A randomized and fully discrete Galerkin finite element method for semilinear stochastic evolution equations

In this paper the numerical solution of non-autonomous semilinear stochastic evolution equations driven by an additive Wiener noise is investigated. We introduce a novel fully discrete numerical approximation that combines a standard Galerkin finite element method with a randomized Runge-Kutta scheme. Convergence of the method to the mild solution is proven with respect to the $L^p$-norm, $p \in [2,\infty)$. We obtain the same temporal order of convergence as for Milstein-Galerkin finite element methods but without imposing any differentiability condition on the nonlinearity. The results are extended to also incorporate a spectral approximation of the driving Wiener process. An application to a stochastic partial differential equation is discussed and illustrated through a numerical experiment.Comment: 31 pages, 1 figur

Integrating reliability and resilience to support microgrid design

Quantifying the potential benefits of microgrids in the design phase can support the transition of passive distribution networks into microgrids. At current, reliability and resilience are the main drivers for this transition. Therefore, this paper presents a mathematical optimization model to support the retrofitting of distribution networks into microgrids integrating techno-economic, resilience and reliability objectives. Storage and distributed generation are optionally installed to complement renewable generation, enabling the microgrid to supply priority demands during stochastic islanding events with uncertain duration. For a comprehensive quantification and optimization of microgrid resilience and reliability, islanding due to external events is combined with a detailed model of internal faults. Minimizing the interruption costs yields optimal capacities and placements of distributed energy resources and new lines for reconfiguration. The proposed method produces microgrid designs with up to 95% reliability and resilience gain and moderate cost increase in two benchmark distribution networks using data from the US Department of Energy. The developed methodology is scalable to large networks owing to the tailored Column-and-Constraint-Generation approach

DiactTOD: Learning Generalizable Latent Dialogue Acts for Controllable Task-Oriented Dialogue Systems

Dialogue act annotations are important to improve response generation quality in task-oriented dialogue systems. However, it can be challenging to use dialogue acts to control response generation in a generalizable way because different datasets and tasks may have incompatible annotations. While alternative methods that utilize latent action spaces or reinforcement learning do not require explicit annotations, they may lack interpretability or face difficulties defining task-specific rewards. In this work, we present a novel end-to-end latent dialogue act model (DiactTOD) that represents dialogue acts in a latent space. DiactTOD, when pre-trained on a large corpus, is able to predict and control dialogue acts to generate controllable responses using these latent representations in a zero-shot fashion. Our approach demonstrates state-of-the-art performance across a wide range of experimental settings on the MultiWOZ dataset, including zero-shot, few-shot, and full data fine-tuning with both end-to-end and policy optimization configurations.Comment: SIGDial 202

ATP-Dependent Histone Octamer Sliding Mediated by the Chromatin Remodeling Complex NURF

AbstractDrosophila NURF is an ATP-dependent chromatin remodeling complex that contains ISWI, a member of the SWI2/SNF2 family of ATPases. We demonstrate that NURF catalyzes the bidirectional redistribution of mononucleosomes reconstituted on hsp70 promoter DNA. In the presence of NURF, nucleosomes adopt one predominant position from an ensemble of possible locations within minutes. Movements occur in cis, with no transfer to competing DNA. Migrating intermediates trapped by Exo III digestion reveal progressive nucleosome motion in increments of several base pairs. All four core histones are retained quantitatively during this process, indicating that the general integrity of the histone octamer is maintained. We suggest that NURF remodels nucleosomes by transiently decreasing the activation energy for short-range sliding of the histone octamer

Limitations in the determination of surface emission distributions on comets through modelling of observational data -- A case study based on Rosetta observations

The European Space Agency's (ESA) Rosetta mission has returned a vast data set of measurements of the inner gas coma of comet 67P/Churyumov-Gerasimenko. These measurements have been used by different groups to determine the distribution of the gas sources at the nucleus surface. The solutions that have been found differ from each other substantially and illustrate the degeneracy of this issue. It is the aim of this work to explore the limitations that current gas models have in linking the coma measurements to the surface. In particular, we discuss the sensitivity of Rosetta's ROSINA/COPS, VIRTIS, and MIRO instruments to differentiate between vastly different spatial distributions of the gas emission from the surface. We have applied a state of the art 3D DSMC gas dynamics code to simulate the inner gas coma of different models that vary in the fraction of the surface that contains ice and in different sizes of active patches. These different distributions result in jet interactions that differ in their dynamical behaviour. We have found that ROSINA/COPS measurements by themselves cannot detect the differences in our models. While ROSINA/COPS measurements are important to constrain the regional inhomogeneities of the gas emission, they can by themselves not determine the surface emission distribution of the gas sources to a spatial accuracy of better than a few hundred metres (400 m). Any solutions fitting the ROSINA/COPS measurements is hence fundamentally degenerate, be it through a forward or inverse model. Only other instruments with complementary measurements can potentially lift this degeneracy as we show here for VIRTIS and MIRO. Finally, as a by-product, we have explored the effect of our activity distributions on lateral flow at the surface that may be responsible for some of the observed aeolian features.Comment: Icarus (in press

Toward forward-looking OCT needle tip vision of the spinal neuroforamen: animal studies

Neurologic complications have been reported with spinal transforaminal injections. Causes include intraneural injection, plus embolization occlusion of the radicular artery with subsequent spinal cord infarction. 1 Optical coherence tomography (OCT) is a non-invasive imaging modality, which is used to image tissue microstructure with very high resolution (less than 20 microns) in real-time. With a view toward needle tip OCT visualization of the spinal neuroforamen, we conducted animal studies to explore OCT imaging of paraspinal neurovascular structures. With institutional animal care committee approval, we performed ex-vivo and in situ OCT studies in a euthanized dog, pig, and rabbit. Image data was gathered on spinal nerve roots, dura, and brachial plexus. Two systems were used: frequency domain OCT imaging system developed at California Institute of Technology, and time domain Imalux NIRIS system with a 2.7 mm diameter probe. In a euthanized pig, excised dura was punctured with a 17-gauge Tuohy needle. FDOCT dural images of the puncture showed a subsurface cone-shaped defect. In a rabbit in situ study, puncture of the dura with a 26-gauge needle is imaged as a discontinuity. FDOCT imaging of both small artery and large arteries will be presented, along with H&E and OCT images of the brachial plexus

Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments

Traffic waves are phenomena that emerge when the vehicular density exceeds a critical threshold. Considering the presence of increasingly automated vehicles in the traffic stream, a number of research activities have focused on the influence of automated vehicles on the bulk traffic flow. In the present article, we demonstrate experimentally that intelligent control of an autonomous vehicle is able to dampen stop-and-go waves that can arise even in the absence of geometric or lane changing triggers. Precisely, our experiments on a circular track with more than 20 vehicles show that traffic waves emerge consistently, and that they can be dampened by controlling the velocity of a single vehicle in the flow. We compare metrics for velocity, braking events, and fuel economy across experiments. These experimental findings suggest a paradigm shift in traffic management: flow control will be possible via a few mobile actuators (less than 5%) long before a majority of vehicles have autonomous capabilities