5 resultados para Identity and spatiality

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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‘Who can be Greek?’ This was the question posed to the Greek society for the first time before the implementation of the Act 3838 in March 2010 which gave the right to access the Greek citizenship -under specific preconditions- to all children of legal migrants born or schooled in Greece. This change of the Nationality Code in order to include all those children was coincided by the economic crisis resulting into the rise of xenophobia, racism and extreme-right rhetoric. The outcome was the cancellation of the Act 3838 by the State Council in February 2013. Under this particular framework, the notions of identity and belonging formed among the youth of African background in Athens are explored. The ways those youngsters perceive not only themselves but also their peers, their countries of origin and the country they live in, are crucial elements of their self-identification. Researches have shown that the integration of the second generation is highly connected to their legal and social status. However, integration is a rather complex process, influenced and shaped by many variables and multiple factors. It is not linear; therefore, its outcomes are difficult to be predicted. Yet, I argue that citizenship acquisition facilitates the process as it transforms those children from ‘aliens’ to ‘citizens’. How these youngsters are perceived by the majority society and the State is one of the core questions of the research, focusing on the imposed dual ‘otherness’ they are subject to. On the one hand, they have to deal with the ‘otherness’ originating from the migrant status inherited to them by their parents, and on the other with the ‘otherness’ deriving from their different phenotypic characteristics. Race matters and becomes a means of discrimination against youth of African background who are perceived as inassimilable and ‘forever others’.

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The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

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My aim is to develop a theory of cooperation within the organization and empirically test it. Drawing upon social exchange theory, social identity theory, the idea of collective intentions, and social constructivism, the main assumption of my work implies that both cooperation and the organization itself are continually shaped and restructured by actions, judgments, and symbolic interpretations of the parties involved. Therefore, I propose that the decision to cooperate, expressed say as an intention to cooperate, reflects and depends on a three step social process shaped by the interpretations of the actors involved. The first step entails an instrumental evaluation of cooperation in terms of social exchange. In the second step, this “social calculus” is translated into cognitive, emotional and evaluative reactions directed toward the organization. Finally, once the identification process is completed and membership awareness is established, I propose that individuals will start to think largely in terms of “We” instead of “I”. Self-goals are redefined at the collective level, and the outcomes for self, others, and the organization become practically interchangeable. I decided to apply my theory to an important cooperative problem in management research: knowledge exchange within organizations. Hence, I conducted a quantitative survey among the members of the virtual community, “www.borse.it” (n=108). Within this community, members freely decide to exchange their knowledge about the stock market among themselves. Because of the confirmatory requirements and the structural complexity of the theory proposed (i.e., the proposal that instrumental evaluations will induce social identity and this in turn will causes collective intentions), I use Structural Equation Modeling to test all hypotheses in this dissertation. The empirical survey-based study found support for the theory of cooperation proposed in this dissertation. The findings suggest that an appropriate conceptualization of the decision to exchange knowledge is one where collective intentions depend proximally on social identity (i.e., cognitive identification, affective commitment, and evaluative engagement) with the organization, and this identity depends on instrumental evaluations of cooperators (i.e., perceived value of the knowledge received, assessment of past reciprocity, expected reciprocity, and expected social outcomes of the exchange). Furthermore, I find that social identity fully mediates the effects of instrumental motives on collective intentions.

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The body is represented in the brain at levels that incorporate multisensory information. This thesis focused on interactions between vision and cutaneous sensations (i.e., touch and pain). Experiment 1 revealed that there are partially dissociable pathways for visual enhancement of touch (VET) depending upon whether one sees one’s own body or the body of another person. This indicates that VET, a seeming low-level effect on spatial tactile acuity, is actually sensitive to body identity. Experiments 2-4 explored the effect of viewing one’s own body on pain perception. They demonstrated that viewing the body biases pain intensity judgments irrespective of actual stimulus intensity, and, more importantly, reduces the discriminative capacities of the nociceptive pathway encoding noxious stimulus intensity. The latter effect only occurs if the pain-inducing event itself is not visible, suggesting that viewing the body alone and viewing a stimulus event on the body have distinct effects on cutaneous sensations. Experiment 5 replicated an enhancement of visual remapping of touch (VRT) when viewing fearful human faces being touched, and further demonstrated that VRT does not occur for observed touch on non-human faces, even fearful ones. This suggests that the facial expressions of non-human animals may not be simulated within the somatosensory system of the human observer in the same way that the facial expressions of other humans are. Finally, Experiment 6 examined the enfacement illusion, in which synchronous visuo-tactile inputs cause another’s face to be assimilated into the mental self-face representation. The strength of enfacement was not affected by the other’s facial expression, supporting an asymmetric relationship between processing of facial identity and facial expressions. Together, these studies indicate that multisensory representations of the body in the brain link low-level perceptual processes with the perception of emotional cues and body/face identity, and interact in complex ways depending upon contextual factors.