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Biowaste-derived substances as a tool for obtaining magnet-sensitive materials for environmental applications in wastewater treatments
No full textIn this study, bio-based substances (BBS) obtained from composted urban biowaste are used as stabilizers for the synthesis of magnet-sensitive nanoparticles (NPs). The BBS-stabilized NPs are characterized by means of different techniques (FTIR, XRD, SEM, BET analysis, magnetization curves). Additionally, TGA coupled on-line with FTIR and GC/MS analysis of the exhausted gas are performed in order to simultaneously identify all the degradation products and evaluate the exact composition of such BBS-stabilized materials. Moreover, Fenton-like or photo-Fenton-like experiments carried out at circumneutral pH are performed in order to evaluate the BBS-functionalized NPs photo-activity towards the degradation of caffeine (taken as model emerging pollutant). The obtained promising results encourage the use of BBS as a green alternative tool for the preparation of smart materials with enhanced magnet-sensitive properties, also suitable for applications in wastewater purification treatments
Analysis of Quench Propagation in the ITER Central Solenoid Insert (CSI) Coil
No full textThe Central Solenoid Insert (CSI) coil, a single-layer Nb3Sn solenoid, wound using the same conductor of the 3L module of the ITER Central Solenoid, was tested in 2015 at the National Institutes for Quantum and Radiological Science and Technology (former JAEA) Naka, Japan, inside the bore of the Central Solenoid Model Coil. At the end of the test campaign, quench tests were carried out to study the quench initiation and propagation. Different delay times (up to 7 s) between quench detection and current dump were set, in order to explore to which extent the dump could be delayed without exceeding the maximum allowed hot spot temperature. The experimental data for different time delays are presented and compared, showing a good reproducibility of the measurements and confirming the safe operation of the coil during these tests. The previously developed and already extensively validated 4C thermal-hydraulic code is then used to model the transient up to the current dump and a comprehensive comparison between the simulation results and the measurements is presented, including the evolution of the local voltages and of the jacket temperature distribution along the conductor, the quench front propagation, and the SHe pressurization and mass flow rate behaviour measured at the CSI inlet and outlet. The good agreement between simulation results and measurements confirms the validation of the 4C code for this type of transients and the code is then used to explain the acceleration of the quench and to get an improved estimate of the hot spot temperature
Torsion shear strength of ceramics joined by brittle or ductile materials
No full textAssessing the shear strength of a joined ceramic or CMC is an essential task in components design. Indeed, what is needed for design purposes, is the true shear strength, while several standard tests only give conventional values, disregarding multiaxiality and non-uniformity of the actual stress distribution. If used under proper conditions, torsion test has the advantage of producing a state of pure shear stress with a known distribution in the joint section. A distinction must be done whether the joining material is brittle or ductile. In case of brittle behavior, the stress concentration factor due to the specimen geometry must be taken into account; moreover, since the stress state is intrinsically biaxial, failure may occur out of the joint section. In case of ductile behavior, the non-linear effect of plasticity must be included. The talk discusses these aspects and proposes a procedure suitable to assess the pure shear strength of joined ceramics
Analysis of Timed Properties Using the Jump-Diffusion Approximation
No full textDensity dependent Markov chains (DDMCs) describe the interaction of groups of identical objects. In case of large numbers of objects a DDMC can be approximated efficiently by means of either a set of ordinary differential equations (ODEs) or by a set of stochastic dif- ferential equations (SDEs). While with the ODE approximation the chain stochasticity is not maintained, the SDE approximation, also known as the diffusion approximation, can capture specific stochastic phenomena (e.g., bi-modality) and has also better convergence characteristics. In this paper we introduce a method for assessing temporal properties, specified in terms of a timed automaton, of a DDMC through a jump diffusion approximation. The added value is in terms of runtime: the costly simu- lation of a very large DDMC model can be replaced through much faster simulation of the corresponding jump diffusion model. We show the effi- cacy of the framework through the analysis of a biological oscillator
Assessment of the Methodology for Establishing the EU List of Critical Raw Materials - Background report
No full textThis report presents the results of work carried out by the Directorate General (DG) Joint Research Centre (JRC) of the European Commission (EC), in close cooperation with Directorate-General for Internal Market, Industry, Entrepreneurship and SMEs (GROW), in the context of the revision of the EC methodology that was used to identify the list of critical raw materials (CRMs) for the EU in 2011 and 2014 (EC 2011, 2014). As a background report, it complements the corresponding Guidelines Document, which contains the "ready-to-apply" methodology for updating the list of CRMs in 2017. This background report highlights the needs for updating the EC criticality methodology, the analysis and the proposals for improvement with related examples, discussion and justifications. However, a few initial remarks are necessary to clarify the context, the objectives of the revision and the approach. As the in-house scientific service of the EC, DG JRC was asked to provide scientific advice to DG GROW in order to assess the current methodology, identify aspects that have to be adapted to better address the needs and expectations of the list of CRMs and ultimately propose an improved and integrated methodology. This work was conducted closely in consultation with the adhoc working group on CRMs, who participated in regular discussions and provided informed expert feedback. The analysis and subsequent revision started from the assumption that the methodology used for the 2011 and 2014 CRMs lists proved to be reliable and robust and, therefore, the JRC mandate was focused on fine-tuning and/or targeted incremental methodological improvements. An in depth re-discussion of fundamentals of criticality assessment and/or major changes to the EC methodology were not within the scope of this work. High priority was given to ensure good comparability with the criticality exercises of 2011 and 2014. The existing methodology was therefore retained, except for specific aspects for which there were policy and/or stakeholder needs on the one hand, or strong scientific reasons for refinement of the methodology on the other. This was partially facilitated through intensive dialogue with DG GROW, the CRM adhoc working group, other key EU and extra-EU stakeholders
Data miners' little helper: data transformation activity cues for cluster analysis on document collections
No full textIn this paper we propose a new self-learning engine to streamline the analytics process, as it enables analysts to mine massive data repositories with minimal user intervention. In the context of cluster analysis on a collection of documents this new system, named SELF-DATA (SELF-learning DAta TrAnsformation), suggests to the analyst how to con�figure the whole mining process for a given dataset. SELF-DATA relies on an engine exploring different data weighting schemas (e.g., normalized term frequencies) and data transformation methods (e.g., PCA) before applying the cluster analysis, evaluating and comparing solutions through different quality indices (e.g., weighted Silhouette), and presenting the k-top solutions to the analyst. SELF-DATA will also include a knowledge base storing results of experiments on previously processed datasets, and a classifi�cation algorithm trained on the knowledge base content to forecast the best con�figuration for the whole mining process for an unexplored dataset. The first development of SELF-DATA running on Apache Spark has been validated on 5 collections of documents. Experimental results highlight that TF-IDF and logarithmic entropy are effective to measure item relevance with sparse datasets, and the LSI method outperforms PCA with a large dictionary
Exploring Woman architect's in own Home. MoMoWo, International Photo Competition Reportages
No full textLa mostra fotografica propone in 50 scatti l'abitare al femminile, o meglio la casa realizzata da donne progettiste, architette, Ingegneri civili, paesaggiste non per un committente esterno ma per loro stesse e per le proprie famiglie. Attraverso 10 reportage, ritratti ed autoritratti, si incrociano nel linguaggio degli spazi e degli oggetti temi differenti: il dentro e il fuori, la presenza e l'assenza, il valore simbolico e la ricerca di funzionalità, ma soprattutto la contaminazione fra vita professionale ed esistenza quotidiana
Adaptive schedulers for deadline-constrained content upload from mobile multihomed vehicles
No full textWe consider the practical problem of video surveillance in public transport systems, where security videos are stored onboard, and a central operator occasionally needs to access portions of the recordings. When this happens, the selected video must be uploaded within a deadline, possibly using multiple parallel wireless interfaces. Interfaces have different associated costs, related to tariffs charged by Mobile Network Operators (MNOs), energy consumption, data quotas, system load. Our goal is to choose which interfaces to use, and when, so as to minimize the cost of the upload while meeting the deadline, despite the unknown short-term variations in throughput. To achieve this goal, we first collect real traces of mobile uploads from vehicles for different MNOs. Examination of these traces confirms the unpredictability of the short-term throughput of wireless connections, and motivates the adoption of adaptive schedulers with limited a-priori knowledge of the system status. To effectively solve our problem, we devised a family of adaptive algorithms, that we thoroughly evaluated using a trace-driven approach. Results show that our adaptive approach can effectively leverage the fundamental tradeoff between the total cost and the delivery time of content upload, despite unknown short-term variations in throughput