939 resultados para Biased sampling
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We present a generalized framework for gradient-domain Metropolis rendering, and introduce three techniques to reduce sampling artifacts and variance. The first one is a heuristic weighting strategy that combines several sampling techniques to avoid outliers. The second one is an improved mapping to generate offset paths required for computing gradients. Here we leverage the properties of manifold walks in path space to cancel out singularities. Finally, the third technique introduces generalized screen space gradient kernels. This approach aligns the gradient kernels with image structures such as texture edges and geometric discontinuities to obtain sparser gradients than with the conventional gradient kernel. We implement our framework on top of an existing Metropolis sampler, and we demonstrate significant improvements in visual and numerical quality of our results compared to previous work.
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The term 'inflammatory airway disease' (IAD) is often used to describe the syndrome of lower airway inflammation that frequently affects young racehorses in training around the world. In practice, this inflammation is generally diagnosed using a combination of endoscopic tracheal examination, including grading of amounts of mucus present and tracheal wash sampling. However, a recent consensus statement from the American College of Veterinary Internal Medicine concluded that bronchoalveolar lavage (BAL) sampling, rather than tracheal wash (TW) sampling, is required for cytological diagnosis of IAD and that tracheal mucus is not an essential criterion. However, as BAL is a relatively invasive procedure that is not commonly used on racing yards, this definition can only be applied routinely to a biased referral population. In contrast, many practitioners continue to diagnose IAD using endoscopic tracheal examination and sampling. We argue that, rather than restricting the use of the term IAD to phenotypes diagnosed by BAL, it is important to distinguish in the literature between airway inflammation diagnosed by BAL and that identified in the field using TW sampling. We suggest the use of the term brIAD for the former and trIAD for the latter. It is essential that we continue to endeavour to improve our understanding of the aetiology, pathogenesis and clinical relevance of airway inflammation identified in racehorses in training using tracheal examination and sampling. Future studies should focus on investigations of the component signs of airway inflammation.
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Intestinal dendritic cells (DCs) are believed to sample and present commensal bacteria to the gut-associated immune system to maintain immune homeostasis. How antigen sampling pathways handle intestinal pathogens remains elusive. We present a murine colitogenic Salmonella infection model that is highly dependent on DCs. Conditional DC depletion experiments revealed that intestinal virulence of S. Typhimurium SL1344 DeltainvG mutant lacking a functional type 3 secretion system-1 (DeltainvG)critically required DCs for invasion across the epithelium. The DC-dependency was limited to the early phase of infection when bacteria colocalized with CD11c(+)CX3CR1(+) mucosal DCs. At later stages, the bacteria became associated with other (CD11c(-)CX3CR1(-)) lamina propria cells, DC depletion no longer attenuated the pathology, and a MyD88-dependent mucosal inflammation was initiated. Using bone marrow chimeric mice, we showed that the MyD88 signaling within hematopoietic cells, which are distinct from DCs, was required and sufficient for induction of the colitis. Moreover, MyD88-deficient DCs supported transepithelial uptake of the bacteria and the induction of MyD88-dependent colitis. These results establish that pathogen sampling by DCs is a discrete, and MyD88-independent, step during the initiation of a mucosal innate immune response to bacterial infection in vivo.
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We propose a nonparametric variance estimator when ranked set sampling (RSS) and judgment post stratification (JPS) are applied by measuring a concomitant variable. Our proposed estimator is obtained by conditioning on observed concomitant values and using nonparametric kernel regression.
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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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OBJECTIVES Respondent-driven sampling (RDS) is a new data collection methodology used to estimate characteristics of hard-to-reach groups, such as the HIV prevalence in drug users. Many national public health systems and international organizations rely on RDS data. However, RDS reporting quality and available reporting guidelines are inadequate. We carried out a systematic review of RDS studies and present Strengthening the Reporting of Observational Studies in Epidemiology for RDS Studies (STROBE-RDS), a checklist of essential items to present in RDS publications, justified by an explanation and elaboration document. STUDY DESIGN AND SETTING We searched the MEDLINE (1970-2013), EMBASE (1974-2013), and Global Health (1910-2013) databases to assess the number and geographical distribution of published RDS studies. STROBE-RDS was developed based on STROBE guidelines, following Guidance for Developers of Health Research Reporting Guidelines. RESULTS RDS has been used in over 460 studies from 69 countries, including the USA (151 studies), China (70), and India (32). STROBE-RDS includes modifications to 12 of the 22 items on the STROBE checklist. The two key areas that required modification concerned the selection of participants and statistical analysis of the sample. CONCLUSION STROBE-RDS seeks to enhance the transparency and utility of research using RDS. If widely adopted, STROBE-RDS should improve global infectious diseases public health decision making.
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Palaeoclimatic information can be retrieved from the diffusion of the stable water isotope signal during firnification of snow. The diffusion length, a measure for the amount of diffusion a layer has experienced, depends on the firn temperature and the accumulation rate. We show that the estimation of the diffusion length using power spectral densities (PSDs) of the record of a single isotope species can be biased by uncertainties in spectral properties of the isotope signal prior to diffusion. By using a second water isotope and calculating the difference in diffusion lengths between the two isotopes, this problem is circumvented. We study the PSD method applied to two isotopes in detail and additionally present a new forward diffusion method for retrieving the differential diffusion length based on the Pearson correlation between the two isotope signals. The two methods are discussed and extensively tested on synthetic data which are generated in a Monte Carlo manner. We show that calibration of the PSD method with this synthetic data is necessary to be able to objectively determine the differential diffusion length. The correlation-based method proves to be a good alternative for the PSD method as it yields precision equal to or somewhat higher than the PSD method. The use of synthetic data also allows us to estimate the accuracy and precision of the two methods and to choose the best sampling strategy to obtain past temperatures with the required precision. In addition to application to synthetic data the two methods are tested on stable-isotope records from the EPICA (European Project for Ice Coring in Antarctica) ice core drilled in Dronning Maud Land, Antarctica, showing that reliable firn temperatures can be reconstructed with a typical uncertainty of 1.5 and 2 °C for the Holocene period and 2 and 2.5 °C for the last glacial period for the correlation and PSD method, respectively.
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Phylogenetic reconstruction of the evolutionary history of closely related organisms may be difficult because of the presence of unsorted lineages and of a relatively high proportion of heterozygous sites that are usually not handled well by phylogenetic programs. Genomic data may provide enough fixed polymorphisms to resolve phylogenetic trees, but the diploid nature of sequence data remains analytically challenging. Here, we performed a phylogenomic reconstruction of the evolutionary history of the common vole (Microtus arvalis) with a focus on the influence of heterozygosity on the estimation of intraspecific divergence times. We used genome-wide sequence information from 15 voles distributed across the European range. We provide a novel approach to integrate heterozygous information in existing phylogenetic programs by repeated random haplotype sampling from sequences with multiple unphased heterozygous sites. We evaluated the impact of the use of full, partial, or no heterozygous information for tree reconstructions on divergence time estimates. All results consistently showed four deep and strongly supported evolutionary lineages in the vole data. These lineages undergoing divergence processes split only at the end or after the last glacial maximum based on calibration with radiocarbon-dated paleontological material. However, the incorporation of information from heterozygous sites had a significant impact on absolute and relative branch length estimations. Ignoring heterozygous information led to an overestimation of divergence times between the evolutionary lineages of M. arvalis. We conclude that the exclusion of heterozygous sites from evolutionary analyses may cause biased and misleading divergence time estimates in closely related taxa.
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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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Research on open source software (OSS) projects often focuses on the SourceForge collaboration platform. We argue that a GNU/Linwr distribution, such as Debian, is better suited for the sampling ofprojects because it avoids biases and contains unique information only available in an integrated environment. Especially research on the reuse of components can build on dependency information inherent in the Debian GNU/Linux packaging system. This paper therefore contributes to the practice of sampling methods in OSS research and provides empirical data on reuse dependencies in Debian.
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OBJECTIVES To examine whether circulating levels of matrix metalloproteinase 9 (MMP-9) were associated with ultrasound-assessed intima-media thickness (IMT) and echolucent plaques in the carotid and femoral arteries. To examine preanalytical sources of variability in MMP-9 concentrations related to sampling procedures. SUBJECTS AND DESIGN Plasma and serum MMP-9 levels were compared with ultrasound assessed measures of femoral and carotid atherosclerosis, in a cross-sectional study of 61-year-old men (n = 473). Preanalytical sources of variability in MMP-9 levels were examined in 10 healthy subjects. Main outcome measures were circulating levels of MMP-9 in serum and plasma, IMT of the carotid and femoral arteries, and plaque status based on size and echolucency. SETTING Research unit at university hospital. RESULTS Plasma concentrations of total and active MMP-9 were associated with femoral artery IMT independently of traditional cardiovascular risk factors, and were higher in subjects with moderate to large femoral plaques. Plasma MMP-9 concentration was higher in men with echolucent femoral plaques (P = 0.006) compared with subjects without femoral plaques. No similar associations were found for carotid plaques. MMP-9 concentrations were higher in serum than in plasma, and higher when sampling was performed with Vacutainer than with syringe. MMP-9 levels in serum were more strongly associated with peripheral neutrophil count compared with MMP-9 levels in plasma. CONCLUSIONS Plasma MMP-9 levels were associated with atherosclerosis in the femoral artery, and total MMP-9 concentration was higher in men with echolucent femoral plaques. The choice of sample material and sampling method affect the measurements of circulating MMP-9 levels.
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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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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.