On credibility improvements for automotive navigation systems

Automotive navigation systems are becoming ubiquitous as driver assistance systems. Vendors continuously aim to enhance route guidance by adding new features to their systems. However, we found in an analysis of current navigation systems that many share interaction weaknesses, which can damage the system’s credibility. Such issues are most prevalent when selecting a route, deviating from the route intentionally, or when systems react to dynamic traffic warnings. In this work, we analyze the impact on credibility and propose improved interaction mechanisms to enhance perceived credibility of navigation systems. We improve route selection and the integration of dynamic traffic warnings by optimizing route comparability with relevance-based information display. Further, we show how bidirectional communication between driver and device can be enhanced to achieve a better mapping between device behavior and driver intention. We evaluated the proposed mechanisms in a comparative user study and present results that confirm positive effects on perceived credibility

Interaction Weaknesses of Personal Navigation Devices

Automotive navigation systems, especially portable navigation devices (PNDs), are gaining popularity worldwide. Drivers increasingly rely on these devices to guide them to their destination. Some follow them almost blindly, with devastating consequences if the routing goes wrong. Wrong messages as well as superfuous and unnecessary messages can potentially reduce the credibility of those devices. We performed a comparative study with current PNDs from different vendors and market segments, in order to assess the extent of this problem and how it is related to the interaction between device and driver. In this paper, we report the corresponding results and identify multiple interaction weaknesses that are prevalent throughout all tested device classes

Wildflower areas within revitalized agricultural matrices boost small mammal populations but not breeding Barn Owls

Agro-ecosystems have recently experienced dramatic losses of biodiversity due to more intensive production methods. In order to increase species diversity, agri-environment schemes provide subsidies to farmers who devote a fraction of their land to ecological compensation areas (ECAs). Several studies have shown that invertebrate biodiversity is actually higher in ECAs than in nearby intensively cultivated farmland. It remains poorly understood, however, to what extent ECAs also favour vertebrates, such as small mammals and their predators, which would contribute to restoring functional food chains within revitalised agricultural matrices. We studied small mammal populations among eight habitat types—including wildflower areas, a specific ECA in Switzerland—and habitat selection (radiotracking) by the Barn Owl Tyto alba, one of their principal predators. Our prediction was that habitats with higher abundances of small mammals would be more visited by foraging Barn Owls during the period of chicks' provisioning. Small mammal abundance tended to be higher in wildflower areas than in any other habitat type. Barn Owls, however, preferred to forage in cereal fields and grassland. They avoided all types of crops other than cereals, as well as wildflower areas, which suggests that they do not select their hunting habitat primarily with respect to prey density. Instead of prey abundance, prey accessibility may play a more crucial role: wildflower areas have a dense vegetation cover, which may impede access to prey for foraging owls. The exploitation of wildflower areas by the owls might be enhanced by creating open foraging corridors within or around wildflower areas. Wildflower areas managed in that way might contribute to restore functional links in food webs within agro-ecosystem

Neighborhood Structure Configuration Models

We develop a new method to efficiently sample synthetic networks that preserve the d-hop neighborhood structure of a given network for any given d. The proposed algorithm trades off the diversity in network samples against the depth of the neighborhood structure that is preserved. Our key innovation is to employ a colored Configuration Model with colors derived from iterations of the so-called Color Refinement algorithm. We prove that with increasing iterations the preserved structural information increases: the generated synthetic networks and the original network become more and more similar, and are eventually indistinguishable in terms of centrality measures such as PageRank, HITS, Katz centrality and eigenvector centrality. Our work enables to efficiently generate samples with a precisely controlled similarity to the original network, especially for large networks

Improving the visibility of minorities through network growth interventions

Improving the position of minorities in networks via interventions is a challenge of high theoretical and societal importance. In this work, we examine how different network growth interventions impact the position of minority nodes in degree rankings over time. We distinguish between two kinds of interventions: (i) group size interventions, such as introducing quotas, that regulate the ratio of incoming minority and majority nodes; and (ii) behavioural interventions, such as homophily, i.e. varying how groups interact and connect to each other. We find that even extreme group size interventions do not have a strong effect on the position of minorities in rankings if certain behavioural changes do not manifest at the same time. For example, minority representation in rankings is not increased by high quotas if the actors in the network do not adopt homophilic behaviour. As a result, a key finding of our research is that in order for the visibility of minorities to improve, group size and behavioural interventions need to be coordinated. Moreover, their potential benefit is highly dependent on pre-intervention conditions in social networks. In a real-world case study, we explore the effectiveness of interventions to reach gender parity in academia. Our work lays a theoretical and computational foundation for further studies aiming to explore the effectiveness of interventions in growing networks

Value of arterial blood gas analysis in patients with acute dyspnea: an observational study

ABSTRACT: INTRODUCTION: The diagnostic and prognostic value of arterial blood gas analysis (ABGA) parameters in unselected patients presenting with acute dyspnea to the Emergency Department (ED) is largely unknown. METHODS: We performed a post-hoc analysis of two different prospective studies to investigate the diagnostic and prognostic value of ABGA parameters in patients presenting to the ED with acute dyspnea. RESULTS: We enrolled 530 patients (median age 74 years). ABGA parameters were neither useful to distinguish between patients with pulmonary disorders and other causes of dyspnea nor to identify specific disorders responsible for dyspnea. Only in patients with hyperventilation from anxiety disorder, the diagnostic accuracy of pH and hypoxemia rendered valuable with an area under the receiver operating characteristics curve (AUC) of 0.86. Patients in the lowest pH tertile more often required admission to Intensive Care Unit (28% vs 12% in the first tertile, P >0.001) and had higher in-hospital (14% vs 5%, P =0.003) and 30-day mortality (17% vs 7%, P =0.002). Cumulative mortality rate was higher in the first (37%), than in the second (28%), and the third tertile (23%, P =0.005) during 12 months follow-up. pH at presentation was an independent predictor of 12-month mortality in multivariable Cox proportional hazard analysis both for patients with pulmonary (P =0.043) and non-pulmonary disorders (P =0.038). CONCLUSIONS: ABGA parameters provide limited diagnostic value in patients with acute dyspnea, but pH is an independent predictor of 12 months mortality

Midregional pro-Adrenomedullin in addition to b-type natriuretic peptides in the risk stratification of patients with acute dyspnea: an observational study

The identification of patients at highest risk for adverse outcome who are presenting with acute dyspnea to the emergency department remains a challenge. This study investigates the prognostic value of the newly described midregional fragment of the pro-Adrenomedullin molecule (MR-proADM) alone and combined to B-type natriuretic peptide (BNP) or N-terminal proBNP (NT-proBNP) in patients with acute dyspnea.; We conducted a prospective, observational cohort study in the emergency department of a University Hospital and enrolled 287 unselected, consecutive patients (48% women, median age 77 (range 68 to 83) years) with acute dyspnea.; MR-proADM levels were elevated in non-survivors (n = 77) compared to survivors (median 1.9 (1.2 to 3.2) nmol/L vs. 1.1 (0.8 to 1.6) nmol/L; P > 0.001). The areas under the receiver operating characteristic curve (AUC) to predict 30-day mortality were 0.81 (95% CI 0.73 to 0.90), 0.76 (95% CI 0.67 to 0.84) and 0.63 (95% CI 0.53 to 0.74) for MR-proADM, NT-proBNP and BNP, respectively (MRproADM vs. NTproBNP P = 0.38; MRproADM vs. BNP P = 0.009). For one-year mortality the AUC were 0.75 (95% CI 0.69 to 0.81), 0.75 (95% CI 0.68 to 0.81), 0.69 (95% CI 0.62 to 0.76) for MR-proADM, NT-proBNP and BNP, respectively without any significant difference. Using multivariate linear regression analysis, MR-proADM strongly predicted one-year all-cause mortality independently of NT-proBNP and BNP levels (OR = 10.46 (1.36 to 80.50), P = 0.02 and OR = 24.86 (3.87 to 159.80) P = 0.001, respectively). Using quartile approaches, Kaplan-Meier curve analyses demonstrated a stepwise increase in one-year all-cause mortality with increasing plasma levels (P > 0.0001). Combined levels of MR-proADM and NT-proBNP did risk stratify acute dyspneic patients into a low (90% one-year survival rate), intermediate (72 to 82% one-year survival rate) or high risk group (52% one-year survival rate).; MR-proADM alone or combined to NT-proBNP has a potential to assist clinicians in risk stratifying patients presenting with acute dyspnea regardless of the underlying disease