Upcycling by grafting onto semi-crystalline polymers using supercritical CO2

The creation of graft copolymers by selectively grafting a second polymer to the amorphous fraction of a semi-crystalline polymer in supercritical CO₂ is demonstrated herein. The graft copolymer is synthesized by free radical polymerization of a vinyl monomer within the semi-crystalline polymer below its melt temperature. Such conditions afford selective grafting on the amorphous regions (block “B”) while leaving the crystalline domains (block “A”) unmodified. Accordingly, unique A-B, A-B-A, A-B-A-B-A, and so forth. block structures are formed. In this work, styrene is polymerized within polyamide 6, polyethylene terephthalate, and isotactic polypropylene. Purification of these material is performed to remove the un-grafted homopolymer, allowing for determination of the graft yield, the portion of polymer which covalently bonds to the semi-crystalline matrix. Grafting yields achieved in polyamide 6, polyethylene terephthalate, and isotactic polypropylene were 98%, 59%, and 15%, respectively. Property enhancements were observed upon further characterization of polystyrene-polyamide 6 copolymers, including high glass transition temperatures, the ability to be remelted, and tunable grafting molecular weight. Additionally, hydrophobicity is controlled by varying polystyrene composition. The remarkable range of accessed properties demonstrates this as a potential route to upcycling plastics.     

High temperature oxidation mechanism of dilute copper aluminium alloys

Dilute copper-aluminium alloys were oxidized in air from 700 to 1000 °C. Two distinctive behaviours were observed: alloys with at least 3 wt% aluminium showed excellent oxidation resistance in the whole temperature range. Alloys with 2 wt% or less aluminium exhibited good oxidation resistance up to 800 °C; but as the temperature was further increased, the oxidation rate of these alloys increased and became comparable to that of pure copper. A kinetic model was developed to explain the oxidation behaviour and indirectly determine the amount of dissolved oxygen in the alloys tested. It was found that the oxygen dissolved in alloys with up to 2 wt% Al exceeded its solubility limit in copper, whereas the dissolved oxygen in alloys with higher aluminium contents was below the solubility limit. This difference may account for the significantly different oxidation resistance.     

Influence of the corrosion products of copper on its atmospheric corrosion kinetics in tropical climate

In the present paper, the identification of the corrosion product phases formed on copper under different atmospheres of Cuban tropical climate is reported. Cuprite (Cu₂O), paratacamite (Cu₂Cl(OH)₃), posnjakite (Cu₄SO₄(OH)₆ · 2H₂O) and brochantite (Cu₄SO₄(OH)₆) were the main phases identified by X-ray diffraction (XRD) analysis and Fourier transform infrared spectroscopy (FTIR).Copper corrosion products are known to have a protective effect against corrosion. However, a different behaviour was obtained under sheltered coastal conditions. This can be due to the corrosion products morphology and degree of crystallisation, rather than their phase composition. A higher time of wetness and the accumulation of pollutants not washed away from the metal surface can also play an important role.     

Stabilised finite element methods for a bending moment formulation of the Reissner-Mindlin plate model

This work presents new stabilised finite element methods for a bending moments formulation of the Reissner-Mindlin plate model. The introduction of the bending moment as an extra unknown leads to a new weak formulation, where the symmetry of this variable is imposed strongly in the space. This weak problem is proved to be well-posed, and stabilised Galerkin schemes for its discretisation are presented and analysed. The finite element methods are such that the bending moment tensor is sought in a finite element space constituted of piecewise linear continuos and symmetric tensors. Optimal error estimates are proved, and these findings are illustrated by representative numerical experiments.     

A Model for Incident Tickets Correlation in Network Management

In Information Technology Service Management (ITSM), network management teams typically use an Incident Ticket System (ITS) as a tool to track, troubleshoot, and coordinate the resolution of network incidents that occur during the daily operation of the network. A well organized ITS may positively impact on the efficiency of the incident management process. Nevertheless, in many cases the handling of tickets by the management team is not completely systematic and may be incoherent and inefficient. This way, irrelevant or redundant tickets for the same incident may be issued, thus creating a redundancy in the system that leads to inefficiencies. In this paper, we suggest a model aimed to correlate redundant tickets in order to reduce the information to a single ticket per incident. We validate the proposed correlation model by evaluating it with two datasets taken from a real ticketing system of a telecommunications network company. Using this model as a basis, we also develop and evaluate a methodology that assesses the efficiency of the management team during the process of tickets creation and management. Based on it, we also get some insights on the performance of the different management groups involved in the ticket creation process. These analyses can be leveraged for improving both the management groups functioning and the policies for the tickets’ creation.     

Music staff removal with supervised pixel classification

This work presents a novel approach to tackle the music staff removal. This task is devoted to removing the staff lines from an image of a music score while maintaining the symbol information. It represents a key step in the performance of most optical music recognition systems. In the literature, staff removal is usually solved by means of image processing procedures based on the intrinsics of music scores. However, we propose to model the problem as a supervised learning classification task. Surprisingly, although there is a strong background and a vast amount of research concerning machine learning, the classification approach has remained unexplored for this purpose. In this context, each foreground pixel is labelled as either staff or symbol. We use pairs of scores with and without staff lines to train classification algorithms. We test our proposal with several well-known classification techniques. Moreover, in our experiments no attempt of tuning the classification algorithms has been made, but the parameters were set to the default setting provided by the classification software libraries. The aim of this choice is to show that, even with this straightforward procedure, results are competitive with state-of-the-art algorithms. In addition, we also discuss several advantages of this approach for which conventional methods are not applicable such as its high adaptability to any type of music score.     

Numerical simulation of contaminant transport in groundwater using software tools of $$r^3t$$

When a realistic modelling of radioactive contaminant transport in flowing groundwater is required, very large systems of coupled partial and ordinary differential equations can arise that have to be solved numerically. For that purpose, the software package \(r^3t\) is developed in which several advanced numerical methods are implemented to solve such models efficiently and accurately. Using software tools of \(r^3t\) one can treat successfully nontrivial mathematical problems like advection-dominated system with different retardation of transport for each component and with nonlinear Freundlich sorption and/or precipitation. Additionally, long time simulations on complex 3D geological domains using unstructured grids can be realized. In this paper we introduce and summarize the most important and novel features of numerical simulation for radioactive contaminant transport in porous media when using \(r^3t\).     

Hefestos: an intelligent system applied to ubiquitous accessibility

This article proposes Hefestos, an intelligent system applied to ubiquitous accessibility. This model uses ubiquitous computing concepts to manage accessibility resources for people with disabilities. Among the concepts employed, context awareness, user profiles and trails management can be highlighted. The paper proposes an ontology for accessibility and delineates scenarios of its application in everyday life of people with disabilities. Moreover, the implementation of a smart wheelchair prototype and its application in a practical experiment is described. Ten users with a range of disability degrees tried the system and filled out a survey based on the technology acceptance model. This experiment demonstrated the main functionalities and the acceptance of the system. The results showed 96 % of acceptance regarding perceived easy of use and 98 % in perceived usefulness. These results were encouraging and show the potential for implementing Hefestos in real life situations.