882 resultados para Predicted Distribution Data
Resumo:
Constructing a 3D surface model from sparse-point data is a nontrivial task. Here, we report an accurate and robust approach for reconstructing a surface model of the proximal femur from sparse-point data and a dense-point distribution model (DPDM). The problem is formulated as a three-stage optimal estimation process. The first stage, affine registration, is to iteratively estimate a scale and a rigid transformation between the mean surface model of the DPDM and the sparse input points. The estimation results of the first stage are used to establish point correspondences for the second stage, statistical instantiation, which stably instantiates a surface model from the DPDM using a statistical approach. This surface model is then fed to the third stage, kernel-based deformation, which further refines the surface model. Handling outliers is achieved by consistently employing the least trimmed squares (LTS) approach with a roughly estimated outlier rate in all three stages. If an optimal value of the outlier rate is preferred, we propose a hypothesis testing procedure to automatically estimate it. We present here our validations using four experiments, which include 1 leave-one-out experiment, 2 experiment on evaluating the present approach for handling pathology, 3 experiment on evaluating the present approach for handling outliers, and 4 experiment on reconstructing surface models of seven dry cadaver femurs using clinically relevant data without noise and with noise added. Our validation results demonstrate the robust performance of the present approach in handling outliers, pathology, and noise. An average 95-percentile error of 1.7-2.3 mm was found when the present approach was used to reconstruct surface models of the cadaver femurs from sparse-point data with noise added.
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Sizes and power of selected two-sample tests of the equality of survival distributions are compared by simulation for small samples from unequally, randomly-censored exponential distributions. The tests investigated include parametric tests (F, Score, Likelihood, Asymptotic), logrank tests (Mantel, Peto-Peto), and Wilcoxon-Type tests (Gehan, Prentice). Equal sized samples, n = 18, 16, 32 with 1000 (size) and 500 (power) simulation trials, are compared for 16 combinations of the censoring proportions 0%, 20%, 40%, and 60%. For n = 8 and 16, the Asymptotic, Peto-Peto, and Wilcoxon tests perform at nominal 5% size expectations, but the F, Score and Mantel tests exceeded 5% size confidence limits for 1/3 of the censoring combinations. For n = 32, all tests showed proper size, with the Peto-Peto test most conservative in the presence of unequal censoring. Powers of all tests are compared for exponential hazard ratios of 1.4 and 2.0. There is little difference in power characteristics of the tests within the classes of tests considered. The Mantel test showed 90% to 95% power efficiency relative to parametric tests. Wilcoxon-type tests have the lowest relative power but are robust to differential censoring patterns. A modified Peto-Peto test shows power comparable to the Mantel test. For n = 32, a specific Weibull-exponential comparison of crossing survival curves suggests that the relative powers of logrank and Wilcoxon-type tests are dependent on the scale parameter of the Weibull distribution. Wilcoxon-type tests appear more powerful than logrank tests in the case of late-crossing and less powerful for early-crossing survival curves. Guidelines for the appropriate selection of two-sample tests are given. ^
Resumo:
Maximizing data quality may be especially difficult in trauma-related clinical research. Strategies are needed to improve data quality and assess the impact of data quality on clinical predictive models. This study had two objectives. The first was to compare missing data between two multi-center trauma transfusion studies: a retrospective study (RS) using medical chart data with minimal data quality review and the PRospective Observational Multi-center Major Trauma Transfusion (PROMMTT) study with standardized quality assurance. The second objective was to assess the impact of missing data on clinical prediction algorithms by evaluating blood transfusion prediction models using PROMMTT data. RS (2005-06) and PROMMTT (2009-10) investigated trauma patients receiving ≥ 1 unit of red blood cells (RBC) from ten Level I trauma centers. Missing data were compared for 33 variables collected in both studies using mixed effects logistic regression (including random intercepts for study site). Massive transfusion (MT) patients received ≥ 10 RBC units within 24h of admission. Correct classification percentages for three MT prediction models were evaluated using complete case analysis and multiple imputation based on the multivariate normal distribution. A sensitivity analysis for missing data was conducted to estimate the upper and lower bounds of correct classification using assumptions about missing data under best and worst case scenarios. Most variables (17/33=52%) had <1% missing data in RS and PROMMTT. Of the remaining variables, 50% demonstrated less missingness in PROMMTT, 25% had less missingness in RS, and 25% were similar between studies. Missing percentages for MT prediction variables in PROMMTT ranged from 2.2% (heart rate) to 45% (respiratory rate). For variables missing >1%, study site was associated with missingness (all p≤0.021). Survival time predicted missingness for 50% of RS and 60% of PROMMTT variables. MT models complete case proportions ranged from 41% to 88%. Complete case analysis and multiple imputation demonstrated similar correct classification results. Sensitivity analysis upper-lower bound ranges for the three MT models were 59-63%, 36-46%, and 46-58%. Prospective collection of ten-fold more variables with data quality assurance reduced overall missing data. Study site and patient survival were associated with missingness, suggesting that data were not missing completely at random, and complete case analysis may lead to biased results. Evaluating clinical prediction model accuracy may be misleading in the presence of missing data, especially with many predictor variables. The proposed sensitivity analysis estimating correct classification under upper (best case scenario)/lower (worst case scenario) bounds may be more informative than multiple imputation, which provided results similar to complete case analysis.^
Resumo:
As a response to ocean warming, shifts in fish species distribution and changes in production have been reported that have been partly attributed to temperature effects on the physiology of animals. The Southern Ocean hosts some of the most rapidly warming regions on earth and Antarctic organisms are reported to be especially temperature sensitive. While cellular and molecular organismic levels appear, at least partially, to compensate for elevated temperatures, the consequences of acclimation to elevated temperature for the whole organism are often less clear. Growth and reproduction are the driving factors for population structure and abundance. The aim of this study was to assess the effect of long-term acclimation to elevated temperature on energy budget parameters in the high-Antarctic fish Trematomus bernacchii. Our results show a complete temperature compensation for routine metabolic costs after 9 weeks of acclimation to 4°C. However, an up to 84% reduction in mass growth was measured at 2 and 4°C compared with the control group at 0°C, which is best explained by reduced food assimilation rates at warmer temperatures. With regard to a predicted temperature increase of up to 1.4°C in the Ross Sea by 2200, such a significant reduction in growth is likely to affect population structures in nature, for example by delaying sexual maturity and reducing production, with severe impacts on Antarctic fish communities and ecosystems.
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Using an extensive network of occurrence records for 293 plant species collected over the past 40 years across a climatically diverse geographic section of western North America, we find that plant species distributions were just as likely to shift upwards (i.e., towards higher elevations) as downward (i.e., towards lower elevations) - despite consistent warming across the study area. Although there was no clear directional response to climate warming across the entire study area, there was significant region-to region- variation in responses (i.e. from as many as 73% to as few as32% of species shifting upward or downward). To understand the factors that might be controlling region-specific distributional shifts, we explored the relationship between the direction of change in distribution limits and the nature of recent climate change. We found that the direction of distribution limit shifts was explained by an interaction between the rate of change in local summer temperatures and seasonal precipitation. Specifically, species shifted upward at their upper elevational limit when snowfall declined at slower rates and minimum temperatures increased. By contrast, species shifted upwards at their lower elevation limit when maximum temperatures increased or both temperature and precipitation decreased. Our results suggest that future species' elevational distribution shifts will be complex, depending on the interaction between seasonal temperature and precipitation change.
Resumo:
This paper reports the concentrations and within-class distributions of long-chain alkenones and alkyl alkenoates in the surface waters (0-50 m) of the eastern North Atlantic, and correlates their abundance and distribution with those of source organisms and with water temperature and other environmental variables. We collected these samples of >0.8 µm particulate material from the euphotic zone along the JGOFS 20°W longitude transect, from 61°N to 24°N, during seven cruises of the UK-JGOFS Biogeochemical Ocean Flux Study (BOFS) in 1989-1991; the biogeographical range of our 53 samples extends from the cold (<10°C), nutrient-rich and highly productive subarctic waters of the Iceland Basin to the warm (>25°C) oligotrophic subtropical waters off Africa. Surface water concentrations of total alkenone and alkenoates ranged from <50 ng/l in oligotrophic waters below 40°N to 2000-4500 ng/l in high latitude E. huxleyi blooms, and were well correlated with E. huxleyi cell densities, supporting the assumption that E. huxleyi is the predominant source of these compounds in the present day North Atlantic. The within-class distribution of the C37 and C38 alkenones and C36 alkenoates varied strongly as a function of temperature, and was largely unaffected by nutrient concentration, bloom status and other surface water properties. The biosynthetic response of the source organisms to growth temperature differed between the cold (<16°C) waters above 47°N and the warmer waters to the south. In cold (<16°C) waters above 47°N, the relative amounts of alkenoates and C38 alkenones synthesized was a strong function of growth temperature, while the unsaturation ratio of the alkenones (C37 and C38) was uncorrelated with temperature. Conversely, in warm (>16°C) waters below 47°N, the relative proportions of alkenoates and alkenones synthesized remained constant with increasing temperature while the unsaturation ratios of the C37 and C38 methyl alkenones (Uk37 and Uk38Me, respectively) increased linearly. The fitted regressions of Uk37 and Uk38Me versus temperature for waters >16°C were both highly significant (r**2 > 0.96) and had identical slopes (0.057) that were 50% higher than the slope (0.034) of the temperature calibration of Uk37 reported by Prahl and Wakeham (1987; doi:10.1038/330367a0) over the same temperature range. These observations suggest either a physiological adjustment in biochemical response to growth temperature above a 16-17°C threshold and/or variation between different E. huxleyi strains and/or related species inhabiting the cold and warm water regions of the eastern North Atlantic. Using our North Atlantic data set, we have produced multivariate temperature calibrations incorporating all major features of the alkenone and alkenoate data set. Predicted temperatures using multivariate calibrations are largely unbiased, with a standard error of approximately ±1°C over the entire data range. In contrast, simpler calibration models cannot adequately incorporate regional diversity and nonlinear trends with temperature. Our results indicate that calibrations based upon single variables, such as Uk37, can be strongly biased by unknown systematic errors arising from natural variability in the biosynthetic response of the source organisms to growth temperature. Multivariate temperature calibration can be expected to give more precise estimates of Integrated Production Temperatures (IPT) in the sedimentary record over a wider range of paleoenvironmental conditions, when derived using a calibration data set incorporating a similar range of natural variability in biosynthetic response.
Resumo:
Kelp forests represent a major habitat type in coastal waters worldwide and their structure and distribution is predicted to change due to global warming. Despite their ecological and economical importance, there is still a lack of reliable spatial information on their abundance and distribution. In recent years, various hydroacoustic mapping techniques for sublittoral environments evolved. However, in turbid coastal waters, such as off the island of Helgoland (Germany, North Sea), the kelp vegetation is present in shallow water depths normally excluded from hydroacoustic surveys. In this study, single beam survey data consisting of the two seafloor parameters roughness and hardness were obtained with RoxAnn from water depth between 2 and 18 m. Our primary aim was to reliably detect the kelp forest habitat with different densities and distinguish it from other vegetated zones. Five habitat classes were identified using underwater-video and were applied for classification of acoustic signatures. Subsequently, spatial prediction maps were produced via two classification approaches: Linear discriminant analysis (LDA) and manual classification routine (MC). LDA was able to distinguish dense kelp forest from other habitats (i.e. mixed seaweed vegetation, sand, and barren bedrock), but no variances in kelp density. In contrast, MC also provided information on medium dense kelp distribution which is characterized by intermediate roughness and hardness values evoked by reduced kelp abundances. The prediction maps reach accordance levels of 62% (LDA) and 68% (MC). The presence of vegetation (kelp and mixed seaweed vegetation) was determined with higher prediction abilities of 75% (LDA) and 76% (MC). Since the different habitat classes reveal acoustic signatures that strongly overlap, the manual classification method was more appropriate for separating different kelp forest densities and low-lying vegetation. It became evident that the occurrence of kelp in this area is not simply linked to water depth. Moreover, this study shows that the two seafloor parameters collected with RoxAnn are suitable indicators for the discrimination of different densely vegetated seafloor habitats in shallow environments.
Resumo:
Fine-grained sediment depocenters on continental shelves are of increased scientific interest since they record environmental changes sensitively. A north-south elongated mud depocenter extends along the Senegalese coast in mid-shelf position. Shallow-acoustic profiling was carried out to determine extent, geometry and internal structures of this sedimentary body. In addition, four sediment cores were retrieved with the main aim to identify how paleoclimatic signals and coastal changes have controlled the formation of this mud depocenter. A general paleoclimatic pattern in terms of fluvial input appears to be recorded in this depositional archive. Intervals characterized by high terrigenous input, high sedimentation rates and fine grain sizes occur roughly contemporaneously in all cores and are interpreted as corresponding to intensified river discharge related to more humid conditions in the hinterland. From 2750 to 1900 and from 1000 to 700 cal a BP, wetter conditions are recorded off Senegal, an observation which is in accordance with other records from NW-Africa. Nevertheless, the three employed proxies (sedimentation rate, grain size and elemental distribution) do not always display consistent inter-core patterns. Major differences between the individual core records are attributed to sediment remobilization which was linked to local hydrographic variations as well as reorganizations of the coastal system. The Senegal mud belt is a layered inhomogeneous sedimentary body deposited on an irregular erosive surface. Early Holocene deceleration in the rate of the sea-level rise could have enabled initial mud deposition on the shelf. These favorable conditions for mud deposition occur coevally with a humid period over NW-Africa, thus, high river discharge. Sedimentation started preferentially in the northern areas of the mud belt. During mid-Holocene, a marine incursion led to the formation of an embayment. Afterwards, sedimentation in the north was interrupted in association with a remarkable southward shift in the location of the active depocenter as it is reflected by the sedimentary architecture and confirmed by radiocarbon dates. These sub-recent shifts in depocenters location are caused by migrations of the Senegal River mouth. During late Holocene times, the weakening of river discharge allowed the longshore currents to build up a chain of beach barriers which have forced the river mouth to shift southwards.
Ice rafted debris (> 2 mm gravel) distribution and susceptibility raw data of sediment core PS2450-3