939 resultados para multiple sclerosis


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A central tenet in the theory of reliability modelling is the quantification of the probability of asset failure. In general, reliability depends on asset age and the maintenance policy applied. Usually, failure and maintenance times are the primary inputs to reliability models. However, for many organisations, different aspects of these data are often recorded in different databases (e.g. work order notifications, event logs, condition monitoring data, and process control data). These recorded data cannot be interpreted individually, since they typically do not have all the information necessary to ascertain failure and preventive maintenance times. This paper presents a methodology for the extraction of failure and preventive maintenance times using commonly-available, real-world data sources. A text-mining approach is employed to extract keywords indicative of the source of the maintenance event. Using these keywords, a Naïve Bayes classifier is then applied to attribute each machine stoppage to one of two classes: failure or preventive. The accuracy of the algorithm is assessed and the classified failure time data are then presented. The applicability of the methodology is demonstrated on a maintenance data set from an Australian electricity company.

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While performing a mission, multiple Unmanned Aerial Vehicles (UAVs) need to avoid each other to prevent collisions among them. In this paper, we design a collision avoidance algorithm to resolve the conflict among UAVs that are on a collision course while flying to heir respective destinations. The collision avoidance algorithm consist of each UAV that is on a collision course reactively executing a maneuver that will, as in `inverse' Proportional Navigation (PN), increase Line of Sight (LOS) rate between them, resulting in a `pulling out' of collision course. The algorithm is tested for high density traffic scenarios as well as for robustness in the presence of noise.

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This paper presents a comparative population dynamics study of three closely related species of buttercups (Ranunculus repens, R. acris, and R. bulbosus). The study is based on an investigation of the behaviour of the seeds in soil under field conditions and a continuous monitoring of survival and reproduction of some 9000 individual plants over a period of 21/2 years in a coastal grassland in North Wales. The data were analysed with the help of an extension of Leslie's matrix method which makes possible an simultaneous treatment of vegetative and sexual reproduction. It was found that R. repens (a) depends more heavily on vegetative as compared with sexual reproduction, (b) shows indications of negatively density-dependent population regulation, and (c) exhibits little variation in population growth rates from site to site and from one year to the next. In contrast, R. bulbosus (a) depends exclusively on sexual reproduction, (b) shows indications of a positively density-dependent population behaviour, and (c) exhibits great variation in population growth rates from site to site and from one year to the next. R. acris exhibits an intermediate behaviour in all these respects. It is suggested that the attributes of R. repens are those expected of a species inhabiting a stable environment, while R. bulbosus exhibits some of the characteristics of a fugitive species.

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Relative abundance distributions of multiply-charged ionic species have been measured for the RF spark and vacuum vibrator are ion sources, for a number of elements. An attempt has been made to explain the observed charge state distribution on the basis of models for the arc and spark plasma. The difficulties in the way of explaining the observed charge state distributions, using the LTE model with Saha distribution as well as the corona model, are pointed out. The distribution can be explained by a diffusion-dominated plasma model with known or calculated values for ionization cross-sections, the single impact model being suitable for the RF spark and the multiple impact model for the vibrator arc.

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Forkhead box class O (FoxO) transcription factors are members of the forkhead box transcription factor superfamily, with orthologues in various species such as human, worm and fly. FoxO proteins are key regulators of growth, metabolism, stress resistance and, consequently, life span. FoxOs integrate signals from different pathways, e.g. the growth controlling Insulin-TOR signaling pathway and the stress induced JNK and Hippo signaling pathways. FoxO proteins have evolved to guide the cellular response to varying energy and stress conditions by inducing the expression of genes involved in the regulation of growth and metabolism. This work has aimed to deepen the understanding of how FoxO executes its biological functions. A particular emphasis has been laid to its role in growth control. Specifically, evidence is presented indicating that FoxO restricts tissue growth in a situation when TOR signaling is high. This finding can have implications in a human condition called Tuberous sclerosis, manifested by multiple benign tumors. Further, it is shown that FoxO directly binds to the promoter and regulates the expression of a Drosophila Adenylate cyclase gene, ac76e, which in turn modulates the fly s development and growth systemically. These results strengthen FoxOs position among central size regulators as it is able to operate at the level of individual cells as well as in the whole organism. Finally, an attempt to reveal the regulatory network upstream of FoxO has been carried out. Several putative FoxO activity regulators were identified in an RNAi screen of Drosophila kinases and phosphatases. The results underscore that FoxO is regulated through an elaborate network, ensuring the correct execution of key cellular processes in metabolism and response to stress. Overall, the evidence provided in this study strengthens our view of FoxO as a key integrator of growth and stress signals.

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This paper will discuss the complexities of the role of contemporary dancer in this current epoch, with a particular focus on the multiple identities dancers embody within dance practice and how these accumulate to form a creative self-in-process or ‘moving identity’. Wider issues, such as training will be explored questioning how technical skills can be imparted alongside autonomous learning approaches to ensure that dancers are prepared to negotiate the entrepreneurial ecology of various dance sectors. Furthermore, the paper will examine the shifting relationship between choreographer and dancer from hierarchical to co-creative including how, in spite of the often collaborative nature of dance creation, the marketplace continues to celebrate the singular authorial position of the choreographer. Each of these elements will reflect back the complex issues of agency and creative self-hood that dancers must negotiate in an increasingly diverse and changeable arts environment.

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This paper investigates multiple roles of transfer prices for shipments of goods and services between entities of a multinational enterprise. At the center is the role of transfer pricing (TP) in tax manipulation, but other roles having to do with internal operations or strategic delegation, etc. are also considered. The interesting question is to what extent and how the different roles of TPs interfere with each other. The answer depends on whether companies use one or two books, i.e. whether they (can) apply different TPs for different purposes. We illustrate, in a stylized model, the competing aims of tax manipulation and strategic delegation. Finally, we briefly look at selected reform proposals, concluding that either TP problems are not addressed, or else new distortions will be introduced instead.

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We are addressing the novel problem of jointly evaluating multiple speech patterns for automatic speech recognition and training. We propose solutions based on both the non-parametric dynamic time warping (DTW) algorithm, and the parametric hidden Markov model (HMM). We show that a hybrid approach is quite effective for the application of noisy speech recognition. We extend the concept to HMM training wherein some patterns may be noisy or distorted. Utilizing the concept of ``virtual pattern'' developed for joint evaluation, we propose selective iterative training of HMMs. Evaluating these algorithms for burst/transient noisy speech and isolated word recognition, significant improvement in recognition accuracy is obtained using the new algorithms over those which do not utilize the joint evaluation strategy.

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In lake ecosystems, both fish and invertebrate predators have dramatic effects on their prey communities. Fish predation selects large cladocerans while invertebrate predators prefer prey of smaller size. Since invertebrate predators are the preferred food items for fish, their occurrence at high densities is often connected with the absence or low number of fish. It is generally believed that invertebrate predators can play a significant role only if the density of planktivorous fish is low. However, in eutrophic clay-turbid Lake Hiidenvesi (southern Finland), a dense population of predatory Chaoborus flavicans larvae coexists with an abundant fish population. The population covers the stratifying area of the lake and attains a maximum population density of 23000 ind. m-2. This thesis aims to clarify the effects of Chaoborus flavicans on the zooplankton community and the environmental factors facilitating the coexistence of fish and invertebrate predators. In the stratifying area of Lake Hiidenvesi, the seasonal succession of cladocerans was exceptional. The spring biomass peak of cladocerans was missing and the highest biomass occurred in midsummer. In early summer, the consumption rate by chaoborids clearly exceeded the production rate of cladocerans and each year the biomass peak of cladocerans coincided with the minimum chaoborid density. In contrast, consumption by fish was very low and each study year cladocerans attained maximum biomass simultaneously with the highest consumption by smelt (Osmerus eperlanus). The results indicated that Chaoborus flavicans was the main predator of cladocerans in the stratifying area of Lake Hiidenvesi. The clay turbidity strongly contributed to the coexistence of chaoborids and smelt at high densities. Turbidity exceeding 30 NTU combined with light intensity below 0.1 μE m-2 s-1provides an efficient daytime refuge for chaoborids, but turbidity alone is not an adequate refuge unless combined with low light intensity. In the non-stratifying shallow basins of Lake Hiidenvesi, light intensity exceeds this level during summer days at the bottom of the lake, preventing Chaoborus forming a dense population in the shallow parts of the lake. Chaoborus can be successful particularly in deep, clay-turbid lakes where they can remain high in the water column close to their epilimnetic prey. Suspended clay alters the trophic interactions by weakening the link between fish and Chaoborus, which in turn strengthens the effect of Chaoborus predation on crustacean zooplankton. Since food web management largely relies on manipulations of fish stocks and the cascading effects of such actions, the validity of the method in deep clay-turbid lakes may be questioned.

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Missense and frameshift mutations in TRAF family member-associated NF-kappa-B activator (TANK)-binding kinase 1 (TBK1) have been reported in European sporadic and familial amyotrophic lateral sclerosis (ALS) cohorts. To assess the role of TBK1 in ALS patient cohorts of wider ancestry, we have analyzed whole-exome sequence data from an Australian cohort of familial ALS (FALS) patients and controls. We identified a novel TBK1 deletion (c.1197delC) in a FALS patient of Chinese origin. This frameshift mutation (p.L399fs) likely results in a truncated protein that lacks functional domains required for adapter protein binding, as well as protein activation and structural integrity. No novel or reported TBK1 mutations were identified in FALS patients of European ancestry. This is the first report of a TBK1 mutation in an ALS patient of Asian origin and indicates that sequence variations in TBK1 are a rare cause of FALS in Australia. © 2015 Elsevier Inc.

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Agriculture-mediated habitat loss and degradation together with climate change are among the greatest global threats to species, communities, and ecosystem functioning. During the last century, more than 50% of the world's wetlands have been lost and agricultural activities have subjected wetland species to increased isolation and decreased quality of habitats. Likewise, as a part of agricultural intensification, the use of pesticides has increased notably, and pesticide residues occur frequently in wetlands making the exposure of wetland organisms to pesticides highly probable. In this thesis, a set of ecotoxicological and landscape ecological studies were carried out to investigate pesticide-effects on tadpoles, and species-habitat relationships of amphibians in agricultural landscapes. The results show that the fitness of R. temporaria tadpoles can be negatively affected by sublethal pesticide concentrations, and that pesticides may increase the costs of response to natural environmental stressors. However, tadpoles may also be able to compensate for some of the negative effects of pesticides. The results further demonstrate that both historic and current-day agricultural land use can negatively impact amphibians, but that in some cases the costs of living in agricultural habitats may only become apparent when amphibians face other environmental stressors, such as drought. Habitat heterogeneity may, however, increase the persistence of amphibians in agricultural landscapes. Hence, the results suggest that amphibians are likely to be affected by agricultural processes that operate at several spatial and temporal scales, and that it is probable that various processes related to current-day agriculture will affect both larval and adult amphibians. The results imply that maintaining dense wetland patterns could enhance persistence of amphibian populations in agricultural habitats, and indicate that heterogeneous landscapes may lower the risk of regional amphibian population declines under extreme weather perturbations.

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In this work, we evaluate the benefits of using Grids with multiple batch systems to improve the performance of multi-component and parameter sweep parallel applications by reduction in queue waiting times. Using different job traces of different loads, job distributions and queue waiting times corresponding to three different queuing policies(FCFS, conservative and EASY backfilling), we conducted a large number of experiments using simulators of two important classes of applications. The first simulator models Community Climate System Model (CCSM), a prominent multi-component application and the second simulator models parameter sweep applications. We compare the performance of the applications when executed on multiple batch systems and on a single batch system for different system and application configurations. We show that there are a large number of configurations for which application execution using multiple batch systems can give improved performance over execution on a single system.

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Accurately quantifying total greenhouse gas emissions (e.g. methane) from natural systems such as lakes, reservoirs and wetlands requires the spatial-temporal measurement of both diffusive and ebullitive (bubbling) emissions. Traditional, manual, measurement techniques provide only limited localised assessment of methane flux, often introducing significant errors when extrapolated to the whole-of-system. In this paper, we directly address these current sampling limitations and present a novel multiple robotic boat system configured to measure the spatiotemporal release of methane to atmosphere across inland waterways. The system, consisting of multiple networked Autonomous Surface Vehicles (ASVs) and capable of persistent operation, enables scientists to remotely evaluate the performance of sampling and modelling algorithms for real-world process quantification over extended periods of time. This paper provides an overview of the multi-robot sampling system including the vehicle and gas sampling unit design. Experimental results are shown demonstrating the system’s ability to autonomously navigate and implement an exploratory sampling algorithm to measure methane emissions on two inland reservoirs.

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We consider the problem of transmission of correlated discrete alphabet sources over a Gaussian Multiple Access Channel (GMAC). A distributed bit-to-Gaussian mapping is proposed which yields jointly Gaussian codewords. This can guarantee lossless transmission or lossy transmission with given distortions, if possible. The technique can be extended to the system with side information at the encoders and decoder.