Magnetostatic vortices in two-dimensional abelian gauge theories

We study the existence of vortices of the Klein-Gordon-Maxwell equations in the two dimensional case. In particular we find sufficient conditions for the existence of vortices in the magneto-static case, i.e. when the electric potential phi = 0. This result, due to the lack of suitable embedding theorems for the vector potential A is achieved with the help of a penalization method

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

Review of the occurrence and management of <i>Sotalia</i> bycatch in Central and South American coastal and riverine fisheries: priorities for immediate action

Despite the fact that cetacean bycatch has been acknowledged as the “greatest immediate and well documented threat to the survival of cetacean species and populations… …progress at reducing the scale and conservation impact of cetacean bycatch has been slow, sporadic, and limited to a few specific fisheries or circumstances “. In this paper, we 1) Review the occurrence of Sotalia bycatch all along its distribution area, 2) Examine how the problem has been addressed in some areas and 3) Outline some priority actions for conservation of the genus regarding management of bycatch issues. A recent review of cetacean bycatch in the Wider Caribbean Region indicates that mortality of Sotalia in fisheries-related operations with gillnets occurs in Colombia, French Guyana, Honduras, Surinam and Venezuela. Bycatch is also reported in Brazil, Nicaragua and Peru. Some mitigative measures including a ban on fisheries in protected areas, monitoring programs and field surveys for evaluation of bycatch have been made or are planned in Costa Rica and Venezuela. In Brazil, bycatch of Sotalia has been widely documented in coastal areas and also in the Amazon River Basin. In this country, an official action plan for the conservation of aquatic mammals includes specific recommendations to evaluate the impact of bycatch and to develop mitigative measures. According to recent statistics, most of cetacean bycatch worldwide occurs in gillnet fisheries. A precautionary approach suggests that – to protect Sotalia and other cetacean populations-these fisheries should be either regulated, monitored, limited or -in some instances – banned, taking into account that creative solutions should be provided by means of collaborative efforts between resource managers, fishermen, scientists and interested parties. On the other side, because of the socioeconomic aspects involved in such a decision, appropriate alternatives and/or incentives as well as local characteristics of some fisheries must be properly considered

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

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 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

Multi-waypoint-based path planning for free-floating space robots

This paper studies the multi-waypoint-based path planning problem (MWPP) for redundant space robots. The end-effector of a space robot should visit a set of predefined waypoints with optimal distance, and the free-floating base should suffer minimum attitude disturbances from the manipulator during manoeuver. The MWPP is decomposed into two sub-problems: the problem of optimal waypoint-sequence and the problem of optimal joint-movements. First, the Hybrid Self-adaptive Particle Swarm Optimization algorithm is proposed for optimal waypoint-sequence. Second, an Improved Particle Swarm Optimization algorithm, combined with direct kinematics of the space robot, is proposed for optimal jointmovements. Finally, simulations are presented to validate the approach, including comparisons with other approaches

Synthesis and gas-sensing properties of pd-doped SnO2 nanocrystals. A case study of a general methodology for doping metal oxide nanocrystals

Pd-modified SnO2 nanocrystals, with a Pd/Sn nominal atomic ratio of 0.025, were prepared by injecting SnO2 sols and a Pd precursor solution into tetradecene and dodecylamine at 160 degrees C. Two different doping procedures were investigated: in co-injection, a Pd acetylacetonate solution in chloroform was mixed with the SnO2 sol before the injection; in sequential injection, the Pd solution was injected separately after the SnO2 sol. The obtained suspensions were heated at the resulting 80 degrees C temperature, then the product was collected by centrifugation and dried at 80 degrees C. When using co-injection, in the dried products PdO and Pd nanoparticles were observed by high-resolution transmission electron microscopy. Only SnO2 nanocrystals were observed in dried products prepared by sequential injection. After heat-treatment at 500 degrees C, no Pd species were observed for both doping procedures. Moreover, X-ray photoelectron spectroscopy showed that, in both the doping procedures, after heat-treatment Pd is distributed only into the SnO2 nanocrystal structure. This conclusion was reinforced by the measurement of the electrical properties of Pd-doped nanocrystals, showing a remarkable increase of the electrical resistance if compared with pure SnO2 nanocrystals. This result was interpreted as Pd insertion as a dopant inside the cassiterite lattice of tin dioxide. The addition of Pd resulted in a remarkable improvement of the gas-sensing properties, allowing the detection of carbon monoxide concentrations below 50 ppm and of very low concentrations (below 25 ppm) of other reducing gases such as ethanol and acetone