Investigation and prediction of slug flow characteristics in highly viscous liquid and gas flows in horizontal pipes

Slug flow characteristics in highly viscous liquid and gas flow are studied experimentally in a horizontal pipe with 0.074 m ID and 17 m length. Results of flow regime map, liquid holdup and pressure gradient are discussed and liquid viscosity effects are investigated. Applicable correlations which are developed to predict liquid holdup in slug body for low viscosity flow are assessed with high viscosity liquids. Furthermore, a mechanistic model is developed for predicting the characteristics of slug flows of highly viscous liquid in horizontal pipes. A control volume is drawn around the slug body and slug film in a slug unit. Momentum equations with a momentum source term representing the significant momentum exchange between film zone and slug body are applied. Liquid viscosity effects are considered in closure relations. The mechanistic model is validated by comparing available pressure gradient and mean slug liquid holdup data produced in the present study and those obtained from literature, showing satisfactory capabilities over a large range of liquid viscosity

Self-Organization of Balanced Nodes in Random Networks with Transportation Bandwidths

We apply statistical physics to study the task of resource allocation in random networks with limited bandwidths along the transportation links. The mean-field approach is applicable when the connectivity is sufficiently high. It allows us to derive the resource shortage of a node as a well-defined function of its capacity. For networks with uniformly high connectivity, an efficient profile of the allocated resources is obtained, which exhibits features similar to the Maxwell construction. These results have good agreements with simulations, where nodes self-organize to balance their shortages, forming extensive clusters of nodes interconnected by unsaturated links. The deviations from the mean-field analyses show that nodes are likely to be rich in the locality of gifted neighbors. In scale-free networks, hubs make sacrifice for enhanced balancing of nodes with low connectivity.Comment: 7 pages, 8 figure

Models of Financial Markets with Extensive Participation Incentives

We consider models of financial markets in which all parties involved find incentives to participate. Strategies are evaluated directly by their virtual wealths. By tuning the price sensitivity and market impact, a phase diagram with several attractor behaviors resembling those of real markets emerge, reflecting the roles played by the arbitrageurs and trendsetters, and including a phase with irregular price trends and positive sums. The positive-sumness of the players' wealths provides participation incentives for them. Evolution and the bid-ask spread provide mechanisms for the gain in wealth of both the players and market-makers. New players survive in the market if the evolutionary rate is sufficiently slow. We test the applicability of the model on real Hang Seng Index data over 20 years. Comparisons with other models show that our model has a superior average performance when applied to real financial data.Comment: 17 pages, 16 figure

Measuring the mode volume of plasmonic nanocavities using coupled optical emitters

Metallic optical systems can confine light to deep sub-wavelength dimensions, but verifying the level of confinement at these length scales typically requires specialized techniques and equipment for probing the near-field of the structure. We experimentally measured the confinement of a metal-based optical cavity by using the cavity modes themselves as a sensitive probe of the cavity characteristics. By perturbing the cavity modes with conformal dielectric layers of sub-nm thickness using atomic layer deposition, we find the exponential decay length of the modes to be less than 5% of the free-space wavelength (\lambda) and the mode volume to be of order \lambda^3/1000. These results provide experimental confirmation of the deep sub-wavelength confinement capabilities of metal-based optical cavities.Comment: 11 pages, 4 figure

Dynamic game of offending and law enforcement: a stochastic extension

This article provides an extension of the Fend-Feichtinger-Tragler dynamic game of offending and law enforcement to a stochastic framework. This allows the analysis to reflect actual crime statistics which displays randomness in its distribution. Stochastic paths of crimes are derived. The asymptotic stationary distribution of crime records is also obtained. © 2010 World Scientific Publishing Company.postprin

A Multivariate Model of Strategic Asset Allocation

Much recent work has documented evidence for predictability of asset returns. We show how such predictability can affect the portfolio choices of long-lived investors who value wealth not for its own sake but for the consumption their wealth can support. We develop an approximate solution method for the optimal consumption and portfolio choice problem of an infinitely-lived investor with Epstein-Zin utility who faces a set of asset returns described by a vector autoregression in returns and state variables. Empirical estimates in long-run annual and postwar quarterly US data suggest that the predictability of stock returns greatly increases the optimal demand for stocks. The role of nominal bonds in long-term portfolios depends on the importance of real interest rate risk relative to other sources of risk. We extend the analysis to consider long-term inflation-indexed bonds and find that these bonds greatly increase the utility of conservative investors, who should hold large positions when they are available.

Definite discourse-new reference in L1 and L2: The case of L2 Mandarin

Definite discourse-new bridging reference (e.g., a school … the teacher; Clark, 1975) is a complex syntax-pragmatic component of referential movement, one that is subject to relatively opaque form-function contingency compared with forms used for discourse-old reference, and one that is especially prone to crosslinguistic influence. Research shows Asian second language (L2) learners of English struggle to produce bridging reference appropriately, yet little research has been done on the L2 production of bridging in Asian languages. We collected oral picture sequence narrative data from 80 lower-intermediate L2 Mandarin learners from first language (L1) English (+ article, n = 23) and L1 Korean and Japanese (- article, n = 57) backgrounds, alongside equivalent L1 data. Speakers of article-L1s were more likely than those from article-less L1s to use numeral + classifier noun phrases (NPs) for nonbridging referents and demonstrative + classifier NPs when introducing bridging referents, essentially (and infelicitously) using these constructions as de facto English-like indefinite/definite articles in their L2 Mandarin production. Speakers of article-less languages infelicitously marked bridging relations with nonbridging forms. These findings confirm substantial crosslinguistic difficulties for the L2 marking of this complex syntax-pragmatic phenomenon across relatively underexplored L1/L2 pairs.postprin

Marginalized average attentional network for weakly-supervised learning

© 7th International Conference on Learning Representations, ICLR 2019. All Rights Reserved. In weakly-supervised temporal action localization, previous works have failed to locate dense and integral regions for each entire action due to the overestimation of the most salient regions. To alleviate this issue, we propose a marginalized average attentional network (MAAN) to suppress the dominant response of the most salient regions in a principled manner. The MAAN employs a novel marginalized average aggregation (MAA) module and learns a set of latent discriminative probabilities in an end-to-end fashion. MAA samples multiple subsets from the video snippet features according to a set of latent discriminative probabilities and takes the expectation over all the averaged subset features. Theoretically, we prove that the MAA module with learned latent discriminative probabilities successfully reduces the difference in responses between the most salient regions and the others. Therefore, MAAN is able to generate better class activation sequences and identify dense and integral action regions in the videos. Moreover, we propose a fast algorithm to reduce the complexity of constructing MAA from O(2T) to O(T2). Extensive experiments on two large-scale video datasets show that our MAAN achieves a superior performance on weakly-supervised temporal action localization