945 resultados para General and Comparative Linguistics and Literature


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Edwardsielia tarda is one of the leading marine pathogens that can infect a wide range of cultured marine species. In this study, the acrR-acrAB cluster was cloned from TX1, a pathogenic E. tarda strain isolated from diseased fish. AcrR and AcrAB were found to be involved in resistance against acriflavine and methyl viologen, which positively regulate the expression of acrAB. AcrR negatively regulates its own expression and the expression of the acrAB operon, most likely by interacting with a 24-bp operator site that overlaps the putative promoter of acrA (PacrA). The repressive effect of AcrR on PacrA could be relieved by acriflavine, methyl viologen, and ethidium bromide, the presence of each of which enhanced transcription from PacrA. Interruption of the regulated expression of acrR by introducing into TX1 a plasmid that overexpresses acrR affected growth under stress conditions, AI-2 production, and bacterial virulence. In addition, mutational analyses identified a constitutively active AcrR mutant (named N215), which exhibits full repressor activity but is impaired in its ability to interact with the inducer. Overexpression of N215 produced the same kind of but moderately stronger effect on TX1 compared to that produced by overexpression of the wild-type acrR.

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Malicious software (malware) have significantly increased in terms of number and effectiveness during the past years. Until 2006, such software were mostly used to disrupt network infrastructures or to show coders’ skills. Nowadays, malware constitute a very important source of economical profit, and are very difficult to detect. Thousands of novel variants are released every day, and modern obfuscation techniques are used to ensure that signature-based anti-malware systems are not able to detect such threats. This tendency has also appeared on mobile devices, with Android being the most targeted platform. To counteract this phenomenon, a lot of approaches have been developed by the scientific community that attempt to increase the resilience of anti-malware systems. Most of these approaches rely on machine learning, and have become very popular also in commercial applications. However, attackers are now knowledgeable about these systems, and have started preparing their countermeasures. This has lead to an arms race between attackers and developers. Novel systems are progressively built to tackle the attacks that get more and more sophisticated. For this reason, a necessity grows for the developers to anticipate the attackers’ moves. This means that defense systems should be built proactively, i.e., by introducing some security design principles in their development. The main goal of this work is showing that such proactive approach can be employed on a number of case studies. To do so, I adopted a global methodology that can be divided in two steps. First, understanding what are the vulnerabilities of current state-of-the-art systems (this anticipates the attacker’s moves). Then, developing novel systems that are robust to these attacks, or suggesting research guidelines with which current systems can be improved. This work presents two main case studies, concerning the detection of PDF and Android malware. The idea is showing that a proactive approach can be applied both on the X86 and mobile world. The contributions provided on this two case studies are multifolded. With respect to PDF files, I first develop novel attacks that can empirically and optimally evade current state-of-the-art detectors. Then, I propose possible solutions with which it is possible to increase the robustness of such detectors against known and novel attacks. With respect to the Android case study, I first show how current signature-based tools and academically developed systems are weak against empirical obfuscation attacks, which can be easily employed without particular knowledge of the targeted systems. Then, I examine a possible strategy to build a machine learning detector that is robust against both empirical obfuscation and optimal attacks. Finally, I will show how proactive approaches can be also employed to develop systems that are not aimed at detecting malware, such as mobile fingerprinting systems. In particular, I propose a methodology to build a powerful mobile fingerprinting system, and examine possible attacks with which users might be able to evade it, thus preserving their privacy. To provide the aforementioned contributions, I co-developed (with the cooperation of the researchers at PRALab and Ruhr-Universität Bochum) various systems: a library to perform optimal attacks against machine learning systems (AdversariaLib), a framework for automatically obfuscating Android applications, a system to the robust detection of Javascript malware inside PDF files (LuxOR), a robust machine learning system to the detection of Android malware, and a system to fingerprint mobile devices. I also contributed to develop Android PRAGuard, a dataset containing a lot of empirical obfuscation attacks against the Android platform. Finally, I entirely developed Slayer NEO, an evolution of a previous system to the detection of PDF malware. The results attained by using the aforementioned tools show that it is possible to proactively build systems that predict possible evasion attacks. This suggests that a proactive approach is crucial to build systems that provide concrete security against general and evasion attacks.

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Pykett, Lyn. 'Women writing woman: representations of gender and sexuality', In: Women and literature in Britain 1800 - 1900 (Cambridge: Cambridge University Press, 2001), pp.78-98, 2008. RAE2008

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The present book is devoted to "European connections of Richard Rorty's neopragmatism". The theme, chosen carefully and intentionally, is supposed to show the motivation behind the writing of the present work, as well as to show its intended extent. Let us consider briefly the first three parts of the theme, to enlighten a little our intentions. "European" is perhaps the most important description for it was precisely that thread that was most important to me, being the only context seriously taken into account, as I assumed right from the start that I would not be writing about rather more widely unknown to me - and much less fascinating (even to Rorty, the hero of the story) from my own, traditional, Continental philosophical perspective - American analytic philosophy. So accordingly I have almost totally skipped "American" connections (to use the distinction I need here) of Rorty's philosophy, that is to say, firstly, a years-long work within analytic philosophy, secondly struggles with it on its own grounds, and finally attempts to use classical American, mainly Deweyan, pragmatism for his own needs and numerous polemics associated with it - the questions that are far away from my interests and that arise limited interest among reading and writing philosophical audience in Poland, and perhaps also among Continental philosophers. It did not seem possible to me to write a book on Rorty in his American connections for they are insufficiently known to me, demanding knowledge of both post-war American analytic philosophy as well as pragmatism of its father-founders. I could see, setting to work on Richard Rorty, that a book on his American connections (leaving aside the issue that it would not be a philosophical problem but rather, let us say, the one of writing a monograph) written by a Polish philosopher in Poland and then in the USA was not a stimulating intellectual challenge but rather a thankless working task. Besides, having spent much time on Rorty's philosophy, writing extensively about him and translating his works, I already knew that the "Continental" context was extremely important to his neopragmatism, and that thinking about it could be relatively prolific (as opposed to the context potentially given by American philosophy).

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Overlay networks have been used for adding and enhancing functionality to the end-users without requiring modifications in the Internet core mechanisms. Overlay networks have been used for a variety of popular applications including routing, file sharing, content distribution, and server deployment. Previous work has focused on devising practical neighbor selection heuristics under the assumption that users conform to a specific wiring protocol. This is not a valid assumption in highly decentralized systems like overlay networks. Overlay users may act selfishly and deviate from the default wiring protocols by utilizing knowledge they have about the network when selecting neighbors to improve the performance they receive from the overlay. This thesis goes against the conventional thinking that overlay users conform to a specific protocol. The contributions of this thesis are threefold. It provides a systematic evaluation of the design space of selfish neighbor selection strategies in real overlays, evaluates the performance of overlay networks that consist of users that select their neighbors selfishly, and examines the implications of selfish neighbor and server selection to overlay protocol design and service provisioning respectively. This thesis develops a game-theoretic framework that provides a unified approach to modeling Selfish Neighbor Selection (SNS) wiring procedures on behalf of selfish users. The model is general, and takes into consideration costs reflecting network latency and user preference profiles, the inherent directionality in overlay maintenance protocols, and connectivity constraints imposed on the system designer. Within this framework the notion of user’s "best response" wiring strategy is formalized as a k-median problem on asymmetric distance and is used to obtain overlay structures in which no node can re-wire to improve the performance it receives from the overlay. Evaluation results presented in this thesis indicate that selfish users can reap substantial performance benefits when connecting to overlay networks composed of non-selfish users. In addition, in overlays that are dominated by selfish users, the resulting stable wirings are optimized to such great extent that even non-selfish newcomers can extract near-optimal performance through naïve wiring strategies. To capitalize on the performance advantages of optimal neighbor selection strategies and the emergent global wirings that result, this thesis presents EGOIST: an SNS-inspired overlay network creation and maintenance routing system. Through an extensive measurement study on the deployed prototype, results presented in this thesis show that EGOIST’s neighbor selection primitives outperform existing heuristics on a variety of performance metrics, including delay, available bandwidth, and node utilization. Moreover, these results demonstrate that EGOIST is competitive with an optimal but unscalable full-mesh approach, remains highly effective under significant churn, is robust to cheating, and incurs minimal overheads. This thesis also studies selfish neighbor selection strategies for swarming applications. The main focus is on n-way broadcast applications where each of n overlay user wants to push its own distinct file to all other destinations as well as download their respective data files. Results presented in this thesis demonstrate that the performance of our swarming protocol for n-way broadcast on top of overlays of selfish users is far superior than the performance on top of existing overlays. In the context of service provisioning, this thesis examines the use of distributed approaches that enable a provider to determine the number and location of servers for optimal delivery of content or services to its selfish end-users. To leverage recent advances in virtualization technologies, this thesis develops and evaluates a distributed protocol to migrate servers based on end-users demand and only on local topological knowledge. Results under a range of network topologies and workloads suggest that the performance of the distributed deployment is comparable to that of the optimal but unscalable centralized deployment.

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We introduce Collocation Games as the basis of a general framework for modeling, analyzing, and facilitating the interactions between the various stakeholders in distributed systems in general, and in cloud computing environments in particular. Cloud computing enables fixed-capacity (processing, communication, and storage) resources to be offered by infrastructure providers as commodities for sale at a fixed cost in an open marketplace to independent, rational parties (players) interested in setting up their own applications over the Internet. Virtualization technologies enable the partitioning of such fixed-capacity resources so as to allow each player to dynamically acquire appropriate fractions of the resources for unencumbered use. In such a paradigm, the resource management problem reduces to that of partitioning the entire set of applications (players) into subsets, each of which is assigned to fixed-capacity cloud resources. If the infrastructure and the various applications are under a single administrative domain, this partitioning reduces to an optimization problem whose objective is to minimize the overall deployment cost. In a marketplace, in which the infrastructure provider is interested in maximizing its own profit, and in which each player is interested in minimizing its own cost, it should be evident that a global optimization is precisely the wrong framework. Rather, in this paper we use a game-theoretic framework in which the assignment of players to fixed-capacity resources is the outcome of a strategic "Collocation Game". Although we show that determining the existence of an equilibrium for collocation games in general is NP-hard, we present a number of simplified, practically-motivated variants of the collocation game for which we establish convergence to a Nash Equilibrium, and for which we derive convergence and price of anarchy bounds. In addition to these analytical results, we present an experimental evaluation of implementations of some of these variants for cloud infrastructures consisting of a collection of multidimensional resources of homogeneous or heterogeneous capacities. Experimental results using trace-driven simulations and synthetically generated datasets corroborate our analytical results and also illustrate how collocation games offer a feasible distributed resource management alternative for autonomic/self-organizing systems, in which the adoption of a global optimization approach (centralized or distributed) would be neither practical nor justifiable.

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This thesis seeks to clarify the faceted organisation of psychopathy with a view to developing a comprehensive protocol for the assessment of core psychopathic personality traits. The framework developed will, as best as possible, be free of sample bias. The Self-and Informant-report Deviant Personality Screen (DPS) is introduced and a series of empirical studies are conducted to examine the psychometric properties and construct validity of these measures in general and offender populations. Findings from these studies provide strong support for the utility of the DPS scales for the appraisal of psychopathy across diverse population samples. In addition to this, the utility of cognitive based performance measures for the assessment of emotional deficits in psychopathy is evaluated. Results from this study suggest limited correspondence between these measurement techniques and self-report psychopathy measures. Finally, research conducted on offenders suggests that information obtained from DPS reports may be useful within a broad framework of risk assessment. Further empirical and theoretical implications of the research are discussed.

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This study examines the relationship between rural livelihoods and livestock keeping in Sidama Zones, southern Ethiopia. The livelihood context, assets and strategies of households are the key features of rural livelihoods considered in the study; while households’ livestock ownership, dependence on livestock and livestock management are the main aspects of livestock keeping examined. The study used the sustainable livelihood approach as a framework for data collection and analysis. Describing the main features of rural livelihoods and livestock keeping, and the general pattern of relationship between them, this study mainly aims at identifying the main livelihood factors that determine livestock keeping in the study area. Descriptive statistics, pair wise correlations, mean comparisons and analysis of variance were used to describe rural livelihoods and livestock keeping as well as the relationship between them. Tobit regressions were used to examine the effect of the various livelihood factors on households’ livestock ownership and dependence; Poisson regressions are used to investigate the factors that influence the intensity of livestock management measured by the use of different technologies and inputs. The findings indicated that a number of livelihood factors - assets, livelihood strategies, livelihood shocks and institutional supports - significantly determine the different aspects of livestock keeping. These include: human assets such as age, education and family size; social assets such as membership to social groups; financial assets such as credit; natural assets such as land, and household physical assets; and livelihood strategies such as diversification into farm and nonfarm activities, and coping mechanisms. In addition the livelihood vulnerability context such as shocks and institutional support are among the main determinants of livestock keeping. The results, by and large, matched the findings of previous studies, and it is concluded that households livestock keeping depends on their livelihoods. Accordingly, it is recommended that policies aiming at livestock asset building and productivity improvement should take the livelihoods of rural households in to consideration. As such the study contribute to scholarly works in the area of rural livelihoods, in general, and livestock keeping, in particular. It also contributes to a better understanding of the problems of livestock keeping within the context of rural livelihoods in the country and to the formulation of appropriate policy for the development of the sector.

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BACKGROUND: Previous investigations revealed that the impact of task-irrelevant emotional distraction on ongoing goal-oriented cognitive processing is linked to opposite patterns of activation in emotional and perceptual vs. cognitive control/executive brain regions. However, little is known about the role of individual variations in these responses. The present study investigated the effect of trait anxiety on the neural responses mediating the impact of transient anxiety-inducing task-irrelevant distraction on cognitive performance, and on the neural correlates of coping with such distraction. We investigated whether activity in the brain regions sensitive to emotional distraction would show dissociable patterns of co-variation with measures indexing individual variations in trait anxiety and cognitive performance. METHODOLOGY/PRINCIPAL FINDINGS: Event-related fMRI data, recorded while healthy female participants performed a delayed-response working memory (WM) task with distraction, were investigated in conjunction with behavioural measures that assessed individual variations in both trait anxiety and WM performance. Consistent with increased sensitivity to emotional cues in high anxiety, specific perceptual areas (fusiform gyrus--FG) exhibited increased activity that was positively correlated with trait anxiety and negatively correlated with WM performance, whereas specific executive regions (right lateral prefrontal cortex--PFC) exhibited decreased activity that was negatively correlated with trait anxiety. The study also identified a role of the medial and left lateral PFC in coping with distraction, as opposed to reflecting a detrimental impact of emotional distraction. CONCLUSIONS: These findings provide initial evidence concerning the neural mechanisms sensitive to individual variations in trait anxiety and WM performance, which dissociate the detrimental impact of emotion distraction and the engagement of mechanisms to cope with distracting emotions. Our study sheds light on the neural correlates of emotion-cognition interactions in normal behaviour, which has implications for understanding factors that may influence susceptibility to affective disorders, in general, and to anxiety disorders, in particular.

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Recurrent involuntary memories are autobiographical memories that come to mind with no preceding retrieval attempt and that are subjectively experienced as being repetitive. Clinically, they are classified as a symptom of posttraumatic stress disorder. The present work is the first to systematically examine recurrent involuntary memories outside clinical settings. Study 1 examines recurrent involuntary memories among survivors of the tsunami catastrophe in Southeast Asia in 2004. Study 2 examines recurrent involuntary memories in a large general population. Study 3 examines whether the contents of recurrent involuntary memories recorded in a diary study are duplicates of, or differ from, one another. We show that recurrent involuntary memories are not limited to clinical populations or to emotionally negative experiences; that they typically do not come to mind in a fixed and unchangeable form; and that they show the same pattern regarding accessibility as do autobiographical memories in general. We argue that recurrent involuntary memories after traumas and in everyday life can be explained in terms of general and well-established mechanisms of autobiographical memory.

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Meta-analyses of genome-wide association studies (GWAS) have demonstrated that the same genetic variants can be associated with multiple diseases and other complex traits. We present software called CPAG (Cross-Phenotype Analysis of GWAS) to look for similarities between 700 traits, build trees with informative clusters, and highlight underlying pathways. Clusters are consistent with pre-defined groups and literature-based validation but also reveal novel connections. We report similarity between plasma palmitoleic acid and Crohn's disease and find that specific fatty acids exacerbate enterocolitis in zebrafish. CPAG will become increasingly powerful as more genetic variants are uncovered, leading to a deeper understanding of complex traits. CPAG is freely available at www.sourceforge.net/projects/CPAG/.

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In this volume, experts on the Spanish Golden Age from the United Kingdom, Ireland, and the United States offer analyses of contemporary works that have been influenced by the classics from the sixteenth and seventeenth centuries.

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Ecosystems consist of complex dynamic interactions among species and the environment, the understanding of which has implications for predicting the environmental response to changes in climate and biodiversity. However, with the recent adoption of more explorative tools, like Bayesian networks, in predictive ecology, few assumptions can be made about the data and complex, spatially varying interactions can be recovered from collected field data. In this study, we compare Bayesian network modelling approaches accounting for latent effects to reveal species dynamics for 7 geographically and temporally varied areas within the North Sea. We also apply structure learning techniques to identify functional relationships such as prey–predator between trophic groups of species that vary across space and time. We examine if the use of a general hidden variable can reflect overall changes in the trophic dynamics of each spatial system and whether the inclusion of a specific hidden variable can model unmeasured group of species. The general hidden variable appears to capture changes in the variance of different groups of species biomass. Models that include both general and specific hidden variables resulted in identifying similarity with the underlying food web dynamics and modelling spatial unmeasured effect. We predict the biomass of the trophic groups and find that predictive accuracy varies with the models' features and across the different spatial areas thus proposing a model that allows for spatial autocorrelation and two hidden variables. Our proposed model was able to produce novel insights on this ecosystem's dynamics and ecological interactions mainly because we account for the heterogeneous nature of the driving factors within each area and their changes over time. Our findings demonstrate that accounting for additional sources of variation, by combining structure learning from data and experts' knowledge in the model architecture, has the potential for gaining deeper insights into the structure and stability of ecosystems. Finally, we were able to discover meaningful functional networks that were spatially and temporally differentiated with the particular mechanisms varying from trophic associations through interactions with climate and commercial fisheries.