An efficient algorithm for line extraction from laser scans

In this paper, an algorithm for extracting line segments from information gathered by a laser rangefinder is presented. The range scan is processed to compute a parameter that is invariant to the position and orientation of straight lines present. This parameter is then used to identify observations that potentially belong to straight lines and compute the slope of these lines. Log-Hough transform, that only explores a small region of the Hough space identified by the slopes computed, is then used to find the equations of the lines present. The proposed method thus combines robustness of the Hough transform technique with the inherent efficiency of line fitting strategies while carrying out all computation in the sensor coordinate frame yielding a fast and robust algorithm for line extraction from laser range scans. Two practical examples are presented to demonstrate the efficacy of the algorithm and compare its performance to the traditional techniques

Diamondoid naphthenic acids cause in vivo genetic damage in gills and haemocytes of marine mussels

Diamondoids are polycyclic saturated hydrocarbons that possess a cage-like carbon skeleton approaching that of diamond. These ‘nano-diamonds’ are used in a range of industries including nanotechnologies and biomedicine. Diamondoids were thought to be highly resistant to degradation, but their presumed degradation acid products have now been found in oil sands process-affected waters (OSPW) and numerous crude oils. Recently, a diamondoid-related structure, 3-noradamantane carboxylic acid, was reported to cause genetic damage in trout hepatocytes under in vitro conditions. This particular compound has never been reported in the environment but led us to hypothesise that other more environmentally relevant diamondoid acids could also be genotoxic. We carried out in vivo exposures (3 days, semi-static) of marine mussels to two environmentally relevant diamondoid acids, 1-adamantane carboxylic acid and 3,5-dimethyladamantane carboxylic acid plus 3-noradamantane carboxylic acid with genotoxic damage assessed using the Comet assay. An initial screening test confirmed that these acids displayed varying degrees of genotoxicity to haemocytes (increased DNA damage above that of controls) when exposed in vivo to a concentration of 30 μmol L−1. In a further test focused on 1-adamantane carboxylic acid with varying concentrations (0.6, 6 and 30 μmol L−1), significant (P < 0.05 %) DNA damage was observed in different target cells (viz. gills and haemocytes) at 0.6 μmol L−1. Such a level of induced genetic damage was similar to that observed following exposure to a known genotoxin, benzo(a)pyrene (exposure concentration, 0.8 μmol L−1). These findings may have implications for a range of worldwide industries including oil extraction, nanotechnology and biomedicine

Accurate large-scale bearing-only SLAM by map joining

This paper presents a bearing-only SLAM algorithm that generates accurate and consistent maps of large environments by joining a series of small local maps. The local maps are built by least squares optimization with a proper landmark initialization technique. The local maps are then combined to build global map using Iterated Sparse Local Submap Joining Filter (I-SLSJF). The accuracy and consistency of the proposed algorithm is evaluated using simulation data sets. The algorithm is also tested using the DLR-Spatial-Cognition data set and the preprocessed Victoria Park data where the range information is ignored. The global map results are very similar to the result of full least squares optimization starting with very accurate initial values. As I-SLSJF is able to join a given set of local maps and associated uncertainties efficiently without any information loss, these results demonstrate that focusing on generating accurate local maps is a promising direction for solving large-scale bearing-only SLAM problems

Sensor registration for robotic applications

Multi-sensor data fusion plays an essential role in most robotic applications. Appropriate registration of information from different sensors is a fundamental requirement in multi-sensor data fusion. Registration requires significant effort particularly when sensor signals do not have direct geometric interpretations, observer dynamics are unknown and occlusions are present. In this paper, we propose Mutual Information (MI) based sensor registration which exploits the effect of a common cause in the observed space on the sensor outputs that does not require any prior knowledge of relative poses of the observers. Simulation results are presented to substantiate the claim that the algorithm is capable of registering the sensors in the presence of substantial observer dynamics. © 2008 Springer-Verlag Berlin Heidelberg

Mutual information based data association

Relating information originating from disparate sensors without any attempt to model the environment or the behaviour of any particular object within it is a challenging task. Inspired by human perception, the focus of this paper will be on observing objects moving in space using sensors that operate based on different physical principles and the fact that motion has in principle, greater power to specify properties of an object than purely spatial information captured as a single observation in time. The contribution of this paper include the development of a novel strategy for detecting a set of signals that are statistically dependent and correspond to each other related by a common cause. Mutual Information is proposed as a measure of statistical dependence. The algorithm is evaluated through simulations and three application domains, which includes, (1.) Grouping problem in images, (2.) Data association problem in moving observers with dynamic targets, and (3.) Multi-modal sensor fusion. © 2009 IEEE

Rapid diagnostic tests for plague

Background Plague is a severe disease associated with high mortality. Late diagnosis leads to advance stage of the disease with worse outcomes and higher risk of spread of the disease. A rapid diagnostic test (RDT) could help in establishing a prompt diagnosis of plague. This would improve patient care and help appropriate public health response. Objectives To determine the diagnostic accuracy of the RDT based on the antigen F1 (F1RDT) for detecting plague in people with suspected disease. Search methods We searched the CENTRAL, Embase, Science Citation Index, Google Scholar, the World Health Organization International Clinical Trials Registry Platform and ClinicalTrials.gov up to 15 May 2019, and PubMed (MEDLINE) up to 27 August 2019, regardless of language, publication status, or publication date. We handsearched the reference lists of relevant papers and contacted researchers working in the field. Selection criteria We included cross‐sectional studies that assessed the accuracy of the F1RDT for diagnosing plague, where participants were tested with both the F1RDT and at least one reference standard. The reference standards were bacterial isolation by culture, polymerase chain reaction (PCR), and paired serology (this is a four‐fold difference in F1 antibody titres between two samples from acute and convalescent phases). Data collection and analysis Two review authors independently selected studies and extracted data. We appraised the methodological quality of each selected studies and applicability by using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS‐2) tool. When meta‐analysis was appropriate, we used the bivariate model to obtain pooled estimates of sensitivity and specificity. We stratified all analyses by the reference standard used and presented disaggregated data for forms of plague. We assessed the certainty of the evidence using GRADE. Main results We included eight manuscripts reporting seven studies. Studies were conducted in three countries in Africa among adults and children with any form of plague. All studies except one assessed the F1RDT produced at the Institut Pasteur of Madagascar (F1RDT‐IPM) and one study assessed a F1RDT produced by New Horizons (F1RDT‐NH), utilized by the US Centers for Disease Control and Prevention. We could not pool the findings from the F1RDT‐NH in meta‐analyses due to a lack of raw data and a threshold of the test for positivity different from the F1RDT‐IPM. Risk of bias was high for participant selection (retrospective studies, recruitment of participants not consecutive or random, unclear exclusion criteria), low or unclear for index test (blinding of F1RDT interpretation unknown), low for reference standards, and high or unclear for flow and timing (time of sample transportation was longer than seven days, which can lead to decreased viability of the pathogen and overgrowth of contaminating bacteria, with subsequent false‐negative results and misclassification of the target condition). F1RDT for diagnosing all forms of plague F1RDT‐IPM pooled sensitivity against culture was 100% (95% confidence interval (CI) 82 to 100; 4 studies, 1692 participants; very low certainty evidence) and pooled specificity was 70.3% (95% CI 65 to 75; 4 studies, 2004 participants; very low‐certainty evidence). The performance of F1RDT‐IPM against PCR was calculated from a single study in participants with bubonic plague (see below). There were limited data on the performance of F1RDT against paired serology. F1RDT for diagnosing pneumonic plague Performed in sputum, F1RDT‐IPM pooled sensitivity against culture was 100% (95% CI 0 to 100; 2 studies, 56 participants; very low‐certainty evidence) and pooled specificity was 71% (95% CI 59 to 80; 2 studies, 297 participants; very low‐certainty evidence). There were limited data on the performance of F1RDT against PCR or against paired serology for diagnosing pneumonic plague. F1RDT for diagnosing bubonic plague Performed in bubo aspirate, F1RDT‐IPM pooled sensitivity against culture was 100% (95% CI not calculable; 2 studies, 1454 participants; low‐certainty evidence) and pooled specificity was 67% (95% CI 65 to 70; 2 studies, 1198 participants; very low‐certainty evidence). Performed in bubo aspirate, F1RDT‐IPM pooled sensitivity against PCR for the caf1 gene was 95% (95% CI 89 to 99; 1 study, 88 participants; very low‐certainty evidence) and pooled specificity was 93% (95% CI 84 to 98; 1 study, 61 participants; very low‐certainty evidence). There were no data providing data on both F1RDT and paired serology for diagnosing bubonic plague. Authors' conclusions Against culture, the F1RDT appeared highly sensitive for diagnosing either pneumonic or bubonic plague, and can help detect plague in remote areas to assure management and enable a public health response. False positive results mean culture or PCR confirmation may be needed. F1RDT does not replace culture, which provides additional information on resistance to antibiotics and bacterial strains

Integral models for bubble, droplet, and multiphase plume dynamics in stratification and crossflow

We present the development and validation of a numerical modeling suite for bubble and droplet dynamics of multiphase plumes in the environment. This modeling suite includes real-fluid equations of state, Lagrangian particle tracking, and two different integral plume models: an Eulerian model for a double-plume integral model in quiescent stratification and a Lagrangian integral model for multiphase plumes in stratified crossflows. Here, we report a particle tracking algorithm for dispersed-phase particles within the Lagrangian integral plume model and a comprehensive validation of the Lagrangian plume model for single- and multiphase buoyant jets. The model utilizes literature values for all entrainment and spreading coefficients and has one remaining calibration parameter (Formula presented.), which reduces the buoyant force of dispersed phase particles as they approach the edge of a Lagrangian plume element, eventually separating from the plume as it bends over in a crossflow. We report the calibrated form (Formula presented.), where b is the plume half-width, and r is the distance of a particle from the plume centerline. We apply the validated modeling suite to simulate two test cases of a subsea oil well blowout in a stratification-dominated crossflow. These tests confirm that errors from overlapping plume elements in the Lagrangian integral model during intrusion formation for a weak crossflow are negligible for predicting intrusion depth and the fate of oil droplets in the plume. The Lagrangian integral model has the added advantages of being able to account for entrainment from an arbitrary crossflow, predict the intrusion of small gas bubbles and oil droplets when appropriate, and track the pathways of individual bubbles and droplets after they separate from the main plume or intrusion layer