1,721,019 research outputs found
Ionic Liquid-Based Electrolytes for Secondary Mg batteries
No full text(Invited Presentation) The development of innovative electrolytes is one of the most crucial targets in order to devise secondary batteries running on alkaline- and alkaline-earth elements characterized by a high specific energy and power and an extensive cyclability, able to provide power for a wide range of applications ranging from portable electronic devices to light-duty electric vehicles. The electrolytes must satisfy very demanding requirements, including: (a) easy migration of the alkaline- and alkaline-earth cations between the electrodes of the battery; (b) high compatibility with all the other functional materials used in the assembly of the device; (c) wide potential window and excellent stability.1
This report summarizes the preparation and characterization of innovative families of ionic-liquid (IL) -based electrolytes meant to address these issues, thus opening new and promising avenues for the research in this field. The electrolytes are based on δ-MgX2 magnesium salts, AlX3 and 1-Ethyl-3-methylimidazoliumX ILs (with X=Cl-, I- or BF4-). 2,3,4
The resulting electrolytes are suitable for application in secondary Mg batteries, and demonstrates: (1) a conductivity at room temperature higher than 10-3 S/cm; and (2) good electrochemical performance. The chemical composition of the electrolytes is analyzed by ICP-AES and microanalysis. The thermal properties are investigated by HR-TG and DSC measurements. The structure and the interactions in materials is studied by vibrational spectroscopies (FT-MIR and –FIR). The electric response is elucidated by Broadband Electrical Spectroscopy (BES). Results allow to propose a conduction mechanism and to define the interplay existing between structural, thermal transitions and electric properties of proposed innovative electrolytes.
(1) Di Noto, V.; Lavina, S.; Giffin, G. A.; Negro, E.; Scrosati, B. Electrochim. Acta 2011, 57, 4–13.
(2) Bertasi, F.; Hettige, C.; Sepehr, F.; Bogle, X.; Pagot, G.; Vezzù, K.; Negro, E.; Paddison, S. J.; Greenbaum, S. G.; Vittadello, M.; Di Noto, V. ChemSusChem 2015, 8, 3069–3076.
(3) Bertasi, F.; Sepher, F.; Pagot, G.; Paddison, S. J.; Noto, V. Di. Adv. Funct. Mater. 2016, DOI: 10.1002/adfm.201601448.
(4) Bertasi, F.; Hettige, C.; Greenbaum, S. G.; Vittadello, M.; Di Noto, V. Ionic Liquid Comprising Alkaline Earth Metal. PCT Patent App. No. WO2015/069871, 2014
Predicting the impact of public events and mobility in Smart Cities
Full text linkThe ubiquitous presence of smartphones and the ever-expanding Internet of Things are generating a treasure trove of data on human movement. We harness the power of Artificial Intelligence to extract knowledge within this data, in particular for predicting people flows and density in a Smart City. This predictive ability holds immense potential for a multitude of applications, from optimising people flow to streamlining event planning, while offering a powerful tool for pre-emptive identification of situations that may lead to crowd disasters. In this paper, we tackle two crucial aspects of people mobility using data from public events and an Italian mobile phone network: to predict both event attendance and future crowd density in specific areas. The event details (location, time etc.) are automatically gathered and stored in a structured format. Next, we handle these problems are treated in a “supervised learning” setting, and various state-of-art Machine Learning techniques are tested to find the best model for each task. The obtained models will be encapsulated into a Policy Support System contributing to foster planning actions of mobility services
A Machine Learning Pipeline to Analyse Multispectral and Hyperspectral Images
No full textMachine Learning is a branch of Artificial Intelligence with the goal of learning patterns from data. These techniques fall into two big categories: supervised and unsupervised learning. The former classify data based on a given set of examples whose classification is known (hence the name supervised), while the latter try to group the data without knowing a priori the possible classes. Neural Networks and clustering algorithms are two of the most prominent examples of the two aforementioned categories. In this paper, we describe a machine learning pipeline to analyse multispectral and hyperspectral images. Our approach first adopts neural networks to identify relevant pixels and then applies a clustering algorithm to group the pixels according to two different criteria, namely intensity and variation of intensity
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Comparing efficacy of different taxonomic resolutions and surrogates in detecting changes in soft bottom assemblages due to coastal defence structures
No full textSandy shores on the West coast of the North Adriatic Sea are extensively protected by different types of defence structures to prevent coastal erosion. Coastal defence schemes modify the hydrodynamic regime, the sediment structure and composition thus affecting the benthic assemblages. This study examines the effectiveness in detecting changes in soft bottom assemblages caused by coastal defence structures by using different levels of taxonomic resolution, polychaetes and/or bivalves as surrogates and different data transformations. A synoptic analyses of three datasets of subtidal benthic macrofauna used in studies aimed at assessing the impact of breakwaters along the North Adriatic coast has been done. Analyses of similarities and correlations between distance matrices were done using matrices with different levels of taxonomic resolution, and with polychaetes or bivalves data alone. Lentidium mediterraneum was the most abundant species in all datasets. Its abundance was not consistently related to the presence of defence structures. Moreover, distribution patterns of L. mediterraneum were masking the structure of the whole macrofaunal assemblages. Removal of L. mediterraneum from the datasets allowed the detection of changes in benthic assemblages due to coastal defences. Analyses on different levels of taxonomic resolution showed that the level of family maintained sufficient information to detect the impacts of coastal defence structures on benthic assemblages. Moreover, the outcomes depended on the transformation used. Patterns of distribution of bivalves, used as surrogates, showed low correlations with the patterns of the total macrofaunal species assemblages. Patterns of polychaetes, if identified to the species or genus level showed higher correlations with the whole dataset. However, the identification of polychaetes to species and genus level is as costly as the identification of all macrobenthic taxa at family level. This study provided additional evidences that taxonomic sufficiency is a useful tool in environmental monitoring, also in investigations on the impacts of coastal defence structures on subtidal macrofauna. The use of coarser taxonomic level, being time-efficient, would allow improving sampling designs of monitoring programs by increasing replication in space and time and by allowing long term monitoring studies
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