The effect of adding features on product attractiveness: the role of product perceived congruity

Technological progress has been enabling companies to add disparate features to their existing products. This research investigates the effect of adding more features on consumers’ evaluation of the product, by examining in particular the role of the congruity of the features added with the base product as a variable the moderates the effect of increasing the number of features. Grounding on schema-congruity theory, I propose that the cognitive elaboration associated with the product congruity of the features added explains consumers’ evaluation as the number of new features increases. In particular, it is shown that consumers perceive a benefit from increasing the number of features only when these features are congruent with the product. The underlying mechanisms that explains this finding predicts that when the number of incongruent features increases the cognitive resources necessary to elaborate such incongruities increase and consumers are not willing to spend such resources. However, I further show that when encouraged to consider the new features thoughtfully, consumers do seem able to infer value from increasing the number of moderately incongruent features. Nonetheless, this finding does not apply for those new features that are extremely incongruent with the product. Further evidence for consumers’ ability to resolve the moderate incongruity associated with adding more features is also shown, by studying the moderating role of temporal construal. I propose that consumers perceive an increase in product evaluation as the number of moderately incongruent features increases when consumers consider purchasing the product in the distant future, whereas such an increase is not predicted for the near future scenario. I verify these effect in three experimental studies. Theoretical and managerial implications, and possible avenues of future research are also suggested.

Anticancer drug screening from images of zebrafish embryogenesis

During the previous 10 years, global R&D expenditure in the pharmaceuticals and biotechnology sector has steadily increased, without a corresponding increase in output of new medicines. To address this situation, the biopharmaceutical industry's greatest need is to predict the failures at the earliest possible stage of the drug development process. A major key to reducing failures in drug screenings is the development and use of preclinical models that are more predictive of efficacy and safety in clinical trials. Further, relevant animal models are needed to allow a wider testing of novel hypotheses. Key to this is the developing, refining, and validating of complex animal models that directly link therapeutic targets to the phenotype of disease, allowing earlier prediction of human response to medicines and identification of safety biomarkers. Morehover, well-designed animal studies are essential to bridge the gap between test in cell cultures and people. Zebrafish is emerging, complementary to other models, as a powerful system for cancer studies and drugs discovery. We aim to investigate this research area designing a new preclinical cancer model based on the in vivo imaging of zebrafish embryogenesis. Technological advances in imaging have made it feasible to acquire nondestructive in vivo images of fluorescently labeled structures, such as cell nuclei and membranes, throughout early Zebrafishsh embryogenesis. This In vivo image-based investigation provides measurements for a large number of features at cellular level and events including nuclei movements, cells counting, and mitosis detection, thereby enabling the estimation of more significant parameters such as proliferation rate, highly relevant for investigating anticancer drug effects. In this work, we designed a standardized procedure for accessing drug activity at the cellular level in live zebrafish embryos. The procedure includes methodologies and tools that combine imaging and fully automated measurements of embryonic cell proliferation rate. We achieved proliferation rate estimation through the automatic classification and density measurement of epithelial enveloping layer and deep layer cells. Automatic embryonic cells classification provides the bases to measure the variability of relevant parameters, such as cell density, in different classes of cells and is finalized to the estimation of efficacy and selectivity of anticancer drugs. Through these methodologies we were able to evaluate and to measure in vivo the therapeutic potential and overall toxicity of Dbait and Irinotecan anticancer molecules. Results achieved on these anticancer molecules are presented and discussed; furthermore, extensive accuracy measurements are provided to investigate the robustness of the proposed procedure. Altogether, these observations indicate that zebrafish embryo can be a useful and cost-effective alternative to some mammalian models for the preclinical test of anticancer drugs and it might also provides, in the near future, opportunities to accelerate the process of drug discovery.

Fingerprint Recognition: Enhancement, Feature Extraction and Automatic Evaluation of Algorithms

The identification of people by measuring some traits of individual anatomy or physiology has led to a specific research area called biometric recognition. This thesis is focused on improving fingerprint recognition systems considering three important problems: fingerprint enhancement, fingerprint orientation extraction and automatic evaluation of fingerprint algorithms. An effective extraction of salient fingerprint features depends on the quality of the input fingerprint. If the fingerprint is very noisy, we are not able to detect a reliable set of features. A new fingerprint enhancement method, which is both iterative and contextual, is proposed. This approach detects high-quality regions in fingerprints, selectively applies contextual filtering and iteratively expands like wildfire toward low-quality ones. A precise estimation of the orientation field would greatly simplify the estimation of other fingerprint features (singular points, minutiae) and improve the performance of a fingerprint recognition system. The fingerprint orientation extraction is improved following two directions. First, after the introduction of a new taxonomy of fingerprint orientation extraction methods, several variants of baseline methods are implemented and, pointing out the role of pre- and post- processing, we show how to improve the extraction. Second, the introduction of a new hybrid orientation extraction method, which follows an adaptive scheme, allows to improve significantly the orientation extraction in noisy fingerprints. Scientific papers typically propose recognition systems that integrate many modules and therefore an automatic evaluation of fingerprint algorithms is needed to isolate the contributions that determine an actual progress in the state-of-the-art. The lack of a publicly available framework to compare fingerprint orientation extraction algorithms, motivates the introduction of a new benchmark area called FOE (including fingerprints and manually-marked orientation ground-truth) along with fingerprint matching benchmarks in the FVC-onGoing framework. The success of such framework is discussed by providing relevant statistics: more than 1450 algorithms submitted and two international competitions.

Design, development and first evaluation of a client/server system for managing and querying linguistic corpora

This thesis is concerned with the role played by software tools in the analysis and dissemination of linguistic corpora and their contribution to a more widespread adoption of corpora in different fields. Chapter 1 contains an overview of some of the most relevant corpus analysis tools available today, presenting their most interesting features and some of their drawbacks. Chapter 2 begins with an explanation of the reasons why none of the available tools appear to satisfy the requirements of the user community and then continues with technical overview of the current status of the new system developed as part of this work. This presentation is followed by highlights of features that make the system appealing to users and corpus builders (i.e. scholars willing to make their corpora available to the public). The chapter concludes with an indication of future directions for the projects and information on the current availability of the software. Chapter 3 describes the design of an experiment devised to evaluate the usability of the new system in comparison to another corpus tool. Usage of the tool was tested in the context of a documentation task performed on a real assignment during a translation class in a master's degree course. In chapter 4 the findings of the experiment are presented on two levels of analysis: firstly a discussion on how participants interacted with and evaluated the two corpus tools in terms of interface and interaction design, usability and perceived ease of use. Then an analysis follows of how users interacted with corpora to complete the task and what kind of queries they submitted. Finally, some general conclusions are drawn and areas for future work are outlined.

Kernel Methods for Tree Structured Data

Machine learning comprises a series of techniques for automatic extraction of meaningful information from large collections of noisy data. In many real world applications, data is naturally represented in structured form. Since traditional methods in machine learning deal with vectorial information, they require an a priori form of preprocessing. Among all the learning techniques for dealing with structured data, kernel methods are recognized to have a strong theoretical background and to be effective approaches. They do not require an explicit vectorial representation of the data in terms of features, but rely on a measure of similarity between any pair of objects of a domain, the kernel function. Designing fast and good kernel functions is a challenging problem. In the case of tree structured data two issues become relevant: kernel for trees should not be sparse and should be fast to compute. The sparsity problem arises when, given a dataset and a kernel function, most structures of the dataset are completely dissimilar to one another. In those cases the classifier has too few information for making correct predictions on unseen data. In fact, it tends to produce a discriminating function behaving as the nearest neighbour rule. Sparsity is likely to arise for some standard tree kernel functions, such as the subtree and subset tree kernel, when they are applied to datasets with node labels belonging to a large domain. A second drawback of using tree kernels is the time complexity required both in learning and classification phases. Such a complexity can sometimes prevents the kernel application in scenarios involving large amount of data. This thesis proposes three contributions for resolving the above issues of kernel for trees. A first contribution aims at creating kernel functions which adapt to the statistical properties of the dataset, thus reducing its sparsity with respect to traditional tree kernel functions. Specifically, we propose to encode the input trees by an algorithm able to project the data onto a lower dimensional space with the property that similar structures are mapped similarly. By building kernel functions on the lower dimensional representation, we are able to perform inexact matchings between different inputs in the original space. A second contribution is the proposal of a novel kernel function based on the convolution kernel framework. Convolution kernel measures the similarity of two objects in terms of the similarities of their subparts. Most convolution kernels are based on counting the number of shared substructures, partially discarding information about their position in the original structure. The kernel function we propose is, instead, especially focused on this aspect. A third contribution is devoted at reducing the computational burden related to the calculation of a kernel function between a tree and a forest of trees, which is a typical operation in the classification phase and, for some algorithms, also in the learning phase. We propose a general methodology applicable to convolution kernels. Moreover, we show an instantiation of our technique when kernels such as the subtree and subset tree kernels are employed. In those cases, Direct Acyclic Graphs can be used to compactly represent shared substructures in different trees, thus reducing the computational burden and storage requirements.

Studio di fenomeni d'instabilità gravitativa sui fondali marini, con particolare riferimento all'isola di Stromboli

In the last decade the interest for submarine instability grew up, driven by the increasing exploitation of natural resources (primary hydrocarbons), the emplacement of bottom-lying structures (cables and pipelines) and by the development of coastal areas, whose infrastructures increasingly protrude to the sea. The great interest for this topic promoted a number of international projects such as: STEAM (Sediment Transport on European Atlantic Margins, 93-96), ENAM II (European North Atlantic Margin, 96-99), GITEC (Genesis and Impact of Tsunamis on the European Coast 92-95), STRATAFORM (STRATA FORmation on Margins, 95-01), Seabed Slope Process in Deep Water Continental Margin (Northwest Gulf of Mexico, 96-04), COSTA (Continental slope Stability, 00-05), EUROMARGINS (Slope Stability on Europe’s Passive Continental Margin), SPACOMA (04-07), EUROSTRATAFORM (European Margin Strata Formation), NGI's internal project SIP-8 (Offshore Geohazards), IGCP-511: Submarine Mass Movements and Their Consequences (05-09) and projects indirectly related to instability processes, such as TRANSFER (Tsunami Risk ANd Strategies For the European region, 06-09) or NEAREST (integrated observations from NEAR shore sourcES of Tsunamis: towards an early warning system, 06-09). In Italy, apart from a national project realized within the activities of the National Group of Volcanology during the framework 2000-2003 “Conoscenza delle parti sommerse dei vulcani italiani e valutazione del potenziale rischio vulcanico”, the study of submarine mass-movement has been underestimated until the occurrence of the landslide-tsunami events that affected Stromboli on December 30, 2002. This event made the Italian Institutions and the scientific community more aware of the hazard related to submarine landslides, mainly in light of the growing anthropization of coastal sectors, that increases the vulnerability of these areas to the consequences of such processes. In this regard, two important national projects have been recently funded in order to study coastal instabilities (PRIN 24, 06-08) and to map the main submarine hazard features on continental shelves and upper slopes around the most part of Italian coast (MaGIC Project). The study realized in this Thesis is addressed to the understanding of these processes, with particular reference to Stromboli submerged flanks. These latter represent a natural laboratory in this regard, as several kind of instability phenomena are present on the submerged flanks, affecting about 90% of the entire submerged areal and often (strongly) influencing the morphological evolution of subaerial slopes, as witnessed by the event occurred on 30 December 2002. Furthermore, each phenomenon is characterized by different pre-failure, failure and post-failure mechanisms, ranging from rock-falls, to turbidity currents up to catastrophic sector collapses. The Thesis is divided into three introductive chapters, regarding a brief review of submarine instability phenomena and related hazard (cap. 1), a “bird’s-eye” view on methodologies and available dataset (cap. 2) and a short introduction on the evolution and the morpho-structural setting of the Stromboli edifice (cap. 3). This latter seems to play a major role in the development of largescale sector collapses at Stromboli, as they occurred perpendicular to the orientation of the main volcanic rift axis (oriented in NE-SW direction). The characterization of these events and their relationships with successive erosive-depositional processes represents the main focus of cap.4 (Offshore evidence of large-scale lateral collapses on the eastern flank of Stromboli, Italy, due to structurally-controlled, bilateral flank instability) and cap. 5 (Lateral collapses and active sedimentary processes on the North-western flank of Stromboli Volcano), represented by articles accepted for publication on international papers (Marine Geology). Moreover, these studies highlight the hazard related to these catastrophic events; several calamities (with more than 40000 casualties only in the last two century) have been, in fact, the direct or indirect result of landslides affecting volcanic flanks, as observed at Oshima-Oshima (1741) and Unzen Volcano (1792) in Japan (Satake&Kato, 2001; Brantley&Scott, 1993), Krakatau (1883) in Indonesia (Self&Rampino, 1981), Ritter Island (1888), Sissano in Papua New Guinea (Ward& Day, 2003; Johnson, 1987; Tappin et al., 2001) and Mt St. Augustine (1883) in Alaska (Beget& Kienle, 1992). Flank landslide are also recognized as the most important and efficient mass-wasting process on volcanoes, contributing to the development of the edifices by widening their base and to the growth of a volcaniclastic apron at the foot of a volcano; a number of small and medium-scale erosive processes are also responsible for the carving of Stromboli submarine flanks and the transport of debris towards the deeper areas. The characterization of features associated to these processes is the main focus of cap. 6; it is also important to highlight that some small-scale events are able to create damage to coastal areas, as also witnessed by recent events of Gioia Tauro 1978, Nizza, 1979 and Stromboli 2002. The hazard potential related to these phenomena is, in fact, very high, as they commonly occur at higher frequency with respect to large-scale collapses, therefore being more significant in terms of human timescales. In the last chapter (cap. 7), a brief review and discussion of instability processes identified on Stromboli submerged flanks is presented; they are also compared with respect to analogous processes recognized in other submerged areas in order to shed lights on the main factors involved in their development. Finally, some applications of multibeam data to assess the hazard related to these phenomena are also discussed.

Social network e capitale sociale degli ex-ospiti di Comunita' Liberta': Drug free e ricaduti a confronto

L'indagine condotta, avvalendosi del paradigma della social network analysis, offre una descrizione delle reti di supporto personale e del capitale sociale di un campione di 80 italiani ex post un trattamento terapeutico residenziale di lungo termine per problemi di tossicodipendenza. Dopo aver identificato i profili delle reti di supporto sociale degli intervistati, si è proceduto, in primis, alla misurazione e comparazione delle ego-centered support networks tra soggetti drug free e ricaduti e, successivamente, all'investigazione delle caratteristiche delle reti e delle forme di capitale sociale – closure e brokerage – che contribuiscono al mantenimento dell'astinenza o al rischio di ricaduta nel post-trattamento. Fattori soggettivi, come la discriminazione pubblica percepita e l'attitudine al lavoro, sono stati inoltre esplorati al fine di investigare la loro correlazione con la condotta di reiterazione nell'uso di sostanze. Dai risultati dello studio emerge che un più basso rischio di ricaduta è positivamente associato ad una maggiore attitudine al lavoro, ad una minore percezione di discriminazione da parte della società, all'avere membri di supporto con un più alto status socio-economico e che mobilitano risorse reputazionali e, infine, all'avere reti più eterogenee nell'occupazione e caratterizzate da più elevati livelli di reciprocità. Inoltre, il capitale sociale di tipo brokerage contribuisce al mantenimento dell'astinenza in quanto garantisce l'accesso del soggetto ad informazioni meno omogenee e la sua esposizione a opportunità più numerose e differenziate. I risultati dello studio, pertanto, dimostrano l'importante ruolo delle personal support networks nel prevenire o ridurre il rischio di ricaduta nel post-trattamento, in linea con precedenti ricerche che suggeriscono la loro incorporazione nei programmi terapeutici per tossicodipendenti.