Aluminum oxide barrier coatings on polymer films for food packaging applications

In the field of packaging, barrier layers are functional films, which can be applied to polymeric substrates with the objective of enhancing their end-use properties. For food packaging applications, the packaging material is required to preserve packaged food stuffs and protect them from a variety of environmental influences, particularly moisture and oxygen ingress and UV radiation. Aluminum metallized films are widely used for this purpose. More recently, transparent barrier coatings based on aluminum oxide or silicon oxide have been introduced in order to fulfill requirements such as product visibility, microwaveability or retortability. With the demand for transparent barrier films for low-cost packaging applications growing, the use of high-speed vacuum deposition techniques, such as roll-to-roll metallizers, has become a favorable and powerful tool. In this study, aluminum oxide barrier coatings have been deposited onto biaxially oriented polypropylene and polyethylene terephthalate film substrates via reactive evaporation using an industrial 'boat-type' roll-to-roll metallizer. The coated films have been investigated and compared to uncoated films in terms of barrier properties, surface topography, roughness and surface energy using scanning electron microscopy, atomic force microscopy and contact angle measurement. Coating to substrate adhesion and coating thickness have been examined via peel tests and transmission electron microscopy, respectively. © 2013 Elsevier B.V

On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection

A new 1D radial fluid code, IMAGINE, is used to simulate the penetration of gas into a tokamak plasma during a massive gas injection (MGI). The main result is that the gas is in general strongly braked as it reaches the plasma, due to mechanisms related to charge exchange and (to a smaller extent) recombination. As a result, only a fraction of the gas penetrates into the plasma. Also, a shock wave is created in the gas which propagates away from the plasma, braking and compressing the incoming gas. Simulation results are quantitatively consistent, at least in terms of orders of magnitude, with experimental data for a D 2 MGI into a JET Ohmic plasma. Simulations of MGI into the background plasma surrounding a runaway electron beam show that if the background electron density is too high, the gas may not penetrate, suggesting a possible explanation for the recent results of Reux et al in JET (2015 Nucl. Fusion 55 093013)

Living and working in the (post-pandemic) city: a research agenda

During the COVID-19 pandemic, Work from home (WFH) received much public attention. Imposing such a measure was feasible in the context of labour markets’ flexibilisation, which has reshaped urban live-work relationships. However, the pandemic’s effects on those relationships have rarely been explored in housing and planning studies. This paper draws a research agenda based on a literature review of the changes in urban live-work relationships, which were accelerated and legitimised under COVID-19. The latter is considered an exogenous shock contingent upon several other shocks, embedded in structural crises and accelerating ongoing trends. The literature confirms the acceleration of hybrid work for those able to do so, which has fuelled debates on home usage and legitimated planning discourses based on urban proximity, densification and mixed use. Hence, we encourage critical research on (i) the conceptualisations of WFH and COVID-19, (ii) housing policy responses to accumulated uncertainties and regulations for quality and resilient housing, and (iii) the critical analysis of WFH-oriented planning.Spatial Planning and Strateg

Mining maximal frequent patterns in transactional databases and dynamic data streams: A spark-based approach

Mining maximal frequent patterns (MFPs) in transactional databases (TDBs) and dynamic data streams (DDSs) is substantially important for business intelligence. MFPs, as the smallest set of patterns, help to reveal customers’ purchase rules and market basket analysis (MBA). Although, numerous studies have been carried out in this area, most of them extend the main-memory based Apriori or FP-growth algorithms. Therefore, these approaches are not only unscalable but also lack parallelism. Consequently, ever increasing big data sources requirements cannot be met. In addition, mining performance in some existing approaches degrade drastically due to the presence of null transactions. We, therefore, proposed an efficient way to mining MFPs with Apache Spark to overcome these issues. For the faster computation and efficient utilization of memory, we utilized a prime number based data transformation technique, in which values of individual transaction have been preserved. After removing null transactions and infrequent items, the resulting transformed dataset becomes denser compared to the original distributions. We tested our proposed algorithms in both real static TDBs and DDSs. Experimental results and performance analysis show that our approach is efficient and scalable to large dataset sizes