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Stable recombinant mammalian cells are of growing importance in pharmaceutical biotechnology production scenarios for biologics such as monoclonal antibodies, growth and blood factors, cytokines and subunit vaccines. However, the establishment of recombinant producer cells using classical stable transfection of plasmid DNA is hampered by low stable gene transfer efficiencies. Consequently, subsequent selection of transgenic cells and the screening of clonal cell populations are time- and thus cost-intensive. To overcome these limitations, expression cassettes were embedded into transposon-derived donor vectors. Upon the co-transfection with transposase-encoding constructs, elevated vector copy numbers stably integrated into the genomes of the host cells are readily achieved facilitating under stringent selection pressure the establishment of cell pools characterized by sustained and high-yield recombinant protein production. Here, we discuss some aspects of transposon vector technologies, which render these vectors promising candidates for their further utilization in the production of biologics.
In this paper we describe traffic sign recognition with neural networks in the frequency domain. Traffic signs exist in all countries to regulate the traffic of vehicles and pedestrians. Each country has its own set of traffic signs that are more or less similar. They consist of a set of abstract forms, symbols, numbers and letters, which are combined into different signs. Automatic traffic sign recognition is important for driver assistance systems and for autonomous driving. Traffic sign recognition is a subtype of image recognition. The traffic signs are usually recorded by a camera and must be recognized in real time, i.e. assigned to a class. We use neural networks for traffic sign recognition. The special feature of our method is that the traffic sign recognition does not take place in the spatial domain but in the frequency domain. This has advantages because it is possible to significantly reduce the number of neurons and thus the computing effort of the neural network compared to a conventional neural network.
We examine the impact of the existence on an explicit deposit insurance (DI) scheme and its design features on bilateral cross‐border deposits (CBD) in a gravity model setting. We find that both the absolute quality of a country's DI and its relative quality vis‐à‐vis other countries' DI generally affect depositor behavior. However, during systemic banking crises, cross‐border depositors primarily seek countries with the best DI schemes. Similarly, during the 2008–2009 great financial crisis, the emergency actions taken by the governments, which supply and maintain these safe havens, have led to substantial relocations of CBD. (JEL F34, G18)
Emergency management services, such as firefighting, rescue teams and ambulances,are all heavily reliant on road networks. However, even for highly industrialised countries such asGermany, and even for large cities, spatial planning tools are lacking for road network interruptionsof emergency services. Moreover, dependencies of emergency management expand not only onroads but on many other systemic interrelations, such as blockages of bridges. The first challenge thispaper addresses is the development of a novel assessment that captures systemic interrelations ofcritical services and their dependencies explicitly designed to the needs of the emergency services.This aligns with a second challenge: capturing system nodes and areas around road networksand their geographical interrelation. System nodes, road links and city areas are integrated into aspatial grid of tessellated hexagons (also referred to as tiles) with geographical information systems.The hexagonal grid is designed to provide a simple map visualisation for emergency planners andfire brigades. Travel time planning is then optimised for accessing city areas in need by weighingimpaired areas of past events based on operational incidents. The model is developed and testedwith official incident data for the city of Cologne, Germany, and will help emergency managers tobetter device planning of resources based on this novel identification method of critical areas.
This article explores the relationship between digital transformation and disaster risk.Vulnerability studies aim at differentiating impacts and losses by using fine-grained information fromdemographic, social, and personal characteristics of humans. With ongoing digital development,these characteristics will transform and result in new traits, which need to be identified andintegrated. Digital transformations will produce new social groups, partly human, semi-human,or non-human—some of which already exist, and some which can be foreseen by extrapolating fromrecent developments in the field of brain wearables, robotics, and software engineering. Thoughinvolved in the process of digital transformation, many researchers and practitioners in the field ofDisaster Risk Reduction or Climate Change Adaptation are not yet aware of the repercussions fordisaster and vulnerability assessments. Emerging vulnerabilities are due to a growing dependency ondigital services and tools in the case of a severe emergency or crisis. This article depicts the differentimplications for future theoretical frameworks when identifying novel semi-human groups and theirvulnerabilities to disaster risks. Findings include assumed changes within common indicators of socialvulnerability, new indicators, a typology of humans, and human interrelations with digital extensionsand two different perspectives on these groups and their dependencies with critical infrastructure.
Wärme‐ und Kältespeicher von Gebäuden beruhen auf verschiedenen Konzepten der Wärmeübertragung. Bei thermischen Hybridspeichern befindet sich das Phasen-wechselmaterial (PCM) makroverkapselt in PCM‐Objekten, die im Speicherbehälter positioniert sind und vom Wärmeträgerfluid umströmt werden. Die experimentellen Untersuchungen widmen sich den Belade‐ und Entladeeigenschaften des in Kugeln makroverkapselten PCM. Es wird gezeigt, dass die spezifische Wärmeübertragungs-leistung eines Hybridspeichers unmittelbar von der Größe der Kugeln als auch von der spezifischen Wärmeleitfähigkeit des PCM abhängt.
Mental illnesses in adolescence and young adulthood are steadily increasing. Thus,mental disorders represent an individual and societal challenge and an enormous health economicburden, creating an urgent need for research and action. Mental health problems are omnipresent inthe life of young people and the internet is the first resource, which helps them to understand theirsituation. Young people with migration background often have more difficulties accessing health careservices. Digital technologies offer an ideal opportunity for a low-threshold platform that addressesthe needs of young people. The current project “GeKo:mental” aims to design a multilingual websitefor Cologne-based adolescents and young adults that will enable them to obtain comprehensiveinformation about mental illness and health, treatment options and first contact points. To designthis website, this study aims to find out what kind of health information is needed and how itshould best be presented. Nine focus group discussions with adolescents and young adults withand without migration background (N = 68) were conducted; the focus group discussions took placeat schools, in an association for social youth work and in an cultural association, which is linkedto a mosque in Cologne, Germany. A qualitative content analysis was conducted on the gatheredmaterial. The participants reported concrete challenges and needs. The results will form the basis forthe development and design of a website.
We consider a risk model in discrete time with dividends and capital injections. The goal is to maximise the value of a dividend strategy. We show that the optimal strategy is of barrier type. That is, all capital above a certain threshold is paid as dividend. A second problem adds tax to the dividends but an injection leads to an exemption from tax. We show that the value function fulfils a Bellman equation. As a special case, we consider the case of premia of size one. In this case we show that the optimal strategy is a two barrier strategy. That is, there is a barrier if a next dividend of size one can be paid without tax and a barrier if the next dividend of size one will be taxed. In both models, we illustrate the findings by de Finetti’s example.
One-step preparation of bilayered films from kraft lignin and cellulose acetate to mimic tree bark
(2020)
This contribution presents the development of a dry-cast method for the one-step preparation of bio-based films from wood polymers that mimic the bilayered structure of tree bark, the natural protective layer of the tree. In a simplified view, natural bark can be considered as the superposition of an external homogeneous and non-porous layer (outer bark) and a porous substructure layer (inner bark). This work is a first step for the future development of bio-based biomimetic wood coatings. The film had a bark-like appearance and its total density, bulk density and porosity were similar to values measured in natural bark. Furthermore, the structural characteristics of the studied film, namely specific surface area (BET) and pore size distribution, as well as the performance of the water adsorption ability were investigated and discussed.
Against the background of a worldwide decrease in the number of gauging stations,the estimation of river discharge using spaceborne data is crucial for hydrological research, rivermonitoring, and water resource management. Based on the at-many-stations hydraulic geometry(AMHG) concept, a novel approach is introduced for estimating river discharge using Sentinel-1time series within an automated workflow. By using a novel decile thresholding method, no a prioriknowledge of the AMHG function or proxy is used, as proposed in previous literature. With arelative root mean square error (RRMSE) of 19.5% for the whole period and a RRMSE of 15.8%considering only dry seasons, our method is a significant improvement relative to the optimizedAMHG method, achieving 38.5% and 34.5%, respectively. As the novel approach is embedded intoan automated workflow, it enables a global application for river discharge estimation using solelyremote sensing data. Starting with the mapping of river reaches, which have large differences inriver width overthe year, continuous river width time series are created using high-resolution andweather-independent SAR imaging. It is applied on a 28 km long section of the Mekong River nearVientiane, Laos, for the period from 2015 to 2018.