Semi-Automated 3D Registration for Heterogeneous Unmanned Robots Based on Scale Invariant Method

This paper addresses the problem of 3D registration of outdoor environments combining heterogeneous datasets acquired from unmanned aerial (UAV) and ground (UGV) vehicles. In order to solve this problem, we introduced a novel Scale Invariant Registration Method (SIRM) for semi-automated registration of 3D point clouds. The method is capable of coping with an arbitrary scale difference between the point clouds, without any information about their initial position and orientation. Furthermore, the SIRM does not require having a good initial overlap between two heterogeneous datasets. Our method strikes an elegant balance between the existing fully automated 3D registration systems (which often fail in the case of heterogeneous datasets and harsh outdoor environments) and fully manual registration approaches (which are labour-intensive). The experimental validation of the proposed 3D heterogeneous registration system was performed on large-scale datasets representing unstructured and harsh outdoor environments, demonstrating the potential and benefits of the proposed 3D registration system in real-world environments

3D registration and integrated segmentation framework for heterogeneous unmanned robotic systems

The paper proposes a novel framework for registering and segmenting 3D point clouds of large-scale natural terrain and complex environments coming from a multisensor heterogeneous robotics system, consisting of unmanned aerial and ground vehicles. This framework involves data acquisition and pre-processing, 3D heterogeneous registration and integrated multi-sensor based segmentation modules. The first module provides robust and accurate homogeneous registrations of 3D environmental models based on sensors' measurements acquired from the ground (UGV) and aerial (UAV) robots. For 3D UGV registration, we proposed a novel local minima escape ICP (LME-ICP) method, which is based on the well known iterative closest point (ICP) algorithm extending it by the introduction of our local minima estimation and local minima escape mechanisms. It did not require any prior known pose estimation information acquired from sensing systems like odometry, global positioning system (GPS), or inertial measurement units (IMU). The 3D UAV registration has been performed using the Structure from Motion (SfM) approach. In order to improve and speed up the process of outliers removal for large-scale outdoor environments, we introduced the Fast Cluster Statistical Outlier Removal (FCSOR) method. This method was used to filter out the noise and to downsample the input data, which will spare computational and memory resources for further processing steps. Then, we co-registered a point cloud acquired from a laser ranger (UGV) and a point cloud generated from images (UAV) generated by the SfM method. The 3D heterogeneous module consists of a semi-automated 3D scan registration system, developed with the aim to overcome the shortcomings of the existing fully automated 3D registration approaches. This semi-automated registration system is based on the novel Scale Invariant Registration Method (SIRM). The SIRM provides the initial scaling between two heterogenous point clouds and provides an adaptive mechanism for tuning the mean scale, based on the difference between two consecutive estimated point clouds' alignment error values. Once aligned, the resulting homogeneous ground-aerial point cloud is further processed by a segmentation module. For this purpose, we have proposed a system for integrated multi-sensor based segmentation of 3D point clouds. This system followed a two steps sequence: ground-object segmentation and color-based region-growing segmentation. The experimental validation of the proposed 3D heterogeneous registration and integrated segmentation framework was performed on large-scale datasets representing unstructured outdoor environments, demonstrating the potential and benefits of the proposed semi-automated 3D registration system in real-world environments

Fast Statistical Outlier Removal Based Method for Large 3D Point Clouds of Outdoor Environments

This paper proposes a very effective method for data handling and preparation of the input 3D scans acquired from laser scanner mounted on the Unmanned Ground Vehicle (UGV). The main objectives are to improve and speed up the process of outliers removal for large-scale outdoor environments. This process is necessary in order to filter out the noise and to downsample the input data which will spare computational and memory resources for further processing steps, such as 3D mapping of rough terrain and unstructured environments. It includes the Voxel-subsampling and Fast Cluster Statistical Outlier Removal (FCSOR) subprocesses. The introduced FCSOR represents an extension on the Statistical Outliers Removal (SOR) method which is effective for both homogeneous and heterogeneous point clouds. This method is evaluated on real data obtained in outdoor environment

Fast Iterative 3D Mapping for Large-Scale Outdoor Environments with Local Minima Escape Mechanism

This paper introduces a novel iterative 3D mapping framework for large scale natural terrain and complex environments. The framework is based on an Iterative-Closest-Point (ICP) algorithm and an iterative error minimization mechanism, allowing robust 3D map registration. This was accomplished by performing pairwise scan registrations without any prior known pose estimation information and taking into account the measurement uncertainties due to the 6D coordinates (translation and rotation) deviations in the acquired scans. Since the ICP algorithm does not guarantee to escape from local minima during the mapping, new algorithms for the local minima estimation and local minima escape process were proposed. The proposed framework is validated using large scale field test data sets. The experimental results were compared with those of standard, generalized and non-linear ICP registration methods and the performance evaluation is presented, showing improved performance of the proposed 3D mapping framework

Tumors of the labial mucosa:a retrospective study of 1045 biopsies

To investigate the relative frequency of localized mucosal swellings of the upper and lower labial mucosa, the clinical-pathological diagnosis agreement and whether patient?s age and gender and tumor?s site and size may raise the suspicion of neoplasm. Retrospective analysis was performed on upper or lower labial mucosal tumors, histopathologically diagnosed between 2009-2018. The diagnostic categories developmental/reactive tumors, benign and malignant neoplasms were associated with patient?s age and gender and tumor?s site and size; clinical-pathological diagnosis agreement was, also, evaluated. Overall, 1000 (95.7%) developmental/reactive tumors, 35 (3.3%) benign and 10 (1%) malignant neoplasms were found. Upper/lower lip tumor ratio was 0.14:1. The diagnostic category was significantly associated with age (p1cm were independent predictors for neoplasms. Patients presenting 2 or 3 of these variables were 20.2 times (p?1cm in patients?60 years have significantly higher probability to be neoplasms

Adaptation and evaluation of the bottle assay for monitoring insecticide resistance in disease vector mosquitoes in the Peruvian Amazon

<p>Abstract</p> <p>Background</p> <p>The purpose of this study was to establish whether the "bottle assay", a tool for monitoring insecticide resistance in mosquitoes, can complement and augment the capabilities of the established WHO assay, particularly in resource-poor, logistically challenging environments.</p> <p>Methods</p> <p>Laboratory reared <it>Aedes aegypti </it>and field collected <it>Anopheles darlingi </it>and <it>Anopheles albimanus </it>were used to assess the suitability of locally sourced solvents and formulated insecticides for use with the bottle assay. Using these adapted protocols, the ability of the bottle assay and the WHO assay to discriminate between deltamethrin-resistant <it>Anopheles albimanus </it>populations was compared. The diagnostic dose of deltamethrin that would identify resistance in currently susceptible populations of <it>An. darlingi </it>and <it>Ae. aegypti </it>was defined. The robustness of the bottle assay during a surveillance exercise in the Amazon was assessed.</p> <p>Results</p> <p>The bottle assay (using technical or formulated material) and the WHO assay were equally able to differentiate deltamethrin-resistant and susceptible <it>An. albimanus </it>populations. A diagnostic dose of 10 μg a.i./bottle was identified as the most sensitive discriminating dose for characterizing resistance in <it>An. darlingi </it>and <it>Ae. aegypti</it>. Treated bottles, prepared using locally sourced solvents and insecticide formulations, can be stored for > 14 days and used three times. Bottles can be stored and transported under local conditions and field-assays can be completed in a single evening.</p> <p>Conclusion</p> <p>The flexible and portable nature of the bottle assay and the ready availability of its components make it a potentially robust and useful tool for monitoring insecticide resistance and efficacy in remote areas that require minimal cost tools.</p

The Fate of Foodborne Pathogens in Manure Treated Soil

Publication history: Accepted - 22 November 2021; Published online - 10 December 2021.The aim of this review was to provide an update on the complex relationship between manure application, altered pathogen levels and antibiotic resistance. This is necessary to protect health and improve the sustainability of this major farming practice in agricultural systems based on high levels of manure production. It is important to consider soil health in relation to environment and land management practices in the context of the soil microflora and the introduction of pathogens on the health of the soil microbiome. Viable pathogens in manure spread on agricultural land may be distributed by leaching, surface run-off, water source contamination and contaminated crop removal. Thus it is important to understand how multiple pathogens can persist in manures and on soil at farm-scale and how crops produced under these conditions could be a potential transfer route for zoonotic pathogens. The management of pathogen load within livestock manure is a potential mechanism for the reduction and prevention of outbreaks infection with Escherichia coli, Listeria Salmonella, and Campylobacter. The ability of Campylobacter, E. coli, Listeria and Salmonella to combat environmental stress coupled with their survival on food crops and vegetables postharvest emphasizes the need for further study of these pathogens along with the emerging pathogen Providencia given its link to disease in the immunocompromised and its’ high levels of antibiotic resistance. The management of pathogen load within livestock manure has been widely recognized as a potential mechanism for the reduction and prevention of outbreaks infection but any studies undertaken should be considered as region specific due to the variable nature of the factors influencing pathogen content and survival in manures and soil. Mediocre soils that require nutrients could be one template for research on manure inputs and their influence on soil health and on pathogen survival on grassland and in food crops.This work was funded by the Department of Agriculture, Environment and Rural Affairs (DAERA); https://www.daera-ni.gov.uk) as part of the DAERA Postgraduate Studentship Programme and by the DAERA Evidence and Innovation project 18/1/21: Evaluating the impact of a range of organic manures applied to arable land on soil, crop and NI agriculture

Scenarios for the Development of Smart Grids in the UK: Literature Review

This Working Paper reviews the existing literature on the socio-technical aspects of smart grid development. This work was undertaken as part of the Scenarios for the Development of Smart Grids in the UK project

Scenarios for the Development of Smart Grids in the UK: Synthesis Report

Building on extensive expert feedback and input, this Research Report describes four smart grid scenarios which consider how the UK' electricity system might develop to 2050. The scenarios outline how political decisions, as well as those made in regulation, finance, technology, consumer and social behaviour, market design or response, might affect the decisions of other actors and limit or allow the availability of future options

Rapid generation of endogenously driven transcriptional reporters in cells through CRISPR/Cas9

CRISPR/Cas9 technologies have been employed for genome editing to achieve gene knockouts and knock-ins in somatic cells. Similarly, certain endogenous genes have been tagged with fluorescent proteins. Often, the detection of tagged proteins requires high expression and sophisticated tools such as confocal microscopy and flow cytometry. Therefore, a simple, sensitive and robust transcriptional reporter system driven by endogenous promoter for studies into transcriptional regulation is desirable. We report a CRISPR/Cas9-based methodology for rapidly integrating a firefly luciferase gene in somatic cells under the control of endogenous promoter, using the TGFβ-responsive gene PAI-1. Our strategy employed a polycistronic cassette containing a non-fused GFP protein to ensure the detection of transgene delivery and rapid isolation of positive clones. We demonstrate that firefly luciferase cDNA can be efficiently delivered downstream of the promoter of the TGFβ-responsive gene PAI-1. Using chemical and genetic regulators of TGFβ signalling, we show that it mimics the transcriptional regulation of endogenous PAI-1 expression. Our unique approach has the potential to expedite studies on transcription of any gene in the context of its native chromatin landscape in somatic cells, allowing for robust high-throughput chemical and genetic screens