Choice Of Reference Data Research Articles

The Impact of Reference Data Selection for the Prediction Accuracy of Intrinsic Hepatic Metabolic Clearance

In vitro-in vivo prediction results for hepatic metabolic clearance (CLH) and intrinsic CLH (CLint) vary widely among studies. Reasons are not fully investigated and understood. The possibility to select favorable reference data for in vivo CLH and CLint and unbound fraction in plasma (fu) is among possible explanations. The main objective was to investigate how reference data selection influences log in vitro and in vivo CLint-correlations (r2). Another aim was to make a head-to-head comparison vs an in silico prediction method. Human hepatocyte CLint-data for 15 compounds from two studies were selected. These were correlated to in vivo CLint estimated using different reported CLH- and fu-estimates. Depending on the choice of reference data, r2 from two studies were 0.07 to 0.86 and 0.06 to 0.79. When using average reference estimates a r2 of 0.62 was achieved. Inclusion of two outliers in one of the studies resulted in a r2 of 0.38, which was lower than the predictive accuracy (q2) for the in silico method (0.48). In conclusion, the selection of reference data appears to play a major role for demonstrated predictions and the in silico method showed higher accuracy and wider range than hepatocytes for human in vivo CLint-predictions.

Changes in extreme precipitation events in the Zambezi River basins based on CORDEX‐CORE models: Part I—Evaluation of historical simulation

AbstractThis study evaluates the ability of the Coordinated Output for Regional Evaluations (CORE) initiated under the Coordinated Regional Climate Downscaling Experiment (CORDEX) to reproduce austral summer extreme precipitation indices over the Zambezi River basin (ZRB) from 1983 to 2005. The ability of the RCMs to simulate the spatial distributions of observed extreme precipitation was assessed using multiple datasets. The spatially averaged performance of the CORDEX‐CORE ensemble mean (CORE‐ENS) and RCM ensembles (RCM‐ENSEMBLES developed from different combinations of CORE‐ENS ensemble members) was evaluated using statistical metrics. The results showed similarities in the spatial distribution of extreme precipitation among the observations. However, there were considerable differences in the magnitude of extreme precipitation among the observations. The frequency of days with very heavy precipitation (R20) showed the largest differences in magnitude among the observations. Although there are differences in magnitude, CORE‐ENS, its ensemble members, and RCM‐ENSEMBLES can capture the spatial distribution of extreme precipitation. Specifically, CORE‐ENS, its ensemble members, and RCM‐ENSEMBLES overestimated (underestimated) the frequency of rainy days (RR1) and maximum consecutive wet days (CWD) (maximum consecutive dry days [CDD]). In contrast, some members of CORE‐ENS overestimate, while others underestimate, the simple daily intensity index (SDII), the frequency of days with heavy precipitation (R10), and R20, depending on the choice of reference data. The Consortium for Small‐scale MOdelling in CLimate Mode (CCLM) and Regional MOdel (REMO) performed better than the Regional Climate Model (RegCM4.7) in simulating the spatial distributions of extreme precipitation. The regionally averaged uncertainties (biases) of the CORE‐ENS, its ensemble members, and RCMENSEMBLES were within the range of those in the observational datasets, except for CWD (CWD and RR1). Overall, CORE‐ENS performed better than its ensemble members in simulating extreme precipitation.

Assessment of the implant geometry in fractionated interstitial HDR breast brachytherapy using an electromagnetic tracking system

PurposeDuring the partial-breast treatment course by interstitial brachytherapy, electromagnetic tracking (EMT) was applied to measure the implant geometry. Implant-geometry variation, choice of reference data, and three registration methods were assessed. Methods and materialsThe implant geometry was measured in 28 patients after catheter implantation (EMTbed), during CT imaging (EMTCT), and in each of up to n = 9 treatment fractions (EMTF(k), k = 1, 2,… n). EMTF(k) were registered to the planned implant reconstruction (CTplan) by using all dwell positions (DPs), the button centers, or three fiducial sensors on the patient's skin. Variation in implant geometry obtained from EMTF(k) was assessed for EMTbed, EMTCT, and CTplan. ResultsEMT was used to measure 3932 catheters. A duration of 6.5 ± 1.7 min was needed for each implant measurement (mean, 17 catheters) plus setup of the EMT system. Data registration based on the DP deviated significantly lower than registration on button centers or fiducial sensors. Within a registration group, there was a <0.5-mm difference in the choice of reference data. Using CTplan as reference for registration, the mean residual distance of DPs on EMT-derived DPs was found at 2.1 ± 1.6 mm (EMTbed), 1.3 ± 0.9 mm (EMTCT), and 2.5 ± 1.5 mm (EMTF(k)). ConclusionsEMT can assess the implant geometry in high-dose-rate interstitial brachytherapy breast treatments. EMTbed, EMTCT, and CTplan data can serve as reference for assessment of implant changes.

Trends in Automatic Individual Tree Crown Detection and Delineation—Evolution of LiDAR Data

Automated individual tree crown detection and delineation (ITCD) using remotely sensed data plays an increasingly significant role in efficiently, accurately, and completely monitoring forests. This paper reviews trends in ITCD research from 1990–2015 from several perspectives—data/forest type, method applied, accuracy assessment and research objective—with a focus on studies using LiDAR data. This review shows that active sources are becoming more prominent in ITCD studies. Studies using active data—LiDAR in particular—accounted for 80% of the total increase over the entire time period, those using passive data or fusion of passive and active data comprised relatively small proportions of the total increase (8% and 12%, respectively). Additionally, ITCD research has moved from incremental adaptations of algorithms developed for passive data sources to innovative approaches that take advantage of the novel characteristics of active datasets like LiDAR. These improvements make it possible to explore more complex forest conditions (e.g., closed hardwood forests, suburban/urban forests) rather than a single forest type although most published ITCD studies still focused on closed softwood (41%) or mixed forest (22%). Approximately one-third of studies applied individual tree level (30%) assessment, with only a quarter reporting more comprehensive multi-level assessment (23%). Almost one-third of studies (32%) that concentrated on forest parameter estimation based on ITCD results had no ITCD-specific evaluation. Comparison of methods continues to be complicated by both choice of reference data and assessment metric; it is imperative to establish a standardized two-level assessment framework to evaluate and compare ITCD algorithms in order to provide specific recommendations about suitable applications of particular algorithms. However, the evolution of active remotely sensed data and novel platforms implies that automated ITCD will continue to be a promising technology and an attractive research topic for both the forestry and remote sensing communities.

Forcebalance: a Systematic, Reproducible, Statistically Driven Approach to More Accurate Molecular Dynamics Models

I will present our first application of the ForceBalance method for systematically parameterizing force fields: the iAMOEBA water model. Force balance uses a combination of experimental data and high-level theoretical calculations, combined with statistical methods to avoid overfitting and efficient schemes for optimizing in parameter space. We will describe our choice of reference data and provide a brief overview of the parameterization method. The accuracy of the direct polarization water model is demonstrated using a published, comprehensive benchmark of water properties across a wide range of phases and thermodynamic conditions. This suggests a new way to systemically create force fields, with both greater accuracy as well as reproducibility and transparency.

Quantitative assessment of Southern Hemisphere ozone in chemistry-climate model simulations

Abstract. Stratospheric ozone recovery in the Southern Hemisphere is expected to drive pronounced trends in atmospheric temperature and circulation from the stratosphere to the troposphere in the 21st century; therefore ozone changes need to be accounted for in future climate simulations. Many climate models do not have interactive ozone chemistry and rely on prescribed ozone fields, which may be obtained from coupled chemistry-climate model (CCM) simulations. However CCMs vary widely in their predictions of ozone evolution, complicating the selection of ozone boundary conditions for future climate simulations. In order to assess which models might be expected to better simulate future ozone evolution, and thus provide more realistic ozone boundary conditions, we assess the ability of twelve CCMs to simulate observed ozone climatology and trends and rank the models according to their errors averaged across the individual diagnostics chosen. According to our analysis no one model performs better than the others in all the diagnostics; however, combining errors in individual diagnostics into one metric of model performance allows us to objectively rank the models. The multi-model average shows better overall agreement with the observations than any individual model. Based on this analysis we conclude that the multi-model average ozone projection presents the best estimate of future ozone evolution and recommend it for use as a boundary condition in future climate simulations. Our results also demonstrate a sensitivity of the analysis to the choice of reference data set for vertical ozone distribution over the Antarctic, highlighting the constraints that large observational uncertainty imposes on such model verification.

WETLAND RESTORATION THRESHOLDS: CAN A DEGRADATION TRANSITION BE REVERSED WITH INCREASED EFFORT?

Previous attempts to reverse the degradation of a coastal wetland and restore nesting habitat for an endangered bird showed that adding nitrogen could temporarily increase the height of Spartina foliosa, but not produce self-sustaining tall canopies. We asked if increased effort (up to five years of N fertilization) would shift canopy attributes across the hypothesized threshold. Thirty plots were treated with 0–5 yr of urea addition, and all were followed for 5 yr. Canopies were robust while urea was being added, but Spartina reverted to short stature soon after fertilization ended, supporting R. J. Hobbs and D. A. Norton's concept of an irreversible transition. However, specific outcomes depended on the choice of response variable (six comparisons), the choice of reference data (initial conditions, same-year data, and pooled data), and the choice of statistical design (repeated measures vs. complete design), indicating the need to assess experiments thoroughly before making strong recommendations for ma...