142,836 research outputs found
The Necessity of Developing Multimodal Transportation in Croatia as a Factor of Meeting the European Union Transportation Policy Recommendation and a Beneficial Factor for the Development of Croatian Economy
The paper emphasises the necessity of developing multimodal transportation solutions in Croatia.
Croatian transport infrastructure is not at a satisfactory stage of development, and, due to Croatia’s
geographical position, the development of multimodal transportation is a beneficial factor for the
development of the country’s economy. European Union recommends multimodal solution as less
polluting and more energy efficient. Further, it is shown that the modernisation of transportation system
in Croatia, by developing a multimodal transportation system, represents a comparative advantage
factor for Croatian economy. The methods used are a comprehensive literature research, methods of
analysis, synthesis and comparison method, as well as methods of collecting secondary sources of
research. The aim of the paper is to point out the importance of developing multimodal transportation
as a significant factor for economy development as well as contribution to raising awareness of this
problem
Imaging markers of disability in aquaporin-4 immunoglobulin G seropositive neuromyelitis optica: a graph theory study
Neuromyelitis optica spectrum disorders lack imaging biomarkers associated with disease course and supporting prognosis. This complex and heterogeneous set of disorders affects many regions of the central nervous system, including the spinal cord and visual pathway. Here, we use graph theory-based multimodal network analysis to investigate hypothesis-free mixed networks and associations between clinical disease with neuroimaging markers in 40 aquaporin-4-immunoglobulin G antibody seropositive patients (age = 48.16 ± 14.3 years, female:male = 36:4) and 31 healthy controls (age = 45.92 ± 13.3 years, female:male = 24:7). Magnetic resonance imaging measures included total brain and deep grey matter volumes, cortical thickness and spinal cord atrophy. Optical coherence tomography measures of the retina and clinical measures comprised of clinical attack types and expanded disability status scale were also utilized. For multimodal network analysis, all measures were introduced as nodes and tested for directed connectivity from clinical attack types and disease duration to systematic imaging and clinical disability measures. Analysis of variance, with group interactions, gave weights and significance for each nodal association (hyperedges). Connectivity matrices from 80% and 95% F-distribution networks were analyzed and revealed the number of combined attack types and disease duration as the most connected nodes, directly affecting changes in several regions of the central nervous system. Subsequent multivariable regression models, including interaction effects with clinical parameters, identified associations between decreased nucleus accumbens (β = −0.85, P = 0.021) and caudate nucleus (β = −0.61, P = 0.011) volumes with higher combined attack type count and longer disease duration, respectively. We also confirmed previously reported associations between spinal cord atrophy with increased number of clinical myelitis attacks. Age was the most important factor associated with normalized brain volume, pallidum volume, cortical thickness and the expanded disability status scale score. The identified imaging biomarker candidates warrant further investigation in larger-scale studies. Graph theory-based multimodal networks allow for connectivity and interaction analysis, where this method may be applied in other complex heterogeneous disease investigations with different outcome measures
Measuring stress and cognitive load effects on the perceived quality of a multimodal dialogue system
In this paper we present the results of a pilot study investigating the impact of stress and cognitive load on the perceived interaction quality of a multimodal dialogue system for crisis management. Four test subjects interacted with the system in four differently configured trials aiming to induce low/high levels of stress and cognitive load. To measure the level of stress and cognitive load physiological sensors and subjective ratings were collected. After each trial the subjects filled in an evaluation questionnaire regarding the system interaction quality. In the end we conducted an in-depth interview with each subject. The trials were recorded with a webcam to facilitate the behaviour analysis. Results showed that both factors have an influence on the way subjects perceived the interaction quality, whereas the cognitive load seems to have a higher impact. Further quantitative experiments are needed in order to validate the results and quantify the weight of each factor. \u
Multimodal nested sampling: an efficient and robust alternative to MCMC methods for astronomical data analysis
In performing a Bayesian analysis of astronomical data, two difficult
problems often emerge. First, in estimating the parameters of some model for
the data, the resulting posterior distribution may be multimodal or exhibit
pronounced (curving) degeneracies, which can cause problems for traditional
MCMC sampling methods. Second, in selecting between a set of competing models,
calculation of the Bayesian evidence for each model is computationally
expensive. The nested sampling method introduced by Skilling (2004), has
greatly reduced the computational expense of calculating evidences and also
produces posterior inferences as a by-product. This method has been applied
successfully in cosmological applications by Mukherjee et al. (2006), but their
implementation was efficient only for unimodal distributions without pronounced
degeneracies. Shaw et al. (2007), recently introduced a clustered nested
sampling method which is significantly more efficient in sampling from
multimodal posteriors and also determines the expectation and variance of the
final evidence from a single run of the algorithm, hence providing a further
increase in efficiency. In this paper, we build on the work of Shaw et al. and
present three new methods for sampling and evidence evaluation from
distributions that may contain multiple modes and significant degeneracies; we
also present an even more efficient technique for estimating the uncertainty on
the evaluated evidence. These methods lead to a further substantial improvement
in sampling efficiency and robustness, and are applied to toy problems to
demonstrate the accuracy and economy of the evidence calculation and parameter
estimation. Finally, we discuss the use of these methods in performing Bayesian
object detection in astronomical datasets.Comment: 14 pages, 11 figures, submitted to MNRAS, some major additions to the
previous version in response to the referee's comment
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