Abstractions of Metabolic Networks Under Kinetic Constraints

International audienceAlgorithms based on abstract interpretation were proposed recently for predicting changes of reaction networks with partial kinetic information. Their prediction precision, however, depends heavily on which heuristics are applied in order to add linear consequences of the steady state equations of the metabolic network. In this paper we ask the question whether such heuristics can be avoided while obtaining the highest possible precision. This leads us to the first algorithm for computing the difference abstractions of a linear equation system exactly without any approximation. This algorithm relies on the usage of elementary flux modes in a nontrivial manner, first-order definitions of the abstractions, and finite domain constraint solving