Driver Trust in Automated Driving Systems

Vehicle automation is a prominent example of safety-critical AI-based task automation. Recent digital innovations have led to the introduction of partial vehicle automation, which can already give vehicle drivers a sense of what fully automated driving would feel like. In the context of current imperfect vehicle automation, establishing an appropriate level of driver trust in automated driving systems (ADS) is seen as a key factor for their safe use and long-term acceptance. This paper thoroughly reviews and synthesizes the literature on driver trust in ADS, covering a wide range of academic disciplines. Pulling together knowledge on trustful user interaction with ADS, this paper offers a first classification of the main trust calibrators. Guided by this analysis, the paper identifies a lack of studies on adaptive, contextual trust calibration in contrast to numerous studies that focus on general trust calibration

Knowledge Management Goals Revisited – A Cross-Sectional Analysis of Social Software Adoption in Corporate Environments

When it comes to tools serving as knowledge management instruments, social software has gained increasing importance. Whereas corporate social software is almost unanimously recognised to have enabled a fundamental shift in the ways of interacting and communicating within a company, the implementation approaches taken vary a lot from company to company and have not yet been examined in detail. This is also true for the goals set when introducing such tools, as well as for the implementation strategy as a whole. Against this background, we have studied and analysed social software adoption in 23 companies and derived six main goals of corporate social software adoption. These were consequently compared with the goals of knowledge management projects and initiatives, as identified in a series of well-known knowledge management studies. While some of the goals set for the introduction of corporate social software seem to coincide with those resulting from knowledge management studies, some others appear to be new and specific for corporate social software

Morphological description and multilocus genotyping of Onchocerca spp. in red deer (Cervus elaphus) in Switzerland

Onchocercosis is a parasitic disease caused by over 30 Onchocerca spp. (Nematoda: Filarioidea) and predominantly affecting ungulates. Four Onchocerca spp. have been described in the European red deer (Cervus elaphus). Onchocerca flexuosa and Onchocerca jakutensis form subcutaneous nodules in the back region. The other two species, Onchocerca skrjabini and the lesser-known Onchocerca garmsi, are found freely in the subcutaneous tissue of carpal and tarsal joints, and the sternal region, respectively. The presence of Onchocerca spp. in eight red deer shot in the hunting season during September 2020 in the Grisons region, Switzerland, was investigated by analysing nodules and free worms in the subcutaneous tissue. The obtained worms were morphologically and genetically identified as O. jakutensis, O. flexuosa and O. skrjabini. The latter two are first reports from Switzerland, and morphological redescriptions of these two species are presented. Onchocerca skrjabini and O. jakutensis are newly described from the sternal region of deer. One female of O. jakutensis was found free in the subcutaneous tissue of the sternal region, an atypical presentation for this species. Phylogenetic analyses were based on four mitochondrial and one nuclear loci, revealing that O. jakutensis belongs to a clade which so far only included non-cervid Onchocerca spp. Analysis of sequences from this study and GenBank entries revealed two distinct subpopulations of O. skrjabini: one from European red deer and another from Japanese serow and sika deer. Morphological identification can be challenging, also because worm location in the host is less strictly determined than previously described. Genetic identification is straightforward for O. flexuosa, O. jakutensis and O. skrjabini for which complete data of five loci are now available whereas genetic data of O. garmsi is still lacking

Nutzbarkeit, Nutzungsmotivation, Nutzung und Mehrwert von Offenen Sozialen Netzwerken: Eine Befragung der Nutzer von StudiVZ

Viele Studien zu Sozialen Netzwerken befassen sich lediglich mit der Untersuchung elektronischer Spuren und bedienen sich dabei der Sozialen Netzwerkanalyse als Untersuchungsmethode. Nach wie vor herrscht ein Mangel an Befragungen der Nutzer offener Sozialer Netzwerke wie Facebook, Xing oder StudiVZ vor. Obwohl in klassischen und neuen Medien häufig über diese Plattformen berichtet wird - vorzugsweise über negative Aspekte wie mangelnder Schutz der Privatsphäre oder Missbrauch von Nutzerdaten – besteht nach wie vor erheblicher Forschungsbedarf hinsichtlich Nutzungsmotivation, Nutzbarkeit, Nutzung und Mehrwert. In diesem Beitrag werden die Ergebnisse einer in diesem Kontext durchgeführten Online-Befragung von 133 Nutzern der Sozialen Netzwerkplattform StudiVZ vorgestellt. Interessant ist, dass StudiVZ vom Großteil der Nutzer vor allem zur Erleichterung der Kommunikation und zur Kontaktpflege verwendet wird. StudiVZ wird jedoch kaum zur Unterstützung des Studiums eingesetzt, obwohl diesbezügliche Funktionen auch zentral angeboten werden

CARMAweb: comprehensive R- and bioconductor-based web service for microarray data analysis

CARMAweb (Comprehensive R-based Microarray Analysis web service) is a web application designed for the analysis of microarray data. CARMAweb performs data preprocessing (background correction, quality control and normalization), detection of differentially expressed genes, cluster analysis, dimension reduction and visualization, classification, and Gene Ontology-term analysis. This web application accepts raw data from a variety of imaging software tools for the most widely used microarray platforms: Affymetrix GeneChips, spotted two-color microarrays and Applied Biosystems (ABI) microarrays. R and packages from the Bioconductor project are used as an analytical engine in combination with the R function Sweave, which allows automatic generation of analysis reports. These report files contain all R commands used to perform the analysis and guarantee therefore a maximum transparency and reproducibility for each analysis. The web application is implemented in Java based on the latest J2EE (Java 2 Enterprise Edition) software technology. CARMAweb is freely available at

Systematic Spatial Bias in DNA Microarray Hybridization Is Caused by Probe Spot Position-Dependent Variability in Lateral Diffusion

Background The hybridization of nucleic acid targets with surface-immobilized probes is a widely used assay for the parallel detection of multiple targets in medical and biological research. Despite its widespread application, DNA microarray technology still suffers from several biases and lack of reproducibility, stemming in part from an incomplete understanding of the processes governing surface hybridization. In particular, non-random spatial variations within individual microarray hybridizations are often observed, but the mechanisms underpinning this positional bias remain incompletely explained. Methodology/Principal Findings This study identifies and rationalizes a systematic spatial bias in the intensity of surface hybridization, characterized by markedly increased signal intensity of spots located at the boundaries of the spotted areas of the microarray slide. Combining observations from a simplified single-probe block array format with predictions from a mathematical model, the mechanism responsible for this bias is found to be a position-dependent variation in lateral diffusion of target molecules. Numerical simulations reveal a strong influence of microarray well geometry on the spatial bias. Conclusions Reciprocal adjustment of the size of the microarray hybridization chamber to the area of surface-bound probes is a simple and effective measure to minimize or eliminate the diffusion-based bias, resulting in increased uniformity and accuracy of quantitative DNA microarray hybridization.Austrian Science Fund (P18836-B17)Austrian Science Fund (P20185-B17 )Austrian Science Fund (P16566-B14)Austria. Federal Ministry of Science and Research (GEN-AU III InflammoBiota)National Institutes of Health (U.S.) (1-R21-EB008844 to RS)National Science Foundation (U.S.) (OCE-0744641-CAREER

CWeb 2.0 Profile-Map: Ein Schema zur Beschreibung und Kategorisierung für Business-Cases im Corporate Web 2.0

Web 2.0 nimmt in vielen Unternehmen eine zunehmend gewichtigere Rolle in deren aktuellen und künftigen Geschäftsmodellen ein. Dieser Entwicklung entspringt der Begriff „Corporate Web 2.0“, welcher den Einsatz von Web-2.0-Anwendungen im Business-Kontext bezeichnet. Hohe Komplexität und fehlende Strukturen lassen derzeit im Web 2.0 einen systematischen, lernorientierten Vergleich von Business- Cases nur eingeschränkt zu. Die vorgestellte CWeb 2.0 Profile-Map ermöglicht als Schema zur Charakterisierung und Kategorisierung von Web 2.0-Fallbeispielen eine systematische, Businesskontext-abhängige Beschreibung und Kategorisierung. Vergleichbare Anwendungen des Web 2.0 können so besser erkannt und Erfahrungen aus einzelnen Anwendungsfällen über Organisationsgrenzen hinweg effektiver transferiert werden

EXPLORING THREAT-SPECIFIC PRIVACY ASSURANCES IN THE CONTEXT OF CONNECTED VEHICLE APPLICATIONS

Connected vehicles enable a wide range of use cases, often facilitated by smartphone apps and involving extensive processing of driving-related data. Since information about actual driving behavior or even daily routines can be derived from this data, the question of privacy arises. We explore the impact of privacy assurances on driving data sharing concerns. Specifically, we consider two data-intensive cases: usage-based insurance and traffic hazard warning apps. We conducted two experimental comparisons to investigate whether and how privacy-related perceptions about vehicle data sharing can be altered by different types of text-based privacy assurances on fictional app store pages. Our results are largely inconclusive, and we did not find clear evidence that text-based privacy guarantees can significantly alter privacy concerns and download intentions. Our results suggest that general and threat-specific privacy assurance statements likely yield no or only negligible benefits for providers of connected vehicle apps regarding user perceptions