Point clouds of measurements in the Dechen Cave near Iserlohn, Germany

Modeling natural phenomena from 3D information enhances our understanding of the environment. Dense 3D point clouds are increasingly used as highly detailed input datasets. In addition to the capturing techniques of point clouds with LiDAR, low-cost sensors have been released in the last few years providing access to new research fields and facilitating 3D data acquisition for a broader range of applications. This letter presents an analysis of different speleothem features using 3D point clouds acquired with the gaming device Microsoft® Kinect. We compare the Kinect sensor with terrestrial LiDAR reference measurements using the KinFu pipeline for capturing complete 3D objects (< 4m**3). The results demonstrate the suitability of the Kinect to capture flowstone walls and to derive morphometric parameters of cave features. Although the chosen capturing strategy (KinFu) reveals a high correlation (R2=0.92) of stalagmite morphometry along the vertical object axis, a systematic overestimation (22% for radii and 44% for volume) is found. The comparison of flowstone wall datasets predominantly shows low differences (mean of 1 mm with 7 mm standard deviation) of the order of the Kinect depth precision. For both objects the major differences occur at strongly varying and curved surface structures (e.g. with fine concave parts).

Data for validation of crash victim simulator. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Single-subject research designs and data analyses for assessing elite athletes' conditioning

Research in conditioning (all the processes of preparation for competition) has used group research designs, where multiple athletes are observed at one or more points in time. However, empirical reports of large inter-individual differences in response to conditioning regimens suggest that applied conditioning research would greatly benefit from single-subject research designs. Single-subject research designs allow us to find out the extent to which a specific conditioning regimen works for a specific athlete, as opposed to the average athlete, who is the focal point of group research designs. The aim of the following review is to outline the strategies and procedures of single-subject research as they pertain to.. the assessment of conditioning for individual athletes. The four main experimental designs in single-subject research are: the AB design, reversal (withdrawal) designs and their extensions, multiple baseline designs and alternating treatment designs. Visual and statistical analyses commonly used to analyse single-subject data, and advantages and limitations are discussed. Modelling of multivariate single-subject data using techniques such as dynamic factor analysis and structural equation modelling may identify individualised models of conditioning leading to better prediction of performance. Despite problems associated with data analyses in single-subject research (e.g. serial dependency), sports scientists should use single-subject research designs in applied conditioning research to understand how well an intervention (e.g. a training method) works and to predict performance for a particular athlete.

The effect of adsorption, filter material and point of dilution on antibiotic elimination by haemofiltration - An in vitro study of levofloxacin

We studied an in vitro model of continuous venous-venous haemofiltration (CVVH), into which levofloxacin 100 mg was infused, to determine levofloxacin adsorption and to determine the effect of filter material and point of dilution (pre- or post-filter) on sieving coefficient. Mean (standard deviation; S.D.) adsorption was 18.7 (5.3) mg for the polyamide filter and 40.2 (2.0) mg for the polyacrylonitrile (PAN) filter (P < 0.001). Post-dilution resulted in a minor, but statistically significant, decrease in sieving coefficient (pre-dilution 0.96 (S.D. 0.10), post-dilution 0.88 (S.D. 0.11) with the PAN filter. These data indicate that the variability in published values for levofloxacin sieving coefficient are not due to variation in point of dilution or membrane type (PAN or polyamide). Significant adsorption of levofloxacin onto PAN filters occurs. (C) 2004 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved.