994 resultados para multiple hypotheses
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2000 Mathematics Subject Classification: 62P30.
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The boreal forest of western Canada is being dissected by seismic lines used for oil and gas exploration. The vast amount of edge being created is leading to concerns that core habitat will be reduced for forest interior species for extended periods of time. The Ovenbird (Seiurus aurocapilla) is a boreal songbird known to be sensitive to newly created seismic lines because it does not include newly cut lines within its territory. We examined multiple hypotheses to explain potential mechanisms causing this behavior by mapping Ovenbird territories near lines with varying states of vegetation regeneration. The best model to explain line exclusion behavior included the number of neighboring conspecifics, the amount of bare ground, leaf-litter depth, and canopy closure. Ovenbirds exclude recently cut seismic lines from their territories because of lack of protective cover (lower tree and shrub cover) and because of reduced food resources due to large areas of bare ground. Food reduction and perceived predation risk effects seem to be mitigated once leaf litter (depth and extent of cover) and woody vegetation cover are restored to forest interior levels. However, as conspecific density increases, lines are more likely to be used as landmarks to demarcate territorial boundaries, even when woody vegetation cover and leaf litter are restored. This behavior can reduce territory density near seismic lines by changing the spatial distribution of territories. Landmark effects are longer lasting than the effects from reduced food or perceived predation risk because canopy height and tree density take >40 years to recover to forest interior levels. Mitigation of seismic line impacts on Ovenbirds should focus on restoring forest cover as quickly as possible after line cutting.
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During the development of new therapies, it is not uncommon to test whether a new treatment works better than the existing treatment for all patients who suffer from a condition (full population) or for a subset of the full population (subpopulation). One approach that may be used for this objective is to have two separate trials, where in the first trial, data are collected to determine if the new treatment benefits the full population or the subpopulation. The second trial is a confirmatory trial to test the new treatment in the population selected in the first trial. In this paper, we consider the more efficient two-stage adaptive seamless designs (ASDs), where in stage 1, data are collected to select the population to test in stage 2. In stage 2, additional data are collected to perform confirmatory analysis for the selected population. Unlike the approach that uses two separate trials, for ASDs, stage 1 data are also used in the confirmatory analysis. Although ASDs are efficient, using stage 1 data both for selection and confirmatory analysis introduces selection bias and consequently statistical challenges in making inference. We will focus on point estimation for such trials. In this paper, we describe the extent of bias for estimators that ignore multiple hypotheses and selecting the population that is most likely to give positive trial results based on observed stage 1 data. We then derive conditionally unbiased estimators and examine their mean squared errors for different scenarios.
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Pós-graduação em Ciências Biológicas (Zoologia) - IBRC
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In this paper we present a model-based approach for real-time camera pose estimation in industrial scenarios. The line model which is used for tracking is generated by rendering a polygonal model and extracting contours out of the rendered scene. By un-projecting a point on the contour with the depth value stored in the z-buffer, the 3D coordinates of the contour can be calculated. For establishing 2D/3D correspondences the 3D control points on the contour are projected into the image and a perpendicular search for gradient maxima for every point on the contour is performed. Multiple hypotheses of 2D image points corresponding to a 3D control point make the pose estimation robust against ambiguous edges in the image.
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Background: Nigeria was one of the 13 countries where avian influenza outbreak in poultry farms was reported during the 2006 avian influenza pandemic threat and was also the first country in Africa to report the presence of H5N1influenza among its poultry population. There are multiple hypotheses on how the avian influenza outbreak of 2006 was introduced to Nigeria, but the consensus is that once introduced, poultry farms and their workers were responsible for 70% of the spread of avian influenza virus to other poultry farms and the population. ^ The spread of avian influenza has been attributed to lack of compliance by poultry farms and their workers with poultry farm biosecurity measures. When poultry farms fail to adhere to biosecurity measures and there is an outbreak of infectious diseases like in 2006, epidemiological investigations usually assess poultry farm biosecurity—often with the aid of a questionnaire. Despite the importance of questionnaires in determining farm compliance with biosecurity measures, there have been few efforts to determine the validity of questionnaires designed to assess poultry farms risk factors. Hence, this study developed and validated a tool (questionnaire) that can be used for poultry farm risk stratification in Imo State, Nigeria. ^ Methods: Risk domains were generated using literature and recommendations from agricultural organizations and the Nigeria government for poultry farms. The risk domains were then used to develop a questionnaire. Both the risk domain and questionnaire were verified and modified by a group of five experts with a research interest in Nigeria's poultry industry and/or avian influenza prevention. Once a consensus was reached by the experts, the questionnaire was distributed to 30 selected poultry farms in Imo State, Nigeria that participated in this study. Survey responses were received for all the 30 poultry farms that were selected. The same poultry farms were visited one week after they completed the questionnaires for on-site observation. Agreement among survey and observation results were analyzed using a kappa test and rated as poor, fair, moderate, substantial, or nearly perfect; and internal consistency of the survey was also computed. ^ Result: Out of the 43 items on the questionnaire, 32 items were validated by this study. The agreement between the survey result and onsite observation was analyzed using kappa test and ranged from poor to nearly perfect. Most poultry farms had their best agreements in the contact section of the survey. The least agreement was noted in the farm management section of the survey. Thirty-two questions on the survey had a coefficient alpha > 0.70, which is a robust internal consistency for the survey. ^ Conclusion: This study developed 14 risk domains for poultry farms in Nigeria and validated 32 items from the original questionnaire that contained 43 items. The validated items can be used to determine the risk of introduction and spread of avian influenza virus in poultry farms in Imo State, Nigeria. After further validations in other states, regions and poultry farm sectors in Nigeria; this risk assessment tool can then be used to determine the risk profile of poultry farms across Nigeria.^
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Six alternative hypotheses for the phylogenetic origin of Bilateria are evaluated by using complete 18S rRNA gene sequences for 52 taxa. These data suggest that there is little support for three of these hypotheses. Bilateria is not likely to be the sister group of Radiata or Ctenophora, nor is it likely that Bilateria gave rise to Cnidaria or Ctenophora. Instead, these data reveal a close relationship between bilaterians, placozoans, and cnidarians. From this, several inferences can be drawn. Morphological features that previously have been identified as synapomorphies of Bilateria and Ctenophora, e.g., mesoderm, more likely evolved independently in each clade. The endomesodermal muscles of bilaterians may be homologous to the endodermal muscles of cnidarians, implying that the original bilaterian mesodermal muscles were myoepithelial. Placozoans should have a gastrulation stage during development. Of the three hypotheses that cannot be falsified with the 18S rRNA data, one is most strongly supported. This hypothesis states that Bilateria and Placozoa share a more recent common ancestor than either does to Cnidaria. If true, the simplicity of placozoan body architecture is secondarily derived from a more complex ancestor. This simplification may have occurred in association with a planula-type larva becoming reproductive before metamorphosis. If this simplification took place during the common history that placozoans share with bilaterians, then placozoan genes that contain a homeobox, such as Trox2, should be explored, for they may include the gene or genes most closely related to Hox genes of bilaterians.
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The advances made in channel-capacity codes, such as turbo codes and low-density parity-check (LDPC) codes, have played a major role in the emerging distributed source coding paradigm. LDPC codes can be easily adapted to new source coding strategies due to their natural representation as bipartite graphs and the use of quasi-optimal decoding algorithms, such as belief propagation. This paper tackles a relevant scenario in distributedvideo coding: lossy source coding when multiple side information (SI) hypotheses are available at the decoder, each one correlated with the source according to different correlation noise channels. Thus, it is proposed to exploit multiple SI hypotheses through an efficient joint decoding technique withmultiple LDPC syndrome decoders that exchange information to obtain coding efficiency improvements. At the decoder side, the multiple SI hypotheses are created with motion compensated frame interpolation and fused together in a novel iterative LDPC based Slepian-Wolf decoding algorithm. With the creation of multiple SI hypotheses and the proposed decoding algorithm, bitrate savings up to 8.0% are obtained for similar decoded quality.
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One debated issues in evolutionary biology is, why in many species females mate with multiple males. Several hypotheses have been put forward, yet the benefits of multiple mating (here defined as mating with several males) remain unclear in many cases. The sperm sexual selection (SSS) hypothesis has been developed to account for the widespread occurrence of multiple mating in females. It argues that multiple mating by females may rapidly spread, when initially a small fraction of the females mate multiply, and if there is a heritable difference among males in one or several of the four characteristics: (1) the quantity of sperm they produce; (2) the success of their sperm in reaching and fertilizing an egg; (3) their ability to displace the sperm that females stored during previous mating; and (4) their ability to prevent any other male from subsequently introducing sperm (e.g., differential efficiency of mating plugs).
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It is common in econometric applications that several hypothesis tests arecarried out at the same time. The problem then becomes how to decide whichhypotheses to reject, accounting for the multitude of tests. In this paper,we suggest a stepwise multiple testing procedure which asymptoticallycontrols the familywise error rate at a desired level. Compared to relatedsingle-step methods, our procedure is more powerful in the sense that itoften will reject more false hypotheses. In addition, we advocate the useof studentization when it is feasible. Unlike some stepwise methods, ourmethod implicitly captures the joint dependence structure of the teststatistics, which results in increased ability to detect alternativehypotheses. We prove our method asymptotically controls the familywise errorrate under minimal assumptions. We present our methodology in the context ofcomparing several strategies to a common benchmark and deciding whichstrategies actually beat the benchmark. However, our ideas can easily beextended and/or modied to other contexts, such as making inference for theindividual regression coecients in a multiple regression framework. Somesimulation studies show the improvements of our methods over previous proposals. We also provide an application to a set of real data.
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Consider the problem of testing k hypotheses simultaneously. In this paper,we discuss finite and large sample theory of stepdown methods that providecontrol of the familywise error rate (FWE). In order to improve upon theBonferroni method or Holm's (1979) stepdown method, Westfall and Young(1993) make eective use of resampling to construct stepdown methods thatimplicitly estimate the dependence structure of the test statistics. However,their methods depend on an assumption called subset pivotality. The goalof this paper is to construct general stepdown methods that do not requiresuch an assumption. In order to accomplish this, we take a close look atwhat makes stepdown procedures work, and a key component is a monotonicityrequirement of critical values. By imposing such monotonicity on estimatedcritical values (which is not an assumption on the model but an assumptionon the method), it is demonstrated that the problem of constructing a validmultiple test procedure which controls the FWE can be reduced to the problemof contructing a single test which controls the usual probability of a Type 1error. This reduction allows us to draw upon an enormous resamplingliterature as a general means of test contruction.
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Although multiple sclerosis (MS) is recognized as a disorder involving the immune system, the interplay of environmental factors and individual genetic susceptibility seems to influence MS onset and clinical expression, as well as therapeutic responsiveness. Multiple human epidemiological and animal model studies have evaluated the effect of different environmental factors, such as viral infections, vitamin intake, sun exposure, or still dietary and life habits on MS prevalence. Previous Epstein-Barr virus infection, especially if this infection occurs in late childhood, and lack of vitamin D (VitD) currently appear to be the most robust environmental factors for the risk of MS, at least from an epidemiological standpoint. Ultraviolet radiation (UVR) activates VitD production but there are also some elements supporting the fact that insufficient UVR exposure during childhood may represent a VitD-independent risk factor of MS development, as well as negative effect on the clinical and radiological course of MS. Recently, there has been a growing interest in the gut-brain axis, a bidirectional neuro-hormonal communication system between the intestinal microbiota and the central nervous system (CNS). Indeed, components of the intestinal microbiota may be pro-inflammatory, promote the migration of immune cells into the CNS, and thus be a key parameter for the development of autoimmune disorders such as MS. Interestingly most environmental factors seem to play a role during childhood. Thus, if childhood is the most fragile period to develop MS later in life, preventive measures should be applied early in life. For example, adopting a diet enriched in VitD, playing outdoor and avoiding passive smoking would be extremely simple measures of primary prevention for public health strategies. However, these hypotheses need to be confirmed by prospective evaluations, which are obviously difficult to conduct. In addition, it remains to be determined whether and how VitD supplementation in adult life would be useful in alleviating the course of MS, once this disease has already started. A better knowledge of the influence of various environmental stimuli on MS risk and course would certainly allow the development of add-on therapies or measures in parallel to the immunotherapies currently used in MS.
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In a recent paper, Bai and Perron (1998) considered theoretical issues related to the limiting distribution of estimators and test statistics in the linear model with multiple structural changes. In this companion paper, we consider practical issues for the empirical applications of the procedures. We first address the problem of estimation of the break dates and present an efficient algorithm to obtain global minimizers of the sum of squared residuals. This algorithm is based on the principle of dynamic programming and requires at most least-squares operations of order O(T 2) for any number of breaks. Our method can be applied to both pure and partial structural-change models. Secondly, we consider the problem of forming confidence intervals for the break dates under various hypotheses about the structure of the data and the errors across segments. Third, we address the issue of testing for structural changes under very general conditions on the data and the errors. Fourth, we address the issue of estimating the number of breaks. We present simulation results pertaining to the behavior of the estimators and tests in finite samples. Finally, a few empirical applications are presented to illustrate the usefulness of the procedures. All methods discussed are implemented in a GAUSS program available upon request for non-profit academic use.
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Ce mémoire examine les questions à mouvement multiple en bulgare, en accordant une importance particulière aux mécanismes qui régissent l’ordre des syntagmes interrogatifs antéposés. Outre la présentation d’un phénomène linguistique complexe et très intéressant, l’étude propose un aperçu critique des hypothèses les plus importantes émises au fil des ans à propos des interrogatives multiples. Dans un premier temps, nous discutons des différentes approches renfermant l’idée que l’ordre des mots interrogatifs au début de la proposition dépend entièrement des règles syntaxiques. Ensuite, nous présentons les analyses qui tentent d’expliquer la problématique en faisant appel à des traits spécifiques des syntagmes Qu-, tels que [animé] ou [lié au discours]. Le rôle de la topicalisation et de la focalisation dans la formation des questions multiples, les projections fonctionnelles de la « périphérie gauche » en bulgare accueillant différents syntagmes, ainsi que la résomption comptent également parmi les sujets traités dans ce mémoire.
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Global change may substantially affect biodiversity and ecosystem functioning but little is known about its effects on essential biotic interactions. Since different environmental drivers rarely act in isolation it is important to consider interactive effects. Here, we focus on how two key drivers of anthropogenic environmental change, climate change and the introduction of alien species, affect plant–pollinator interactions. Based on a literature survey we identify climatically sensitive aspects of species interactions, assess potential effects of climate change on these mechanisms, and derive hypotheses that may form the basis of future research. We find that both climate change and alien species will ultimately lead to the creation of novel communities. In these communities certain interactions may no longer occur while there will also be potential for the emergence of new relationships. Alien species can both partly compensate for the often negative effects of climate change but also amplify them in some cases. Since potential positive effects are often restricted to generalist interactions among species, climate change and alien species in combination can result in significant threats to more specialist interactions involving native species.