bluuebunny/crossref_metadata_2025 huggingface dataset:
Efavirenz: A review of the epidemiology, severity and management of neuropsychiatric side-effects
Authors: Gaida Razia , Truter Ilse , Grobler Christoffel
Published: June 2017

South Africa has the highest proportion of HIV-positive people in the world. HIV cannot be cured; however, there are several major classes of drugs used in its management. Efavirenz is one such agent of the class non-nucleoside reverse transcriptase inhibitors which inhibits the replication of the virus. Efavirenz is associated with causing neuropsychiatric side-effects (NPSEs), with almost 50% of patients experiencing at least one NPSE while on treatment. The NPSEs tend to occur within the first few days of initiation of therapy and resolve spontaneously within the first 4 - 6 weeks, with the most commonly reported being dizziness, insomnia, headache, abnormal dreams and impaired concentration. The plasma level of efavirenz and genetic polymorphisms are thought to play a role in the development of such NPSEs. NPSEs need to be treated according to severity. If necessary, efavirenz may be replaced with nevirapine or lopinavir/ritonavir. It should be remembered that nevirapine may also produce some severe side-effects such as skin abnormalities and hepatotoxicity. The monitoring of patients receiving efavirenz therapy should be ongoing, with those with a history of mental illness requiring closer monitoring than others. 

 
Alcohol use among sixth-year medical students at the University of the Free State
Authors: Marais A L , Calitz F J W , Rataemane L U Z , Joubert G
Published: June 2017

Introduction. Excessive alcohol consumption among students is cause for concern, not only because medical students them- selves may suffer in the long term but also because of the potential negative impact this may have on their effectiveness as tomorrow’s doctors. Objectives. The aim of the study was to investigate alcohol use among 6th-year medical students at the University of the Free State (UFS) and reasons for their alcohol use. Methods. After a compulsory lecture on an unrelated topic, the 6th-year medical students at the UFS were given a demo- graphic questionnaire, the self-rated Alcohol Use Disorders Identification Test (AUDIT) and a shortened version of the self- rated Inventory of Drug-taking Situations (IDTS) to complete. Conclusion. From the results of this study it is clear that a sig- nificant number of 6th-year medical students at the UFS (28.3%) use alcohol in a harmful way. Most students use alco- hol when they are with friends or in some kind of social setting. However, a number of students use alcohol to cope with stress- ful situations. It is therefore important that the prevention of harmful use of alcohol should receive attention in medical schools.
AN APPROACH TO EXTRACT MOVING OBJECTS FROM MLS DATA USING A VOLUMETRIC BACKGROUND REPRESENTATION
Authors: Gehrung J. , Hebel M. , Arens M. , Stilla U.
Published: June 2017

Abstract. Data recorded by mobile LiDAR systems (MLS) can be used for the generation and refinement of city models or for the automatic detection of long-term changes in the public road space. Since for this task only static structures are of interest, all mobile objects need to be removed. This work presents a straightforward but powerful approach to remove the subclass of moving objects. A probabilistic volumetric representation is utilized to separate MLS measurements recorded by a Velodyne HDL-64E into mobile objects and static background. The method was subjected to a quantitative and a qualitative examination using multiple datasets recorded by a mobile mapping platform. The results show that depending on the chosen octree resolution 87-95% of the measurements are labeled correctly.
MATCHING REAL AND SYNTHETIC PANORAMIC IMAGES USING A VARIANT OF GEOMETRIC HASHING
Authors: Li-Chee-Ming J. , Armenakis C.
Published: June 2017

Abstract. This work demonstrates an approach to automatically initialize a visual model-based tracker, and recover from lost tracking, without prior camera pose information. These approaches are commonly referred to as tracking-by-detection. Previous tracking-by-detection techniques used either fiducials (i.e. landmarks or markers) or the object’s texture. The main contribution of this work is the development of a tracking-by-detection algorithm that is based solely on natural geometric features. A variant of geometric hashing, a model-to-image registration algorithm, is proposed that searches for a matching panoramic image from a database of synthetic panoramic images captured in a 3D virtual environment. The approach identifies corresponding features between the matched panoramic images. The corresponding features are to be used in a photogrammetric space resection to estimate the camera pose. The experiments apply this algorithm to initialize a model-based tracker in an indoor environment using the 3D CAD model of the building.
SYSTEM DESIGN, CALIBRATION AND PERFORMANCE ANALYSIS OF A NOVEL 360° STEREO PANORAMIC MOBILE MAPPING SYSTEM
Authors: Blaser S. , Nebiker S. , Cavegn S.
Published: June 2017

Abstract. Image-based mobile mapping systems enable the efficient acquisition of georeferenced image sequences, which can later be exploited in cloud-based 3D geoinformation services. In order to provide a 360° coverage with accurate 3D measuring capabilities, we present a novel 360° stereo panoramic camera configuration. By using two 360° panorama cameras tilted forward and backward in combination with conventional forward and backward looking stereo camera systems, we achieve a full 360° multi-stereo coverage. We furthermore developed a fully operational new mobile mapping system based on our proposed approach, which fulfils our high accuracy requirements. We successfully implemented a rigorous sensor and system calibration procedure, which allows calibrating all stereo systems with a superior accuracy compared to that of previous work. Our study delivered absolute 3D point accuracies in the range of 4 to 6 cm and relative accuracies of 3D distances in the range of 1 to 3 cm. These results were achieved in a challenging urban area. Furthermore, we automatically reconstructed a 3D city model of our study area by employing all captured and georeferenced mobile mapping imagery. The result is a very high detailed and almost complete 3D city model of the street environment.
BOOSTED UNSUPERVISED MULTI-SOURCE SELECTION FOR DOMAIN ADAPTATION
Authors: Vogt K. , Paul A. , Ostermann J. , Rottensteiner F. , Heipke C.
Published: June 2017

Abstract. Supervised machine learning needs high quality, densely sampled and labelled training data. Transfer learning (TL) techniques have been devised to reduce this dependency by adapting classifiers trained on different, but related, (source) training data to new (target) data sets. A problem in TL is how to quantify the relatedness of a source quickly and robustly, because transferring knowledge from unrelated data can degrade the performance of a classifier. In this paper, we propose a method that can select a nearly optimal source from a large number of candidate sources. This operation depends only on the marginal probability distributions of the data, thus allowing the use of the often abundant unlabelled data. We extend this method to multi-source selection by optimizing a weighted combination of sources. The source weights are computed using a very fast boosting-like optimization scheme. The run-time complexity of our method scales linearly in regard to the number of candidate sources and the size of the training set and is thus applicable to very large data sets. We also propose a modification of an existing TL algorithm to handle multiple weighted training sets. Our method is evaluated on five survey regions. The experiments show that our source selection method is effective in discriminating between related and unrelated sources, almost always generating results within 3% in overall accuracy of a classifier based on fully labelled training data. We also show that using the selected source as training data for a TL method will additionally result in a performance improvement.
DISOCCLUSION OF 3D LIDAR POINT CLOUDS USING RANGE IMAGES
Authors: Biasutti P. , Aujol J.-F. , Brédif M. , Bugeau A.
Published: June 2017

Abstract. This paper proposes a novel framework for the disocclusion of mobile objects in 3D LiDAR scenes aquired via street-based Mobile Mapping Systems (MMS). Most of the existing lines of research tackle this problem directly in the 3D space. This work promotes an alternative approach by using a 2D range image representation of the 3D point cloud, taking advantage of the fact that the problem of disocclusion has been intensively studied in the 2D image processing community over the past decade. First, the point cloud is turned into a 2D range image by exploiting the sensor’s topology. Using the range image, a semi-automatic segmentation procedure based on depth histograms is performed in order to select the occluding object to be removed. A variational image inpainting technique is then used to reconstruct the area occluded by that object. Finally, the range image is unprojected as a 3D point cloud. Experiments on real data prove the effectiveness of this procedure both in terms of accuracy and speed.
A TWO-STEP DECISION FUSION STRATEGY: APPLICATION TO HYPERSPECTRAL AND MULTISPECTRAL IMAGES FOR URBAN CLASSIFICATION
Authors: Ouerghemmi W. , Le Bris A. , Chehata N. , Mallet C.
Published: June 2017

Abstract. Very high spatial resolution multispectral images and lower spatial resolution hyperspectral images are complementary sources for urban object classification. The first enables a fine delineation of objects, while the second can better discriminate classes and consider richer land cover semantics. This paper presents a decision fusion scheme taking advantage of both sources classification maps, to produce a better classification map. The proposed method aims at dealing with both semantic and spatial uncertainties and consists in two steps. First, class membership maps are merged at pixel level. Several fusion rules are considered and compared in this study. Secondly, classification is obtained from a global regularization of a graphical model, involving a fit-to-data term related to class membership measures and an image based contrast sensitive regularization term. Results are presented on three datasets. The classification accuracy is improved up to 5 %, with comparison to the best single source classification accuracy.
STRUCTURE-FROM-MOTION FOR CALIBRATION OF A VEHICLE CAMERA SYSTEM WITH NON-OVERLAPPING FIELDS-OF-VIEW IN AN URBAN ENVIRONMENT
Authors: Hanel A. , Stilla U.
Published: June 2017

Abstract. Vehicle environment cameras observing traffic participants in the area around a car and interior cameras observing the car driver are important data sources for driver intention recognition algorithms. To combine information from both camera groups, a camera system calibration can be performed. Typically, there is no overlapping field-of-view between environment and interior cameras. Often no marked reference points are available in environments, which are a large enough to cover a car for the system calibration. In this contribution, a calibration method for a vehicle camera system with non-overlapping camera groups in an urban environment is described. A-priori images of an urban calibration environment taken with an external camera are processed with the structure-frommotion method to obtain an environment point cloud. Images of the vehicle interior, taken also with an external camera, are processed to obtain an interior point cloud. Both point clouds are tied to each other with images of both image sets showing the same real-world objects. The point clouds are transformed into a self-defined vehicle coordinate system describing the vehicle movement. On demand, videos can be recorded with the vehicle cameras in a calibration drive. Poses of vehicle environment cameras and interior cameras are estimated separately using ground control points from the respective point cloud. All poses of a vehicle camera estimated for different video frames are optimized in a bundle adjustment. In an experiment, a point cloud is created from images of an underground car park, as well as a point cloud of the interior of a Volkswagen test car is created. Videos of two environment and one interior cameras are recorded. Results show, that the vehicle camera poses are estimated successfully especially when the car is not moving. Position standard deviations in the centimeter range can be achieved for all vehicle cameras. Relative distances between the vehicle cameras deviate between one and ten centimeters from tachymeter reference measurements.
POINTING ANGLE CALIBRATION OF ZY3-02 SATELLITE LASER ALTIMETER USING TERRAIN MATCHING
Authors: Li G. , Tang X. , Gao X. , Huang J. P. , Chen J. , Lu J.
Published: June 2017

Abstract. After GLAS (Geo-science Laser Altimeter System) loaded on the ICESat (Ice Cloud and land Elevation Satellite), satellite laser altimeter attracts more and more attention. ZY3-02 equipped with the Chinese first satellite laser altimeter has been successfully launched on 30th May, 2016. The geometric calibration is an important step for the laser data processing and application. The method to calculate the laser pointing angle error based on existed reference terrain data is proposed in this paper. The public version terrain data, such as 90m-SRTM and 30m-AW3D30, can be used to estimate the pointing angle of laser altimeter. The GLAS data with simulated pointing error and actual ZY3-02 laser altimetry data is experimented to validate the algorithm. The conclusion will be useful for the future domestic satellite laser altimeter.
FOREST STEM VOLUME CALCULATION USING AIRBORNE LIDAR DATA
Authors: Büyüksalih I. , Bayburt S. , Schardt M. , Büyüksalih G.
Published: June 2017

Abstract. Airborne LiDAR data have been collected for the city of Istanbul using Riegl laser scanner Q680i with 400 kHz and an average flight height of 600 m. The flight campaign was performed by a helicopter and covers an area of 5400 km2. According to a flight speed of 80 knot a point density of more than 16 points/m2 and a laser footprint size of 30 cm could be achieved. As a result of bundle adjustment, in total, approximately 17,000 LAS files with the file size of 500 m by 700 m have been generated for the whole city. The main object classes Ground, Building, Vegetation (medium, high) were derived from these LAS files using the macros in Terrasolid software. The forest area under investigation is located northwest of the city of Istanbul, main tree species occurring in the test site are pine (pinus pinaster), oak (quercus) and beech (fagus). In total, 120 LAS tiles covering the investigation area have been analysed using the software IMPACT of Joanneum Research Forschungsgesellschaft, Graz, Austria. First of all, the digital terrain model (DTM) and the digital surface models (DSM) were imported and converted into a raster file from the original laser point clouds with a spatial resolution of 50 cm. Then, a normalized digital surface model (nDSM) was derived as the difference between DSM and the DTM. Tree top detection was performed by multi – resolution filter operations and tree crowns were segmented by a region growing algorithms develop specifically for this purpose. Breast Height Diameter (BHD) was calculated on the base of tree height and crown areas derived from image segmentation applying allometric functions found in literature. The assessment of stem volume was then calculated as a function of tree height and BHD. A comparison of timber volume estimated from the LiDAR data and field plots measured by the Forest Department of Istanbul showed R2 of 0.46. The low correlation might arise either from the low quality of the field plots or from the inadequacy of the allometric functions used for BHD and stem volume modelling. Further investigations therefore will concentrate both on improving the quality of field measurements and the adoption of the allometric functions to the specific site condition of the forests under investigation. Finally stand boundaries of the forest area made available by the forest department of Istanbul were superimposed to the LiDAR data and the single tree measurements aggregated to the stand level. Aside from the LiDAR data, a Pleiades multispectral image characterized by four spectral bands (blue, green, red and near infrared) and a GSD of 2.8 m has been used for the classification of different tree species. For this purpose the near infrared band covering the spectral range of 0.75 μm to 0.90 μm has been utilized and the IMPACT software used.
FULLY AUTOMATIC FEATURE-BASED REGISTRATION OF MOBILE MAPPING AND AERIAL NADIR IMAGES FOR ENABLING THE ADJUSTMENT OF MOBILE PLATFORM LOCATIONS IN GNSS-DENIED URBAN ENVIRONMENTS
Authors: Jende P. , Nex F. , Gerke M. , Vosselman G.
Published: June 2017

Abstract. Mobile Mapping (MM) has gained significant importance in the realm of high-resolution data acquisition techniques. MM is able to record georeferenced street-level data in a continuous (laser scanners) and/or discrete (cameras) fashion. MM’s georeferencing relies on a conjunction of Global Navigation Satellite Systems (GNSS), Inertial Measurement Units (IMU) and optionally on odometry sensors. While this technique does not pose a problem for absolute positioning in open areas, its reliability and accuracy may be diminished in urban areas where high-rise buildings and other tall objects can obstruct the direct line-of-sight between the satellite and the receiver unit. Consequently, multipath measurements or complete signal outages impede the MM platform’s localisation and may affect the accurate georeferencing of collected data. This paper presents a technique to recover correct orientation parameters for MM imaging platforms by utilising aerial images as an external georeferencing source. This is achieved by a fully automatic registration strategy which takes into account the overall differences between aerial and MM data, such as scale, illumination, perspective and content. Based on these correspondences, MM data can be verified and/or corrected by using an adjustment solution. The registration strategy is discussed and results in a success rate of about 95 %.
MANHOLE COVER LOCALIZATION IN AERIAL IMAGES WITH A DEEP LEARNING APPROACH
Authors: Commandre B. , En-Nejjary D. , Pibre L. , Chaumont M. , Delenne C. , Chahinian N.
Published: June 2017

Abstract. Urban growth is an ongoing trend and one of its direct consequences is the development of buried utility networks. Locating these networks is becoming a challenging task. While the labeling of large objects in aerial images is extensively studied in Geosciences, the localization of small objects (smaller than a building) is in counter part less studied and very challenging due to the variance of object colors, cluttered neighborhood, non-uniform background, shadows and aspect ratios. In this paper, we put forward a method for the automatic detection and localization of manhole covers in Very High Resolution (VHR) aerial and remotely sensed images using a Convolutional Neural Network (CNN). Compared to other detection/localization methods for small objects, the proposed approach is more comprehensive as the entire image is processed without prior segmentation. The first experiments using the Prades-Le-Lez and Gigean datasets show that our method is indeed effective as more than 49% of the ground truth database is detected with a precision of 75 %. New improvement possibilities are being explored such as using information on the shape of the detected objects and increasing the types of objects to be detected, thus enabling the extraction of more object specific features.
HIERARCHICAL REGULARIZATION OF POLYGONS FOR PHOTOGRAMMETRIC POINT CLOUDS OF OBLIQUE IMAGES
Authors: Xie L. , Hu H. , Zhu Q. , Wu B. , Zhang Y.
Published: June 2017

Abstract. Despite the success of multi-view stereo (MVS) reconstruction from massive oblique images in city scale, only point clouds and triangulated meshes are available from existing MVS pipelines, which are topologically defect laden, free of semantical information and hard to edit and manipulate interactively in further applications. On the other hand, 2D polygons and polygonal models are still the industrial standard. However, extraction of the 2D polygons from MVS point clouds is still a non-trivial task, given the fact that the boundaries of the detected planes are zigzagged and regularities, such as parallel and orthogonal, cannot preserve. Aiming to solve these issues, this paper proposes a hierarchical polygon regularization method for the photogrammetric point clouds from existing MVS pipelines, which comprises of local and global levels. After boundary points extraction, e.g. using alpha shapes, the local level is used to consolidate the original points, by refining the orientation and position of the points using linear priors. The points are then grouped into local segments by forward searching. In the global level, regularities are enforced through a labeling process, which encourage the segments share the same label and the same label represents segments are parallel or orthogonal. This is formulated as Markov Random Field and solved efficiently. Preliminary results are made with point clouds from aerial oblique images and compared with two classical regularization methods, which have revealed that the proposed method are more powerful in abstracting a single building and is promising for further 3D polygonal model reconstruction and GIS applications.
INTEGRATED USE OF REMOTE SENSING, GIS AND GPS TECHNOLOGY FOR MONITORING THE ENVIRONMENTAL PROBLEM OF SHYAMNAGAR
Authors: Akbar M. S. , Sarker M. H. , Sattar M. A. , Sarwar G. M. , Rahman S. M. M. , Rahman M. M. , Khan Z. U.
Published: June 2017

Abstract. Cultivation of shrimp mostly in unplanned way has been considered as one of the major environmental disasters of Shamnagar. Villagers surrounding the rivers are mainly involved with fish (shrimp) cultivation. So, fertile agriculture land has been converted to shrimp cultivation. Conversion of agriculture land to other usage is a common but acute problem for land resources of the country like Bangladesh. Conventional methods for collecting this information are relatively costly and time consuming. Contrarily, Remote Sensing satellite observation with its unique capability to provide cost-effective support in compiling the latest information about the natural resource. Remote sensing, in conjunction with GIS, has been widely applied and been recognized as a powerful and effective tool in detecting land use and land cover changes. RapidEye, Landsat8 images were used to identify land use and land cover of the area during the period 2008 and 2015. Google images were used to identify the micro-level land use features of the same period. Multi-spectral classifications using unsupervised and supervised classification were done and results have been compared based on the field investigation. The study reveals that during the period 2008 to 2015 agricultural practice has been reduced from 35 % to 21 % and shrimp cultivation area increased from 38 % to 50 %. Due to the impact of high salinity and salt water intrusion caused by natural disaster, agricultural activities is reduced and farmers have been converted to other practices, as a result shrimp farming is gaining popularity in the area.
APPLICATION OF SOFTMAX REGRESSION AND ITS VALIDATION FOR SPECTRAL-BASED LAND COVER MAPPING
Authors: Wolfe J. , Jin X. , Bahr T. , Holzer N.
Published: June 2017

Abstract. The presented Softmax Regression classifier is a generalization of logistic regression. It is used for multi-class classification, where classes are mutually exclusive. Implemented in a classification framework, it provides a flexible approach to customize a classification process. Traditional classification is focused with classifiers that can only be applied on the same dataset. The Softmax Regression classifier can be created and trained on a reference dataset using spectral and spatial information and then applied to similar data multiple times. We present the general workflow of Softmax Regression classification as part of a case study that is based on attribute images derived from hyperspectral airborne and elevation imagery.
Learning Oriented Region-based Convolutional Neural Networks for Building Detection in Satellite Remote Sensing Images
Authors: Chen C. , Gong W. , Hu Y. , Chen Y. , Ding Y.
Published: June 2017

Abstract. The automated building detection in aerial images is a fundamental problem encountered in aerial and satellite images analysis. Recently, thanks to the advances in feature descriptions, Region-based CNN model (R-CNN) for object detection is receiving an increasing attention. Despite the excellent performance in object detection, it is problematic to directly leverage the features of R-CNN model for building detection in single aerial image. As we know, the single aerial image is in vertical view and the buildings possess significant directional feature. However, in R-CNN model, direction of the building is ignored and the detection results are represented by horizontal rectangles. For this reason, the detection results with horizontal rectangle cannot describe the building precisely. To address this problem, in this paper, we proposed a novel model with a key feature related to orientation, namely, Oriented R-CNN (OR-CNN). Our contributions are mainly in the following two aspects: 1) Introducing a new oriented layer network for detecting the rotation angle of building on the basis of the successful VGG-net R-CNN model; 2) the oriented rectangle is proposed to leverage the powerful R-CNN for remote-sensing building detection. In experiments, we establish a complete and bran-new data set for training our oriented R-CNN model and comprehensively evaluate the proposed method on a publicly available building detection data set. We demonstrate State-of-the-art results compared with the previous baseline methods.
RECONSTRUCTING BUILDINGS WITH DISCONTINUITIES AND ROOF OVERHANGS FROM OBLIQUE AERIAL IMAGERY
Authors: Frommholz D. , Linkiewicz M. , Meissner H. , Dahlke D.
Published: June 2017

Abstract. This paper proposes a two-stage method for the reconstruction of city buildings with discontinuities and roof overhangs from oriented nadir and oblique aerial images. To model the structures the input data is transformed into a dense point cloud, segmented and filtered with a modified marching cubes algorithm to reduce the positional noise. Assuming a monolithic building the remaining vertices are initially projected onto a 2D grid and passed to RANSAC-based regression and topology analysis to geometrically determine finite wall, ground and roof planes. If this should fail due to the presence of discontinuities the regression will be repeated on a 3D level by traversing voxels within the regularly subdivided bounding box of the building point set. For each cube a planar piece of the current surface is approximated and expanded. The resulting segments get mutually intersected yielding both topological and geometrical nodes and edges. These entities will be eliminated if their distance-based affiliation to the defining point sets is violated leaving a consistent building hull including its structural breaks. To add the roof overhangs the computed polygonal meshes are projected onto the digital surface model derived from the point cloud. Their shapes are offset equally along the edge normals with subpixel accuracy by detecting the zero-crossings of the second-order directional derivative in the gradient direction of the height bitmap and translated back into world space to become a component of the building. As soon as the reconstructed objects are finished the aerial images are further used to generate a compact texture atlas for visualization purposes. An optimized atlas bitmap is generated that allows perspectivecorrect multi-source texture mapping without prior rectification involving a partially parallel placement algorithm. Moreover, the texture atlases undergo object-based image analysis (OBIA) to detect window areas which get reintegrated into the building models. To evaluate the performance of the proposed method a proof-of-concept test on sample structures obtained from real-world data of Heligoland/Germany has been conducted. It revealed good reconstruction accuracy in comparison to the cadastral map, a speed-up in texture atlas optimization and visually attractive render results.
LANDSLIDE MONITORING USING INSAR TIME-SERIES AND GPS OBSERVATIONS, CASE STUDY: SHABKOLA LANDSLIDE IN NORTHERN IRAN
Authors: Mirzaee S. , Motagh M. , Akbari B.
Published: June 2017

Abstract. Shabkola is a village located in Mazandaran province of northern Iran that suffers from the mass movement happening in the upstream. Deforestation and changes to land use are the main reasons for the soil instability in this region, which together with steep slope, relatively high precipitation rate and natural erosion has led to such a condition. The area of mass movement is approximately 90 hectares which is a big threat for people living in the region. In this study, we have utilized two different geodetic techniques including InSAR time-series analysis and GPS measurements to assess slope stability in Shabkola. The SAR dataset includes 19 ALOS/PALSAR images spanning from July 2007 to February 2011 while GPS observations are collected in 5 campaigns from September 2011 to May 2014. Displacement as much as approximately 11.7 m in slope direction was detected by GPS observations for the 2011-2014 time period. Most of the slope geometry is in north-south direction, for which the sensitivity of InSAR for displacement detection is low. However, ALOS PALSAR data analysis revealed a previously unknown landslide, covered by dense vegetation in the northern part of main Shabkola landslide, showing line-of-sight velocity of approximately 2cm/year in the time period 2007-2011.
AN INTEGRATED RAPID MAPPING SYSTEM FOR DISASTER MANAGEMENT
Authors: Hein D. , Bayer S. , Berger R. , Kraft T. , Lesmeister D.
Published: June 2017

Abstract. Natural disasters as well as major man made incidents are an increasingly serious threat for civil society. Effective, fast and coordinated disaster management crucially depends on the availability of a real-time situation picture of the affected area. However, in situ situation assessment from the ground is usually time-consuming and of limited effect, especially when dealing with large or inaccessible areas. A rapid mapping system based on aerial images can enable fast and effective assessment and analysis of medium to large scale disaster situations. This paper presents an integrated rapid mapping system that is particularly designed for real-time applications, where comparatively large areas have to be recorded in short time. The system includes a lightweight camera system suitable for UAV applications and a software tool for generating aerial maps from recorded sensor data within minutes after landing. The paper describes in particular which sensors are applied and how they are operated. Furthermore it outlines the procedure, how the aerial map is generated from image and additional gathered sensor data.
RELATIVE ORIENTATION AND MODIFIED PIECEWISE EPIPOLAR RESAMPLING FOR HIGH RESOLUTION SATELLITE IMAGES
Authors: Gong K. , Fritsch D.
Published: June 2017

Abstract. High resolution, optical satellite sensors are boosted to a new era in the last few years, because satellite stereo images at half meter or even 30cm resolution are available. Nowadays, high resolution satellite image data have been commonly used for Digital Surface Model (DSM) generation and 3D reconstruction. It is common that the Rational Polynomial Coefficients (RPCs) provided by the vendors have rough precision and there is no ground control information available to refine the RPCs. Therefore, we present two relative orientation methods by using corresponding image points only: the first method will use quasi ground control information, which is generated from the corresponding points and rough RPCs, for the bias-compensation model; the second method will estimate the relative pointing errors on the matching image and remove this error by an affine model. Both methods do not need ground control information and are applied for the entire image. To get very dense point clouds, the Semi-Global Matching (SGM) method is an efficient tool. However, before accomplishing the matching process the epipolar constraints are required. In most conditions, satellite images have very large dimensions, contrary to the epipolar geometry generation and image resampling, which is usually carried out in small tiles. This paper also presents a modified piecewise epipolar resampling method for the entire image without tiling. The quality of the proposed relative orientation and epipolar resampling method are evaluated, and finally sub-pixel accuracy has been achieved in our work.
FREE GLOBAL DSM ASSESSMENT ON LARGE SCALE AREAS EXPLOITING THE POTENTIALITIES OF THE INNOVATIVE GOOGLE EARTH ENGINE PLATFORM
Authors: Nascetti A. , Di Rita M. , Ravanelli R. , Amicuzi M. , Esposito S. , Crespi M.
Published: June 2017

Abstract. The high-performance cloud-computing platform Google Earth Engine has been developed for global-scale analysis based on the Earth observation data. In particular, in this work, the geometric accuracy of the two most used nearly-global free DSMs (SRTM and ASTER) has been evaluated on the territories of four American States (Colorado, Michigan, Nevada, Utah) and one Italian Region (Trentino Alto- Adige, Northern Italy) exploiting the potentiality of this platform. These are large areas characterized by different terrain morphology, land covers and slopes. The assessment has been performed using two different reference DSMs: the USGS National Elevation Dataset (NED) and a LiDAR acquisition. The DSMs accuracy has been evaluated through computation of standard statistic parameters, both at global scale (considering the whole State/Region) and in function of the terrain morphology using several slope classes. The geometric accuracy in terms of Standard deviation and NMAD, for SRTM range from 2-3 meters in the first slope class to about 45 meters in the last one, whereas for ASTER, the values range from 5-6 to 30 meters. In general, the performed analysis shows a better accuracy for the SRTM in the flat areas whereas the ASTER GDEM is more reliable in the steep areas, where the slopes increase. These preliminary results highlight the GEE potentialities to perform DSM assessment on a global scale.
Closed-loop Helium Circulation System for Actuation of a Continuously Operating Heart Catheter Pump
Authors: Karabegovic Alen , Hinteregger Markus , Janeczek Christoph , Mohl Werner , Gföhler Margit
Published: June 2017

Background

Currently available, pneumatic-based medical devices are operated using closed-loop pulsatile or open continuous systems. Medical devices utilizing gases with a low atomic number in a continuous closed loop stream have not been documented to date. This work presents the construction of a portable helium circulation addressing the need for actuating a novel, pneumatically operated catheter pump. The design of its control system puts emphasis on the performance, safety and low running cost of the catheter pump.

Methods and results

Static and dynamic characteristics of individual elements in the circulation are analyzed to ensure a proper operation of the system. The pneumatic circulation maximizes the working range of the drive unit inside the catheter pump while reducing the total size and noise production. Separate flow and pressure controllers position the turbine's working point into the stable region of the pressure creation element. A subsystem for rapid gas evacuation significantly decreases the duration of helium removal after a leak, reaching subatmospheric pressure in the intracorporeal catheter within several milliseconds.

Conclusions

The system presented in the study offers an easy control of helium mass flow while ensuring stable behavior of its internal components.
Venlafaxine Intoxication with Development of Takotsubo Cardiomyopathy: Successful Use of Extracorporeal Life Support, Intravenous Lipid Emulsion and Cytosorb®
Authors: Schroeder Ines , Zoller Michael , Angstwurm Matthias , Kur Felix , Frey Lorenz
Published: June 2017

We describe a young patient who ingested 18 g (240 times the daily therapeutic dose) of venlafaxine in a suicide attempt. She developed severe cardiomyopathy in a takotsubo distribution causing cardiogenic shock and multi-organ dysfunction syndrome (MODS). She was successfully treated with intravenous lipid emulsion (ILE), extracorporeal life support (ECLS) and CytoSorb®. This is remarkable as, to the best of the authors’ knowledge, this is the highest amount of venlafaxine intake seen in the literature with a nonfatal outcome.
Bone Response to Porous Alumina Implants Coated with Bioactive Materials, Observed Using Different Characterization Techniques
Authors: Camilo Claudia C. , Silveira Celey A.E. , Faeda Rafael S. , de Almeida Rollo João M.D. , de Moraes Purquerio Benedito , Fortulan Carlos Alberto
Published: June 2017

Background

Implants or implantable devices should integrate into the host tissue faster than fibrous capsule formation, in which the design of the interface is one of the biggest challenges. Generally, bioactive materials are not viable for load-bearing applications, so inert biomaterials are proposed. However, the surface must be modified through techniques such as coating with bioactive materials, roughness and sized pores. The aim of this research was to validate an approach for the evaluation of the tissue growth on implants of porous alumina coated with bioactive materials.

Methods

Porous alumina implants were coated with 45S5 Bioglass® (BG) and hydroxyapatite (HA) and implanted in rat tibiae for a period of 28 days. Ex vivo resections were performed to analyze osseointegration, along with histological analysis, Scanning Electron Microscopy with Energy Dispersive X-Ray spectroscopy (SEM-EDX) line scanning, radiography and biomechanical testing.

Results

Given that the process of implant integration needs with the bone tissue to be accelerated, it was then seen that BG acted to start the rapid integration, and HA acted to sustaining the process.

Conclusions

Inert materials coated with bioglass and HA present a potential for application as bone substitutes, preferably with pores of diameters between 100 μm and 400 μm and, restrict for smaller than 100 μm, because it prevents pores without organized tissue formation or vacant. Designed as functional gradient material, stand out for applications in bone tissue under load, where, being the porous surface responsible for the osseointegration and the inner material to bear and to transmit the loads.
First-Principles Calculation of Adsorption of Shale Gas on CaCO3 (100) Surfaces
Authors: Luo Qiang , Pan Yikun , Guo Ping , Wang Zhouhua , Wei Na , Sun Pengfei , Liu Yuxiao
Published: June 2017

Background

To demonstrate the adsorption strength of shale gas to calcium carbonate in shale matrix, the adsorption of shale gas on CaCO3 (100) surfaces was studied using the first-principles method, which is based on the density functional theory (DFT).

Methods

The structures and electronic properties of CH4, C2H6, CO2 and N2 molecules were calculated by the generalized gradient approximation (GGA), for a coverage of 1 monolayer (ML). Under the same conditions, the density of states (DOS) of CaCO3 (100) surfaces before and after the adsorption of shale gas molecules at high-symmetry adsorption sites were compared.

Results

The results showed that the adsorption energies of CH4, C2H6, CO2 and N2 on CaCO3 (100) surfaces were between 0.2683 eV and -0.7388 eV. When a CH4 molecule was adsorbed at a hollow site and its 2 hydrogen atoms were parallel to the long diagonal (H3) on the CaCO3 (100) surface, it had the most stable adsorption, and the adsorption energy was only -0.4160 eV. The change of adsorption energy of CH4 was no more than 0.0535 eV. Compared with the DOS distribution of CH4 before adsorption, it shifted to the left overall after adsorption. At the same time, the partial density of states (PDOS) curves of CaCO3 (100) surfaces before and after adsorption basically overlapped.

Conclusions

This work showed that the adsorption effect of shale gas on calcium carbonate is very weak, and the adsorption is physisorption at the molecular level.
Retrospective Evaluation of Healing of Periapical Lesions after Unintentional Extrusion of Mineral Trioxide Aggregate
Authors: Demiriz Levent , Bodrumlu Ebru Hazar
Published: June 2017

Background

During the apexification procedure for teeth with open apices, mineral trioxide aggregate (MTA) may be unintentionally extruded. The aim of the present study was the retrospective evaluation of the healing of periapical lesions in permanent incisor teeth with open apices after the unintentional extrusion of MTA.

Methods

The clinical and radiographic records of 55 maxillary permanent central teeth treated by MTA apexification were evaluated. Filled teeth with unintentionally extruded MTA were selected as group 1 (n = 21), whereas the teeth with no MTA extrusion were selected as group 2 (n = 34). For each tooth, the clinical and radiographic records from a 3-year follow-up were investigated.

Results

Complete healing (CH) was observed in 19 teeth (90.4%) in group 1, whereas the same type of healing was observed in all 34 teeth (100%) in group 2 (p>0.05). At the 6-month follow-up appointment, 25 teeth (73.5%) showed CH in group 2, whereas 15 teeth (71.4%) showed CH at the 1-year follow-up in group 1 (p<0.001). At the end of the 3-year follow-up period, the amount of MTA extrusion was reduced in 17 teeth (85%) (p<0.05), whereas it was almost absent in 2 teeth (10%).

Conclusions

The unintentional extrusion of MTA does not prevent the healing of periapical lesions, but may be a delaying factor for periapical healing.
Characterization of an Improved 1-3 Piezoelectric Composite by Simulation and Experiment
Authors: Zhong Chao , Wang Likun , Qin Lei , Zhang Yanjun
Published: June 2017

Introduction

To increase electromechanical coupling factor of 1-3 piezoelectric composite and reduce its bending deformation under external stress, an improved 1-3 piezoelectric composite is developed. In the improved structure, both epoxy resin and silicone rubber are used as polymer material.

Methods

The simulation model of the improved 1-3 piezoelectric composite was established using the finite element software ANSYS. The relationship of the performance of the improved composite to the volume percentage of silicone rubber was determined by harmonic response analysis and the bending deformation under external stress was simulated by static analysis. The improved composite samples were prepared by cutting and filling methods, and the performance was tested.

Results

The feasibility of the improved structure was verified by finite element simulation and experiment. The electromechanical coupling factor of the improved composite can reach 0.67 and meanwhile the characteristic impedance can decline to 13 MRayl. The electromechanical coupling factor of the improved composite is higher than that of the composite with only epoxy resin as the polymer and the improved composite can reduce bending deformation.

Discussion

Comparison of simulation and experiment, the results of the experiment are in general agreement with those from the simulation. However, most experimental values were higher than the simulation results, and the abnormality of the test results was also more obvious than that of the simulation. These findings may be attributed to slight difference in the material parameters of simulation and experiment.
Endometrial Stromal Sarcoma Arising from Endometriosis
Authors: Cosentino Francesco , Turco Luigi C. , Ferrandina Gabriella , Fagotti Anna , Alletti Salvatore Gueli , Cianci Stefano , Vizzielli Giuseppe , Vargiu Virginia , Scambia Giovanni
Published: June 2017

The malignant transformation of endometriosis is a very uncommon event but can occur in 0.7% to 1% of all cases. Any histological type of tumor found in the endometrium might also occur in endometriosis. Most malignant tumors that originate from endometriosis are endometrioid adenocarcinomas and also clear-cell type carcinomas. On the other hand, sarcomas, especially endometrial stromal sarcoma (ESS), are extremely unusual representing 12% of all cases. ESS is an uncommon neoplasm and accounts for 0.2% of the uterine malignances. Malignant tumors arising from endometriosis can derive from the uterine wall as well as from extra-uterine sites. The most frequent extrauterine location is the ovary (78.7%), followed by the pelvic peritoneum (5.7%), the rectovaginal septum (4.3%), the colon (4.3%) and the vagina (2%), representing the majority of extragonadal sites. ESSs arising from the extrauterine and extraovarian endometriosis sites in the absence of a primary uterine lesion are extremely rare and the treatment options are not clear. Surgical debulking seems to be the best treatment. Adjuvant therapy, such as radiation, hormonal therapy and chemotherapy are not yet proven to be effective. Molecular target therapy could be a future possibility of treatment.

A systematic review of English Medical Literature about incidence, treatment and prognosis of extrauterine ESS arising from endometriosis foci was performed. The selected articles on which this review is based are the following: 9 literature reviews, 8 retrospective studies, 7 case series, 1 prospective trial and 11 case reports.
The Critical Need for Accurately Defining Digital Ulcers in Scleroderma
Authors: Li Wendy , Frech Tracy M.
Published: June 2017

Digital ulcers are one of the key predictors of disease progression and quality of life in patients with systemic sclerosis. Choosing the right treatment for the individual patient begins at developing a consensus among clinicians of what constitutes a digital ulcer. The aim of this editorial is to describe the high unmet need for a standardized method of defining digital ulcers, which is a major challenge not only for treatment, but also for development of new therapies. We discuss the potential role of ultrasound in the development of a validated definition of digital ulcers in systemic sclerosis.
Early Accrual of Organ Damage in Systemic Sclerosis: Rationale for Development of a Disease Damage Index
Authors: Tay Tien , Huq Molla , Ferdowsi Nava , Stevens Wendy , Sahhar Joanne , Ngian Gene-Siew , Roddy Janet , Zochling Jane , Walker Jenny , Proudman Susanna M , Nikpour Mandana
Published: June 2017

Introduction

Systemic sclerosis (SSc) is characterized by irreversible organ damage rather than fluctuating disease activity. However, there is no validated measure of damage in SSc. We aimed to quantify the accrual of organ damage in patients with early SSc.

Methods

Patients enrolled in the Australian Scleroderma Cohort Study with less than 2 years of SSc since the onset of the first non-Raynaud's symptom were included. Organ damage was defined by a group of six experts as substantial and permanent loss of organ function due to SSc.

Results

We identified 278 patients with early SSc. Among these, 38% had diffuse SSc. Damage was more common in the diffuse than in the limited disease subtype in the skin/musculoskeletal (75% vs. 25.2%, p<0.001) and lung (31.4% vs. 19.9%, p = 0.035) domains at year seven. The rates of damage accrual were highest in the skin/musculoskeletal, gastrointestinal and respiratory systems at year two (29.1%, 18.7%, 14.4%), increasing at year five (41.4%, 30.6%, 21.2%) and declining thereafter to year seven (43.9%, 32.7%, 23.0%). In particular, there was early accrual of damage due to joint contracture (22.3%), gastrointestinal dysmotility (11.5%) and pulmonary fibrosis with forced vital capacity <70% predicted (9.7%) at year two. The highest accrual rate of organ-specific damage from years two to seven was seen in fecal incontinence followed by proximal muscle weakness and pulmonary fibrosis.

Conclusions

Substantial accrual of organ damage occurs early in the course of disease, particularly in diffuse SSc. This provides the rationale for the development of a SSc damage index.