921 resultados para Skyways Limited
Resumo:
Pseudomonas aeruginosa is an opportunistic pathogen and an important cause of infection, particularly amongst cystic fibrosis (CF) patients. While specific strains capable of patient-to-patient transmission are known, many infections appear to be caused by unique and unrelated strains. There is a need to understand the relationship between strains capable of colonising the CF lung and the broader set of P. aeruginosa isolates found in natural environments. Here we report the results of a multilocus sequence typing (MLST)-based study designed to understand the genetic diversity and population structure of an extensive regional sample of P. aeruginosa isolates from South East Queensland, Australia. The analysis is based on 501 P. aeruginosa isolates obtained from environmental, animal and human (CF and non-CF) sources with particular emphasis on isolates from the Lower Brisbane River and isolates from CF patients obtained from the same geographical region. Overall, MLST identified 274 different sequence types, of which 53 were shared between one or more ecological settings. Our analysis revealed a limited association between genotype and environment and evidence of frequent recombination. We also found that genetic diversity of P. aeruginosa in Queensland, Australia was indistinguishable from that of the global P. aeruginosa population. Several CF strains were encountered frequently in multiple ecological settings; however, the most frequently encountered CF strains were confined to CF patients. Overall, our data confirm a non-clonal epidemic structure and indicate that most CF strains are a random sample of the broader P. aeruginosa population. The increased abundance of some CF strains in different geographical regions is a likely product of chance colonisation events followed by adaptation to the CF lung and horizontal transmission among patients.
On the complexity of solving polytree-shaped limited memory influence diagrams with binary variables
Resumo:
Influence diagrams are intuitive and concise representations of structured decision problems. When the problem is non-Markovian, an optimal strategy can be exponentially large in the size of the diagram. We can avoid the inherent intractability by constraining the size of admissible strategies, giving rise to limited memory influence diagrams. A valuable question is then how small do strategies need to be to enable efficient optimal planning. Arguably, the smallest strategies one can conceive simply prescribe an action for each time step, without considering past decisions or observations. Previous work has shown that finding such optimal strategies even for polytree-shaped diagrams with ternary variables and a single value node is NP-hard, but the case of binary variables was left open. In this paper we address such a case, by first noting that optimal strategies can be obtained in polynomial time for polytree-shaped diagrams with binary variables and a single value node. We then show that the same problem is NP-hard if the diagram has multiple value nodes. These two results close the fixed-parameter complexity analysis of optimal strategy selection in influence diagrams parametrized by the shape of the diagram, the number of value nodes and the maximum variable cardinality.
Resumo:
We present a new algorithm for exactly solving decision-making problems represented as an influence diagram. We do not require the usual assumptions of no forgetting and regularity, which allows us to solve problems with limited information. The algorithm, which implements a sophisticated variable elimination procedure, is empirically shown to outperform a state-of-the-art algorithm in randomly generated problems of up to 150 variables and 10^64 strategies.
Resumo:
We present a new algorithm for exactly solving decision making problems represented as influence diagrams. We do not require the usual assumptions of no forgetting and regularity; this allows us to solve problems with simultaneous decisions and limited information. The algorithm is empirically shown to outperform a state-of-the-art algorithm on randomly generated problems of up to 150 variables and 10^64 solutions. We show that these problems are NP-hard even if the underlying graph structure of the problem has low treewidth and the variables take on a bounded number of states, and that they admit no provably good approximation if variables can take on an arbitrary number of states.
Resumo:
We present a new algorithm for exactly solving decision making problems represented as influence diagrams. We do not require the usual assumptions of no forgetting and regularity; this allows us to solve problems with simultaneous decisions and limited information. The algorithm is empirically shown to outperform a state-of-the-art algorithm on randomly generated problems of up to 150 variables and 10^64 solutions. We show that the problem is NP-hard even if the underlying graph structure of the problem has small treewidth and the variables take on a bounded number of states, but that a fully polynomial time approximation scheme exists for these cases. Moreover, we show that the bound on the number of states is a necessary condition for any efficient approximation scheme.
Resumo:
We describe some unsolved problems of current interest; these involve quantum critical points in
ferroelectrics and problems which are not amenable to the usual density functional theory, nor to
classical Landau free energy approaches (they are kinetically limited), nor even to the Landau–
Kittel relationship for domain size (they do not satisfy the assumption of infinite lateral diameter)
because they are dominated by finite aperiodic boundary conditions.
Resumo:
This paper presents a novel method of audio-visual fusion for person identification where both the speech and facial modalities may be corrupted, and there is a lack of prior knowledge about the corruption. Furthermore, we assume there is a limited amount of training data for each modality (e.g., a short training speech segment and a single training facial image for each person). A new representation and a modified cosine similarity are introduced for combining and comparing bimodal features with limited training data as well as vastly differing data rates and feature sizes. Optimal feature selection and multicondition training are used to reduce the mismatch between training and testing, thereby making the system robust to unknown bimodal corruption. Experiments have been carried out on a bimodal data set created from the SPIDRE and AR databases with variable noise corruption of speech and occlusion in the face images. The new method has demonstrated improved recognition accuracy.
Resumo:
High levels of genetic diversity and high propagule pressure are favoured by conservation biologists as the basis for successful reintroductions and ensuring the persistence of populations. However, invasion ecologists recognize the ‘paradox of invasion’, as successful species introductions may often be characterized by limited numbers of individuals and associated genetic bottlenecks. In the present study, we used a combination of high-resolution nuclear and mitochondrial genetic markers to investigate the invasion history of Reeves' muntjac deer in the British Isles. This invasion has caused severe economic and ecological damage, with secondary spread currently a concern throughout Europe and potentially globally. Microsatellite analysis based on eight loci grouped all 176 introduced individuals studied from across the species' range in the UK into one genetic cluster, and seven mitochondrial D-loop haplotypes were recovered, two of which were present at very low frequency and were related to more common haplotypes. Our results indicate that the entire invasion can be traced to a single founding event involving a low number of females. These findings highlight the fact that even small releases of species may, if ignored, result in irreversible and costly invasion, regardless of initial genetic diversity or continual genetic influx.
Resumo:
his paper considers a problem of identification for a high dimensional nonlinear non-parametric system when only a limited data set is available. The algorithms are proposed for this purpose which exploit the relationship between the input variables and the output and further the inter-dependence of input variables so that the importance of the input variables can be established. A key to these algorithms is the non-parametric two stage input selection algorithm.
Resumo:
Tal como o título indica, esta tese estuda problemas de cobertura com alcance limitado. Dado um conjunto de antenas (ou qualquer outro dispositivo sem fios capaz de receber ou transmitir sinais), o objectivo deste trabalho é calcular o alcance mínimo das antenas de modo a que estas cubram completamente um caminho entre dois pontos numa região. Um caminho que apresente estas características é um itinerário seguro. A definição de cobertura é variável e depende da aplicação a que se destina. No caso de situações críticas como o controlo de fogos ou cenários militares, a definição de cobertura recorre à utilização de mais do que uma antena para aumentar a eficácia deste tipo de vigilância. No entanto, o alcance das antenas deverá ser minimizado de modo a manter a vigilância activa o maior tempo possível. Consequentemente, esta tese está centrada na resolução deste problema de optimização e na obtenção de uma solução particular para cada caso. Embora este problema de optimização tenha sido investigado como um problema de cobertura, é possível estabelecer um paralelismo entre problemas de cobertura e problemas de iluminação e vigilância, que são habitualmente designados como problemas da Galeria de Arte. Para converter um problema de cobertura num de iluminação basta considerar um conjunto de luzes em vez de um conjunto de antenas e submetê-lo a restrições idênticas. O principal tema do conjunto de problemas da Galeria de Arte abordado nesta tese é a 1-boa iluminação. Diz-se que um objecto está 1-bem iluminado por um conjunto de luzes se o invólucro convexo destas contém o objecto, tornando assim este conceito num tipo de iluminação de qualidade. O objectivo desta parte do trabalho é então minimizar o alcance das luzes de modo a manter uma iluminação de qualidade. São também apresentadas duas variantes da 1-boa iluminação: a iluminação ortogonal e a boa !-iluminação. Esta última tem aplicações em problemas de profundidade e visualização de dados, temas que são frequentemente abordados em estatística. A resolução destes problemas usando o diagrama de Voronoi Envolvente (uma variante do diagrama de Voronoi adaptada a problemas de boa iluminação) é também proposta nesta tese.
Resumo:
This article discusses the application in a CAMHS setting of a distinctive intervention for adolescent mental health difficulties, Time‐limited Adolescent Psychodynamic Psychotherapy (TAPP). TAPP has been developed specifically for working with adolescents and the characteristic developmental and psychosocial complexities they present to mental health services. It is widely recognised that supporting the developmental process in adolescence is central to therapeutic interventions and the therapeutic aim of TAPP is to enable recovery of the capacity to meet developmental challenges. The key factors of TAPP are described, including the formulation and working with a developmental focus, the therapeutic stance, working with transference and counter‐transference, working with time limits, and the emphasis on engagement of adolescents in therapy in TAPP. The experiences of introducing and developing TAPP in the CAMHS service are discussed with two brief and one extended case examples and this leads to a discussion of the kinds of outcomes achieved. It is concluded that TAPP is a key and relevant intervention for adolescents in complex and vulnerable situations; further work will be undertaken to continue its application in these settings and to formally assess outcomes.
Resumo:
Background In recent years, an abstinence-focused, ‘recovery’ agenda has emerged in UK drug policy, largely in response to the perception that many opioid users had been ‘parked indefinitely’ on Opioid Substitution Therapy (OST). The introduction of ten pilot ‘Drug Recovery Wings’ (DRWs) in 2011 represents the application of this recovery agenda to prisons. This paper describes the DRWs’ operational models, the place of opiate dependent prisoners within them, and the challenges of delivering ‘recovery’ in prison. Methods In 2013, the implementation and operational models of all ten pilot DRWs were rapidly assessed. Up to three days were spent in each DRW, undertaking semi-structured interviews with a sample of 94 DRW staff and 102 DRW residents. Interviews were fully transcribed, and coded using grounded theory. Findings from the nine adult prisons are presented here. Results Four types of DRW were identified, distinguished by their size and selection criteria. Strikingly, no mid- or large-sized units regularly supported OST recipients through detoxification. Type A were large units whose residents were mostly on OST with long criminal records and few social or personal resources. Detoxification was rare, and medication reduction slow. Type B's mid-sized DRW was developed as a psychosocial support service for OST clients seeking detoxification. However, staff struggled to find such prisoners, and detoxification again proved rare. Type C DRWs focused on abstinence from all drugs, including OST. Though OST clients were not intentionally excluded, very few applied to these wings. Only Type D DRWs, offering intensive treatment on very small wings, regularly recruited OST recipients into abstinence-focused interventions. Conclusion Prison units wishing to support OST recipients in making greater progress towards abstinence may need to be small, intensive and take a stepped approach based on preparatory motivational work and extensive preparation for release. However, concerns about post-release deaths will remain.
Resumo:
This paper analyzes the optimal quality decision of a producer in a multi-period setting with reputation effects. Using a unique database of returns on real estate limited partnerships (RELPs), we empirically examine alternative theoretical predictions of optimal producer strategy. In particular, we test whether the producers in our market invest in reputation building by initially selling high quality goods and then lowering quality. Using a variety of statistical tests, we find evidence consistent with reputation building, both in the aggregate and for individual developers.
Resumo:
Many-core platforms are an emerging technology in the real-time embedded domain. These devices offer various options for power savings, cost reductions and contribute to the overall system flexibility, however, issues such as unpredictability, scalability and analysis pessimism are serious challenges to their integration into the aforementioned area. The focus of this work is on many-core platforms using a limited migrative model (LMM). LMM is an approach based on the fundamental concepts of the multi-kernel paradigm, which is a promising step towards scalable and predictable many-cores. In this work, we formulate the problem of real-time application mapping on a many-core platform using LMM, and propose a three-stage method to solve it. An extended version of the existing analysis is used to assure that derived mappings (i) guarantee the fulfilment of timing constraints posed on worst-case communication delays of individual applications, and (ii) provide an environment to perform load balancing for e.g. energy/thermal management, fault tolerance and/or performance reasons.
Resumo:
This article deals with a real-life waste collection routing problem. To efficiently plan waste collection, large municipalities may be partitioned into convenient sectors and only then can routing problems be solved in each sector. Three diverse situations are described, resulting in three different new models. In the first situation, there is a single point of waste disposal from where the vehicles depart and to where they return. The vehicle fleet comprises three types of collection vehicles. In the second, the garage does not match any of the points of disposal. The vehicle is unique and the points of disposal (landfills or transfer stations) may have limitations in terms of the number of visits per day. In the third situation, disposal points are multiple (they do not coincide with the garage), they are limited in the number of visits, and the fleet is composed of two types of vehicles. Computational results based not only on instances adapted from the literature but also on real cases are presented and analyzed. In particular, the results also show the effectiveness of combining sectorization and routing to solve waste collection problems.