Clearing Alaskan water supply impoundments: management, laboratory study, and literature review

The literature review prepared in conjunction with this study is contained in IWR-67-A, published separately as "Clearing Alaskan Water Supply Impoundments: Literature Review" by the Institute of Water Resources, University of Alaska, Fairbanks, Alaska. The data developed in the laboratory portion of the study are contained in IWR-67-B. Contact the Institute of Water Resources for access to this material. IWR-67-A and IWR-67-B are available on microfiche.Water supply impoundments in northern regions have seen only limited application. Reasons for the lack of use of such impoundments include the following: 1) little demand for water due to the low population densities and rustic life styles; 2) a lack of conventional distribution systems in many communities; 3) poorly developed technology for construction of dams on permafrost; 4) adequacy of existing river, lake, ice, and lagoon water supplies; 5) shortage of capital to finance the high cost of construction in remote regions.The work upon which this report is based was supported by funds provided by the United States Department of the Interior, Office of Water Research and Technology, as authorized by the Water Resources Research Act of 1964, Public Law 88-379, as amended (Project A-043-ALAS)

Testing the Power of Leading Indicators to Predict Business Cycle Phase Changes

In the business cycle literature researchers often want to determine the extent to which models of the business cycle reproduce broad characteristics of the real world business cycle they purport to represent. Of considerable interest is whether a model’s implied cycle chronology is consistent with the actual business cycle chronology. In the US, a very widely accepted business cycle chronology is that compiled by the National Bureau of Economic research (NBER) and the vast majority of US business cycle scholars have, for many years, proceeded to test their models for their consistency with the NBER dates. In doing this, one of the most prevalent metrics in use since its introduction into the business cycle literature by Diebold and Rudebusch (1989) is the so-called quadratic probability score, or QPS. However, an important limitation to the use of the QPS statistic is that its sampling distribution is unknown so that rigorous statistical inference is not feasible. We suggest circumventing this by bootstrapping the distribution. This analysis yields some interesting insights into the relationship between statistical measures of goodness of fit of a model and the ability of the model to predict some underlying set of regimes of interest. Furthermore, in modeling the business cycle, a popular approach in recent years has been to use some variant of the so-called Markov regime switching (MRS) model first introduced by Hamilton (1989) and we therefore use MRS models as the framework for the paper. Of course, the approach could be applied to any US business cycle model.Markov Regime Switching, Business Cycle, Quadratic Probability Score

Modeling Yield-Factor Volatility

The term structure of interest rates is often summarized using a handful of yield factors that capture shifts in the yield curve. Despite their wide application in financial economics, very little is known on the time-series properties of the yield-factor volatilities. We examine three common yield-factors: the level of short-term interest rates, the slope and curvature in the yield curve. We model the volatility dynamics in these yield factors using both GARCH and level effects and find that both are needed to adequately model yield-factor volatility. The level effect is routinely used when modeling volatility in short-term interest rates and we find that the level of the short-rate is useful in modeling the volatility of the slope and curvature too. We also examine the effect of volatility on the dynamics of the yield-factors and find that the GARCH-based volatility of the short-rate is negatively related to future interest rates and positively related to the slope of the yield curve. This volatility-in-mean effect is much weaker when a level effect is introduced. We also examine regime switching models that recognize different economic regimes and find that this dramatically improves the model's fit. Interestingly, the level effect is strengthened and the GARCH effects is weakened somewhat. The Bayesian information criteria suggests that the correct model is a regime-switching model with level effecC32, C51, G12

DURATION DEPENDENCE IN THE US BUSINESS CYCLE

Durland and McCurdy (1994) investigated the issue of duration dependence in US business cycle phases using a Markov regime switching approach, introduced by Hamilton (1989) and extended to the case of variable transition parameters by Filardo (1994). In Durland and McCurdy’s model duration alone was used as an explanatory of the transition probabilities. They found that recessions were duration dependent whilst expansions were not. In this paper, we explicitly incorporate the widely-accepted US business cycle phase change dates as determined by the NBER, and use a state-dependent multinomial Logit (and Probit) modelling framework. The model incorporates both duration and movements in two leading indexes - one designed to have a short lead (SLI) and the other designed to have a longer lead (LLI) - as potential explanators. We find that doing so suggests that current duration is not only a significant determinant of transition out of recessions, but that there is some evidence that it is also weakly significant in the case of expansions. Furthermore, we find that SLI has more informational content for the termination of recessions whilst LLI does so for expansions.

Spacetime structure and vacuum entanglement

We study the role that both vacuum fluctuations and vacuum entanglement of a scalar field play in identifying the spacetime topology, which is not prescribed from first principles---neither in general relativity or quantum gravity. We analyze how the entanglement and observable correlations acquired between two particle detectors are sensitive to the spatial topology of spacetime. We examine the detector's time evolution to all orders in perturbation theory and then study the phenomenon of vacuum entanglement harvesting in Minkowski spacetime and two flat topologically distinct spacetimes constructed from identifications of the Minkowski space. We show that, for instance, if the spatial topology induces a preferred direction, this direction may be inferred from the dependence of correlations between the two detectors on their orientation. We therefore show that vacuum fluctuations and vacuum entanglement harvesting makes it, in principle, possible to distinguish spacetimes with identical local geometry that differ only in their topology

Calibration of neural networks using genetic algorithms, with application to optimal path planning

Genetic algorithms (GA) are used to search the synaptic weight space of artificial neural systems (ANS) for weight vectors that optimize some network performance function. GAs do not suffer from some of the architectural constraints involved with other techniques and it is straightforward to incorporate terms into the performance function concerning the metastructure of the ANS. Hence GAs offer a remarkably general approach to calibrating ANS. GAs are applied to the problem of calibrating an ANS that finds optimal paths over a given surface. This problem involves training an ANS on a relatively small set of paths and then examining whether the calibrated ANS is able to find good paths between arbitrary start and end points on the surface

Localized shear generates three-dimensional transport

Understanding the mechanisms that control three-dimensional (3D) fluid transport is central to many processes including mixing, chemical reaction and biological activity. Here a novel mechanism for 3D transport is uncovered where fluid particles are kicked between streamlines near a localized shear, which occurs in many flows and materials. This results in 3D transport similar to Resonance Induced Dispersion (RID); however, this new mechanism is more rapid and mutually incompatible with RID. We explore its governing impact with both an abstract 2-action flow and a model fluid flow. We show that transitions from one-dimensional (1D) to two-dimensional (2D) and 2D to 3D transport occur based on the relative magnitudes of streamline jumps in two transverse directions.Comment: Copyright 2017 AIP Publishing. This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishin