A review of the use of terrestrial laser scanning application for change detection and deformation monitoring of structures

Change detection and deformation monitoring is an active area of research within the field of engineering surveying as well as overlapping areas such as structural and civil engineering. The application of Terrestrial Laser Scanning (TLS) techniques for change detection and deformation monitoring of concrete structures has increased over the years as illustrated in the past studies. This paper presents a review of literature on TLS application in the monitoring of structures and discusses registration and georeferencing of TLS point cloud data as a critical issue in the process chain of accurate deformation analysis. Past TLS research work has shown some trends in addressing issues such as accurate registration and georeferencing of the scans and the need of a stable reference frame, TLS error modelling and reduction, point cloud processing techniques for deformation analysis, scanner calibration issues and assessing the potential of TLS in detecting sub-centimetre and millimetre deformations. However, several issues are still open to investigation as far as TLS is concerned in change detection and deformation monitoring studies such as rigorous and efficient workflow methodology of point cloud processing for change detection and deformation analysis, incorporation of measurement geometry in deformation measurements of high-rise structures, design of data acquisition and quality assessment for precise measurements and modelling the environmental effects on the performance of laser scanning. Even though some studies have attempted to address these issues, some gaps exist as information is still limited. Some methods reviewed in the case studies have been applied in landslide monitoring and they seem promising to be applied in engineering surveying to monitor structures. Hence the proposal of a three-stage process model for deformation analysis is presented. Furthermore, with technological advancements new TLS instruments with better accuracy are being developed necessitating more research for precise measurements in the monitoring of structures

Immunopathogenesis and proposed clinical score for identifying Kelch-like protein-11 encephalitis

In this study, we report the clinical features of Kelch-like protein 11 antibody-associated paraneoplastic neurological syndrome, design and validate a clinical score to facilitate the identification of patients that should be tested for Kelch-like protein 11 antibodies, and examine in detail the nature of the immune response in both the brain and the tumour samples for a better characterization of the immunopathogenesis of this condition. The presence of Kelch-like protein 11 antibodies was retrospectively assessed in patients referred to the French Reference Center for paraneoplastic neurological syndrome and autoimmune encephalitis with (i) antibody-negative paraneoplastic neurological syndrome [limbic encephalitis (n = 105), cerebellar degeneration (n = 33)] and (ii) antibody-positive paraneoplastic neurological syndrome [Ma2-Ab encephalitis (n = 34), antibodies targeting N-methyl-D-aspartate receptor encephalitis with teratoma (n = 49)]. Additionally, since 1 January 2020, patients were prospectively screened for Kelch-like protein 11 antibodies as new usual clinical practice. Overall, Kelch-like protein 11 antibodies were detected in 11 patients [11/11, 100% were male; their median (range) age was 44 (35-79) years], 9 of them from the antibody-negative paraneoplastic neurological syndrome cohort, 1 from the antibody-positive (Ma2-Ab) cohort and 1 additional prospectively detected patient. All patients manifested a cerebellar syndrome, either isolated (4/11, 36%) or part of a multi-system neurological disorder (7/11, 64%). Additional core syndromes were limbic encephalitis (5/11, 45%) and myelitis (2/11, 18%). Severe weight loss (7/11, 64%) and hearing loss/tinnitus (5/11, 45%) were common. Rarer neurologic manifestations included hypersomnia and seizures (2/11, 18%). Two patients presented phenotypes resembling primary neurodegenerative disorders (progressive supranuclear palsy and flail arm syndrome, respectively). An associated cancer was found in 9/11 (82%) patients; it was most commonly (7/9, 78%) a spontaneously regressed ('burned-out') testicular germ cell tumour. A newly designed clinical score (MATCH score: male, ataxia, testicular cancer, hearing alterations) with a cut-off ≥4 successfully identified patients with Kelch-like protein 11 antibodies (sensitivity 78%, specificity 99%). Pathological findings (three testicular tumours, three lymph node metastases of testicular tumours, one brain biopsy) showed the presence of a T-cell inflammation with resulting anti-tumour immunity in the testis and one chronic, exhausted immune response - demonstrated by immune checkpoint expression - in the metastases and the brain. In conclusion, these findings suggest that Kelch-like protein 11 antibody paraneoplastic neurological syndrome is a homogeneous clinical syndrome and its detection can be facilitated using the MATCH score. The pathogenesis is probably T-cell mediated, but the stages of inflammation are different in the testis, metastases and the brain

Efficient three-dimensional reconstruction of aquatic vegetation geometry: Estimating morphological parameters influencing hydrodynamic drag

Aquatic vegetation can shelter coastlines from energetic waves and tidal currents, sometimes enabling accretion of fine sediments. Simulation of flow and sediment transport within submerged canopies requires quantification of vegetation geometry. However, field surveys used to determine vegetation geometry can be limited by the time required to obtain conventional caliper and ruler measurements. Building on recent progress in photogrammetry and computer vision, we present a method for reconstructing three-dimensional canopy geometry. The method was used to survey a dense canopy of aerial mangrove roots, called pneumatophores, in Vietnam’s Mekong River Delta. Photogrammetric estimation of geometry required 1) taking numerous photographs at low tide from multiple viewpoints around 1 m2 quadrats, 2) computing relative camera locations and orientations by triangulation of key features present in multiple images and reconstructing a dense 3D point cloud, and 3) extracting pneumatophore locations and diameters from the point cloud data. Step 3) was accomplished by a new ‘sector-slice’ algorithm, yielding geometric parameters every 5 mm along a vertical profile. Photogrammetric analysis was compared with manual caliper measurements. In all 5 quadrats considered, agreement was found between manual and photogrammetric estimates of stem number, and of number × mean diameter, which is a key parameter appearing in hydrodynamic models. In two quadrats, pneumatophores were encrusted with numerous barnacles, generating a complex geometry not resolved by hand measurements. In remaining cases, moderate agreement between manual and photogrammetric estimates of stem diameter and solid volume fraction was found. By substantially reducing measurement time in the field while capturing in greater detail the 3D structure, photogrammetry has potential to improve input to hydrodynamic models, particularly for simulations of flow through large-scale, heterogenous canopies

FACETS : A CLOUDCOMPARE PLUGIN TO EXTRACT GEOLOGICAL PLANES FROM UNSTRUCTURED 3D POINT CLOUDS

Geological planar facets (stratification, fault, joint…) are key features to unravel the tectonic history of rock outcrop or appreciate the stability of a hazardous rock cliff. Measuring their spatial attitude (dip and strike) is generally performed by hand with a compass/clinometer, which is time consuming, requires some degree of censoring (i.e. refusing to measure some features judged unimportant at the time), is not always possible for fractures higher up on the outcrop and is somewhat hazardous. 3D virtual geological outcrop hold the potential to alleviate these issues. Efficiently segmenting massive 3D point clouds into individual planar facets, inside a convenient software environment was lacking. FACETS is a dedicated plugin within CloudCompare v2.6.2 (http://cloudcompare.org/ ) implemented to perform planar facet extraction, calculate their dip and dip direction (i.e. azimuth of steepest decent) and report the extracted data in interactive stereograms. Two algorithms perform the segmentation: Kd-Tree and Fast Marching. Both divide the point cloud into sub-cells, then compute elementary planar objects and aggregate them progressively according to a planeity threshold into polygons. The boundaries of the polygons are adjusted around segmented points with a tension parameter, and the facet polygons can be exported as 3D polygon shapefiles towards third party GIS software or simply as ASCII comma separated files. One of the great features of FACETS is the capability to explore planar objects but also 3D points with normals with the stereogram tool. Poles can be readily displayed, queried and manually segmented interactively. The plugin blends seamlessly into CloudCompare to leverage all its other 3D point cloud manipulation features. A demonstration of the tool is presented to illustrate these different features. While designed for geological applications, FACETS could be more widely applied to any planar objects