892 resultados para Understanding by Design


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This PhD thesis focused on nanomaterial (NM) engineering for occupational health and safety, in the frame of the EU project “Safe Nano Worker Exposure Scenarios (SANOWORK)”. Following a safety by design approach, surface engineering (surface coating, purification process, colloidal force control, wet milling, film coating deposition and granulation) were proposed as risk remediation strategies (RRS) to decrease toxicity and emission potential of NMs within real processing lines. In the first case investigated, the PlasmaChem ZrO2 manufacturing, the colloidal force control applied to the washing of synthesis rector, allowed to reduce ZrO2 contamination in wastewater, performing an efficient recycling procedure of ZrO2 recovered. Furthermore, ZrO2 NM was investigated in the ceramic process owned by CNR-ISTEC and GEA-Niro; the spray drying and freeze drying techniques were employed decreasing NM emissivity, but maintaining a reactive surface in dried NM. Considering the handling operation of nanofibers (NFs) obtained through Elmarco electrospinning procedure, the film coating deposition was applied on polyamide non-woven to avoid free fiber release. For TiO2 NF the wet milling was applied to reduce and homogenize the aspect ratio, leading to a significant mitigation of fiber toxicity. In the Colorobbia spray coating line, Ag and TiO2 nanosols, employed to transfer respectively antibacterial or depolluting properties to different substrates, were investigated. Ag was subjected to surface coating and purification, decreasing NM toxicity. TiO2 was modified by surface coating, spray drying and blending with colloidal SiO2, improving its technological performance. In the extrusion of polymeric matrix charged with carbon nanotube (CNTs) owned by Leitat, the CNTs used as filler were granulated by spray drying and freeze spray drying techniques, allowing to reduce their exposure potential. Engineered NMs tested by biologists were further investigated in relevant biological conditions, to improve the knowledge of structure/toxicity mechanisms and obtain new insights for the design of safest NMs.

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La Tesi tratta i concetti di Privacy e Protezione dei Dati personali, contestualizzandone il quadro normativo e tecnologico con particolare riferimento ai contesti emergenti rappresentati – per un verso – dalla proposta di nuovo Regolamento generale sulla protezione dei dati personali (redatto dal Parlamento Europeo e dal Consiglio dell’Unione Europea), – per un altro – dalla metodologia di progettazione del Privacy by Design e – per entrambi – dalla previsione di un nuovo attore: il responsabile per la protezione dei dati personali (Privacy Officer). L’elaborato si articola su tre parti oltre introduzione, conclusioni e riferimenti bibliografici. La prima parte descrive il concetto di privacy e le relative minacce e contromisure (tradizionali ed emergenti) con riferimento ai contesti di gestione (aziendale e Big Data) e al quadro normativo vigente. La seconda Parte illustra in dettaglio i principi e le prassi del Privacy by Design e la figura del Privacy Officer formalmente riconosciuta dal novellato giuridico. La terza parte illustra il caso di studio nel quale vengono analizzate tramite una tabella comparativa minacce e contromisure rilevabili in un contesto aziendale.

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The Daphniphyllum alkaloids are a group of highly complex polycyclic alkaloids. Examination of the structures if several members of this family of natural products led to a hypothesis about their mode of biosynthesis (depicted in Scheme SI). Based on this hypothetical biosynthetic pathway, a laboratory synthesis was designed that incorporated as a key transformation the novel one-pot transformation of dialdehyde 24 to pentacyclic unsaturated amine 25. This process turned out to be an exceptionally efficient way to construct the pentacyclic nucleus of the Daphniphyllum alkaloids. However, a purely fortuitous discovery, resulting from accidental use of methylamine rather than ammonia, led to a great improvement in the synthesis and suggests an even more attractive possible biosynthesis.

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To gain entry into cells, viruses utilize a variety of different cell-surface molecules. Foot-and-mouth disease virus (FMDV) binds to cell-surface integrin molecules via an arginine-glycine-aspartic acid (RGD) sequence in capsid protein VP1. Binding to this particular cell-surface molecule influences FMDV tropism, and virus/receptor interactions appear to be responsible, in part, for selection of antigenic variants. To study early events of virus-cell interaction, we engineered an alternative and novel receptor for FMDV. Specifically, we generated a new receptor by fusing a virus-binding, single-chain antibody (scAb) to intracellular adhesion molecule 1 (ICAM1). Cells that are normally not susceptible to FMDV infection became susceptible after being transfected with DNA encoding the scAb/ICAM1 protein. An escape mutant (B2PD.3), derived with the mAb used to generate the genetically engineered receptor, was restricted for growth on the scAb/ICAM1 cells, but a variant of B2PD.3 selected by propagation on scAb/ICAM1 cells grew well on these cells. This variant partially regained wild-type sequence in the epitope recognized by the mAb and also regained the ability to be neutralize by the mAb. Moreover, RGD-deleted virions that are noninfectious in animals and other cell types grew to high titers and were able to form plaques on scAb/ ICAM1 cells. These studies demonstrate the first production of a totally synthetic cell-surface receptor for a virus. This novel approach will be useful for studying virus reception and for the development of safer vaccines against viral pathogens of animals and humans.

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Recent organisational and technological changes à la Uber have generated a new labour market fringe: a digital class of workers and contractors. In this paper we study the case of CoContest, a crowdsourcing platform for interior design. Our objective is to investigate how profitable this type of work can be, also from a cross-country perspective, and why professionals choose to supply work on such a platform. Given the low returns, one might expect to see a pattern of northern employer/southern contractor. Yet analysis reveals a more nuanced pattern, in which designers supply their work even if they live in Italy, which is a high-income country. For these designers work on CoContest can make sense if they are new to the labour market and face high entry barriers, although crowdsourcing does not offer them profitable employment full time. The case of Serbia, the second-largest supplier of designers, is different, however. As a result of differences in purchasing power, if the market grows experienced Serbian designers can expect to make a living from crowdsourced contracts.

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Cover title.

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A grants program supported by Build Illinois, and the National Endowment for the Arts.

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DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

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Templated, macroporous Mg-Al hydrotalcites synthesised via alkali-free co-precipitation exhibit superior performance in the transesterification of C4 -C18 triglycerides for biodiesel production, with rate-enhancement increasing with alkyl chain length. Promotion reflects improved diffusion of bulky triglycerides and accessibility of active sites within the hierarchical macropore-micropore architecture. © 2012 The Royal Society of Chemistry.

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Abstract not available

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The first mechanical Automaton concept was found in a Chinese text written in the 3rd century BC, while Computer Vision was born in the late 1960s. Therefore, visual perception applied to machines (i.e. the Machine Vision) is a young and exciting alliance. When robots came in, the new field of Robotic Vision was born, and these terms began to be erroneously interchanged. In short, we can say that Machine Vision is an engineering domain, which concern the industrial use of Vision. The Robotic Vision, instead, is a research field that tries to incorporate robotics aspects in computer vision algorithms. Visual Servoing, for example, is one of the problems that cannot be solved by computer vision only. Accordingly, a large part of this work deals with boosting popular Computer Vision techniques by exploiting robotics: e.g. the use of kinematics to localize a vision sensor, mounted as the robot end-effector. The remainder of this work is dedicated to the counterparty, i.e. the use of computer vision to solve real robotic problems like grasping objects or navigate avoiding obstacles. Will be presented a brief survey about mapping data structures most widely used in robotics along with SkiMap, a novel sparse data structure created both for robotic mapping and as a general purpose 3D spatial index. Thus, several approaches to implement Object Detection and Manipulation, by exploiting the aforementioned mapping strategies, will be proposed, along with a completely new Machine Teaching facility in order to simply the training procedure of modern Deep Learning networks.