Real-Time Visual Analytics for Air Quality

Raise collective awareness about the daily levels of humans exposure to toxic chemicals in the air is of great significance in motivating citizen to act and embrace a more sustainable life style. For this reason, Public Administrations are involved in effectively monitoring urban air quality with high-resolution and provide understandable visualization of the air quality conditions in their cities. Moreover, collecting data for a long period can help to estimate the impact of the policies adopted to reduce air pollutant concentration in the air. The easiest and most cost-effective way to monitor air quality is by employing low-cost sensors distributed in urban areas. These sensors generate a real-time data stream that needs elaboration to generate adequate visualizations. The TRAFAIR Air Quality dashboard proposed in this paper is a web application to inform citizens and decision-makers on the current, past, and future air quality conditions of three European cities: Modena, Santiago de Compostela, and Zaragoza. Air quality data are multidimensional observations update in real-time. Moreover, each observation has both space and a time reference. Interpolation techniques are employed to generate space-continuous visualizations that estimate the concentration of the pollutants where sensors are not available. The TRAFAIR project consists of a chain of simulation models that estimates the levels of NO and NO2 for up to 2 days. Furthermore, new future air quality scenarios evaluating the impact on air quality according to changes in urban traffic can be explored. All these processes generate heterogeneous data: coming from different sources, some continuous and others discrete in the space-time domain, some historical and others in real-time. The dashboard provides a unique environment where all these data and the derived statistics can be observed and understood

A comparative study of state-of-the-art linked data visualization tools

Data visualization tools are of great importance for the exploration and the analysis of Linked Data (LD) datasets. Such tools allow users to get an overview, understand content, and discover interesting insights of a dataset. Visualization approaches vary according to the domain, the type of data, the task that the user is trying to perform, as well as the skills of the user. Thus, the study of the capabilities that each approach offers is crucial in supporting users to select the proper tool/technique based on their need. In this paper we present a comparative study of the state-of-the-art LD visualization tools over a list of fundamental use cases. First, we define 16 use cases that are representative in the setting of LD visual exploration, examining several tool's aspects; e.g., functionality capabilities, feature richness. Then, we evaluate these use cases over 10 LD visualization tools, examining: (1) if the tools have the required functionality for the tasks; and (2) if they allow the successful completion of the tasks over the DBpedia dataset. Finally, we discuss the insights derived from the evaluation, and we point out possible future directions

Semantic traffic sensor data: The TRAFAIR experience

Modern cities face pressing problems with transportation systems including, but not limited to, traffic congestion, safety, health, and pollution. To tackle them, public administrations have implemented roadside infrastructures such as cameras and sensors to collect data about environmental and traffic conditions. In the case of traffic sensor data not only the real-time data are essential, but also historical values need to be preserved and published. When real-time and historical data of smart cities become available, everyone can join an evidence-based debate on the city''s future evolution. The TRAFAIR (Understanding Traffic Flows to Improve Air Quality) project seeks to understand how traffic affects urban air quality. The project develops a platform to provide real-time and predicted values on air quality in several cities in Europe, encompassing tasks such as the deployment of low-cost air quality sensors, data collection and integration, modeling and prediction, the publication of open data, and the development of applications for end-users and public administrations. This paper explicitly focuses on the modeling and semantic annotation of traffic data. We present the tools and techniques used in the project and validate our strategies for data modeling and its semantic enrichment over two cities: Modena (Italy) and Zaragoza (Spain). An experimental evaluation shows that our approach to publish Linked Data is effective

Effects of coexisting spin disorder and antiferromagnetism on the magnetic behavior of nanostructured (Fe79Mn21)1xCux alloys

We report a magnetic study on nanostructured (Fe79Mn21)1xCux (0.00x0.30) alloys using static magnetic measurements. The alloys are mainly composed by an antiferromagnetic fcc phase and a disordered region that displays a spin-glass-like behavior. The interplay between the antiferromagnetic and magnetically disordered phases establishes an exchange anisotropy that gives rise to a loop shift at temperatures below the freezing temperature of moments belonging to the disordered region. The loop shift is more noticeable as the Cu content increases, which also enhances the spin-glass-like features. Further, in the x¼0.30 alloy the alignment imposed by applied magnetic fields higher than 4 kOe prevail over the configuration determined by the frustration mechanism that characterizes the spin glass-like phase.Fil: Mizrahi, Martin Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; ArgentinaFil: Cabrera, Alejandra Fabiana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Instituto de Física La Plata; ArgentinaFil: Stewart, Silvana Jacqueline. Universidad Nacional Arturo Jauretche. Instituto Ciencias de la Salud; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Instituto de Física La Plata; ArgentinaFil: Desimoni, Judith. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Instituto de Física La Plata; Argentin

Diastereo- and Enantioselective Pd(II)-Catalyzed Additions of 2-Alkylazaarenes to N-Boc Imines and Nitroalkenes

A chiral Pd(II)–bis(oxazoline) complex was found to be highly effective in promoting the first direct diastereo- and enantioselective addition of alkylazaarenes to N-Boc aldimines and nitroalkenes under mild conditions. Deprotection of Boc-protected products proceeded readily to provide amines in high yields