Probabilistic Simulation of a Railway Timetable

Railway systems are often highly utilized, which makes them vulnerable to delay propagation. In order to minimize delays timetables are desired to be robust, a property that is often estimated by simulating the respective timetable for different deterministic delay values. To achieve an accurate estimation under consideration of uncertain delays many simulation runs need to be executed. Most established simulation systems additionally use microscopic models of the railway systems, which further increases the simulations running times and makes them applicable rather for small areas of interest for complexity reasons. In this paper, we present a probabilistic, symbolic simulation algorithm for given timetables, this means we do not simulate individual executions, but all possible executions at once. We use a macroscopic model of the railway infrastructure as input. This way we consider the railway systems in less detail but are able to examine certain performance indicators for larger areas. For a given input model this simulation computes exact results. We implement the algorithm, examine its results, and discuss possible improvements of this approach

Guided Proofreading of Automatic Segmentations for Connectomics

Automatic cell image segmentation methods in connectomics produce merge and split errors, which require correction through proofreading. Previous research has identified the visual search for these errors as the bottleneck in interactive proofreading. To aid error correction, we develop two classifiers that automatically recommend candidate merges and splits to the user. These classifiers use a convolutional neural network (CNN) that has been trained with errors in automatic segmentations against expert-labeled ground truth. Our classifiers detect potentially-erroneous regions by considering a large context region around a segmentation boundary. Corrections can then be performed by a user with yes/no decisions, which reduces variation of information 7.5x faster than previous proofreading methods. We also present a fully-automatic mode that uses a probability threshold to make merge/split decisions. Extensive experiments using the automatic approach and comparing performance of novice and expert users demonstrate that our method performs favorably against state-of-the-art proofreading methods on different connectomics datasets.Comment: Supplemental material available at http://rhoana.org/guidedproofreading/supplemental.pd

Shock accelerated vortex ring

The interaction of a shock wave with a spherical density inhomogeneity leads to the development of a vortex ring through the impulsive deposition of baroclinic vorticity. The present fluid dynamics videos display this phenomenon and were experimentally investigated at the Wisconsin Shock Tube Laboratory's (WiSTL) 9.2 m, downward firing shock tube. The tube has a square internal cross-section (0.25 m x 0.25 m) with multiple fused silica windows for optical access. The spherical soap bubble is generated by means of a pneumatically retracted injector and released into free-fall 200 ms prior to initial shock acceleration. The downward moving, M = 2.07 shock wave impulsively accelerates the bubble and reflects off the tube end wall. The reflected shock wave re-accelerates the bubble (reshock), which has now developed into a vortex ring, depositing additional vorticity. In the absence of any flow disturbances, the flow behind the reflected shock wave is stationary. As a result, any observed motion of the vortex ring is due to circulation. The shocked vortex ring is imaged at 12,500 fps with planar Mie scattering.Comment: For Gallery of Fluid Motion 200

Lesion Search with Self-supervised Learning

Content-based image retrieval (CBIR) with self-supervised learning (SSL) accelerates clinicians' interpretation of similar images without manual annotations. We develop a CBIR from the contrastive learning SimCLR and incorporate a generalized-mean (GeM) pooling followed by L2 normalization to classify lesion types and retrieve similar images before clinicians' analysis. Results have shown improved performance. We additionally build an open-source application for image analysis and retrieval. The application is easy to integrate, relieving manual efforts and suggesting the potential to support clinicians' everyday activities.Comment: ICLR 2023 Tiny Pape

An Evaluation of Mississippi Barrier Islands as a Spawning and Nesting Habitat for the American Horseshoe Crab, Limulus polyphemus, with Implications for Island Restoration

The American horseshoe crab (HSC), Limulus polyphemus, is an economically and ecologically important species in the coastal ecosystem. Horseshoe crabs inhabit the continental shelf and estuaries from Maine to the central Gulf Coast and the Yucatán Peninsula. Although the presence of horseshoe crabs in southern Mississippi is known locally, there are limited data specific to the area and population, particularly regarding spawning and nesting habitat. Surveys of HSC presence, habitat use, and behavior on Mississippi barrier islands were conducted between March and November 2007 to 2009. These data, combined with habitat surveys of the barrier islands, were used to characterize HSC use of these islands. Horseshoe crabs were present on barrier island beaches from March to November, but active spawning and nesting occurred primarily in April and May. Peak abundance varied by year but not between islands surveyed. Nesting activity was only observed on the north side of both islands and was generally clustered in areas with a mild elevation profile. In comparison to other studied populations both in the Gulf of Mexico (GOM) and along the U.S. Atlantic coast, HSC nesting on Mississippi barrier islands followed generally similar patterns, but did display some important differences. Nesting was highest in low energy, well oxygenated habitat, which included the sub-tidal sand flats that are common along these islands. In addition, HSC are smaller than the range-wide mean reported in the literature, but that may be related to these islands being close to the edge of the reported HSC range in the GOM. The continued existence of HSC in Mississippi appears tied to their preference for barrier island beaches as spawning and nursery habitat. More research is needed, but this study documents that the distribution of HSC nesting habitat includes Mississippi beaches and this should be considered as a part of restoration plans being evaluated for these barrier islands

Visual characteristics of walleye pollock and Chinook salmon: Modeling theoretical visual space and target contrast of trawling materials in the Bering Sea

Walleye pollock (Gadus chalcogrammus) and Chinook salmon (Oncorhynchus tshawytscha) are economic and cultural resources in Alaska. Chinook salmon bycatch is a large concern within the pollock fishery. Current strategies to reduce salmon bycatch include modifying trawl gear by implementing artificial light near or on escapement panels to increase salmon escapement. The visual characteristics of pollock and Chinook salmon were investigated to understand the perception of trawl gear. The visual pigments of each species were measured using microspectrophotometry (MSP). Pollock were dichromats with spectral sensitivity ranging from 449nm–518 nm and Chinook salmon were trichromats with sensitivity ranging from 436 nm–545 nm. The green opsins within Chinook salmon will activate when stimulated by wavelengths that are outside of the spectral sensitivity of pollock. Microspectrophotometry data defining pollock and Chinook salmon visual pigments, spectral irradiance data from the Bering Sea, and spectral reflectance of commonly used trawl components were input into two visual models, VPModel® and the R package pavo. Visual models predict how the organism’s visual system responds to visual stimuli. Modeling the spectral distribution and physiological visual characteristics predicts how fish interact and adapt to the changing light environment. Spectral irradiance availability decreased with depth and increasing chlorophyll a concentration. Target contrast against the background space light was dependent on the light environment characteristics including depth. Using the physiological data and theoretical model output provides spectral range and intensity limitations to behavior experiments aiming to increase the escapement potential of Chinook salmon in the pollock fisher