970 resultados para sampling methods


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Linkage disequilibrium methods can be used to find genes influencing quantitative trait variation in humans. Linkage disequilibrium methods can require smaller sample sizes than linkage equilibrium methods, such as the variance component approach to find loci with a specific effect size. The increase in power is at the expense of requiring more markers to be typed to scan the entire genome. This thesis compares different linkage disequilibrium methods to determine which factors influence the power to detect disequilibrium. The costs of disequilibrium and equilibrium tests were compared to determine whether the savings in phenotyping costs when using disequilibrium methods outweigh the additional genotyping costs.^ Nine linkage disequilibrium tests were examined by simulation. Five tests involve selecting isolated unrelated individuals while four involved the selection of parent child trios (TDT). All nine tests were found to be able to identify disequilibrium with the correct significance level in Hardy-Weinberg populations. Increasing linked genetic variance and trait allele frequency were found to increase the power to detect disequilibrium, while increasing the number of generations and distance between marker and trait loci decreased the power to detect disequilibrium. Discordant sampling was used for several of the tests. It was found that the more stringent the sampling, the greater the power to detect disequilibrium in a sample of given size. The power to detect disequilibrium was not affected by the presence of polygenic effects.^ When the trait locus had more than two trait alleles, the power of the tests maximized to less than one. For the simulation methods used here, when there were more than two-trait alleles there was a probability equal to 1-heterozygosity of the marker locus that both trait alleles were in disequilibrium with the same marker allele, resulting in the marker being uninformative for disequilibrium.^ The five tests using isolated unrelated individuals were found to have excess error rates when there was disequilibrium due to population admixture. Increased error rates also resulted from increased unlinked major gene effects, discordant trait allele frequency, and increased disequilibrium. Polygenic effects did not affect the error rates. The TDT, Transmission Disequilibrium Test, based tests were not liable to any increase in error rates.^ For all sample ascertainment costs, for recent mutations ($<$100 generations) linkage disequilibrium tests were less expensive than the variance component test to carry out. Candidate gene scans saved even more money. The use of recently admixed populations also decreased the cost of performing a linkage disequilibrium test. ^

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We present a technique for online compression of ECG signals using the Golomb-Rice encoding algorithm. This is facilitated by a novel time encoding asynchronous analog-to-digital converter targeted for low-power, implantable, long-term bio-medical sensing applications. In contrast to capturing the actual signal (voltage) values the asynchronous time encoder captures and encodes the time information at which predefined changes occur in the signal thereby minimizing the sensor's energy use and the number of bits we store to represent the information by not capturing unnecessary samples. The time encoder transforms the ECG signal data to pure time information that has a geometric distribution such that the Golomb-Rice encoding algorithm can be used to further compress the data. An overall online compression rate of about 6 times is achievable without the usual computations associated with most compression methods.

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Many techniques based on data which are drawn by Ranked Set Sampling (RSS) scheme assume that the ranking of observations is perfect. Therefore it is essential to develop some methods for testing this assumption. In this article, we propose a parametric location-scale free test for assessing the assumption of perfect ranking. The results of a simulation study in two special cases of normal and exponential distributions indicate that the proposed test performs well in comparison with its leading competitors.

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BACKGROUND Pathogenic bacteria are often asymptomatically carried in the nasopharynx. Bacterial carriage can be reduced by vaccination and has been used as an alternative endpoint to clinical disease in randomised controlled trials (RCTs). Vaccine efficacy (VE) is usually calculated as 1 minus a measure of effect. Estimates of vaccine efficacy from cross-sectional carriage data collected in RCTs are usually based on prevalence odds ratios (PORs) and prevalence ratios (PRs), but it is unclear when these should be measured. METHODS We developed dynamic compartmental transmission models simulating RCTs of a vaccine against a carried pathogen to investigate how VE can best be estimated from cross-sectional carriage data, at which time carriage should optimally be assessed, and to which factors this timing is most sensitive. In the models, vaccine could change carriage acquisition and clearance rates (leaky vaccine); values for these effects were explicitly defined (facq, 1/fdur). POR and PR were calculated from model outputs. Models differed in infection source: other participants or external sources unaffected by the trial. Simulations using multiple vaccine doses were compared to empirical data. RESULTS The combined VE against acquisition and duration calculated using POR (VEˆacq.dur, (1-POR)×100) best estimates the true VE (VEacq.dur, (1-facq×fdur)×100) for leaky vaccines in most scenarios. The mean duration of carriage was the most important factor determining the time until VEˆacq.dur first approximates VEacq.dur: if the mean duration of carriage is 1-1.5 months, up to 4 months are needed; if the mean duration is 2-3 months, up to 8 months are needed. Minor differences were seen between models with different infection sources. In RCTs with shorter intervals between vaccine doses it takes longer after the last dose until VEˆacq.dur approximates VEacq.dur. CONCLUSION The timing of sample collection should be considered when interpreting vaccine efficacy against bacterial carriage measured in RCTs.

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We present three methods for the distortion-free enhancement of THz signals measured by electro-optic sampling in zinc blende-type detector crystals, e.g., ZnTe or GaP. A technique commonly used in optically heterodyne-detected optical Kerr effect spectroscopy is introduced, which is based on two measurements at opposite optical biases near the zero transmission point in a crossed polarizer detection geometry. In contrast to other techniques for an undistorted THz signal enhancement, it also works in a balanced detection scheme and does not require an elaborate procedure for the reconstruction of the true signal as the two measured waveforms are simply subtracted to remove distortions. We study three different approaches for setting an optical bias using the Jones matrix formalism and discuss them also in the framework of optical heterodyne detection. We show that there is an optimal bias point in realistic situations where a small fraction of the probe light is scattered by optical components. The experimental demonstration will be given in the second part of this two-paper series [J. Opt. Soc. Am. B, doc. ID 204877 (2014, posted online)].

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Three methods for distortion-free enhancement of electro-optic sampling measurements of terahertz signals are tested. In the first part of this two-paper series [J. Opt. Soc. Am B 31, 904–910 (2014)], the theoretical framework for describing the signal enhancement was presented and discussed. As the applied optical bias is decreased, individual signal traces become enhanced but distorted. Here we experimentally show that nonlinear signal components that distort the terahertz electric field measurement can be removed by subtracting traces recorded with opposite optical bias values. In all three methods tested, we observe up to an order of magnitude increase in distortion-free signal enhancement, in agreement with the theory, making possible measurements of small terahertz-induced transient birefringence signals with increased signal-to-noise ratio.

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Oscillations between high and low values of the membrane potential (UP and DOWN states respectively) are an ubiquitous feature of cortical neurons during slow wave sleep and anesthesia. Nevertheless, a surprisingly small number of quantitative studies have been conducted only that deal with this phenomenon’s implications for computation. Here we present a novel theory that explains on a detailed mathematical level the computational benefits of UP states. The theory is based on random sampling by means of interspike intervals (ISIs) of the exponential integrate and fire (EIF) model neuron, such that each spike is considered a sample, whose analog value corresponds to the spike’s preceding ISI. As we show, the EIF’s exponential sodium current, that kicks in when balancing a noisy membrane potential around values close to the firing threshold, leads to a particularly simple, approximative relationship between the neuron’s ISI distribution and input current. Approximation quality depends on the frequency spectrum of the current and is improved upon increasing the voltage baseline towards threshold. Thus, the conceptually simpler leaky integrate and fire neuron that is missing such an additional current boost performs consistently worse than the EIF and does not improve when voltage baseline is increased. For the EIF in contrast, the presented mechanism is particularly effective in the high-conductance regime, which is a hallmark feature of UP-states. Our theoretical results are confirmed by accompanying simulations, which were conducted for input currents of varying spectral composition. Moreover, we provide analytical estimations of the range of ISI distributions the EIF neuron can sample from at a given approximation level. Such samples may be considered by any algorithmic procedure that is based on random sampling, such as Markov Chain Monte Carlo or message-passing methods. Finally, we explain how spike-based random sampling relates to existing computational theories about UP states during slow wave sleep and present possible extensions of the model in the context of spike-frequency adaptation.

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BACKGROUND The objective of the study was to evaluate the implications of different classifications of rheumatic heart disease on estimated prevalence, and to systematically assess the importance of incidental findings from echocardiographic screening among schoolchildren in Peru. METHODS We performed a cluster randomized observational survey using portable echocardiography among schoolchildren aged 5 to 16 years from randomly selected public and private schools in Arequipa, Peru. Rheumatic heart disease was defined according to the modified World Health Organization (WHO) criteria and the World Heart Federation (WHF) criteria. FINDINGS Among 1395 eligible students from 40 classes and 20 schools, 1023 (73%) participated in the present survey. The median age of the children was 11 years (interquartile range [IQR] 8-13 years) and 50% were girls. Prevalence of possible, probable and definite rheumatic heart disease according to the modified WHO criteria amounted to 19.7/1000 children and ranged from 10.2/1000 among children 5 to 8 years of age to 39.8/1000 among children 13 to 16 years of age; the prevalence of borderline/definite rheumatic heart disease according to the WHF criteria was 3.9/1000 children. 21 children (2.1%) were found to have congenital heart disease, 8 of which were referred for percutaneous or surgical intervention. CONCLUSIONS Prevalence of RHD in Peru was considerably lower compared to endemic regions in sub-Saharan Africa, southeast Asia, and Oceania; and paralleled by a comparable number of undetected congenital heart disease. Strategies to address collateral findings from echocardiographic screening are necessary in the setup of active surveillance programs for RHD. TRIAL REGISTRATION ClinicalTrials.gov identifier: NCT02353663.

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During acts of physical aggression, offenders frequently come into contact with clothes of the victim, thereby leaving traces of DNA-bearing biological material on the garments. Since tape-lifting and swabbing, the currently established methods for non-destructive trace DNA sampling from clothing, both have their shortcomings in collection efficiency and handling, we thought about a new collection method for these challenging samples. Testing two readily available electrostatic devices for their potential to sample biological material from garments made of different fabrics, we found one of them, the electrostatic dust print lifter (DPL), to perform comparable to well-established sampling with wet cotton swabs. In simulated aggression scenarios, we had the same success rate for the establishment of single aggressor profiles, suitable for database submission, with both the DPL and wet swabbing. However, we lost a substantial amount of information with electrostatic sampling, since almost no mixed aggressor-victim profiles suitable for database entry could be established, compared to conventional swabbing. This study serves as a proof of principle for electrostatic DNA sampling from items of clothing. The technique still requires optimization before it might be used in real casework. But we are confident that in the future it could be an efficient and convenient contribution to the toolbox of forensic practitioners.

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Governance of food systems is a poorly understood determinant of food security. Much scholarship on food systems governance is non-empirical, while existing research is often case study-based and theoretically and methodologically incommensurable. This frustrates aggregation of evidence and generalisation. We undertook a systematic review of methods used in food systems governance research with a view to identifying a core set of indicators for future research. We gathered literature through a structured consultation and sampling from recent reviews. Indicators were identified and classified according to the levels and sectors they investigate. We found a concentration of indicators in food production at local to national levels and a sparseness in distribution and consumption. Unsurprisingly, many indicators of institutional structure were found, while agency-related indicators are moderately represented. We call for piloting and validation of these indicators and for methodological development to fill gaps identified. These efforts are expected to support a more consolidated future evidence base and eventual meta-analysis.

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Monte Carlo integration is firmly established as the basis for most practical realistic image synthesis algorithms because of its flexibility and generality. However, the visual quality of rendered images often suffers from estimator variance, which appears as visually distracting noise. Adaptive sampling and reconstruction algorithms reduce variance by controlling the sampling density and aggregating samples in a reconstruction step, possibly over large image regions. In this paper we survey recent advances in this area. We distinguish between “a priori” methods that analyze the light transport equations and derive sampling rates and reconstruction filters from this analysis, and “a posteriori” methods that apply statistical techniques to sets of samples to drive the adaptive sampling and reconstruction process. They typically estimate the errors of several reconstruction filters, and select the best filter locally to minimize error. We discuss advantages and disadvantages of recent state-of-the-art techniques, and provide visual and quantitative comparisons. Some of these techniques are proving useful in real-world applications, and we aim to provide an overview for practitioners and researchers to assess these approaches. In addition, we discuss directions for potential further improvements.

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With the ongoing shift in the computer graphics industry toward Monte Carlo rendering, there is a need for effective, practical noise-reduction techniques that are applicable to a wide range of rendering effects and easily integrated into existing production pipelines. This course surveys recent advances in image-space adaptive sampling and reconstruction algorithms for noise reduction, which have proven very effective at reducing the computational cost of Monte Carlo techniques in practice. These approaches leverage advanced image-filtering techniques with statistical methods for error estimation. They are attractive because they can be integrated easily into conventional Monte Carlo rendering frameworks, they are applicable to most rendering effects, and their computational overhead is modest.

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The study was carried out at St. Luke's Episcopal Hospital to evaluate environmental contamination of Clostridium difficile in the infected patient rooms. Samples were collected from the high risk areas and were immediately cultured for the presence of Clostridium difficile . Lack of microbial typing prevented the study of molecular characterization of the Clostridium difficile isolates obtained led to a change in the study hypothesis. The study found a positivity of 10% among 50 Hospital rooms sampled for the presence of Clostridium difficile. The study provided data that led to recommendations that routine environmental sampling be carried in the hospital rooms in which patients with CDAD are housed and that effective environmental disinfection methods are used. The study also recommended molecular typing methods to allow characterization of the CD strains isolated from patients and environmental sampling to determine their type, similarity and origin.^