The AGN dusty torus as a clumpy two-phase medium: radiative transfer modeling with SKIRT

We modeled the AGN dusty torus as a clumpy two-phase medium, with high-density clumps embedded in a low-density interclump dust. To obtain spectral energy distributions and images of the torus at different wavelengths, we employed the 3D Monte Carlo radiative transfer code SKIRT. Apart from the grid of two-phase models, we calculated the corresponding sets of clumps-only models and models with a smooth dust distribution for comparison. We found that the most striking feature of the two-phase model is that it might offer a natural solution to the common issue reported in a number of papers -- the observed excess of the near-infrared emission.Comment: Proceedings of the Torus Workshop 2012 held at the University of Texas at San Antonio, 5-7 December 2012. C. Packham, R. Mason, and A. Alonso-Herrero (eds.). 8 pages, 5 figures. A grid of model SEDs available at https://sites.google.com/site/skirtorus

AGN Dusty Tori as a Clumpy Two-Phase Medium: The 10 Micron Silicate Feature

We investigated the emission of active galactic nuclei dusty tori in the infrared domain, with a focus on the 10 micron silicate feature. We modeled the dusty torus as a clumpy two-phase medium with high-density clumps and a low-density medium filling the space between the clumps. We employed a three-dimensional radiative transfer code to obtain spectral energy distributions and images of tori at different wavelengths. We calculated a grid of models for different parameters and analyzed the influence of these parameters on the shape of the mid-infrared emission. A corresponding set of clumps-only models and models with a smooth dust distribution is calculated for comparison. We found that the dust distribution, the optical depth and a random arrangement of clumps in the innermost region, all have an impact on the shape and strength of the silicate feature. The 10 micron silicate feature can be suppressed for some parameters, but models with smooth dust distribution are also able to produce a wide range of the silicate feature strength.Comment: 5 pages, 2 figures. Proceedings of the "8th Serbian Conference on Spectral Line Shapes in Astrophysics", Divcibare, Serbia, June 6-10 2011. Model SEDs available for download at https://sites.google.com/site/skirtorus

Spectral-spatial classification of hyperspectral images: three tricks and a new supervised learning setting

Spectral-spatial classification of hyperspectral images has been the subject of many studies in recent years. In the presence of only very few labeled pixels, this task becomes challenging. In this paper we address the following two research questions: 1) Can a simple neural network with just a single hidden layer achieve state of the art performance in the presence of few labeled pixels? 2) How is the performance of hyperspectral image classification methods affected when using disjoint train and test sets? We give a positive answer to the first question by using three tricks within a very basic shallow Convolutional Neural Network (CNN) architecture: a tailored loss function, and smooth- and label-based data augmentation. The tailored loss function enforces that neighborhood wavelengths have similar contributions to the features generated during training. A new label-based technique here proposed favors selection of pixels in smaller classes, which is beneficial in the presence of very few labeled pixels and skewed class distributions. To address the second question, we introduce a new sampling procedure to generate disjoint train and test set. Then the train set is used to obtain the CNN model, which is then applied to pixels in the test set to estimate their labels. We assess the efficacy of the simple neural network method on five publicly available hyperspectral images. On these images our method significantly outperforms considered baselines. Notably, with just 1% of labeled pixels per class, on these datasets our method achieves an accuracy that goes from 86.42% (challenging dataset) to 99.52% (easy dataset). Furthermore we show that the simple neural network method improves over other baselines in the new challenging supervised setting. Our analysis substantiates the highly beneficial effect of using the entire image (so train and test data) for constructing a model.Comment: Remote Sensing 201

Effective description of the short-time dynamics in open quantum systems

We address the dynamics of a bosonic system coupled to either a bosonic or a magnetic environment, and derive a set of sufficient conditions that allow one to describe the dynamics in terms of the effective interaction with a classical fluctuating field. We find that for short interaction times the dynamics of the open system is described by a Gaussian noise map for several different interaction models and independently on the temperature of the environment. In order to go beyond a qualitative understanding of the origin and physical meaning of the above short-time constraint, we take a general viewpoint and, based on an algebraic approach, suggest that any quantum environment can be described by classical fields whenever global symmetries lead to the definition of environmental operators that remain well defined when increasing the size, i.e. the number of dynamical variables, of the environment. In the case of the bosonic environment this statement is exactly demonstrated via a constructive procedure that explicitly shows why a large number of environmental dynamical variables and, necessarily, global symmetries, entail the set of conditions derived in the first part of the work.Comment: 9 pages, close to published versio

A MILP algorithm for the optimal sizing of an off-grid hybrid renewable energy system in South Tyrol

The exploitation of renewable energy sources through sustainable energy technologies are taking the field to decrease the pollutions' emissions into the Earth's environment. To offset the limitations of such resources, hybrid energy systems are becoming fundamental in grid-connected applications as well as in off-grid ones. However, the unsteady behavior of renewable sources, such as Sun and Wind, complicates the prediction of the energy production's trend. The main factors and components involved in the design of hybrid energy systems are: (i) type of generators, (ii) their optimal number, (iii) storage systems and (iv) optimal management strategies. All of them have to be considered simultaneously to develop the optimal solution aimed at either reducing the dependence from fossil fuels or granting the supply of energy. In this paper, a methodology based on the Mixed Integer Linear Programming (MILP) is presented and adopted to meet the electric demand of a mountain lodge located in a remote area in South-Tyrol (Italy). The methodology has been developed implementing an algorithm through the Matlab ©software. The algorithm is capable of evaluating the optimal size of a hybrid off-grid Solar–Wind system with battery storage in order to replace an Internal Combustion Engine (ICE) fueled by diesel. Keywords: Hybrid off-grid energy system, Mixed integer linear programming, Matlab©, Optimization algorithm, Renewable energ

Robots for Exploration, Digital Preservation and Visualization of Archeological Sites

Monitoring and conservation of archaeological sites are important activities necessary to prevent damage or to perform restoration on cultural heritage. Standard techniques, like mapping and digitizing, are typically used to document the status of such sites. While these task are normally accomplished manually by humans, this is not possible when dealing with hard-to-access areas. For example, due to the possibility of structural collapses, underground tunnels like catacombs are considered highly unstable environments. Moreover, they are full of radioactive gas radon that limits the presence of people only for few minutes. The progress recently made in the artificial intelligence and robotics field opened new possibilities for mobile robots to be used in locations where humans are not allowed to enter. The ROVINA project aims at developing autonomous mobile robots to make faster, cheaper and safer the monitoring of archaeological sites. ROVINA will be evaluated on the catacombs of Priscilla (in Rome) and S. Gennaro (in Naples)

Optimal path shape for range-only underwater target localization using a Wave Glider

Underwater localization using acoustic signals is one of the main components in a navigation system for an autonomous underwater vehicle (AUV) as a more accurate alternative to dead-reckoning techniques. Although different methods based on the idea of multiple beacons have been studied, other approaches use only one beacon, which reduces the system’s costs and deployment complexity. The inverse approach for single-beacon navigation is to use this method for target localization by an underwater or surface vehicle. In this paper, a method of range-only target localization using a Wave Glider is presented, for which simulations and sea tests have been conducted to determine optimal parameters to minimize acoustic energy use and search time, and to maximize location accuracy and precision. Finally, a field mission is presented, where a Benthic Rover (an autonomous seafloor vehicle) is localized and tracked using minimal human intervention. This mission shows, as an example, the power of using autonomous vehicles in collaboration for oceanographic research.Peer ReviewedPostprint (author's final draft

Fabrication and characterisation of short fibre reinforced elastomer composites for bending and twisting magnetic actuation

Polydimethylsiloxane (PDMS) films reinforced with short Nickel-coated Carbon Fibres (NiCF) were successfully fabricated, with the fibres aligned along different directions using an external magnetic field. The fibres were dispersed in the host matrix using sonication and mechanical mixing before being cured for 48 h in the magnetic field; thanks to the nickel functionalisation, the fibre orientation was achieved by a low intensity field (<0.2 T) which required an inexpensive experimental set-up. The main focus of this study was looking at the actuation potential of this magnetic composite material; successful actuation was achieved, showing its large displacement capability. The results confirm the presence of an instability controlled by the magnetic torque, as predicted by the introduced model. The composite films undergo a transition from a bending-only deformed configuration for the 0° fibre specimen, to a twisting-only configuration, achieved for fibres at 90°, whereas all the intermediate angles show both bending and twisting. This behaviour mirrors that which is used to propel a selection of marine mammals