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This study aims to investigate patterns in international travel behavior of scientific staff depending on the categories of gender, scientific field and scientific seniority level. The learning from salient differences possibly revealed may inform measures for reducing travel greenhouse gas (GHG) emissions, especially for high-emitting staff groups, and help strengthen the equality between scientists of different categories concerning their travel behavior.

The study collected and used novel empirical data on travel GHG emissions from University of Graz scientific staff for five consecutive years (2015–2019) and used statistical analysis and inference to test and answer three distinct research questions on patterns of travel behavior.

The travel footprint of scientific staff, in terms of annual GHG emissions per scientist, exhibits various highly significant differences across scientific fields, seniority and gender, such as male senior natural scientists showing ten times higher per-person emissions than female junior social scientists.

The five-year travel GHG emissions data set across all fields from natural sciences via social sciences to humanities at a large university (Uni Graz, Austria, about 2,000 scientific staff) and across seniority levels from predocs to professors, both for female and male scientists, enabled a robust empirical study revealing distinct differences in travel GHG footprints of academic staff. In this way, the study adds valuable insights for higher research institutions toward effective GHG reduction policies.

The study aims to promote independent mobility for persons with visual impairment or legal blindness (VIB) by developing a Web-based wayfinding application using geographic information systems (GIS). While the literature mainly focuses on technical devices presenting results for wayfinding, a lack of integration of user needs is identified. The inclusive, participative developed application offers step-by-step directions for pre-trip planning through an accessible user interface.

The paper presents a semi-automated approach to extract a pedestrian routing network data set based on open government data and field survey. User profiles calculate different routes using a weighting scheme for landmarks, orientation hints, infrastructure of crossings and sidewalks. The adoption of ArcGIS Web AppBuilder widgets allows access of the user interface additionally through keyboard-only navigation and therefore screen-reader capability.

GIS offers a powerful tool to design network analysis for persons with VIB. The routing algorithm accesses different user profiles, returning individualized turn-by-turn directions. The complex set of attributes, including shorelines, landmarks and barriers, can be integrated by semi-automated processes.

The paper illustrates the benefit of GIS applications for wayfinding of persons with VIB to raise self-determination and independence.

A ubiquitous pedestrian sidewalk network for a medium-size city comprises a novelty, as research has mainly focused on small areas. The integration of shorelines next to a various number of hints, landmarks and potential barriers through semi-automated processes allows reproducibility and transferability of the model to other cities.

The purpose of this paper is to investigate the applicability of a direct current (DC) hysteresis measurement on power transformer terminals for the subsequent hysteresis model parametrization in transformer grey box topology models.

Two transformer topology models with two different hysteresis models are used together with a DC hysteresis measurement via the power transformer terminals to parameterize the hysteresis models by means of an optimization. The calculated current waveform with the derived model in the transformer no-load condition is compared to the measured no-load current waveforms to validate the model.

The proposed DC hysteresis measurement via the power transformer terminals is suitable to parametrize two hysteresis models implemented in transformer topology models to calculate the no-load current waveforms.

Different approaches for the measurement and utilization of transformer terminal measurements for the hysteresis model parametrization are discussed in literature. The transformer topology models, derived with the presented approach, are able to reproduce the transformer no-load current waveform with acceptable accuracy.

This paper aims to explore the manoeuvring room of higher education institutions to take action to reduce emissions from academic flying. In particular, this study investigates how university staff and central actors in university management evaluate potential measures in this area.

The authors applied a single case study design encompassing an online survey directed at staff (N = 338) and 11 semi-structured interviews with key actors from management at an Austrian university. The authors used descriptive statistics and qualitative content analysis to examine the data.

This study found considerable support among university staff in principle for implementing measures to reduce academic flying, but also serious concerns about the fairness and viability of some restrictive measures, especially disincentives and caps on flying. However, bans on short-haul flights were largely supported. Actors from university management saw their manoeuvring room limited by the potential resistance and non-compliance of staff, as well as by framework conditions external to the university.

Dedicated leadership is needed to facilitate broad commitment within the university and to avoid shifting the responsibility between different governance levels. Restrictive measures to reduce academic air travel will be more readily accepted if perceived as fair and viable.

Although several papers have addressed the behavioural and institutional factors that sustain extensive flying in academia, to the best of the authors’ knowledge, this is one of the first contributions to investigate the potentials and challenges of introducing measures to reduce air travel in higher education institutions.

This paper aims to introduce a non-invasive and convenient method to detect a life-threatening disease called aortic dissection. A Bayesian inference based on enhanced multi-sensors impedance cardiography (ICG) method has been applied to classify signals from healthy and sick patients.

A 3D numerical model consisting of simplified organ geometries is used to simulate the electrical impedance changes in the ICG-relevant domain of the human torso. The Bayesian probability theory is used for detecting an aortic dissection, which provides information about the probabilities for both cases, a dissected and a healthy aorta. Thus, the reliability and the uncertainty of the disease identification are found by this method and may indicate further diagnostic clarification.

The Bayesian classification shows that the enhanced multi-sensors ICG is more reliable in detecting aortic dissection than conventional ICG. Bayesian probability theory allows a rigorous quantification of all uncertainties to draw reliable conclusions for the medical treatment of aortic dissection.

This paper presents a non-invasive and reliable method based on a numerical simulation that could be beneficial for the medical management of aortic dissection patients. With this method, clinicians would be able to monitor the patient’s status and make better decisions in the treatment procedure of each patient.

This paper aims to propose a method of parametrizing topological transformer model at high flux densities in the core.

The approach proposed is based on terminal voltages and currents measured in a special purpose saturation test whose data are combined with typical saturation curves of grain-oriented electrical steels; the modeling is carried out in the ATPDraw program.

The authors corroborate experimentally the necessity of dividing the zero sequence impedance between all transformer phases and propose a method of the individual representation of the legs and yokes. This eliminates the use of nonexistent leakage inductances of primary and secondary windings.

The presented modeling approach can be used for predicting inrush current events and in the evaluation of the impact caused by geomagnetically induced currents (GICs).

The proposed approach is completely original and will contribute to a better understanding of the transients occurring in a transformer under abnormal conditions, such as inrush current events and GICs.

The purpose of this paper is to identify whether the prior industry experience (IE) or industry leadership experience (ILE) of the head might influence the department’s publication output, the ability to acquire external research funds or its entrepreneurial activities (e.g. the commercialization of research results through patents).

The study is based on data from 208 Austrian university departments and combines data from different sources (CVs of the heads of departments, commercial register, funding data and publication data).

The results show a positive relationship between ILE and the patent output of the departments as one indicator for the commercialization of research activities. Low positive effects of IE on the extent of third-party funding were also found. Furthermore, the scientific experience of the head of department has a positive influence on the publication output of the whole department.

The findings suggest that the scientific ability of researchers should be key when selecting the head of a department, due to the fact that scientific performance is still essential for most of these units. However, when universities seek to focus more strongly on other, for example, entrepreneurial activities, then additional competencies come into play. As the actual focus of universities is currently subject to change, former IE and ILE will become increasingly more important and the heads of departments will play a decisive role in the transition toward becoming an entrepreneurial university. Therefore, universities are well advised to integrate these experiences in the job specifications and to establish processes that facilitate the change from an industrial to a university job or which allow “double lives” in university and industry.

Previous studies have mostly investigated the role of the scientific experience of academic leaders in the research performance of their institution in later decades. This study examines the actual relevance of previous entrepreneurial experiences of heads of departments to the departments’ research performance, the ability to acquire external research funds or their entrepreneurial activities.

The purpose of this paper is to demonstrate the rationale, technical framework, content creation workflow and evaluation for a multilingual massive open online course (MOOC) to facilitate information literacy (IL) considering cultural aspects.

A good practice analysis built the basis for the technical and content framework. The evaluation approach consisted of three phases: first, the students were asked to fill out a short self-assessment questionnaire and a shortened adapted version of a standardized IL test. Second, they completed the full version of the IL MOOC. Third, they were asked to fill out the full version of a standardized IL test and a user experience questionnaire.

The results show that first the designed workflow was suitable in practice and led to the implementation of a full-grown MOOC. Second, the implementation itself provides implications for future projects developing multilingual educational resources. Third, the evaluation results show that participants achieved significantly higher results in a standardized IL test after attending the MOOC as mandatory coursework. Variations between the different student groups in the participating countries were observed. Fourth, self-motivation to complete the MOOC showed to be a challenge for students asked to attend the MOOC as nonmandatory out-of-classroom task. It seems that multilingual facilitation alone is not sufficient to increase active MOOC participation.

This paper presents an innovative approach of developing multilingual IL teaching resources and is one of the first works to evaluate the impact of an IL MOOC on learners' experience and learning outcomes in an international evaluation study.

This paper aims to deal with the design optimization of a synchronous reluctance machine to be used in an X-ray tube, where the goal is to maximize the torque while keeping low the amount of material used, by means of gradient-based free-form shape optimization.

The presented approach is based on the mathematical concept of shape derivatives and allows to obtain new motor designs without the need to introduce a geometric parametrization. This paper presents an extension of a standard gradient-based free-form shape optimization algorithm to the case of multiple objective functions by determining updates, which represent a descent of all involved criteria. Moreover, this paper illustrates a way to obtain an approximate Pareto front.

The presented method allows to obtain optimal designs of arbitrary, non-parametric shape with very low computational cost. This paper validates the results by comparing them to a parametric geometry optimization in JMAG by means of a stochastic optimization algorithm. While the obtained designs are of similar shape, the computational time used by the gradient-based algorithm is in the order of minutes, compared to several hours taken by the stochastic optimization algorithm.

This paper applies the presented gradient-based multi-objective optimization algorithm in the context of free-form shape optimization using the mathematical concept of shape derivatives. The authors obtain a set of Pareto-optimal designs, each of which is a shape that is not represented by a fixed set of parameters. To the best of the authors’ knowledge, this approach to multi-objective free-form shape optimization is novel in the context of electric machines.

The trend toward subscription economy accelerated the rise of access-based consumption models for durable consumer goods, replacing individual ownership with subscription contracts. At the same time, disruptive platform businesses have arisen in several consumer markets, bypassing traditional value chains while growing through network effects. In a conceptual approach, the authors address the future market for durable consumer goods in light of developments toward access-based consumption, subscription models and platform business models.

In a conceptual approach, the authors apply a scenario analysis following the Framework Foresight method and address trends, constants, plans and projections shaping the future market of subscriptions for durable goods. The authors create a baseline scenario and two alternative scenarios for the future of consumer durables and thereby discuss platform growth stages and implications for manufacturer brands.

The rising market power of platform companies leads to a baseline scenario where these platforms enter the market of subscriptions for durable goods. Alternative scenario 1 addresses the successful market entry of new platform businesses. In contrast, alternative scenario 2 describes the rise of manufacturer brand platforms.

This conceptual research enriches the discussion of access-based business models by creating scenarios depicting possible future developments. Moreover, it adds to the increasing focus on platform business models and thereby addresses the role of traditional manufacturer brands in markets for durable consumer goods subscriptions.