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La relatà applicativa delle sanzioni penali in Italia ed in Germania, tra tensioni rieducative ed istanze europee di armonizzazione
Get PDFIl lavoro si compone essenzialmente di due parti. In un primo segmento(corrispondente al primo capitolo), vengono affrontati alcuni dei temi più classicamente collegati allo studio della pena, con particolare attenzione per il binomio pena detentiva-rieducazione: nonostante il tema sia un po’ trascurato dalle più recenti trattazioni dottrinali, l’ideale rieducativo conserva tutta la sua importanza,
e necessiterebbe di maggiori sforzi per la sua attuazione pratica. Inoltre, si cerca di comprendere se l’idea secondo cui la pena detentiva sta affrontando un momento di crisi è diffusa in tutta Europa, vagliando la percorribilità di alcune alternative (in particolare, la pena pecuniaria e la giustizia riparativa). Infine, si alza lo sguardo al diritto penale internazionale, per testare la tenuta delle teorie sulla pena di fronte a crimini di inusitata durezza.
Più che cristallizzare dei risultati chiari, la parte iniziale risponde alle varie questioni in termini problematici, preparando il terreno per la seconda parte del
lavoro. Questa analizza più nello specifico i sistemi sanzionatori degli ordinamenti italiano e tedesco, provando a calare i rispettivi dibattiti sulla finalità della pena, in particolare detentiva, nella realtà effettuale, confrontandosi con numeri, statistiche e l’esito di ricerche empiriche.
Da ultimo, si provano a mettere in luce somiglianze e differenze tra i due sistemi, cercando di fare emergere i momenti di stridore che potrebbero crearsi tra le due legislazioni una volta diffusa la prassi del mutuo riconoscimento delle sentenze di condanna tra gli Stati dell’Unione Europea, tuttora ad uno stadio embrionale
La riscoperta del diritto civile nell'ottica della strategia differenziata di lotta al crimine
No full textÈ possibile pensare al diritto civile come mezzo per realizzare una strategia di lotta al crimine più efficiente?
Questo è l’interrogativo alla base di questo studio.
Per rispondervi, si è cercato di ipotizzare un coordinamento di mezzi di tutela guardando ai rimedi di diritto civile, per il penalista tradizionalmente lontani, al fine di ricercare soluzioni di maggiore efficienza ed economicità.
Un tentativo che un illustre Autore probabilmente avrebbe descritto come una innovativa rispolverata di “vecchi arnesi già nell’armadio”
Neural representations of movement planning within the human prehension system
Get PDFObject manipulation is central to our daily interactions with the environment. Failing to select, prepare or perform correct prehension movements results in dramatic limitations for the affected individual. Whereas we begin to have a better understanding of the neural mechanisms underlying the execution of object-directed movements, less is known about how exactly our brain makes the plan for action. Previous studies examining movement planning suggested that neuronal populations in parieto-frontal areas contain information about upcoming movements moments before they actually take place. However, such studies typically used experiments in which the participant was instructed about the movement to plan with visual or auditory cues, making it difficult to disentangle movement planning from the processing of cues and stimulus- response (S-R) mapping. In our first functional magnetic resonance imaging (fMRI) study (Study I), we compared an instructed condition with a free-choice condition that allowed participants to select which prehension movement to perform: a condition in which the task was not tied to specific external cues (i.e., no direct S-R mapping). Using multi-variate pattern analysis (MVPA), we found contralateral parietal and frontal regions containing abstract representations of planned movements that generalize across the way these movements were generated (internally vs externally). The majority of previous studies were based on delayed-movement tasks, which introduce brain responses unrelated to movement preparation. Consequently, whether these findings would generalize to immediate movements remained unclear. In our second fMRI study (Study II), we directly compared delayed and immediate reaching and grasping movements. Using time-resolved MVPA allowed us to reveal shared representations for delayed and non-delayed movement planning in human primary motor cortex and examine how movement representations unfolded throughout the different stages of planning and execution. Overall, our findings expand previous understanding of the regions implicated in movement planning and offer new insights into the dynamics of the human prehension system
L'alveare in fiamme: la ricezione della favola delle api nello spazio pubblico britannico (1714-1733)
Get PDFIl presente lavoro si propone di esaminare la ricezione britannica della "Favola delle api" di Bernard Mandeville tra gli anni venti e trenta del Settecento. Questo studio intende esaminare la fortuna dell'opera di Bernard Mandeville alla luce dei linguaggi e dei mezzi di comunicazione attraverso cui essa venne presentata al pubblico britannico
Delayed Forward-Backward stochastic PDE's driven by non Gaussian Lévy noise with application in finance
No full textFrom the very first results, the mathematical theory of financial markets has undergone several changes, mostly due to financial crises who forced the mathematical-economical community to change the basic assumptions on which the whole theory is founded. Consequently a new mathematical foundation were needed. In particular, the 2007/2008 credit crunch showed the word that a new financial theoretical framework was necessary, since several empirical evidences emerged that aspects that were neglected prior to these years were in fact fundamental if one has to deal with financial markets. The goal of the present thesis goes in this direction; we aim at developing rigorous mathematical instruments that allow to treat fundamental problems in modern financial mathematics. In order to do so, the talk is thus divided into three main parts, which focus on three different topics of modern financial mathematics.
The first part is concerned with delay equations. In particular, we will prove Feynman-Kac type result for BSDE's with time-delayed generator, as well as an ad hoc Ito formula for delay equations with jumps. The second part deal with infinite dimensional analysis and network models, focusing in particular on existence and uniqueness results for infinite dimensional SPDE's on networks with general non-local boundary conditions. The last part treats the topic of rigorous asymptotic expansions, providing a small noise asymptotic expansion for SDE with Lévy noise with several concrete application to financial models
On the effect of experience: An experimental approach to delegation and tax compliance
No full textIn the field of decision-making under risk, researchers have started to focus on the effect of information acquisition modality on people’s decisional pro- cess, by means of a comparison between Decision from Description (DfD) and Decision from Experience (DfE). A literature review on the topic is provided in Chapter 1, which analyzes the determinants of the so-called description- experience gap and its translation into the planning-ongoing gap, according to which people tend to overweight rare events under description (or planning) and underweight them under experience (or ongoing decision-making).
In such a framework, Chapter 2 experimentally investigates delegation in risky choices, in a three-party agency framework. Agents build a portfolio for their principals by selecting among prospects that are either fully described or experienced. Nevertheless, principals are given the opportunity to take over control and build their own portfolio by paying a fee. Principals are more efficient and ambitious than agents. Such a higher quality of principals’ portfolios is associated to a higher effort exerted in collecting information on risky options. Principals anticipate this performance difference, but pay a control fee that is generally excessive and negatively impacts on their final earnings.
Chapter 3 and Chapter 4 study tax compliance, by providing a comparison between the two information acquisition modalities. Specifically, Chapter 3 serves as an introduction to Chapter 4, as it reviews the main theoretical and experimental literature on tax compliance, by referring to the role of objec- tive, perceived, and weighted probabilities in compliance decisions. Besides this, it provides a novel methodological analysis that justifies the adoption of laboratory experiments as an externally valid tool if sustained by agent-based simulations in the field of tax compliance. Chapter 4 reports on a laboratory experiment designed to explore the presence of the planning-ongoing gap in taxpayers’ behavior, by means of a (self) commitment system for compliance. In line with overweighting of rare events - i.e., fiscal audits-, planning induces the majority of people not only to opt for a commitment to tax compliance, but also to actually comply
Computational Models for Analyzing Affective Behaviors and Personality from Speech and Text
No full textAutomatic analysis and summarization of affective behaviors and personality from human-human interactions are becoming a central theme in many research areas including computer and social sciences and psychology. Affective behaviors are defined as short- term states, which are very brief in duration, arise in response to an event or situation that are relevant and are rapidly change over time. They include empathy, anger, frustration, satisfaction, and dissatisfaction. Personality is defined as individual's longer-term characteristics that are stable over time and that describe individual's true nature. The stable personality traits have been captured in psychology by the Big-5 model that includes the following traits: openness, conscientiousness, extraversion, agreeableness and neuroticism. Traditional approaches towards measuring behavioral information and personality use either observer- or self- assessed questionnaires. Observers usually monitor the overt signals and label interactional scenarios, whereas self-assessors evaluate what they perceive from the interactional scenarios. Using this measured behavioral and personality information, a typical descriptive summary is designed to improve domain experts' decision-making processes. However, such a manual approach is time-consuming and expensive. Thus it motivated us to the design of automated computational models. Moreover, the motivation of studying affective behaviors and personality is to design a behavioral profile of an individual, from which one can understand/predict how an individual interprets or values a situation. Therefore, the aim of the work presented in this dissertation is to design automated computational models for analyzing affective behaviors such as empathy, anger, frustration, satisfaction, and dissatisfaction and Big-5 personality traits using behavioral signals that are expressed in conversational interactions.
The design of the computational models for decoding affective behaviors and personality is a challenging problem due to the multifaceted nature of behavioral signals. During conversational interactions, many aspects of these signals are expressed and displayed by overt cues in terms of verbal and vocal non-verbal expressions. These expressions also vary depending on the type of interaction, context or situation such as phone conversations, face-to-machine, face-to-face, and social media interactions. The challenges of designing computational models require the investigation of 1) different overt cues expressed in several experimental contexts in real settings, 2) verbal and vocal non-verbal expressions in terms of linguistic, visual, and acoustic cues, and 3) combining the information from multiple channels such as linguistic, visual, and acoustic information.
Regarding the design of computational models of affective behaviors, the contributions of the work presented here are
1. analysis of the call centers' conversations containing agents' and customers' speech,
2. addressing of the issues related to the segmentation and annotation by defining operational guidelines to annotate empathy of the agent and other emotional states of the customer on real call center data,
3. demonstration of how different channels of information such as acoustic, linguistic, and psycholinguistic channels can be combined to improve for both conversation- level and segment-level classification tasks, and
4. development of a computational pipeline for designing affective scenes, i.e., the emotional sequence of the interlocutors, from a dyadic conversation.
In designing models for Big-5 personality traits, we addressed two important problems; personality recognition, which infers self-assessed personality, and personality perception, which infers personalities that observers attribute to an individual. The contributions of this work to personality research are
1. investigation of several scenarios such as broadcast news, human-human spoken conversations from a call center, social media posts such as Facebook status updates and multi-modal youtube blogs,
2. design of classification models using acoustic, linguistic and psycholinguistic features, and
3. investigation of several feature-level and decision-level combination strategies.
Based on studies conducted in this work it is demonstrated that fusion of various sources of information is beneficial for designing automated computational models. The computational models for affective behaviors and personality that are presented here are fully automated and effective - they do not require any human intervention. The outcome of this research is potentially relevant for contributing to the automatic analysis of human interactions in several sectors such as customer care, education, and healthcare
Closing the Gap between Business Process Analysis and Service Workflow Design with the BPM-SIC Methodology
Get PDFNowadays companies and organizations are challenged to integrate and automate their business processes. A business process is a set of logically related tasks, carried out to
produce a product or service. Business processes are typically implemented using Web services. Web services are programmable interfaces that can be invoked through standard
communication protocols. In general, the need to outsource parts of a business processes results in a large number of Web services, which are, generally, heterogeneous and distributed among various organizations and platforms.
The ability to select and integrate these Web services at runtime is desirable as it would enable Web services platforms a quick reaction to changing business needs and
failures, reducing implementation costs and minimizing losses by poor availability. The goal of dynamic and automatic Web services composition is to generate a composition plan (workflow) at runtime that meets certain business goal. Semantics based techniques exploit specialized services annotation to facilitate the discovery of simple or composed services (matchmaking) that form part of composition plan. Usually, the process of matchmaking
places more attention in the selection of services and much less on the behavior of the composed service (workflow) that tends to be very simple. In the industry, on the
contrary, the service compounds or workflows are manually defined and typically follow complex control flow patterns that implement elaborate business processes.
Although a technique of dynamic and automatic service composition produces an executable workflow that implements a business process, it must be validated in relation to
the business goal. This high-level analysis is usually performed by domain experts (BPA Business Process Analyst) who must coordinate with the experts (SA: System Architect)
the implementation of the business processes. The conversation between BPA and SA is a fundamental requirement for the cycle of creation of an executable business process. The lack of communication between both participants not only causes delays in development time, but also generates product failures and unnecessary cycles involving often increases in production costs and large losses of money in organizations. In this thesis, we have developed three approaches that allow decreasing the gap between
BPA and SA and making their collaboration more effective. On one hand we present a Web service composition technique that is dynamic and automatic and is based on services’
semantic descriptions. The composed service corresponds to an executable workflow with complex control flow, facilitating the SAs implementation task. On the other hand,
we provide a tool that allows BPAs to verify and analyze the performance of their business processes. And finally, we exploit both tools in order to propose a methodology that
integrates both perspectives allowing knowledge transfer in both directions. We obtained promising results that reveal inconsistencies in the development and design of the business processes as well as provide recommendations for best practices in both directions
Indexing for Very Large Data Series Collections
Get PDFData series are a prevalent data type that has attracted lots of interest in recent years. Specifically, there has been an explosive interest towards the analysis of large volumes of data series in many different domains. This is both in businesses (e.g., in mobile applications) and in sciences e.g., in biology). In several time-critical scenarios, analysts need to be able to explore these data as soon as they become available, which is not currently possible for very large data series collections.
In this thesis, we present the first adaptive indexing mechanism, specifically tailored to solve the problem of indexing and querying very large data series collections. The main idea is that instead of building the complete index over the complete data set up-front and querying
only later, we interactively and adaptively build parts of the index, only for the parts of the data on which the users pose queries. The contents and the resolution of the index are purely driven by query patterns; the more queries that arrive, the more data series are indexed and at a
higher resolution. Adaptive indexing significantly outperforms previous solutions, gracefully handling large data series collections, reducing the data to query delay: by the time state-of-the-art indexing techniques finish indexing 1 billion data series (and before answering even a single query), our method has already answered 3 * 10^5 queries. At the same time, we present novel algorithms for both full indexing of data series collections, as well as for efficient exact query answering. Our algorithms perform efficient skip-sequential scans of the data, avoiding the need of costly random accesses on the disk.
Moreover, up to this point very little attention has been paid to properly evaluating data series index structures, with most previous work relying solely on randomly selected data series to use as queries (with/without adding noise). In this thesis, we show that random workloads
are inherently not suitable for the task at hand and we argue that there is a need for carefully generating a query workload. We define measures that capture the characteristics of queries, and we propose a method for generating workloads with the desired properties, that is, effectively evaluating and comparing data series summarizations and indexes. In our experimental evaluation, with carefully controlled query workloads, we shed light on key factors affecting the performance of nearest neighbor search in large data series collections.
Finally, apart from ad hoc data exploration, we also investigate methods for the systematic analysis of very large data series collections, supporting business intelligence applications. We present techniques, which borrow ideas from Strategic Management, for a goal-oriented analysis of large collections of performance indicator data series. Such algorithms can additionally be sped up through the use of the index structures presented in this work
Olfactory representation in the honey bee antennal lobe: Investigations on a filter's functions and dysfunctions.
No full textThe honeybee, Apis mellifera, is an established model for the study of olfactory processing, olfactory learning and memory, and the related plasticity. The primary centre for olfactory processing in the bee brain, the antennal lobe, has a very important function in odour coding and odour discrimination. Nevertheless, both its structure and its function are plastic. In this thesis, I analysed the structural antennal lobe plasticity related to associative learning, and that related to a non-associative experience, i.e. prolonged odour exposure, in the adult honeybee. Subsequently, I analysed the functional modification taking place in the latter case within the output units of the antennal lobe, showing that parallel structural and functional changes occur. In the last part of the thesis, I focused on the effects of a common neonicotinoid pesticide, imidacloprid, on antennal lobe function and the discrimination abilities of honeybees. I demonstrated that both are strongly impaired in the acute treatment of the brain with such substance