Bright Ultraviolet Regions and Star Formation Characteristics in Nearby Dwarf Galaxies

We compare star formation in the inner and outer disks of 11 dwarf Irregular galaxies (dIm) within 3.6 Mpc. The regions are identified on GALEX near-UV images, and modeled with UV, optical, and near-IR colors to determine masses and ages. A few galaxies have made 10^5-10^6 Msun complexes in a starburst phase, while others have not formed clusters in the last 50 Myrs. The maximum region mass correlates with the number of regions as expected from the size-of-sample effect. We find no radial gradients in region masses and ages, even beyond the realm of Halpha emission, although there is an exponential decrease in the luminosity density and number density of the regions with radius. Halpha is apparently lacking in the outer parts only because nebular emission around massive stars is too faint to see. The outermost regions for the 5 galaxies with HI data formed at average gas surface densities of 1.9-5.9 Msun/pc2. These low average densities imply either that local gas densities are high or sub-threshold star formation is possible. The distribution of regions on a log Mass - log age plot is is usually uniform along log age for equal intervals of log Mass. This uniformity results from either an individual region mass that varies as 1/age or a region disruption probability that varies as 1/age. A correlation between fading-corrected surface brightness and age suggests the former.Comment: Astronomical Journal, in press for November 2009. 34 pages, 18 figures, 5 table

Structural brain correlates of childhood inhibited temperament: an ENIGMA-Anxiety Mega-analysis

NWORubicon 019.201SG.022Pathways through Adolescenc

Modeling multi-modal traffic in cities

We propose a new functional form for the 3D-MFD. The 3D-MFD links the number of cars and buses in an urban network to the total travel production. The parameters of the functional form are derived from the structure and topology of the road and bus network. The physical interactions of vehicles are described by a single parameter. We apply the methodology to two empirical data sets from London and Zurich, and discuss policy relevant applications of the functional form

Capturing network properties with a functional form for the multi-modal macroscopic fundamental diagram

In urban road networks, the interactions between different modes can clearly impact the overall travel production. Although those interactions can be quantified with the multi-modal macroscopic fundamental diagram; so far, no functional form exists for this diagram to explicitly capture operational and network properties. In this paper, we propose a methodology to generate such functional form, and we show its applicability to the specific case of a bi-modal network with buses and cars. The proposed functional form has two components. First, a three dimensional lower envelope limits travel production to the theoretical best-case situation for any given number of vehicles for the different modes. The lower envelopes parameters are derived from topology and operational features of the road network. Second, a smoothing parameter quantifies how interactions between all vehicle types reduce travel production from the theoretical best-case. The smoothing parameter is estimated with network topology and traffic data. In the case no traffic data is available, our functional form is still applicable. The lower envelope can be approximated assuming fundamental parameters of traffic operations. For the smoothing parameter, we show that it always hold similar values even for different networks, making its approximation also possible. This feature of the proposed functional form is an advantage compared to curve fitting, as it provides a reasonable shape for the multi-modal macroscopic fundamental diagram irrespective of traffic data availability. The methodology is illustrated and validated using simulation and empirical data sets from London and Zurich

How many cars in the city are too many?: Towards finding the optimal modal split for a multi-modal urban road network

Interactions among different modes or vehicle classes in urban road networks affect the network performance in different and complex ways. Thus, an answer to the question of “how many cars are too many for a city?” is not trivial. However, multi-modal macroscopic fundamental diagrams (MFD) offer a novel opportunity to answer this question. So far, no methodology exists to estimate multi-modal MFDs resulting from arbitrary multi-modal interactions. In this paper, we propose a methodology to capture additional delays in the shape of the MFD and derive an approach for estimating multi-modal MFDs thereof. The influence on the MFD shape is established using the two-fluid theory of urban traffic by defining pairwise copula functions between travel times of each mode. In contrast to many existing approaches, the presented approach retains individual mode’s speed information. We show the approach’s applicability with a tri-modal case of bicycles, buses and cars with empirical data from Amsterdam (NL) and London (UK). Although the approach is not limited to this specific tri-modal case, we use the example to discuss the initial policy question by deriving optimal modal splits for a given accumulation of travelers. Last, we compare the new approach to existing estimation methods for bi-modal MFDs describing car and bus traffic

A general framework for multi-modal macroscopic fundamental diagrams (MFD)

Car traffic streams in urban networks are rarely homogeneous and usually contain some disturbances by other transport modes of different physical characteristics, e.g. bicycles or buses. Inevitably, these interactions decrease the network’s capacity and performance, but, so far, no methodology exists to assess the local interaction effects on the network level as for instance described in the macroscopic fundamental diagram (MFD). This paper proposes an analytical framework to link general microscopic disturbances to the shape of the MFD and thus to network capacity. The influence of disturbances is established by linking the two-fluid theory of urban traffic to travel times derived from the MFD. We apply the framework to the interactions of bicycles, buses and cars with an empirical calibration using data from London (UK). This framework allows to identify the maximum possible travel production of a given network and its associated modal split, as well as to identify for a given demand the optimal modal split

How many cars in the city are too many?: Towards finding the optimal modal split for a multi-modal urban road network

Interactions among different modes or vehicle classes in urban road networks affect the network performance in different and complex ways. Thus, an answer to the question of “how many cars are too many for a city?” is not trivial. However, multi-modal macroscopic fundamental diagrams (MFD) offer a novel opportunity to answer this question. So far, no methodology exists to estimate multi-modal MFDs resulting from arbitrary multi-modal interactions. In this paper, we propose a methodology to capture additional delays in the shape of the MFD and derive an approach for estimating multi-modal MFDs thereof. The influence on the MFD shape is established using the two-fluid theory of urban traffic by defining pairwise copula functions between travel times of each mode. In contrast to many existing approaches, the presented approach retains individual mode’s speed information. We show the approach’s applicability with a tri-modal case of bicycles, buses and cars with empirical data from Amsterdam (NL) and London (UK). Although the approach is not limited to this specific tri-modal case, we use the example to discuss the initial policy question by deriving optimal modal splits for a given accumulation of travelers. Last, we compare the new approach to existing estimation methods for bi-modal MFDs describing car and bus traffic.Transport and Plannin