2,244 research outputs found
Proprietà barriera e meccaniche di film edibili a base di "whey protein isolate" e pectine preparati in presenza di trensglutaminasi
No full textI film edibili rappresentano una valida alternativa ai film plastici derivati dal petrolio. I film edibili
possono essere costituiti da proteine, polisaccaridi e lipidi. La reticolazione di tali film può essere migliorata
ricorrendo ad agenti chimici, come la glutaraldeide, o ad agenti enzimatici, quali la transglutaminasi (Tgasi) (Di
Pierro et al., 2005; Mariniello, Porta 2005). E’ noto che i componenti dei film e il loro grado di reticolazione
hanno un effetto sulle proprietà meccaniche e di permeabilità. Recentemente nei nostri laboratori è stato
dimostrato che film idrocolloidali a base mista composti da proteine e polisaccaridi possiedono migliorate
proprietà barriera e meccaniche quando la componente proteica è modificata con l’enzima Tgasi (Di Pierro et
al., 2010; Mariniello et al., 2010). Nel presente lavoro sono stati effettuati studi per preparare film composti da
“whey protein isolate” (WPI) e pectine di limone. Una parte dello studio è stata indirizzata ad indagare il pH nel
quale si ha il numero massimo di cariche dei componenti e quindi il maggior numero di interazioni (pH di
complessazione, pHc). A tal scopo sono state fatte titolazioni potenziometriche di soluzioni di WPI e pectine
miscelate a rapporti diversi. Il pHc è stato determinato a 5.1 mentre il miglior rapporto per la formazione dei
complessi è stato trovato a 4:1 WPI-pectine. I film ottenuti in presenza di enzima possiedono diminuite
proprietà barriera (H20, CO2, O2). Successivamente sono state misurate le proprietà meccaniche dei film: carico
massimo a rottura (TS), percentuale di deformazione (E%) ed modulo di Young (Young ́s modulus). I risultati
hanno mostrato un aumento della TS e E% all ́aumentare del pH, quando quest’ultimo si avvicina al valore di
5.6 (pI medio delle sieroproteine del WPI). In generale è possibile apprezzare che la presenza dell ́enzima
favorisce una maggiore reticolazione del film migliorandone le proprietà meccaniche
La biopolitica nel pensiero di Antonio Negri : Dalla “tendenza” all’eccedenza affermativa della vita
No full textThis essay reflects on the reception and the use of biopolitics in Antonio Negri's work. Within certain essays that Negri wrote in the Seventies, through his attempt of exceeding some Marxist categories, we can find the premises of a possible encounter with the biopolitical paradigm. Negri finds Michel Foucault during the Seventies. Reading the pages of the French philosopher, he discovers the invasiveness of contemporary capitalism and the new form of power. Then, thanks to the work of Gilles Deleuze, he exceeds Foucault, conceiving the immanence of life, discerning from biopolitics and biopower, imagining a subject that represents bio s affirmation: the multitude
Quantum Techniques in Machine Learning
No full textIn the last few years, we have witnessed an increasing interest in bridging two impor-
tant research areas that fundamentally changed our way and abilities of processing
information, namely Machine Learning and Quantum Computation.
In the Summer 2017, we had the idea of inviting major experts in Quantum Compu-
tation and Information on the one hand, and in Machine Learning and Optimisation
on the other hand, for a meeting at the University of Verona to discuss the latest
advances in the newly born field of Quantum Machine Learning.
The idea developed in a very successful workshop, bringing together more than hun-
dred scientists to attend and/or contribute their results on the two-way interaction
between Machine Learning and Quantum Computation, aimed at demonstrating
how the intersection of the two fields can offer great potential for both.
This special issue is dedicated to this event, which was held in Verona on
6-8 November 2017 under the name of QTML 2017 - 1st Workshop on Quantum
Techniques in Machine Learning. It represents the first of a series of workshop that
are now held yearly in diverse places worldwide.
The volume collects original contributions focused on the following topics and not
limited to the works presented at QTML 2017:
- Quantum computing for enhancing machine learning algorithms
- Machine learning techniques for the analysis of interacting quantum systems
- Quantum entanglement and topology for the efficient representation of quan-
tum systems
- Approaches to machine learning based on Topological Quantum Computation
- Algorithmic techniques for quantum optimisation (e.g. quantum annealing).
We wish to thank all the people who contributed to bringing this special issue
to completion. In particular, we are very grateful to the reviewers who provided a
valuable help to ensure the high quality of the papers, to the authors for the scrupu-
lous work in improving their papers following the reviewers' suggestions, and to all
the participants in QTML 2017 whose lively discussions and critical interventions
greatly inspired the authors
Il contributo di Francesco Tesauro agli studi in materia di finanza locale
No full textil contributo analizza il contributo di francesco tesauro allo studio della fiscalità local
A Type Theory for Probabilistic { extdollar}{ extdollar}{ extbackslash}lambda { extdollar}{ extdollar}{ extendash}calculus
No full textWe present a theory of types where formulas may contain a choice constructor. This constructor allows for the selection of a particular type among a finite set of options, each corresponding to a given probabilistic term. We show that this theory induces a type assignment system for the probabilistic λ –calculus introduced in an earlier work by Chris Hankin, Herbert Wiklicky and the author, where probabilistic terms represent probability distributions on classical terms of the simply typed λ –calculus. We prove the soundness of the type assignment with respect to a probabilistic term reduction and a normalization property of the latter
LPG-Based Knowledge Graphs: A Survey, a Proposal and Current Trends
No full textA significant part of the current research in the field of Artificial Intelligence is devoted to knowledge bases. New techniques and methodologies are emerging every day for the storage, maintenance and reasoning over knowledge bases. Recently, the most common way of representing knowledge bases is by means of graph structures. More specifically, according to the Semantic Web perspective, many knowledge sources are in the form of a graph adopting the Resource Description Framework model. At the same time, graphs have also started to gain momentum as a model for databases. Graph DBMSs, such as Neo4j, adopt the Labeled Property Graph model. Many works tried to merge these two perspectives. In this paper, we will overview different proposals aimed at combining these two aspects, especially focusing on possibility for them to add reasoning capabilities. In doing this, we will show current trends, issues and possible solutions. In this context, we will describe our proposal and its novelties with respect to the current state of the art, highlighting its current status, potential, the methodology, and our prospect
Holistic graph-based document representation and management for open science
No full textWhile most previous research focused only on the textual content of documents, advanced support for document management in digital libraries, for open science, requires handling all aspects of a document: from structure, to content, to context. These different but inter-related aspects cannot be handled separately and were traditionally ignored in digital libraries. We propose a graph-based unifying representation and handling model based on the definition of an ontology that integrates all the different perspectives and drives the document description in order to boost the effectiveness of document management. We also show how even simple algorithms can profitably use our proposed approach to return relevant and personalized outcomes in different document management tasks
Homological analysis of multi-qubit entanglement
No full textWe propose the usage of persistent homologies to characterize multipartite entanglement.
On a multi-qubit data set we introduce metric-like measures defined in terms of bipartite
entanglement and then we derive barcodes. We show that, depending on the distance, they are
able to produce different classifications. In one case, it is possible to obtain the standard separability
classes. In the other case, a new classification of entangled states of three and four qubits
is provided
Probabilistic Analysis of Programs: A Weak Limit Approach
No full text25/06/14 meb. ok to add author retained copyright at time of conference
Holistic Graph-Based Document Representation and Management for Open Science
No full text(Extended Abstract) While most previous research focused only on the textual content of documents, advanced support for document management in Digital Libraries, for Open Science, requires handling all aspects of a document: from structure, to content, to context. These different but inter-related aspects cannot be handled separately, and were traditionally ignored in Digital Libraries. We propose a graph-based unifying representation and handling model based on the definition of an ontology that integrates all the different perspectives and drives the document description in order to boost the effectiveness of document management. We also show how even simple algorithms can profitably use our proposed approach to return relevant and personalized outcomes in different document management tasks
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