The cationic polymerization of α-methylstyrene in liquid sulfur dioxide initiated by the HI/I2 system

The polymerization of α-methylstyrene (αMeSty) initiated by HI/I₂ or HI in the presence of liquid sulfur dioxide has been investigated. The number-average molecular weight increased with the monomer concentration for reactions initiated by the HI/I₂ system. I₂ also participates in the initiation process, increasing the number-average polymer chain at higher monomer concentration. HI alone is also able to initiate the polymerization of αMeSty in the presence of SO₂. With this initiator, transfer reaction can be minimized in systems containing low amount of SO₂. Received: 19 December 1996/Revised: 27 January 1997/Accepted 29 January 1997     

Electrochemical behaviour of heat-treated AlZnMg alloys in chloride solutions containing sulphate

The electrochemical corrosion and passivation of Al5Zn1.7Mg0.23Cu0.053Nb alloys, submitted to different heat treatments (cold-rolled, annealed, quenched and aged, and quenched in two steps and aged), in sulphate-containing chloride solutions, has been studied by means of cyclic polarization, electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX), and X-ray photoelectron spectroscopy (XPS). The cyclic polarization curves showed that sulphate addition to the chloride solution produced a poor reproducible shift of the breakdown potential to more positive potentials. The repassivation potentials, much more reproducible, and practically separating the passive from the pitting potential region, were slightly displaced in the negative direction with that addition. When the alloys were potentiodynamically polarized in the passive potential region, sulphate was incorporated in the oxide film, thus precluding chloride ingress. In addition, Zn depletion was favoured, whereas Mg losses were avoided. Different equivalent circuits corresponding to different alloys and potentials in the passive and pitting regions were employed to account for the electrochemical processes taking place in each condition. This work shows that sulphate makes these alloys more sensitive to corrosion, increasing the fracture properties of the surface layer and favouring the pitting attack over greater areas than chloride alone.     

Effect of the addition of Cr and Nb on the microstructure and electrochemical corrosion of heat-treatable Al-Zn-Mg alloys

The effect of the addition of Cr and Nb on the microstructure and the electrochemical corrosion of the weldable, high-strength and stress corrosion cracking (SCC) resistant Al-5%Zn–1.67%Mg–0.23%Cu alloy (H) has been studied. Combined additions of the alloying elements, J (with Nb), L (with Cr) and O (with Cr and Nb) and different heat treatments, ST (cold-rolled), A (annealed), F (quenched), B (quenched and aged) and C (quenched in two steps and aged), to obtain different microstructures and hardness have been performed. To correlate the electrochemical corrosion with the microstructure of the specimens, corrosion potential (E _cor) measurements in different chloride solutions were performed and optical microscopy, SEM, TEM and EDX were applied. In chloride solutions containing dissolved O₂ or H₂O₂, the present alloys were polarized up to the pitting attack. It was shown that theE _cor measurements were very sensitive to the alloy composition and heat treatment, increasing in the order H < J < L < O < Al (for a given heat treatment) and F < A ST < B < C (for a given alloy). The MgZn₂ precipitates of the annealed (A) and cold-rolled (ST) specimens were dissolved in chloride solutions containing oxidizing agents and pitting attack was shown to develop in the cavities where the precipitates were present. In the specimens B and C, the compositions of the precipitate free zones was found to be equal to that of the matrix solid solution and preferential intergranular attack was not evident, this being in agreement with their SCC resistance. The addition of Cr and Nb increased the pitting corrosion resistance. The effects of Cr and Nb were additive, that of Cr being predominant, either, in theE _cor shift or in the increase in the pitting corrosion resistance.     

Learning to rank academic experts in the DBLP dataset

Expert finding is an information retrieval task that is concerned with the search for the most knowledgeable people with respect to a specific topic, and the search is based on documents that describe people's activities. The task involves taking a user query as input and returning a list of people who are sorted by their level of expertise with respect to the user query. Despite recent interest in the area, the current state‐of‐the‐art techniques lack in principled approaches for optimally combining different sources of evidence. This article proposes two frameworks for combining multiple estimators of expertise. These estimators are derived from textual contents, from graph‐structure of the citation patterns for the community of experts and from profile information about the experts. More specifically, this article explores the use of supervised learning to rank methods, as well as rank aggregation approaches, for combining all of the estimators of expertise. Several supervised learning algorithms, which are representative of the pointwise, pairwise and listwise approaches, were tested, and various state‐of‐the‐art data fusion techniques were also explored for the rank aggregation framework. Experiments that were performed on a dataset of academic publications from the Computer Science domain attest the adequacy of the proposed approaches.     

A linear algebra approach to OLAP

Inspired by the relational algebra of data processing, this paper addresses the foundations of data analytical processing from a linear algebra perspective. The paper investigates, in particular, how aggregation operations such as cross tabulations and data cubes essential to quantitative analysis of data can be expressed solely in terms of matrix multiplication, transposition and the Khatri–Rao variant of the Kronecker product. The approach offers a basis for deriving an algebraic theory of data consolidation, handling the quantitative as well as qualitative sides of data science in a natural, elegant and typed way. It also shows potential for parallel analytical processing, as the parallelization theory of such matrix operations is well acknowledged.     

Giant Anomalous Hall and Nernst Conductivities in Magnetic All-d Metal Heusler Alloys

All-d Heuslers are a category of novel compounds combining versatile functionalities such as caloric responses and spintronics with enhanced mechanical properties. Despite the promising transport properties (anomalous Hall (AHC) and anomalous Nernst (ANC) conductivities) shown in the conventional Co₂XY Heuslers with p-d hybridization, the all-d Heuslers with only d-d hybridization open a new horizon to search for new candidates with outstanding transport properties. In this work, the AHC and ANC are evaluated for thermodynamically stable ferro/ferri-magnetic all-d-metal regular Heusler compounds based on high-throughput first-principles calculations. It is observed that quite a few materials exhibit giant AHCs and ANCs, such as cubic Re₂TaMn with an AHC of 2011 S cm^-1, and tetragonal Pt₂CrRh with an AHC of 1966 S cm^-1 and an ANC of 7.50 A m^-1K^-1. Comprehensive analysis on the electronic structure reveals that the high AHC can be attributed to the occurrence of the Weyl nodes or gapped nodal lines in the neighborhood of the Fermi level. The correlations between such transport properties and the number of valence electrons are also thoroughly investigated, which provides a practical guidance to tailor AHC and ANC via chemical doping for transverse thermoelectric applications.     

Slicing for architectural analysis

Current software development often relies on non-trivial coordination logic for combining autonomous services, eventually running on different platforms. As a rule, however, such a coordination layer is strongly woven within the application at source code level. Therefore, its precise identification becomes a major methodological (and technical) problem and a challenge to any program understanding or refactoring process.The approach introduced in this paper resorts to slicing techniques to extract coordination data from source code. Such data are captured in a specific dependency graph structure from which a coordination model can be recovered either in the form of an Orc specification or as a collection of code fragments corresponding to the identification of typical coordination patterns in the system. Tool support is also discussed.     

A strategy for allowing meaningful and comparable scores in approximate matching

Approximate data matching aims at assessing whether two distinct instances of data represent the same real-world object. The comparison between data values is usually done by applying a similarity function which returns a similarity score. If this score surpasses a given threshold, both data instances are considered as representing the same real-world object. These score values depend on the algorithm that implements the function and have no meaning to the user. In addition, score values generated by different functions are not comparable. This will potentially lead to problems when the scores returned by different similarity functions need to be combined for computing the similarity between records. In this article, we propose that thresholds should be defined in terms of the precision that is expected from the matching process rather than in terms of the raw scores returned by the similarity function. Precision is a widely known similarity metric and has a clear interpretation from the user's point of view. Our approach defines mappings from score values to precision values, which we call adjusted scores. In order to obtain such mappings, our approach requires training over a small dataset. Experiments show that training can be reused for different datasets on the same domain. Our results also demonstrate that existing methods for combining scores for computing the similarity between records may be enhanced if adjusted scores are used.     

Traffic analysis and synthetic models of second life

Virtual Worlds (VW), such as Massive Multiplayer Online Social Games, have been gaining increasing attention in the last few years, mainly due to the new way users interact with them. However, little effort has been devoted to understand their traffic profile and the implications to the traffic management area. With the current growing rate of VWs’ usage, their traffic demand could eventually impose a significant burden on the operation of a typical Internet Service Provider (ISP) network. In this paper, we seek to understand the traffic behavior of an increasingly popular VW application, namely Second Life (SL), from both the connection and network level perspectives. We also show results of a traffic analysis of a SL client, when an avatar performs different actions in the VW, at different places and under different network conditions. Our results show that SL makes intensive use of network resources (mostly bandwidth), since the capacity needed for having a full SL experience (listening to live music) may reach 500 kbps. We then extend the traffic analysis work on SL by providing analytical models for its traffic profile. We aim at helping the network management and planning area to estimate the impact of an intense use of such VW on access links or core networks. Such synthetic models are also useful to the networking research community for the use in network simulations.