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When the ECLAS Conference took place in 1972 western societies were undergoing profound change: They transformed from industrial to postindustrial societies – the so-called service societies. 50 years later, the knowledge society is emerging: Knowledge is considered the key resource of this era. Digitalization and widespread dissemination of ICT allow information to be obtained anywhere anytime. This has severe implications for individual lifestyles and everyday practices. Different aspects of living, learning and working are no longer bound to physical limitations but can be enhanced by or even transferred to the virtual space. So being on the move today means travelling in hybrid spaces. We call this the space and practice “en route”.
At the University of Applied Sciences Osnabrück we explore the following questions:
What does “en route” mean and look like in landscapes of higher education?
How is it perceived individually?
(How) can landscape architecture shape it?
Our transdisciplinary research project EN ROUTE aims to meet current challenges at universities (e.g. digitalisation, sustainable development) with a comprehensive understanding of space and practices “en route”. In a transdisciplinary process, researchers from various disciplines – landscape architecture, geography, urban planning, business administrations and marketing, energy technology and computer science – develop concepts and strategies for sustainable and digital mobility in the higher education sector. New “EN ROUTE” types provide insights into the individual production and utilization of spaces “en route”.
The campuses of the University of Applied Science Osnabrück as well as the virtual and physical space network of its members serve as research example. Initial findings will be presented at the conference. While the ECLAS conference in 1972 focused on physical scales, landscape architecture has to reflect them critically and ask: What could be an innovative understanding of spaces “en route”?
Enhancing the nutritional value of pears through agronomic biofortification with iodine (Abstract)
(2024)
In this paper, we evaluate the application of Bayesian Optimization (BO) to discrete event simulation (DES) models. In a first step, we create a simple model, for which we know the optimal set of parameter values in advance. We implement the model in SimPy, a framework for DES written in Python. We then interpret the simulation model as a black box function subject to optimization. We show that it is possible to find the optimal set of parameter values using the open source library GPyOpt. To enhance our evaluation, we create a second and more complex model. To better handle the complexity of the model, and to add a visual component, we build the second model in Simio, a commercial off-the-shelf simulation modeling tool. To apply BO to a model in Simio, we use the Simio API to write an extension for optimization plug-ins. This extension encapsulates the logic of the BO algorithm, which we deployed as a web service in the cloud.
The fact that simulation models are black box functions with regard to their behavior and the influence of their input parameters makes them an apparent candidate for Bayesian Optimization (BO). Simulation models are multivariable and stochastic, and their behavior is to a large extent unpredictable. In particular, we do not know for sure which input parameters to adjust to maximize (or minimize) the model’s outcome. In addition, the complex models can take a substantial amount of time to run.
Bayesian Optimization is a sequential and self-learning algorithm to optimize black box functions similar to as we find them in simulation models: they contain a set of parameters for which we want to identify the optimal set, they are expensive to evaluate, and they exhibit stochastic noise. BO has proven to efficiently optimize black box functions from varius disciplines. Among those, and most notably, it is successfully applied in machine learning algorithms to optimize hyperparameters.
Studies on nutrition have historically concentrated on food-shortages and over-nutrition. The physiological states of feeling hungry or being satiated and its dynamics in food choices, dietary patterns, and nutritional behavior, have not been the focus of many studies. Currently, visual analytic using easy-to-use tooling offers applicability in a wide-range of disciplines. In this interdisciplinary pilot-study we tested a novel visual analytic software to assess dietary patterns and food choices for greater understanding of nutritional behavior when hungry and when satiated. We developed software toolchain and tested the hypotheses that there is no difference between visual search patterns of dishes 1) when hungry and when satiated and 2) in being vegetarian and non-vegetarian. Results indicate that food choices can be deviant from dietary patterns but correlate slightly with dish-gazing. Further, scene perception probably could vary between being hungry and satiated. Understanding t he complicated relationship between scene perception and nutritional behavioral patterns and scaling up this pilot-study to a full-study using our introduced software approaches is indispensable.
Taking the transdisciplinary research study “Green fingers for a climate resilient city”, funded by the German Ministry of education and research (BMBF), as an example, this paper follows the hypothesis that processes of landscape planning and designing multifunctional green spaces and processes of co-creation need to be combined to stimulate climate resilient city transformation. The findings are that efforts to combine these processes benefit from making complex climate-resilient city planning accessible for people of different professional backgrounds. The paper showcases how storytelling (Schmidt 2019), mapping (Langner 2009) and guided walks (Schultz 2019) are means to mutually engage with, perceive and understand multifunctional green spaces, inspire ownership, and build capacity for the city’s climate-resilient transformation.
Wood fibers can contribute to replacing peat in growing media and thus help to protect peatlands. As domestic, renewable raw materials, they represent a sustainable option for this purpose. To date, however, wood fibers are usually used as a peat substitute at a maxi-mum of 30% (v/v). A main reason for this limitation is the insufficient microbial stability of wood fibers, which favors nitrogen immobilization and can thus impair nitrogen supply of plants. To address this drawback, in this study wood fibers were subjected to different thermal or thermal-hydrolytic treatments. Seedling tests with napa cabbage were conducted to determine whether treated wood fibers were free of phytotoxic substances. Mixtures with 50% (v/v) wood fiber and white peat each were used. In addition, three wood fiber varieties were evaluated in the cultivation of petunia. Two wood fiber proportions (30 and 60% v/v) and two nitrogen fertilization rates (common and increased supply) were included in each case. In the seedling trial with napa cabbage, no phytotoxic effects were detectable in any of the wood fiber variants investigated. However, when cultivating petunias, both shoot mass growth and number of flowers decreased with increasing wood fiber content. In substrates with a wood fiber content of 60% (v/v), plant development was inhibited so severely that the petunias no longer achieved marketable quality. Increased nitrogen fertilization was able to compensate for this negative effect only in few cases. This suggests that other factors than nitrogen limited plant growth in wood fiber-rich substrates. Among others, physical proper-ties such as the lower water capacity of wood fibers may be a cause. More in-depth investigations are still required in this regard.