Activities, Access Control, and Crime:a Quasi-Experimental Study regarding Entry Gates at Train Stations in the Netherlands

This article discusses a unique “natural experiment,” the introduction of entry gates at Dutch train stations and the potential effects of this on crime in the areas around these stations. A quasi-experimental study was carried out to show that introducing entry gates correlated with a drop in crime in these areas. After entry gates had been introduced, potential offenders could only enter train stations with a valid ticket, which meant that they would be less likely to enter or leave these stations and more likely to choose other places to hang around in or for entering and leaving trains. A dataset was created in which the crime rates around train stations were registered for each month in the years 2013 through 2018. The changing numbers of travelers at each station were also taken into account, as this variable probably correlates with the amount of crime. A two-way fixed-effects model was run on data for about 260 train stations, with and without entry gates, using the relative crime rate per thousand travelers as the dependent variable. Based on this relative crime rate, the use of entry gates was found to coincide with a decrease of 9% in crime, compared to a situation without entry gates. This study can inform policymakers about the potential effects of entry gates in particular and about situational crime prevention in general. Moreover, it illustrates how implementing measures at various locations at different moments enables the effectiveness of such measures to be tested more precisely and with more confidence

Error analysis of ICESat waveform processing by investigating overlapping pairs over Europe

Full waveform laser altimetry is a recently developed method to obtain a complete vertical profile of the height of objects in the footprint as illuminated by a laser pulse. The richness of the signal also complicates the processing. One way to improve the processing strategy is to analyze differences of waveforms that should be very similar because they were obtained at approximately the same time and location. Such waveform pairs are still difficult to find. Here it is shown how to use the archive of ICESat space-borne altimetry data over Europe to determine a set of tenths of thousands of at least partial overlapping waveform pairs. The differences in the values of the waveform parameters, median energy, waveform extent, relative returned energy and intensity distribution are determined and discussed. As a case study, three typical pairs of almost perfectly overlapping waveforms are shown, were considerable differences are still occurring. In all three cases an explanation for these differences is found and discussed. Further analysis of the waveform pairs in this database is expected to considerably improve automatic processing of full waveform data

Automated calibration of FEM models using LiDAR point clouds

In present work it is pretended to estimate elastic parameters of beams through the combined use of precision geomatic techniques (laser scanning) and structural behaviour simulation tools. The study has two aims, on the one hand, to develop an algorithm able to interpret automatically point clouds acquired by laser scanning systems of beams subjected to different load situations on experimental tests; and on the other hand, to minimize differences between deformation values given by simulation tools and those measured by laser scanning. In this way we will proceed to identify elastic parameters and boundary conditions of structural element so that surface stresses can be estimated more easily.Ministerio de Interior | Ref. SPIP2017-02122Ministerio de Economía, Industria y Competitividad | Ref. EUIN2017- 87598Ministerio de Educación, Cultura y Deporte | Ref. CAS15/00126Xunta de Galicia | Ref. ED431C2016‐03

The role of the IGF axis in IGFBP-1 and IGF-I induced renal enlargement in Snell dwarf mice

Insulin-like growth factor (IGF) binding protein-1 (IGFBP-1) is generally believed to inhibit IGF action in the circulation. In contrast, IGFBP-1 has been reported to interact with cell surfaces and enhance IGF-I action locally in some tissues. Renal IGFBP-1 levels are found elevated in various conditions characterized by renal growth (e.g. diabetes mellitus, hypokalemia). To test whether IGFBP-1 is a renotropic factor, IGFBP-1 was administered alone or in combination with IGF-I to Snell dwarf mice, an in vivo model without compensatory feedback effects on growth hormone (GH) secretion. In three control groups of Snell dwarf mice, placebo, GH or IGF-I was administered. Compared with placebo, kidney weight increased in all treated groups, however, with different effects on kidney morphology. Administration of IGF-I, alone or in combination with IGFBP-1, tended to increase glomerular volume, while no changes were seen in the other groups. Administration of IGFBP-1 or IGFBP-1+IGF-I both caused dilatation of the thin limbs of Henle's loop, while GH or IGF-I administration had no visible effect. Furthermore, IGF-I administration resulted in an increased mean number of nuclei per cortical area and renal weight, whereas GH, IGF-I+IGFBP-1 or IGFBP-1 caused a decreased renal nuclei number. In situ hybridization and immunohistochemistry showed specific changes of the renal IGF system expression patterns in the different groups. Particularly, IGFBP-1 administration resulted in extensive changes in the mRNA expression of the renal IGF system, whereas the other administration regimen resulted in less prominent modifications. In contrast, administration of IGFBP-1 and IGFBP-1+IGF-I resulted in identical changes in the protein expression of the renal IGF system. Our results indicate that IGFBP-1, alone or in combination with IGF-I, demonstrated effects on the renal tubular system that differ from the effects of IGF-I

Monitoring Deformations of a Wooden Church Tower by Laser Scanning

Churches are part of heritage structures that take an important role in Europe's cultural identity. As such, these structures must be protected to prevent catastrophic collapse and any damage must be reported timely to establish planning to maintenance and restoration. This can be achievable when the churches are monitored periodically with regular intervals. However, this monitoring strategy has not been available in most of the Europe’s churches for a number of reasons, complexity of the structures and limited budget are just two of them. Laser scanning has been widely used in capturing rich three-dimensional (3D) topographic data of visible surfaces of a structure with high accuracy. This paper presents a methodology to determine the shape and possible deviation from verticality of the church’s tower for monitoring deformation using a terrestrial laser scanner. The 500-year old wooden tower of St. Bavo Church in Haarlem, Netherlands is selected as a case study. First, point clouds of the tower captured from different views are registered into the same coordinate system. Second, a RANSAC method is employed to extract point clouds of a whole façades of the tower. Next, a point and surface-based method is proposed to compute the deformation of the surface from its data points. The results indicate that there is slightly different deformation between the tower facades in the same story and in neighbour stories. Moreover, the maximum total relative deformation at Story 7 of the tower by 0.63m

ESA's Ice Sheets CCI: validation and inter-comparison of surface elevation changes derived from laser and radar altimetry over Jakobshavn Isbræ, Greenland – Round Robin results

In order to increase the understanding of the changing climate, the European Space Agency has launched the Climate Change Initiative (ESA CCI), a program which joins scientists and space agencies into 13 projects either affecting or affected by the concurrent changes. This work is part of the Ice Sheets CCI and four parameters are to be determined for the Greenland Ice Sheet (GrIS), each resulting in a dataset made available to the public: Surface Elevation Changes (SEC), surface velocities, grounding line locations, and calving front locations. All CCI projects have completed a so-called Round Robin exercise in which the scientific community was asked to provide their best estimate of the sought parameters as well as a feedback sheet describing their work. By inter-comparing and validating the results, obtained from research institutions world-wide, it is possible to develop the most optimal method for determining each parameter. This work describes the SEC Round Robin and the subsequent conclusions leading to the creation of a method for determining GrIS SEC values. The participants used either Envisat radar or ICESat laser altimetry over Jakobshavn Isbræ drainage basin, and the submissions led to inter-comparisons of radar vs. altimetry as well as cross-over vs. repeat-track analyses. Due to the high accuracy of the former and the high spatial resolution of the latter, a method, which combines the two techniques will provide the most accurate SEC estimates. The data supporting the final GrIS analysis stem from the radar altimeters on-board Envisat, ERS-1 and ERS-2. The accuracy of laser data exceeds that of radar altimetry; the Round Robin analysis has, however, proven the latter equally capable of dealing with surface topography thereby making such data applicable in SEC analyses extending all the way from the interior ice sheet to margin regions. This shows good potential for a~future inclusion of ESA CryoSat-2 and Sentinel-3 radar data in the analysis, and thus for obtaining reliable SEC estimates throughout the entire GrIS

INVESTIGATION OF POINTNET FOR SEMANTIC SEGMENTATION OF LARGE-SCALE OUTDOOR POINT CLOUDS

Semantic segmentation of point clouds is indispensable for 3D scene understanding. Point clouds have credibility for capturing geometry of objects including shape, size, and orientation. Deep learning (DL) has been recognized as the most successful approach for image semantic segmentation. Applied to point clouds, performance of the many DL algorithms degrades, because point clouds are often sparse and have irregular data format. As a result, point clouds are regularly first transformed into voxel grids or image collections. PointNet was the first promising algorithm that feeds point clouds directly into the DL architecture. Although PointNet achieved remarkable performance on indoor point clouds, its performance has not been extensively studied in large-scale outdoor point clouds. So far, we know, no study on large-scale aerial point clouds investigates the sensitivity of the hyper-parameters used in the PointNet. This paper evaluates PointNet’s performance for semantic segmentation through three large-scale Airborne Laser Scanning (ALS) point clouds of urban environments. Reported results show that PointNet has potential in large-scale outdoor scene semantic segmentation. A remarkable limitation of PointNet is that it does not consider local structure induced by the metric space made by its local neighbors. Experiments exhibit PointNet is expressively sensitive to the hyper-parameters like batch-size, block partition and the number of points in a block. For an ALS dataset, we get significant difference between overall accuracies of 67.5% and 72.8%, for the block sizes of 5m×5m and 10m×10m, respectively. Results also discover that the performance of PointNet depends on the selection of input vectors