958 resultados para Italic languages and dialects.


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Finite-state methods have been adopted widely in computational morphology and related linguistic applications. To enable efficient development of finite-state based linguistic descriptions, these methods should be a freely available resource for academic language research and the language technology industry. The following needs can be identified: (i) a registry that maps the existing approaches, implementations and descriptions, (ii) managing the incompatibilities of the existing tools, (iii) increasing synergy and complementary functionality of the tools, (iv) persistent availability of the tools used to manipulate the archived descriptions, (v) an archive for free finite-state based tools and linguistic descriptions. Addressing these challenges contributes to building a common research infrastructure for advanced language technology.

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Today 80 % of the content on the Web is in English, which is spoken by only 8% of the World population and 5% of Indian population. There is wealth of useful content in the various languages of the world other than English, which can be made available on the Internet. But, to date, for various reasons most of it is not yet available on the Internet. India itself has 18 officially recognized languages and scores of dialects. Although the medium of instruction for most of the higher education and research in India is English, substantial amount of literature by way of novels, textbooks, scholarly information are being generated in the other languages in the country. Many of the e-governance initiatives are in the respective state languages. In the past, support for different languages by the operating systems and the software packages were not very encouraging. However, with the advent of Unicode technology, operating systems and software packages are supporting almost all the major languages of the world that have scripts. In the work reported in this paper, we have explained the configuration changes that are needed for Eprints.org software to store multilingual content and to create a multilingual user interface.

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Computer science and electrical engineering have been the great success story of the twentieth century. The neat modularity and mapping of a language onto circuits has led to robots on Mars, desktop computers and smartphones. But these devices are not yet able to do some of the things that life takes for granted: repair a scratch, reproduce, regenerate, or grow exponentially fast–all while remaining functional.

This thesis explores and develops algorithms, molecular implementations, and theoretical proofs in the context of “active self-assembly” of molecular systems. The long-term vision of active self-assembly is the theoretical and physical implementation of materials that are composed of reconfigurable units with the programmability and adaptability of biology’s numerous molecular machines. En route to this goal, we must first find a way to overcome the memory limitations of molecular systems, and to discover the limits of complexity that can be achieved with individual molecules.

One of the main thrusts in molecular programming is to use computer science as a tool for figuring out what can be achieved. While molecular systems that are Turing-complete have been demonstrated [Winfree, 1996], these systems still cannot achieve some of the feats biology has achieved.

One might think that because a system is Turing-complete, capable of computing “anything,” that it can do any arbitrary task. But while it can simulate any digital computational problem, there are many behaviors that are not “computations” in a classical sense, and cannot be directly implemented. Examples include exponential growth and molecular motion relative to a surface.

Passive self-assembly systems cannot implement these behaviors because (a) molecular motion relative to a surface requires a source of fuel that is external to the system, and (b) passive systems are too slow to assemble exponentially-fast-growing structures. We call these behaviors “energetically incomplete” programmable behaviors. This class of behaviors includes any behavior where a passive physical system simply does not have enough physical energy to perform the specified tasks in the requisite amount of time.

As we will demonstrate and prove, a sufficiently expressive implementation of an “active” molecular self-assembly approach can achieve these behaviors. Using an external source of fuel solves part of the the problem, so the system is not “energetically incomplete.” But the programmable system also needs to have sufficient expressive power to achieve the specified behaviors. Perhaps surprisingly, some of these systems do not even require Turing completeness to be sufficiently expressive.

Building on a large variety of work by other scientists in the fields of DNA nanotechnology, chemistry and reconfigurable robotics, this thesis introduces several research contributions in the context of active self-assembly.

We show that simple primitives such as insertion and deletion are able to generate complex and interesting results such as the growth of a linear polymer in logarithmic time and the ability of a linear polymer to treadmill. To this end we developed a formal model for active-self assembly that is directly implementable with DNA molecules. We show that this model is computationally equivalent to a machine capable of producing strings that are stronger than regular languages and, at most, as strong as context-free grammars. This is a great advance in the theory of active self- assembly as prior models were either entirely theoretical or only implementable in the context of macro-scale robotics.

We developed a chain reaction method for the autonomous exponential growth of a linear DNA polymer. Our method is based on the insertion of molecules into the assembly, which generates two new insertion sites for every initial one employed. The building of a line in logarithmic time is a first step toward building a shape in logarithmic time. We demonstrate the first construction of a synthetic linear polymer that grows exponentially fast via insertion. We show that monomer molecules are converted into the polymer in logarithmic time via spectrofluorimetry and gel electrophoresis experiments. We also demonstrate the division of these polymers via the addition of a single DNA complex that competes with the insertion mechanism. This shows the growth of a population of polymers in logarithmic time. We characterize the DNA insertion mechanism that we utilize in Chapter 4. We experimentally demonstrate that we can control the kinetics of this re- action over at least seven orders of magnitude, by programming the sequences of DNA that initiate the reaction.

In addition, we review co-authored work on programming molecular robots using prescriptive landscapes of DNA origami; this was the first microscopic demonstration of programming a molec- ular robot to walk on a 2-dimensional surface. We developed a snapshot method for imaging these random walking molecular robots and a CAPTCHA-like analysis method for difficult-to-interpret imaging data.

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Study of emotions in human-computer interaction is a growing research area. This paper shows an attempt to select the most significant features for emotion recognition in spoken Basque and Spanish Languages using different methods for feature selection. RekEmozio database was used as the experimental data set. Several Machine Learning paradigms were used for the emotion classification task. Experiments were executed in three phases, using different sets of features as classification variables in each phase. Moreover, feature subset selection was applied at each phase in order to seek for the most relevant feature subset. The three phases approach was selected to check the validity of the proposed approach. Achieved results show that an instance-based learning algorithm using feature subset selection techniques based on evolutionary algorithms is the best Machine Learning paradigm in automatic emotion recognition, with all different feature sets, obtaining a mean of 80,05% emotion recognition rate in Basque and a 74,82% in Spanish. In order to check the goodness of the proposed process, a greedy searching approach (FSS-Forward) has been applied and a comparison between them is provided. Based on achieved results, a set of most relevant non-speaker dependent features is proposed for both languages and new perspectives are suggested.

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The computer science technique of computational complexity analysis can provide powerful insights into the algorithm-neutral analysis of information processing tasks. Here we show that a simple, theory-neutral linguistic model of syntactic agreement and ambiguity demonstrates that natural language parsing may be computationally intractable. Significantly, we show that it may be syntactic features rather than rules that can cause this difficulty. Informally, human languages and the computationally intractable Satisfiability (SAT) problem share two costly computional mechanisms: both enforce agreement among symbols across unbounded distances (Subject-Verb agreement) and both allow ambiguity (is a word a Noun or a Verb?).

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Jones, E. H. G., Thomas, Ned, and King, Alan, 'Machine Translation and the Internet', Mercator Media Forums (2001) 5(1) pp.84-98 RAE2008

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Wireless Intrusion Detection Systems (WIDS) monitor 802.11 wireless frames (Layer-2) in an attempt to detect misuse. What distinguishes a WIDS from a traditional Network IDS is the ability to utilize the broadcast nature of the medium to reconstruct the physical location of the offending party, as opposed to its possibly spoofed (MAC addresses) identity in cyber space. Traditional Wireless Network Security Systems are still heavily anchored in the digital plane of "cyber space" and hence cannot be used reliably or effectively to derive the physical identity of an intruder in order to prevent further malicious wireless broadcasts, for example by escorting an intruder off the premises based on physical evidence. In this paper, we argue that Embedded Sensor Networks could be used effectively to bridge the gap between digital and physical security planes, and thus could be leveraged to provide reciprocal benefit to surveillance and security tasks on both planes. Toward that end, we present our recent experience integrating wireless networking security services into the SNBENCH (Sensor Network workBench). The SNBENCH provides an extensible framework that enables the rapid development and automated deployment of Sensor Network applications on a shared, embedded sensing and actuation infrastructure. The SNBENCH's extensible architecture allows an engineer to quickly integrate new sensing and response capabilities into the SNBENCH framework, while high-level languages and compilers allow novice SN programmers to compose SN service logic, unaware of the lower-level implementation details of tools on which their services rely. In this paper we convey the simplicity of the service composition through concrete examples that illustrate the power and potential of Wireless Security Services that span both the physical and digital plane.

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— Consideration of how people respond to the question What is this? has suggested new problem frontiers for pattern recognition and information fusion, as well as neural systems that embody the cognitive transformation of declarative information into relational knowledge. In contrast to traditional classification methods, which aim to find the single correct label for each exemplar (This is a car), the new approach discovers rules that embody coherent relationships among labels which would otherwise appear contradictory to a learning system (This is a car, that is a vehicle, over there is a sedan). This talk will describe how an individual who experiences exemplars in real time, with each exemplar trained on at most one category label, can autonomously discover a hierarchy of cognitive rules, thereby converting local information into global knowledge. Computational examples are based on the observation that sensors working at different times, locations, and spatial scales, and experts with different goals, languages, and situations, may produce apparently inconsistent image labels, which are reconciled by implicit underlying relationships that the network’s learning process discovers. The ARTMAP information fusion system can, moreover, integrate multiple separate knowledge hierarchies, by fusing independent domains into a unified structure. In the process, the system discovers cross-domain rules, inferring multilevel relationships among groups of output classes, without any supervised labeling of these relationships. In order to self-organize its expert system, the ARTMAP information fusion network features distributed code representations which exploit the model’s intrinsic capacity for one-to-many learning (This is a car and a vehicle and a sedan) as well as many-to-one learning (Each of those vehicles is a car). Fusion system software, testbed datasets, and articles are available from http://cns.bu.edu/techlab.

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The small GTPases <italic>HRAS, <italic>NRAS and <italic>KRAS are mutated in approximately one-third of all human cancers, rendering the proteins constitutively active and oncogenic. Lung cancer is the leading cause of cancer deaths worldwide, and more than 20% of human lung cancers harbor mutations in <italic>RAS, with 98% of those occurring in the <italic>KRAS isoform. While there have been many advances in the understanding of <italic>KRAS–driven lung tumorigenesis, it remains a therapeutic challenge. To further this understanding and assess novel approaches for treatment, I have investigated two aspects of <italic>Kras–driven tumorigenesis in the lung:

(<italic>I) Despite nearly identical protein sequences, the three <italic>RAS proto-oncogenes exhibit divergent codon usage. Of the three isoforms, <italic>KRAS contains the most rare codons resulting in lower levels of KRAS protein expression relative to <italic>HRAS and <italic>NRAS. To determine the consequences of rare codon bias during <italic>de <italic>novo tumorigenesis, we created a knock-in <italic>Krasex3op mouse in which synonymous mutations in exon 3 converted codons from rare to common. These mice had reduced tumor burden and fewer oncogenic mutations in the <italic>Krasex3op allele following carcinogen exposure. The reduction in tumorigenesis appeared to be a product of rare codons affecting both the oncogenic and non–oncogenic alleles. Converting rare codons to common codons yielded a more potent oncogenic allele that promoted growth arrest and enhanced tumor suppression by the non-oncogenic allele. Thus, rare codons play an integral role in <italic>Kras tumorigenesis.

(<italic>II) Lung cancer patients exhale higher levels of NO and <italic>iNOS-/- mice are resistant to chemically induced lung tumorigenesis. I hypothesize that NO promotes <italic>Kras–driven lung adenocarcinoma, and NOS inhibition may decrease <italic>Kras–driven lung tumorigenesis. To test this hypothesis, I assessed efficacy of the NOS inhibitor L–NAME in a genetically engineered mouse model of <italic>Kras-driven lung adenocarcinoma. Adenoviral Cre recombinase was delivered into the lungs intranasally, resulting in expression of oncogenic <italic>KrasG12D and dominant-negative <italic>Trp53R172H in lung epithelial cells. L–NAME treatment was provided in the water and continued until survival endpoints. In this model, L–NAME treatment decreased tumor growth and prolonged survival. These data establish a potential clinical role for NOS inhibition in lung cancer treatment.

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Light is a critical environmental signal that regulates every phase of the plant life cycle, from germination to floral initiation. Of the many light receptors in the model plant <italic>Arabidopsis thalianaitalic>, the red- and far-red light-sensing phytochromes (phys) are arguably the best studied, but the earliest events in the phy signaling pathway remain poorly understood. One of the earliest phy signaling events is the translocation of photoactivated phys from the cytoplasm to the nucleus, where they localize to subnuclear foci termed photobodies; in continuous light, photobody localization correlates closely with the light-dependent inhibition of embryonic stem growth. Despite a growing body of evidence supporting the biological significance of photobodies in light signaling, photobodies have also been shown to be dispensable for seedling growth inhibition in continuous light, so their physiological importance remains controversial; additionally, the molecular components that are required for phy localization to photobodies are largely unknown. The overall goal of my dissertation research was to gain insight into the early steps of phy signaling by further defining the role of photobodies in this process and identifying additional intragenic and extragenic requirements for phy localization to photobodies.

Even though the domain structure of phys has been extensively studied, not all of the intramolecular requirements for phy localization to photobodies are known. Previous studies have shown that the entire C-terminus of phys is both necessary and sufficient for their localization to photobodies. However, the importance of the individual subdomains of the C-terminus is still unclear. For example a truncation lacking part of the most C-terminal domain, the histidine kinase-related domain (HKRD), can still localize to small photobodies in the light and behaves like a weak allele. However, a point mutation within the HKRD renders the entire molecule completely inactive. To resolve this discrepancy, I explored the hypothesis that this point mutation might impair the dimerization of the HKRD; dimerization has been shown to occur via the C-terminus of phy and is required for more efficient signaling. I show that this point mutation impairs nuclear localization of phy as well as its subnuclear localization to photobodies. Additionally, yeast-two-hybrid analysis shows that the wild-type HKRD can homodimerize but that the HKRD containing the point mutation fails to dimerize with both itself and with wild-type HKRD. These results demonstrate that dimerization of the HKRD is required for both nuclear and photobody localization of phy.

Studies of seedlings grown in diurnal conditions show that photoactivated phy can persist into darkness to repress seedling growth; a seedling's growth rate is therefore fastest at the end of the night. To test the idea that photobodies could be involved in regulating seedling growth in the dark, I compared the growth of two transgenic Arabidopsis lines, one in which phy can localize to photobodies (<italic>PBGitalic>), and one in which it cannot (<italic>NGBitalic>). Despite these differences in photobody morphology, both lines are capable of transducing light signals and inhibiting seedling growth in continuous light. After the transition from red light to darkness, the PBG line was able to repress seedling growth, as well as the accumulation of the growth-promoting, light-labile transcription factor PHYTOCHROME INTERACTING FACTOR 3 (PIF3), for eighteen hours, and this correlated perfectly with the presence of photobodies. Reducing the amount of active phy by either reducing the light intensity or adding a phy-inactivating far-red pulse prior to darkness led to faster accumulation of PIF3 and earlier seedling growth. In contrast, the <italic>NGBitalic> line accumulated PIF3 even in the light, and seedling growth was only repressed for six hours; this behavior was similar in <italic>NGBitalic> regardless of the light treatment. These results suggest that photobodies are required for the degradation of PIF3 and for the prolonged stabilization of active phy in darkness. They also support the hypothesis that photobody localization of phys could serve as an instructive cue during the light-to-dark transition, thereby fine-tuning light-dependent responses in darkness.

In addition to determining an intragenic requirement for photobody localization and further exploring the significance of photobodies in phy signaling, I wanted to identify extragenic regulators of photobody localization. A recent study identified one such factor, HEMERA (HMR); <italic>hmritalic> mutants do not form large photobodies, and they are tall and albino in the light. To identify other components in the HMR-mediated branch of the phy signaling pathway, I performed a forward genetic screen for suppressors of a weak <italic>hmritalic> allele. Surprisingly, the first three mutants isolated from the screen were alleles of the same novel gene, <italic>SON OF HEMERAitalic> (<italic>SOHitalic>). The <italic>sohitalic> mutations rescue all of the phenotypes associated with the weak <italic>hmritalic> allele, and they do so in an allele-specific manner, suggesting a direct interaction between SOH and HMR. Null <italic>sohitalic> alleles, which were isolated in an independent, tall, albino screen, are defective in photobody localization, demonstrating that SOH is an extragenic regulator of phy localization to photobodies that works in the same genetic pathway as HMR.

In this work, I show that dimerization of the HKRD is required for both the nuclear and photobody localization of phy. I also demonstrate a tight correlation between photobody localization and PIF3 degradation, further establishing the significance of photobodies in phy signaling. Finally, I identify a novel gene, <italic>SON OF HEMERAitalic>, whose product is necessary for phy localization to photobodies in the light, thereby isolating a new extragenic determinant of photobody localization. These results are among the first to focus exclusively on one of the earliest cellular responses to light - photobody localization of phys - and they promise to open up new avenues into the study of a poorly understood facet of the phy signaling pathway.

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El Ebro (1917-1936) was a magazine published in Barcelona by Aragonese emigrants at the beginning of the 20th century. It was the first experience of coexistence of different dialectal varieties of the Aragonese language in the same media. El Ebro was an experience that has gone virtually unnoticed in the recent history of one of the most minority languages, and with minor media presence, of Western Europe. In its pages El Ebro mixed dialects spoken in different regions of linguistic Aragonese area together with transcripts of medieval documents. At the same time, this newspaper raised debates about the language issue that they were truncated due to disappearance of the publication and the lack of theoretical realization

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Film, History and Memory examines the relationship between film and history, exploring the multiplicity of ways in which films depict, contest, reinforce or subvert historical understanding. This volume broadens the focus from 'history', the study of past events, to 'memory', the processes – individual, generational, collective or state-driven – by which meanings are attached to the past. This approach acknowledges how the significance of the historical film lies less in its empirical qualities than in its powerful capacity to influence public thinking and discourses about the past, whether by shaping collective memory, popular history and social memory, or by retrieving suppressed or marginalized histories. This study aims to contribute to the growing literature on history and film through the breadth of its approach, both in disciplinary and geographical terms. Contributors are drawn not only from the discipline of history but also film studies, film practice, art history, languages and literature, and cultural studies.

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The chapter argues that language and cultural communication matter in a transnational world and that the transmission of prejudices against minorities has to be closely analysed while contextualising national histories with minorities. Looking at two spatial sites (Leeds and Warsaw) and analysing interview material that was drawn from a larger study, the authors discuss the way local people address difference particularly through the axes of gendered ethnicity (Muslim men) and gendered class (male underclass). It explores how the same categories of difference are discursively produced in Poland and the UK/ England; to what degree they differ or overlap.