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A twenty-one-year old primigravida presented two weeks postpartum with new onset of behavioral alteration and irrelevant talking without fever, headache, or seizures. Magnetic resonance imaging (MRI) of brain showed a lesion with diffusion restriction in splenium of corpus callosum. A possibility of postpartum psychosis was considered after ruling out various etiologies for splenium hyperintense lesion. Near complete resolution of symptoms was noted after initiation of antipsychotic medications. Literature has described multiple etiologies for lesions involving splenium of corpus callosum on brain imaging. We present this case as a unique clinical presentation of splenial pathology in the form of postpartum psychosis.

Dynamic traffic flow models are essential for obtaining information about the time evolution of variables describing the traffic flow phenomena and have a critical role in the development and implementation of real-time applications such as Intelligent Transportation Systems. Macroscopic traffic flow models that treat the traffic as a continuum are preferred for such applications. But, existing macroscopic models characterize homogeneous traffic, and may not be directly applicable to capture the vehicle heterogeneity seen on Indian roads. To address this issue, a non-continuum macroscopic dynamic traffic flow model based on the lumped-parameter approach was developed in this study. The model was developed based on the conservation of vehicles equation and a dynamic speed equation, incorporating an empirically developed traffic stream model, which is an important contribution of this study. Using this model, an estimation scheme has been developed based on the Kalman filtering technique to estimate traffic...

Analysis of traffic at a signalized intersection requires quantification of the number of vehicles in the queue and the corresponding delay. Such analyses can be used for optimal signal con...

Capturing real-time traffic system characteristics is a primary step in any intelligent transportation system (ITS) application. The majority of the traffic sensors used to capture real-tim...

Predicting and providing information about bus arrival time to passengers accurately is a very important aspect of advanced public transportation systems (APTS), a major functional area of ...

Road traffic congestion, which occurs when the traffic demand exceeds the operational capacity of the roadway, has become a serious problem all over the world. Traffic signals are effective in managing the traffic demand if properly designed. Traditionally, signal design has been carried out based on the objective of minimizing the overall queue and associated delays at upstream sections and has not considered the effect on downstream sections and midblock regions. Efficiency of signals may be improved if their design takes this factor into account, which is attempted in the present study. In this paper, a control scheme that regulates the traffic density in the downstream section was developed using a macroscopic-model-based approach with traffic density and speed as the state variables of interest. These state variables were estimated based on a Kalman filter approach. The performance of the estimation scheme was corroborated using field data. A closed-loop system with the developed control sche...

We consider an evolving preferential attachment random graph model where at discrete times a new node is attached to an old node, selected with probability proportional to a superlinear function of its degree. For such schemes, it is known that the graph evolution condenses, that is a.s. in the limit graph there will be a single random node with infinite degree, while all others have finite degree. In this note, we establish a.s. law of large numbers type limits and fluctuation results, as $n\uparrow\infty$, for the counts of the number of nodes with degree $k\geq 1$ at time $n\geq 1$. These limits rigorously verify and extend a physical picture of Krapivisky, Redner and Leyvraz (2000) on how the condensation arises with respect to the degree distribution., 21 pages

We formulate a model for the mass exchange between oil at and below the sea surface. This is a particularly important aspect of modeling oil spills. Surface and subsurface oil have different chemical and transport characteristics and lumping them together would compromise the accuracy of the resulting model. Without observational or computational constraints, it is thus not possible to quantitatively predict oil spills based upon partial field observations of surface and/or sub-surface oil. The primary challenge in capturing the mass exchange is that the principal mechanisms are on the microscale. This is a serious barrier to developing practical models for oil spills that are capable of addressing questions regarding the fate of oil at the large spatio-temporal scales, as demanded by environmental questions. We use upscaling to propose an environmental-scale model which incorporates the mass exchange between surface and subsurface oil due to oil droplet dynamics, buoyancy effects, and sea surface and subsurface mechanics. While the mass exchange mechanism detailed here is generally applicable to oil transport models, it addresses the modeling needs of a particular to an oil spill model [1]. This transport model is designed to capture oil spills at very large spatio-temporal scales. It accomplishes this goal by specializing to shallow-water environments, in which depth averaging is a perfectly good approximation for the flow, while at the same time retaining mass conservation of oil over the whole oceanic domain., Comment: 18 pages, 6 figures

A rear-end collision is one of the most frequent accidents occurring on roadways. In this paper, a model-based longitudinal collision avoidance algorithm is developed for heavy commercial road vehicles to avoid rear-end collisions. This paper focuses on the inclusion of the dynamics of the pneumatic brake system in the collision avoidance algorithm. The developed algorithm also considers the dynamic behaviour of the heavy vehicle during braking such as the dynamic load transfer, the dynamic brake force distribution between the wheels and the maximum traction available at the tyre–road interface. The pressure transients in the brake chamber are modelled as a linear first-order dynamic system with a time delay. Commercially available vehicle dynamic simulation software, TruckSim, is used for simulating the developed control algorithm for realistic traffic scenarios with different loading and road conditions. The results obtained from the simulations are compared with the experimental results obtained from a hardware-in-the-loop system and the simulation results are found to be promising.

We investigate the problem of shaping radially symmetric annular beams into desired intensity patterns along the optical axis. Within the Fresnel approximation, we show that this problem can be expressed in a variational form equivalent to the one arising in phase retrieval. Using the uncertainty principle we prove rigorous lower bounds on the functional that capture how the various physical parameters in the problem determine the accuracy of the beam shaping. We also use the method of stationary phase to construct a natural ansatz for a minimizer in the short wavelength limit. We illustrate the implications of our results by applying the method of stationary phase coupled with the Gerchberg-Saxton algorithm to beam shaping problems arising in remote delivery of beams and pulses., Comment: 34 Pages, 6 figures, 1 appendix; revised figures and discussion

2014 International Oil Spill Conference CARTHE (http://carthe.org/) is a Gulf of Mexico Research Initiative (GoMRI) consortium established through a competitive peer-reviewed selection process. CARTHE comprises 26 principal investigators from 14 universities and research institutions distributed across four Gulf of Mexico states and other four states. It fuses into one group investigators with unique scientific and technical knowledge and extensive publications related to oil fate/transport processes, oceanic and atmospheric turbulence, air-sea interactions, tropical cyclones and winter storms, and coastal and nearshore modeling and observations. Our primary goal is to accurately predict the fate of hydrocarbons released into the environment. Achieving this goal is particularly challenging since petroleum releases into the environment interact with natural processes across six orders of magnitude of time and space scales. We are developing a multi-scale modeling tool by incorporating state-of-the-art hydrophysical models, each applicable for a restricted range of scales, into a single, interconnected modeling system to predict the physical dispersal of hydrocarbons across scales ranging from the microscale at the wellhead to oceanic and atmospheric mesoscales. CARTHE is also conducting novel in-situ observations and laboratory experiments specifically designed for quantifying submesoscale dispersion as well as for both model validation and parameterization. Finally, we are providing a robust set of uncertainty metrics and analysis tools to assess model performance and quantify predictive uncertainty. This research was made possible by a grant from BP/The Gulf of Mexico Research Initiative. This research was made possible by a grant from BP/The Gulf of Mexico Research Initiative.

Congestion and associated traffic safety are the major challenges for transportation systems all over the world in recent years. Congestion occurs when traffic demand exceeds the operational capacity of the roadway. Better management of infrastructure is required in improving the operational capacity. Traffic signals are one of the most popular traffic control strategies that have been adopted for managing the demand and to reduce congestion; but if not properly designed will lead to excessive delay and increase in travel time. Therefore, signals need to be designed based on theory of traffic flow that requires a good understanding of the traffic system. The present study proposes a macroscopic model based control scheme for Indian traffic conditions. Traffic density and speed are used as the state variables to characterize the system and the developed control scheme regulates the density inside the section.

In this paper we investigate the propagation of conical waves in nonlinear media. In particular, we are interested in the effects resulting from applying a Gaussian apodization to an ideal nondiffracting wave. First, we present a multiple scales approach to derive amplitude equations for weakly nonlinear conical waves from a governing equation of cubic nonlinear Schrodinger type. From these equations we obtain asymptotic solutions for the linear and the weakly nonlinear problem for which we state several uniform estimates that describe the deviation from the ideal nondiffracting solution. Moreover, we show numerical simulations based on an implementation of our amplitude equations to support and illustrate our analytical results.

The gradual decline of oil reserves and the increasing demand for energy have resulted in automotive manufacturers developing new environmentally friendly vehicles such as electric and hybrid vehicles. Selection of the correct hybrid configuration for a given driving condition is very important since it affects the performance of the vehicle and its fuel economy. This paper focuses on a detailed parametric analysis of a Series Hybrid Electric vehicle (SHEV). The objective of this paper was to develop a SHEV powertrain by initial parameter matching and component sizing, followed by its optimization for given design constraints. This involved study and calculation of components power specifications based on vehicle dynamics. Initial parameterization was followed by optimization to meet the design objective. The simulation of the optimized SHEV was done in the software ADVISOR for an Indian driving cycle (IDC). Based on the simulation results, an optimum range of the powertrain components was established.

In this paper, a collision avoidance algorithm (CAA) has been proposed using variable time headway considering heterogeneous traffic. The time headway used in the proposed CAA was tuned based on the traffic scenarios, the host vehicle’s load conditions and the type of the lead vehicle that the host vehicle encounters in the traffic. The proposed variable time headway would help to avoid the intervention of the collision avoidance system during normal driving and gain driver’s acceptance. The CAA was evaluated using a hardware-in-the-loop (HiL) experimental set-up integrated with the vehicle dynamic simulation software IPG/TruckMaker® for different categories of lead vehicles such as 2/3 wheelers, passenger cars, light commercial road vehicles (LCVs) and heavy commercial road vehicles (HCVs). From the results, it was observed that while following a HCV, a smaller time headway was sufficient to prevent a collision compared to following a passenger car, LCV and 2/3 wheeler.

Regenerative braking is applied only at the driven wheels in electric and hybrid vehicles. The presence of brake force only at the driven wheels reduces the lateral traction limit of the corresponding tires. This impacts the vehicle lateral response, particularly while applying the regenerative brake in a turn. In this paper, a detailed study was made on the impact of regenerative brake on the vehicle lateral response in front wheel drive and rear wheel drive configurations on dry and wet asphalt road surfaces. Simulations were done considering a typical set of vehicle parameters with the IPG CarMaker® software for different drive conditions and braking configurations along the same reference track. The steering wheel angle, yaw rate, lateral acceleration, vehicle slip angle, and tire forces were obtained. Further, they were compared against the conventional all wheel friction brake configuration. The regenerative braking configuration that had the most impact on vehicle lateral response was analyzed and response variations were quantified.

A model-based scheme has been developed in this paper to estimate the number of vehicles in queue and the total delay, which are typical measures for characterizing a signalized intersection. The estimation was first carried out by using the input-output and queue accumulation polygon methods. These were evaluated by using data from two instrumented intersections in the city of Lincoln, Nebraska. However, the estimates did not agree well with the actual data primarily because of the errors in counts obtained from the automated detectors. Hence, an analysis of the characteristics of the errors was carried out. A model-based estimation approach using the Kalman filter was then developed. Suitable modifications were further applied to the estimation process by incorporating calibration constants for particular site/traffic conditions in the Kalman filter estimation scheme. The results obtained were promising, indicating that the scheme could be used for performance analysis of signalized intersection...

We develop reduced, stochastic models for high dimensional, dissipative dynamical systems that relax very slowly to equilibrium and can encode long term memory. We present a variety of empirical and first principles approaches for model reduction, and build a mathematical framework for analyzing the reduced models. We introduce the notions of universal and asymptotic filters to characterize `optimal' model reductions for sloppy linear models. We illustrate our methods by applying them to the practically important problem of modeling evaporation in oil spills., Comment: 48 Pages, 13 figures. Paper dedicated to the memory of Leo Kadanoff

We connect the theories of the deformation of elastic surfaces and phase surfaces arising in the description of almost periodic patterns. In particular, we show parallels between asymptotic expansions for the energy of elastic surfaces in powers of the thickness $h$ and the free energy for almost periodic patterns expanded in powers of $\epsilon$, the inverse aspect ratio of the pattern field. For sheets as well as patterns, the resulting energy can be expressed in terms of natural geometric invariants, the first and second fundamental forms of the elastic surface, respectively the phase surface. We discuss various results for these energies and also address some of the outstanding questions. We extend previous work on point (in 2D) and loop (in 3D) disclinations and connect their topological indices with the condensation of Gaussian curvature of the phase surface. Motivated by this connection with the charge and spin of pattern quarks and leptons, we lay out an ambitious program to build a multi-scale universe inspired by patterns in which the short (spatial and temporal) scales are given by a nearly periodic microstructure and whose macroscopic/slowly varying/averaged behaviors lead to a hierarchy of structures and features on much longer scales including analogues to quarks and leptons, dark matter, dark energy and inflationary cosmology. One of our new findings is an interpretation of dark matter as the energy density in a pattern field. The associated gravitational forces naturally result in galactic rotation curves that are consistent with observations, while simultaneously avoiding some of the small-scale difficulties of the standard $\Lambda$CDM paradigm in cosmology., Comment: 39 pages, 9 figures, submitted to Studies in Applied Mathematics, Dave Benney special issue