CB-norm estimates for maps between noncommutative Lp-spaces and quantum channel theory.

In the first part of this work, we show how certain techniques from quantum information theory can be used in order to obtain very sharp embeddings between noncommutative Lp-spaces. Then, we use these estimates to study the classical capacity with restricted assisted entanglement of the quantum erasure channel and the quantum depolarizing channel. In particular, we exactly compute the capacity of the first one and we show that certain nonmultiplicative results hold for the second one.

[C II] and 12^CO(1-0) emission maps in HLSJ091828.6+514223: a strongly lensed interacting system AT z = 5.24

We present Submillimeter Array [C II] 158 μm and Karl G. Jansky Very Large Array 12^CO(1-0) line emission maps for the bright, lensed, submillimeter source at z = 5.2430 behind A 773: HLSJ091828.6+514223 (HLS0918). We combine these measurements with previously reported line profiles, including multiple 12^CO rotational transitions, [C I], water, and [N II], providing some of the best constraints on the properties of the interstellar medium in a galaxy at z > 5. HLS0918 has a total far-infrared (FIR) luminosity L_FIR(8–1000 μm) = (1.6 ± 0.1) × 10^14 L_☉ μ^–1, where the total magnification μ_total = 8.9 ± 1.9, via a new lens model from the [C II] and continuum maps. Despite a HyLIRG luminosity, the FIR continuum shape resembles that of a local LIRG. We simultaneously fit all of the observed spectral line profiles, finding four components that correspond cleanly to discrete spatial structures identified in the maps. The two most redshifted spectral components occupy the nucleus of a massive galaxy, with a source-plane separation <1 kpc. The reddest dominates the continuum map (demagnified L_FIR, component = (1.1 ± 0.2) × 10^13 L_☉) and excites strong water emission in both nuclear components via a powerful FIR radiation field from the intense star formation. A third star-forming component is most likely a region of a merging companion (ΔV ~ 500 km s^–1) exhibiting generally similar gas properties. The bluest component originates from a spatially distinct region and photodissociation region analysis suggests that it is lower density, cooler, and forming stars less vigorously than the other components. Strikingly, it has very strong [N II] emission, which may suggest an ionized, molecular outflow. This comprehensive view of gas properties and morphology in HLS0918 previews the science possible for a large sample of high-redshift galaxies once ALMA attains full sensitivity.

Black maps/vivid waters : beauty and horror in David Maisel's The Lake Project and Terminal Mirage

"This paper examines The Lake Project and Terminal Mirage, the two components of David Maisel’s Black Maps series that concern water. Like the section of the Salt Lake chosen by Robert Smithson for his seminal Spiral Jetty, the alkaline waters Maisel photographs are subject to infestations of bacteria that that give them a visceral hue. Smithson provides a reference for this work; the artists are notable for their shared site, disorienting scale, and attraction to entropy"

Growing Neural Gas approach for obtaining homogeneous maps by restricting the insertion of new nodes

The Growing Neural Gas model is used widely in artificial neural networks. However, its application is limited in some contexts by the proliferation of nodes in dense areas of the input space. In this study, we introduce some modifications to address this problem by imposing three restrictions on the insertion of new nodes. Each restriction aims to maintain the homogeneous values of selected criteria. One criterion is related to the square error of classification and an alternative approach is proposed for avoiding additional computational costs. Three parameters are added that allow the regulation of the restriction criteria. The resulting algorithm allows models to be obtained that suit specific needs by specifying meaningful parameters.

Viability study of automobile shredder residue as fuel

Car Fluff samples collected from a shredding plant in Italy were classified based on particle size, and three different size fractions were obtained in this way. A comparison between these size fractions and the original light fluff was made from two different points of view: (i) the properties of each size fraction as a fuel were evaluated and (ii) the pollutants evolved when each size fraction was subjected to combustion were studied. The aim was to establish which size fraction would be the most suitable for the purposes of energy recovery. The light fluff analyzed contained up to 50 wt.% fines (particle size < 20 mm). However, its low calorific value and high emissions of polychlorinated dioxins and furans (PCDD/Fs), generated during combustion, make the fines fraction inappropriate for energy recovery, and therefore, landfilling would be the best option. The 50–100 mm fraction exhibited a high calorific value and low PCDD/F emissions were generated when the sample was combusted, making it the most suitable fraction for use as refuse-derived fuel (RDF). Results obtained suggest that removing fines from the original ASR sample would lead to a material product that is more suitable for use as RDF.

Gibbs Energy of Mixing Function: Topological Analysis in Azeotropic Systems

ESAT 2014. 27th European Symposium on Applied Thermodynamics, Eindhoven University of Technology, July 6-9, 2014.

3D Maps Representation Using GNG

Current RGB-D sensors provide a big amount of valuable information for mobile robotics tasks like 3D map reconstruction, but the storage and processing of the incremental data provided by the different sensors through time quickly become unmanageable. In this work, we focus on 3D maps representation and propose the use of the Growing Neural Gas (GNG) network as a model to represent 3D input data. GNG method is able to represent the input data with a desired amount of neurons or resolution while preserving the topology of the input space. Experiments show how GNG method yields a better input space adaptation than other state-of-the-art 3D map representation methods.

Feature selection by multi-objective optimisation: Application to network anomaly detection by hierarchical self-organising maps

Feature selection is an important and active issue in clustering and classification problems. By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus contributing to decreasing the classification computational complexity, and to improving the classifier performance by avoiding redundant or irrelevant features. Although feature selection can be formally defined as an optimisation problem with only one objective, that is, the classification accuracy obtained by using the selected feature subset, in recent years, some multi-objective approaches to this problem have been proposed. These either select features that not only improve the classification accuracy, but also the generalisation capability in case of supervised classifiers, or counterbalance the bias toward lower or higher numbers of features that present some methods used to validate the clustering/classification in case of unsupervised classifiers. The main contribution of this paper is a multi-objective approach for feature selection and its application to an unsupervised clustering procedure based on Growing Hierarchical Self-Organising Maps (GHSOMs) that includes a new method for unit labelling and efficient determination of the winning unit. In the network anomaly detection problem here considered, this multi-objective approach makes it possible not only to differentiate between normal and anomalous traffic but also among different anomalies. The efficiency of our proposals has been evaluated by using the well-known DARPA/NSL-KDD datasets that contain extracted features and labelled attacks from around 2 million connections. The selected feature sets computed in our experiments provide detection rates up to 99.8% with normal traffic and up to 99.6% with anomalous traffic, as well as accuracy values up to 99.12%.

Subsidence activity maps derived from DInSAR data: Orihuela case study

A new methodology is proposed to produce subsidence activity maps based on the geostatistical analysis of persistent scatterer interferometry (PSI) data. PSI displacement measurements are interpolated based on conditional Sequential Gaussian Simulation (SGS) to calculate multiple equiprobable realizations of subsidence. The result from this process is a series of interpolated subsidence values, with an estimation of the spatial variability and a confidence level on the interpolation. These maps complement the PSI displacement map, improving the identification of wide subsiding areas at a regional scale. At a local scale, they can be used to identify buildings susceptible to suffer subsidence related damages. In order to do so, it is necessary to calculate the maximum differential settlement and the maximum angular distortion for each building of the study area. Based on PSI-derived parameters those buildings in which the serviceability limit state has been exceeded, and where in situ forensic analysis should be made, can be automatically identified. This methodology has been tested in the city of Orihuela (SE Spain) for the study of historical buildings damaged during the last two decades by subsidence due to aquifer overexploitation. The qualitative evaluation of the results from the methodology carried out in buildings where damages have been reported shows a success rate of 100%.

Using causal maps to support ex-post assessment of social impacts of dams

This paper presents the results of an ex-post assessment of two important dams in Brazil. The study follows the principles of Social Impact Management, which offer a suitable framework for analyzing the complex social transformations triggered by hydroelectric dams. In the implementation of this approach, participative causal maps were used to identify the ex-post social impacts of the Porto Primavera and Rosana dams on the community of Porto Rico, located along the High Paraná River. We found that in the operation of dams there are intermediate causes of a political nature, stemming from decisions based on values and interests not determined by neutral, exclusively technical reasons; and this insight opens up an area of action for managing the negative impacts of dams.

Causal Maps and Indirect Influences Analysis in the Diagnosis of Second-Home Tourism Impacts

This paper proposes a method for diagnosing the impacts of second-home tourism and illustrates it for a Mediterranean Spanish destination. This method proposes the application of network analysis software to the analysis of causal maps in order to create a causal network model based on stakeholder-identified impacts. The main innovation is the analysis of indirect relations in causal maps for the identification of the most influential nodes in the model. The results show that the most influential nodes are of a political nature, which contradicts previous diagnoses identifying technical planning as the ultimate cause of problems.

Comparison Between Dcrit Considering the Abrupt Variation and Inflexion in the Concrete Mercury Intrusion Porosimetry Curve

Mercury intrusion porosimetry (MIP) has been widely used to evaluate the quality of concrete through the pore size distribution parameters. Two of these parameters are the critical pore diameter (Dcrit) and the percentage of the most interconnected net of pores compared to the total volume of pores. Some researchers consider Dcrit as the diameter obtained from the inflexion point of the cumulative mercury intrusion curve while others consider Dcrit as the diameter obtained from the point of abrupt variation in the same curve. This study aims to analyze two groups of concretes of varying w/c ratios, one cast with pozzolanic cement and another with high initial strength cement, in order to determine which of these diameters feature a better correlation with the quality parameters of the concretes. The concrete quality parameters used for the evaluations were (1) the w/c ratios and (2) chloride diffusion coefficients measured at approximately 90 days. MIP cumulative distributions of the same concretes were also measured at about 90 days, and Dcrit values were determined (1) from the point of abrupt variation and alternatively, (2) from the inflexion point of each of these plots. It was found that Dcrit values measured from the point of abrupt variation were useful indicators of the quality of the concrete, but the Dcrit values based on the inflexion points were not. Hence, it is recommended that Dcrit and the percentage of the most interconnected volume of pores should be obtained considering the point of abrupt variation of the cumulative curve of pore size distribution.

Accounts related to maps and pamphlets, 1809-1823

This folder contains eight handwritten account statements and notes primarily related to the collection of subscriptions for Croswell's maps and pamphlets, as well as the disbursement and storage of his printed maps and pamphlets.