Modified navigation instructions for spatial navigation assistance systems lead to incidental spatial learning

© 2017 Gramann, Hoepner and Karrer-Gauss. Spatial cognitive skills deteriorate with the increasing use of automated GPS navigation and a general decrease in the ability to orient in space might have further impact on independence, autonomy, and quality of life. In the present study we investigate whether modified navigation instructions support incidental spatial knowledge acquisition. A virtual driving environment was used to examine the impact of modified navigation instructions on spatial learning while using a GPS navigation assistance system. Participants navigated through a simulated urban and suburban environment, using navigation support to reach their destination. Driving performance as well as spatial learning was thereby assessed. Three navigation instruction conditions were tested: (i) a control group that was provided with classical navigation instructions at decision points, and two other groups that received navigation instructions at decision points including either (ii) additional irrelevant information about landmarks or (iii) additional personally relevant information (i.e., individual preferences regarding food, hobbies, etc.), associated with landmarks. Driving performance revealed no differences between navigation instructions. Significant improvements were observed in both modified navigation instruction conditions on three different measures of spatial learning and memory: subsequent navigation of the initial route without navigation assistance, landmark recognition, and sketch map drawing. Future navigation assistance systems could incorporate modified instructions to promote incidental spatial learning and to foster more general spatial cognitive abilities. Such systems might extend mobility across the lifespan

The Triangle Groups (2, 4, 5) and (2, 5, 5) are not Systolic

In this paper we provide new examples of hyperbolic but nonsystolic groups by showing that the triangle groups (2, 4, 5) and (2, 5, 5) are not systolic. Along the way we prove some results about subsets of systolic complexes stable under involutions

The Angioarchitecture of the Lewis Lung Carcinoma in Laboratory Mice (A Light Microscopic and Scanning Electron Microscopic Study)

53 Lewis lung carcinomas implanted subcutaneously into C57BL/6-mice were examined. The animals were killed at various stages of tumor growth (TG) and prepared for histology and for scanning electron microscopy (critical-point-dried tissue; vascular corrosion casts). Prior to casting animals were rinsed using different perfusion pressures. Casting was done by manual injection of the resin, whereby different influx-rates were applied resulting in low, medium and high pressure preparations. We discern 3 phases of tumor angiogenesis (TA) occurring during 4 stages of TG among which vasodilation establishes the first reaction of the host vascular system to a growing tumor implant. During this stage 1 of TG, tumor nidation, nearby sinusoidal dilated host capillaries form globular outgrowings (phase 1 of TA) Subsequently radially arranged sprouts, which preferentially arise from venous host vessels, grow into the centre of the implant (phase 2 of TA). Stage 2 of TG, early tumor growth, is characterized by necrosis of the central tumor tissue and the development of a central avascular cavity. Thus the tumor vascular system is organized like a hollow sphere with a central cavity and a peripheral vascular envelope with large vessels embracing the tumor and centrifugally growing vascular sprouts, which arise from the venous part of the vascular envelope and invade the surrounding host tissue (phase 3 of TA). During stage 3 of TG, late tumor growth, many vessels of the basket-like vascular envelope obliterate. In stage 4 of TG, prefinal phase, the peripheral vascular density decreases continuously. Thus vascular sprouting and proliferation of viable tumor cells is confined to basal regions of the tumor

A Spectral Algorithm with Additive Clustering for the Recovery of Overlapping Communities in Networks

This paper presents a novel spectral algorithm with additive clustering designed to identify overlapping communities in networks. The algorithm is based on geometric properties of the spectrum of the expected adjacency matrix in a random graph model that we call stochastic blockmodel with overlap (SBMO). An adaptive version of the algorithm, that does not require the knowledge of the number of hidden communities, is proved to be consistent under the SBMO when the degrees in the graph are (slightly more than) logarithmic. The algorithm is shown to perform well on simulated data and on real-world graphs with known overlapping communities.Comment: Journal of Theoretical Computer Science (TCS), Elsevier, A Para\^itr

An efficient and principled method for detecting communities in networks

A fundamental problem in the analysis of network data is the detection of network communities, groups of densely interconnected nodes, which may be overlapping or disjoint. Here we describe a method for finding overlapping communities based on a principled statistical approach using generative network models. We show how the method can be implemented using a fast, closed-form expectation-maximization algorithm that allows us to analyze networks of millions of nodes in reasonable running times. We test the method both on real-world networks and on synthetic benchmarks and find that it gives results competitive with previous methods. We also show that the same approach can be used to extract nonoverlapping community divisions via a relaxation method, and demonstrate that the algorithm is competitively fast and accurate for the nonoverlapping problem.Comment: 14 pages, 5 figures, 1 tabl

Effects of Contact Network Models on Stochastic Epidemic Simulations

The importance of modeling the spread of epidemics through a population has led to the development of mathematical models for infectious disease propagation. A number of empirical studies have collected and analyzed data on contacts between individuals using a variety of sensors. Typically one uses such data to fit a probabilistic model of network contacts over which a disease may propagate. In this paper, we investigate the effects of different contact network models with varying levels of complexity on the outcomes of simulated epidemics using a stochastic Susceptible-Infectious-Recovered (SIR) model. We evaluate these network models on six datasets of contacts between people in a variety of settings. Our results demonstrate that the choice of network model can have a significant effect on how closely the outcomes of an epidemic simulation on a simulated network match the outcomes on the actual network constructed from the sensor data. In particular, preserving degrees of nodes appears to be much more important than preserving cluster structure for accurate epidemic simulations.Comment: To appear at International Conference on Social Informatics (SocInfo) 201

Solar-Wind Bulk Velocity Throughout the Inner Heliosphere from Multi-Spacecraft Measurements

We extrapolate solar-wind bulk velocity measurements for different in-ecliptic heliospheric positions by calculating the theoretical time lag between the locations. The solar-wind bulk velocity dataset is obtained from in-situ plasma measurements by STEREO A and B, SOHO, Venus Express, and Mars Express. During their simultaneous measurements between 2007 and 2009 we find typical solar activity minimum conditions. In order to validate our extrapolations of the STEREO A and B data, we compare them with simultaneous in-situ observations from the other spacecraft. This way of cross-calibration we obtain a measure for the goodness of our extrapolations over different heliospheric distances. We find that a reliable solar-wind dataset can be provided in case of a longitudinal separation less than 65 degrees. Moreover, we find that the time lag method assuming constant velocity is a good basis to extrapolate from measurements in Earth orbit to Venus or to Mars. These extrapolations might serve as a good solar-wind input information for planetary studies of magnetospheric and ionospheric processes. We additionally show how the stream-stream interactions in the ecliptic alter the bulk velocity during radial propagation