989 resultados para GLOBULAR CLUSTERS: GENERAL


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Various restrictions on the terms allowed for substitution give rise to different cases of semi-unification. Semi-unification on finite and regular terms has already been considered in the literature. We introduce a general case of semi-unification where substitutions are allowed on non-regular terms, and we prove the equivalence of this general case to a well-known undecidable data base dependency problem, thus establishing the undecidability of general semi-unification. We present a unified way of looking at the various problems of semi-unification. We give some properties that are common to all the cases of semi-unification. We also the principality property and the solution set for those problems. We prove that semi-unification on general terms has the principality property. Finally, we present a recursive inseparability result between semi-unification on regular terms and semi-unification on general terms.

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A new approach is proposed for clustering time-series data. The approach can be used to discover groupings of similar object motions that were observed in a video collection. A finite mixture of hidden Markov models (HMMs) is fitted to the motion data using the expectation-maximization (EM) framework. Previous approaches for HMM-based clustering employ a k-means formulation, where each sequence is assigned to only a single HMM. In contrast, the formulation presented in this paper allows each sequence to belong to more than a single HMM with some probability, and the hard decision about the sequence class membership can be deferred until a later time when such a decision is required. Experiments with simulated data demonstrate the benefit of using this EM-based approach when there is more "overlap" in the processes generating the data. Experiments with real data show the promising potential of HMM-based motion clustering in a number of applications.

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The increasing practicality of large-scale flow capture makes it possible to conceive of traffic analysis methods that detect and identify a large and diverse set of anomalies. However the challenge of effectively analyzing this massive data source for anomaly diagnosis is as yet unmet. We argue that the distributions of packet features (IP addresses and ports) observed in flow traces reveals both the presence and the structure of a wide range of anomalies. Using entropy as a summarization tool, we show that the analysis of feature distributions leads to significant advances on two fronts: (1) it enables highly sensitive detection of a wide range of anomalies, augmenting detections by volume-based methods, and (2) it enables automatic classification of anomalies via unsupervised learning. We show that using feature distributions, anomalies naturally fall into distinct and meaningful clusters. These clusters can be used to automatically classify anomalies and to uncover new anomaly types. We validate our claims on data from two backbone networks (Abilene and Geant) and conclude that feature distributions show promise as a key element of a fairly general network anomaly diagnosis framework.

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Accepted Version

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We report the observation of urchin-like nanostructures consisting of high-density spherical nanotube radial arrays of vanadium oxide nanocomposite, successfully synthesized by a simple chemical route using an ethanolic solution of vanadium tri-isopropoxide and alkyl amine hexadecylamine for 7 days at 180oC. The results show that the growth process of the NanoUrchin occurs in stages, starting with a radial self-organized arrangement of lamina followed by the rolling of the lamina into nanotubes. The longest nanotubes are measured to be several micrometers in length with diameters of ~120 nm and hollow centers typically measured to be ~75 nm. The NanoUrchin have an estimated density of nanotubes of ~40 sr-1. The tube walls comprise layers of vanadium oxide with the organic surfactant intercalated between atomic layers. The interlayer distance is measured to be 2.9 ± 0.1 nm and electron diffraction identified the vanadate phase in the VOx nanocomposite as orthorhombic V2O5. These nanostructures may be used as three-dimensional composite materials and as supports for other materials.

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The recognition and protection of constitutional rights is a fundamental precept. In Ireland, the right to marry is provided for in the equality provisions of Article 40 of the Irish Constitution (1937). However, lesbians and gay men are denied the right to marry in Ireland. The ‘last word’ on this issue came into being in the High Court in 2006, when Katherine Zappone and Ann Louise Gilligan sought, but failed, to have their Canadian marriage recognised in Ireland. My thesis centres on this constitutional court ruling. So as to contextualise the pursuit of marriage equality in Ireland, I provide details of the Irish trajectory vis-à-vis relationship and family recognition for same-sex couples. In Chapter One, I discuss the methodological orientation of my research, which derives from a critical perspective. Chapter Two denotes my theorisation of the principle of equality and the concept of difference. In Chapter Three, I discuss the history of the institution of marriage in the West with its legislative underpinning. Marriage also has a constitutional underpinning in Ireland, which derives from Article 41 of our Constitution. In Chapter Four, I discuss ways in which marriage and family were conceptualised in Ireland, by looking at historical controversies surrounding the legalisation of contraception and divorce. Chapter Five denotes a Critical Discourse Analysis of the High Court ruling in Zappone and Gilligan. In Chapter Six, I critique text from three genres of discourse, i.e. ‘Letters to the Editor’ regarding same-sex marriage in Ireland, communication from legislators vis-à-vis the 2004 legislative impediment to same-sex marriage in Ireland, and parliamentary debates surrounding the 2010 enactment of civil partnership legislation in Ireland. I conclude my research by reflecting on my methodological and theoretical considerations with a view to answering my research questions. Author’s Update: Following the outcome of the 2015 constitutional referendum vis-à-vis Article 41, marriage equality has been realised in Ireland.

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The measurement of users’ attitudes towards and confidence with using the Internet is an important yet poorly researched topic. Previous research has encountered issues that serve to obfuscate rather than clarify. Such issues include a lack of distinction between the terms ‘attitude’ and ‘self-efficacy’, the absence of a theoretical framework to measure each concept, and failure to follow well-established techniques for the measurement of both attitude and self-efficacy. Thus, the primary aim of this research was to develop two statistically reliable scales which independently measure attitudes towards the Internet and Internet self-efficacy. This research addressed the outlined issues by applying appropriate theoretical frameworks to each of the constructs under investigation. First, the well-known three component (affect, behaviour, cognition) model of attitudes was applied to previous Internet attitude statements. The scale was distributed to four large samples of participants. Exploratory factor analyses revealed four underlying factors in the scale: Internet Affect, Internet Exhilaration, Social Benefit of the Internet and Internet Detriment. The final scale contains 21 items, demonstrates excellent reliability and achieved excellent model fit in the confirmatory factor analysis. Second, Bandura’s (1997) model of self-efficacy was followed to develop a reliable measure of Internet self-efficacy. Data collected as part of this research suggests that there are ten main activities which individuals can carry out on the Internet. Preliminary analyses suggested that self-efficacy is confounded with previous experience; thus, individuals were invited to indicate how frequently they performed the listed Internet tasks in addition to rating their feelings of self-efficacy for each task. The scale was distributed to a sample of 841 participants. Results from the analyses suggest that the more frequently an individual performs an activity on the Internet, the higher their self-efficacy score for that activity. This suggests that frequency of use ought to be taken into account in individual’s self-efficacy scores to obtain a ‘true’ self-efficacy score for the individual. Thus, a formula was devised to incorporate participants’ previous experience of Internet tasks in their Internet self-efficacy scores. This formula was then used to obtain an overall Internet self-efficacy score for participants. Following the development of both scales, gender and age differences were explored in Internet attitudes and Internet self-efficacy scores. The analyses indicated that there were no gender differences between groups for Internet attitude or Internet self-efficacy scores. However, age group differences were identified for both attitudes and self-efficacy. Individuals aged 25-34 years achieved the highest scores on both the Internet attitude and Internet self-efficacy measures. Internet attitude and self-efficacy scores tended to decrease with age with older participants achieving lower scores on both measures than younger participants. It was also found that the more exposure individuals had to the Internet, the higher their Internet attitude and Internet self-efficacy scores. Examination of the relationship between attitude and self-efficacy found a significantly positive relationship between the two measures suggesting that the two constructs are related. Implication of such findings and directions for future research are outlined in detail in the Discussion section of this thesis.

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Background: Inclusive education is central to contemporary discourse internationally reflecting societies’ wider commitment to social inclusion. Education has witnessed transforming approaches that have created differing distributions of power, resource allocation and accountability. Multiple actors are being forced to consider changes to how key services and supports are organised. This research constitutes a case study situated within this broader social service dilemma of how to distribute finite resources equitably to meet individual need, while advancing inclusion. It focuses on the national directive with regard to inclusive educational practice for primary schools, Department of Education and Science Special Education Circular 02/05, which introduced the General Allocation Model (GAM) within the legislative context of the Education of Persons with Special Educational Needs (EPSEN) Act (Government of Ireland, 2004). This research could help to inform policy with ‘facts about what is happening on the ground’ (Quinn, 2013). Research Aims: The research set out to unearth the assumptions and definitions embedded within the policy document, to analyse how those who are at the coalface of policy, and who interface with multiple interests in primary schools, understand the GAM and respond to it, and to investigate its effects on students and their education. It examines student outcomes in the primary schools where the GAM was investigated. Methods and Sample The post-structural study acknowledges the importance of policy analysis which explicitly links the ‘bigger worlds’ of global and national policy contexts to the ‘smaller worlds’ of policies and practices within schools and classrooms. This study insists upon taking the detail seriously (Ozga, 1990). A mixed methods approach to data collection and analysis is applied. In order to secure the perspectives of key stakeholders, semi-structured interviews were conducted with primary school principals, class teachers and learning support/resource teachers (n=14) in three distinct mainstream, non-DEIS schools. Data from the schools and their environs provided a profile of students. The researcher then used the Pobal Maps Facility (available at www.pobal.ie) to identify the Small Area (SA) in which each student resides, and to assign values to each address based on the Pobal HP Deprivation Index (Haase and Pratschke, 2012). Analysis of the datasets, guided by the conceptual framework of the policy cycle (Ball, 1994), revealed a number of significant themes. Results: Data illustrate that the main model to support student need is withdrawal from the classroom under policy that espouses inclusion. Quantitative data, in particular, highlighted an association between segregated practice and lower socioeconomic status (LSES) backgrounds of students. Up to 83% of the students in special education programmes are from lower socio-economic status (LSES) backgrounds. In some schools 94% of students from LSES backgrounds are withdrawn from classrooms daily for special education. While the internal processes of schooling are not solely to blame for class inequalities, this study reveals the power of professionals to order children in school, which has implications for segregated special education practice. Such agency on the part of key actors in the context of practice relates to ‘local constructions of dis/ability’, which is influenced by teacher habitus (Bourdieu, 1984). The researcher contends that inclusive education has not resulted in positive outcomes for students from LSES backgrounds because it is built on faulty assumptions that focus on a psycho-medical perspective of dis/ability, that is, placement decisions do not consider the intersectionality of dis/ability with class or culture. This study argues that the student need for support is better understood as ‘home/school discontinuity’ not ‘disability’. Moreover, the study unearths the power of some parents to use social and cultural capital to ensure eligibility to enhanced resources. Therefore, a hierarchical system has developed in mainstream schools as a result of funding models to support need in inclusive settings. Furthermore, all schools in the study are ‘ordinary’ schools yet participants acknowledged that some schools are more ‘advantaged’, which may suggest that ‘ordinary’ schools serve to ‘bury class’ (Reay, 2010) as a key marker in allocating resources. The research suggests that general allocation models of funding to meet the needs of students demands a systematic approach grounded in reallocating funds from where they have less benefit to where they have more. The calculation of the composite Haase Value in respect of the student cohort in receipt of special education support adopted for this study could be usefully applied at a national level to ensure that the greatest level of support is targeted at greatest need. Conclusion: In summary, the study reveals that existing structures constrain and enable agents, whose interactions produce intended and unintended consequences. The study suggests that policy should be viewed as a continuous and evolving cycle (Ball, 1994) where actors in each of the social contexts have a shared responsibility in the evolution of education that is equitable, excellent and inclusive.

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Metal oxide clusters of sub-nm dimensions dispersed on a metal oxide support are an important class of catalytic materials for a number of key chemical reactions, showing enhanced reactivity over the corresponding bulk oxide. In this paper we present the results of a density functional theory study of small sub-nm TiO2 clusters, Ti2O4, Ti3O6 and Ti4O8 supported on the rutile (110) surface. We find that all three clusters adsorb strongly with adsorption energies ranging from -3 eV to -4.5 eV. The more stable adsorption structures show a larger number of new Ti-O bonds formed between the cluster and the surface. These new bonds increase the coordination of cluster Ti and O as well as surface oxygen, so that each has more neighbours. The electronic structure shows that the top of the valence band is made up of cluster derived states, while the conduction band is made up of Ti 3d states from the surface, resulting in a reduction of the effective band gap and spatial separation of electrons and holes after photon absorption, which shows their potential utility in photocatalysis. To examine reactivity, we study the formation of oxygen vacancies in the cluster-support system. The most stable oxygen vacancy sites on the cluster show formation energies that are significantly lower than in bulk TiO2, demonstrating the usefulness of this composite system for redox catalysis.

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To screen for novel ribosomally synthesised antimicrobials, in-silico genome mining was performed on all publically available fully sequenced bacterial genomes. 49 novel type 1 lantibiotic clusters were identified from a number of species, genera and phyla not usually associated with lantibiotic production, and indicates high prevalence. A crucial step towards the commercialisation of fermented beverages is the characterisation of the microbial content. To achieve this goal, we applied next-generation sequencing techniques to analyse the bacterial and yeast populations of the organic, symbiotically-fermented beverages kefir, water kefir and kombucha. A number of minor components were revealed, many of which had not previously been associated with these beverages. The dominant microorganism in each of the water kefir grains and fermentates was Zymomonas, an ethanol-producing bacterium that had not previously been detected on such a scale. These studies represent the most accurate description of these populations to date, and should aid in future starter design and in determining which species are responsible for specific attributes of the beverages. Finally, high-throughput robotics was applied to screen for the presence of antimicrobial producers associated with these beverages. This revealed a low frequency of bacteriocin production amongst the bacterial isolates, with only lactococcins A, B and LcnN of lactococcin M being identified. However, a proteinaceous antimicrobial produced by the yeast Dekkera bruxellensis, isolated from kombucha, was found to be active against Lactobacillus bulgaricus. This peptide was patially purified.

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Continuing our development of a mathematical theory of stochastic microlensing, we study the random shear and expected number of random lensed images of different types. In particular, we characterize the first three leading terms in the asymptotic expression of the joint probability density function (pdf) of the random shear tensor due to point masses in the limit of an infinite number of stars. Up to this order, the pdf depends on the magnitude of the shear tensor, the optical depth, and the mean number of stars through a combination of radial position and the star's mass. As a consequence, the pdf's of the shear components are seen to converge, in the limit of an infinite number of stars, to shifted Cauchy distributions, which shows that the shear components have heavy tails in that limit. The asymptotic pdf of the shear magnitude in the limit of an infinite number of stars is also presented. All the results on the random microlensing shear are given for a general point in the lens plane. Extending to the general random distributions (not necessarily uniform) of the lenses, we employ the Kac-Rice formula and Morse theory to deduce general formulas for the expected total number of images and the expected number of saddle images. We further generalize these results by considering random sources defined on a countable compact covering of the light source plane. This is done to introduce the notion of global expected number of positive parity images due to a general lensing map. Applying the result to microlensing, we calculate the asymptotic global expected number of minimum images in the limit of an infinite number of stars, where the stars are uniformly distributed. This global expectation is bounded, while the global expected number of images and the global expected number of saddle images diverge as the order of the number of stars. © 2009 American Institute of Physics.

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The population structure of an organism reflects its evolutionary history and influences its evolutionary trajectory. It constrains the combination of genetic diversity and reveals patterns of past gene flow. Understanding it is a prerequisite for detecting genomic regions under selection, predicting the effect of population disturbances, or modeling gene flow. This paper examines the detailed global population structure of Arabidopsis thaliana. Using a set of 5,707 plants collected from around the globe and genotyped at 149 SNPs, we show that while A. thaliana as a species self-fertilizes 97% of the time, there is considerable variation among local groups. This level of outcrossing greatly limits observed heterozygosity but is sufficient to generate considerable local haplotypic diversity. We also find that in its native Eurasian range A. thaliana exhibits continuous isolation by distance at every geographic scale without natural breaks corresponding to classical notions of populations. By contrast, in North America, where it exists as an exotic species, A. thaliana exhibits little or no population structure at a continental scale but local isolation by distance that extends hundreds of km. This suggests a pattern for the development of isolation by distance that can establish itself shortly after an organism fills a new habitat range. It also raises questions about the general applicability of many standard population genetics models. Any model based on discrete clusters of interchangeable individuals will be an uneasy fit to organisms like A. thaliana which exhibit continuous isolation by distance on many scales.

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PURPOSE: A projection onto convex sets reconstruction of multiplexed sensitivity encoded MRI (POCSMUSE) is developed to reduce motion-related artifacts, including respiration artifacts in abdominal imaging and aliasing artifacts in interleaved diffusion-weighted imaging. THEORY: Images with reduced artifacts are reconstructed with an iterative projection onto convex sets (POCS) procedure that uses the coil sensitivity profile as a constraint. This method can be applied to data obtained with different pulse sequences and k-space trajectories. In addition, various constraints can be incorporated to stabilize the reconstruction of ill-conditioned matrices. METHODS: The POCSMUSE technique was applied to abdominal fast spin-echo imaging data, and its effectiveness in respiratory-triggered scans was evaluated. The POCSMUSE method was also applied to reduce aliasing artifacts due to shot-to-shot phase variations in interleaved diffusion-weighted imaging data corresponding to different k-space trajectories and matrix condition numbers. RESULTS: Experimental results show that the POCSMUSE technique can effectively reduce motion-related artifacts in data obtained with different pulse sequences, k-space trajectories and contrasts. CONCLUSION: POCSMUSE is a general post-processing algorithm for reduction of motion-related artifacts. It is compatible with different pulse sequences, and can also be used to further reduce residual artifacts in data produced by existing motion artifact reduction methods.

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Scheduling a set of jobs over a collection of machines to optimize a certain quality-of-service measure is one of the most important research topics in both computer science theory and practice. In this thesis, we design algorithms that optimize {\em flow-time} (or delay) of jobs for scheduling problems that arise in a wide range of applications. We consider the classical model of unrelated machine scheduling and resolve several long standing open problems; we introduce new models that capture the novel algorithmic challenges in scheduling jobs in data centers or large clusters; we study the effect of selfish behavior in distributed and decentralized environments; we design algorithms that strive to balance the energy consumption and performance.

The technically interesting aspect of our work is the surprising connections we establish between approximation and online algorithms, economics, game theory, and queuing theory. It is the interplay of ideas from these different areas that lies at the heart of most of the algorithms presented in this thesis.

The main contributions of the thesis can be placed in one of the following categories.

1. Classical Unrelated Machine Scheduling: We give the first polygorithmic approximation algorithms for minimizing the average flow-time and minimizing the maximum flow-time in the offline setting. In the online and non-clairvoyant setting, we design the first non-clairvoyant algorithm for minimizing the weighted flow-time in the resource augmentation model. Our work introduces iterated rounding technique for the offline flow-time optimization, and gives the first framework to analyze non-clairvoyant algorithms for unrelated machines.

2. Polytope Scheduling Problem: To capture the multidimensional nature of the scheduling problems that arise in practice, we introduce Polytope Scheduling Problem (\psp). The \psp problem generalizes almost all classical scheduling models, and also captures hitherto unstudied scheduling problems such as routing multi-commodity flows, routing multicast (video-on-demand) trees, and multi-dimensional resource allocation. We design several competitive algorithms for the \psp problem and its variants for the objectives of minimizing the flow-time and completion time. Our work establishes many interesting connections between scheduling and market equilibrium concepts, fairness and non-clairvoyant scheduling, and queuing theoretic notion of stability and resource augmentation analysis.

3. Energy Efficient Scheduling: We give the first non-clairvoyant algorithm for minimizing the total flow-time + energy in the online and resource augmentation model for the most general setting of unrelated machines.

4. Selfish Scheduling: We study the effect of selfish behavior in scheduling and routing problems. We define a fairness index for scheduling policies called {\em bounded stretch}, and show that for the objective of minimizing the average (weighted) completion time, policies with small stretch lead to equilibrium outcomes with small price of anarchy. Our work gives the first linear/ convex programming duality based framework to bound the price of anarchy for general equilibrium concepts such as coarse correlated equilibrium.

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Our media is saturated with claims of ``facts'' made from data. Database research has in the past focused on how to answer queries, but has not devoted much attention to discerning more subtle qualities of the resulting claims, e.g., is a claim ``cherry-picking''? This paper proposes a Query Response Surface (QRS) based framework that models claims based on structured data as parameterized queries. A key insight is that we can learn a lot about a claim by perturbing its parameters and seeing how its conclusion changes. This framework lets us formulate and tackle practical fact-checking tasks --- reverse-engineering vague claims, and countering questionable claims --- as computational problems. Within the QRS based framework, we take one step further, and propose a problem along with efficient algorithms for finding high-quality claims of a given form from data, i.e. raising good questions, in the first place. This is achieved to using a limited number of high-valued claims to represent high-valued regions of the QRS. Besides the general purpose high-quality claim finding problem, lead-finding can be tailored towards specific claim quality measures, also defined within the QRS framework. An example of uniqueness-based lead-finding is presented for ``one-of-the-few'' claims, landing in interpretable high-quality claims, and an adjustable mechanism for ranking objects, e.g. NBA players, based on what claims can be made for them. Finally, we study the use of visualization as a powerful way of conveying results of a large number of claims. An efficient two stage sampling algorithm is proposed for generating input of 2d scatter plot with heatmap, evalutaing a limited amount of data, while preserving the two essential visual features, namely outliers and clusters. For all the problems, we present real-world examples and experiments that demonstrate the power of our model, efficiency of our algorithms, and usefulness of their results.