The Writing, Production, and Direction of an Original Readers Theatre Script "A toast to gods"

It was the purpose of this thesis to write an original script especially designed for Readers Theatre and to direct and produce that script for public performance. The thesis consists of an introduction which includes background material, a review of the literature concerning Readers Theatre, and the problems of writing an original script. The thesis includes the script as well as an evaluation of the attendant problems concerning the direction and production

Closed-Loop Scheduling for Cost Minimization in HVAC Central Plants

In this paper, we examine closed-loop operation of an HVAC central plant to demonstrate that closed-loop receding-horizon scheduling provides robustness to inaccurate forecasts, and that economic performance is not seriously impaired by shortened prediction horizons or inaccurate forecasts when feedback is employed. Using a general mixed-integer linear programming formulation for the scheduling problem, we show that optimization can be performed in real time. Furthermore, we demonstrate that closed-loop operation with a moderate prediction horizon is not significantly worse than a long-horizon implementation in the nominal case, and that closed-loop operation can correct for inaccurate long-term forecasts without significant cost increase. In addition, we show that terminal constraints can be employed to ensure recursive feasibility. The end result is that forecasts of demand need not be extremely accurate over long times, indicating that closed-loop scheduling can be implemented in new or existing central plants

Extreme wet conditions coincident with Bronze Age abandonment of upland areas in Britain

Abandonment of farming systems on upland areas in southwest Britain during the Late Bronze Age – some 3000 years ago – is widely considered a ‘classic’ demonstration of the impact of deteriorating climate on the vulnerability of populations in such marginal environments. Here we test the hypothesis that climate change drove the abandonment of upland areas by developing new chronologies for human activity on upland areas during the Bronze Age across southwest Britain (Dartmoor, Exmoor and Bodmin Moor). We find Bronze Age activity in these areas spanned 3900–2950 calendar years ago with abandonment by 2900 calendar years ago. Holocene Irish bog and lake oak tree populations provide evidence of major shifts in hydroclimate across western Britain and Ireland, coincident with ice rafted debris layers recognized in North Atlantic marine sediments, indicating significant changes in the latitude and intensity of zonal atmospheric circulation across the region. We observe abandonment of upland areas in southwest Britain coinciding with a sustained period of extreme wet conditions that commenced 3100 calendar years ago. Our results are consistent with the view that climate change increased the vulnerability of these early farming communities and led to a less intensive use of such marginal environments across Britain

Uptake of zinc and phosphorus by plants is affected by zinc fertiliser material and arbuscular mycorrhizas

Background and Aims Water solubility of zinc (Zn) fertilisers affects their plant availability. Further, simultaneous application of Zn and phosphorus (P) fertiliser can have antagonistic effects on plant Zn uptake. Arbuscular mycorrhizas (AM) can improve plant Zn and P uptake. We conducted a glasshouse experiment to test the effect of different Zn fertiliser materials, in conjunction with P fertiliser application, and colonisation by AM, on plant nutrition and biomass. Methods We grew a mycorrhiza-defective tomato geno-type (rmc) and its mycorrhizal wild-type progenitor(76R) in soil with six different Zn fertilisers ranging in water solubility (Zn sulphate, Zn oxide, Zn oxide (nano), Zn phosphate, Zn carbonate, Zn phosphate carbonate), and supplemental P. We measured plant biomass, Zn and P contents, mycorrhizal colonisation and water use efficiency. Results Whereas water solubility of the Zn fertilisers was not correlated with plant biomass or Zn uptake, plant Zn and P contents differed among Zn fertiliser treatments. Plant Zn and P uptake was enhanced when supplied as Zn phosphate carbonate. Mycorrhizal plants took up more P than non-mycorrhizal plants; the reverse was true for Zn. Conclusions Zinc fertiliser composition and AM have a profound effect on plant Zn and P uptake.Stephanie J. Watts-Williams, Terence W. Turney, Antonio F. Patti, Timothy R. Cavagnar

The New Zealand Kauri (Agathis Australis) Research Project: A Radiocarbon Dating Intercomparison of Younger Dryas Wood and Implications for IntCal13

We describe here the New Zealand kauri (Agathis australis) Younger Dryas (YD) research project, which aims to undertake Δ14C analysis of ~140 decadal floating wood samples spanning the time interval ~13.1–11.7 kyr cal BP. We report 14C intercomparison measurements being undertaken by the carbon dating laboratories at University of Waikato (Wk), University of California at Irvine (UCI), and University of Oxford (OxA). The Wk, UCI, and OxA laboratories show very good agreement with an interlaboratory comparison of 12 successive decadal kauri samples (average offsets from consensus values of –7 to +4 14C yr). A University of Waikato/University of Heidelberg (HD) intercomparison involving measurement of the YD-age Swiss larch tree Ollon505, shows a HD/Wk offset of ~10–20 14C yr (HD younger), and strong evidence that the positioning of the Ollon505 series is incorrect, with a recommendation that the 14C analyses be removed from the IntCal calibration database

A Case Study of Economic Optimization of HVAC Systems based on the Stanford University Campus Airside and Waterside Systems

Commercial buildings account for $200 billion per year in energy expenditures, with heating, ventilation, and air conditioning (HVAC) systems accounting for most of these costs. In energy markets with time-varying prices and peak demand charges, a significant potential for cost savings is provided by using thermal energy storage to shift energy loads. Since most implementations of HVAC control systems do not optimize energy costs, they have become a primary focus for new strategies aimed at economic optimization. Model predictive control (MPC) has emerged as one popular method to achieve this load shifting, while respecting system constraints. MPC uses a model of the system to make predictions and to solve an optimization problem. Much research has shown the benefits of MPC over alternative strategies for HVAC control [1]. However, some industrial applications, such as large research centers or university campuses, are too large to be solved in a single MPC instance. Decompositions have been proposed in the literature, but it is difficult to evaluate and to compare decompositions against one another when using different systems. In this paper, we present a large-scale relevant case study where solving a single MPC optimization problem is neither desirable nor feasible for real-time implementations. The study is modeled after the Stanford University campus, consisting of both an airside and waterside system [2]. The airside system includes 500 zones spread throughout 25 campus buildings along with the air handler units and regulatory building automation system used for temperature regulation. The waterside system includes the central plant equipment, such as chillers, that is used to meet the load from the buildings. Active thermal energy storage is available to the campus in addition to the passive thermal energy storage present in the form of building mass. The airside models describe the temperature dynamics in each of the 500 zones, and the waterside models describe the power consumption of the central plant equipment. The aim of the control system is to minimize costs in the presence of time-varying electricity prices and a peak demand charge as well as environmental disturbances such as weather while meeting constraints on comfort and equipment. We perform an economic optimization of the entire campus using a hierarchical system with distributed airside controllers to demonstrate the potential savings. The models from this case study are made publicly available for other researchers interested in designing alternative control strategies for managing chilled water production to meet airside loads. The aim of the case study release is to provide a standardized problem for the research community. A benchmark is provided for evaluating performance. References [1] A. Afram and F. Janabi-Sharifi. Theory and applications of HVAC control systems—A review of model predictive control (MPC). Building and Environment, 72:343–355, February 2014. [2] J. B. Rawlings, N. R. Patel, M. J. Risbeck, C. T. Maravelias, M. J. Wenzel, and R. D. Turney. Economic MPC and real-time decision making with application to large-scale HVAC energy systems. Computers & Chemical Engineering, 2017. In Press

Incremental dimension reduction of tensors with random index

We present an incremental, scalable and efficient dimension reduction technique for tensors that is based on sparse random linear coding. Data is stored in a compactified representation with fixed size, which makes memory requirements low and predictable. Component encoding and decoding are performed on-line without computationally expensive re-analysis of the data set. The range of tensor indices can be extended dynamically without modifying the component representation. This idea originates from a mathematical model of semantic memory and a method known as random indexing in natural language processing. We generalize the random-indexing algorithm to tensors and present signal-to-noise-ratio simulations for representations of vectors and matrices. We present also a mathematical analysis of the approximate orthogonality of high-dimensional ternary vectors, which is a property that underpins this and other similar random-coding approaches to dimension reduction. To further demonstrate the properties of random indexing we present results of a synonym identification task. The method presented here has some similarities with random projection and Tucker decomposition, but it performs well at high dimensionality only (n>10^3). Random indexing is useful for a range of complex practical problems, e.g., in natural language processing, data mining, pattern recognition, event detection, graph searching and search engines. Prototype software is provided. It supports encoding and decoding of tensors of order >= 1 in a unified framework, i.e., vectors, matrices and higher order tensors.Comment: 36 pages, 9 figure

Inducing safer oblique trees without costs

Decision tree induction has been widely studied and applied. In safety applications, such as determining whether a chemical process is safe or whether a person has a medical condition, the cost of misclassification in one of the classes is significantly higher than in the other class. Several authors have tackled this problem by developing cost-sensitive decision tree learning algorithms or have suggested ways of changing the distribution of training examples to bias the decision tree learning process so as to take account of costs. A prerequisite for applying such algorithms is the availability of costs of misclassification. Although this may be possible for some applications, obtaining reasonable estimates of costs of misclassification is not easy in the area of safety. This paper presents a new algorithm for applications where the cost of misclassifications cannot be quantified, although the cost of misclassification in one class is known to be significantly higher than in another class. The algorithm utilizes linear discriminant analysis to identify oblique relationships between continuous attributes and then carries out an appropriate modification to ensure that the resulting tree errs on the side of safety. The algorithm is evaluated with respect to one of the best known cost-sensitive algorithms (ICET), a well-known oblique decision tree algorithm (OC1) and an algorithm that utilizes robust linear programming

Linguistic and statistically derived features for cause of death prediction from verbal autopsy text

Automatic Text Classification (ATC) is an emerging technology with economic importance given the unprecedented growth of text data. This paper reports on work in progress to develop methods for predicting Cause of Death from Verbal Autopsy (VA) documents recommended for use in low-income countries by the World Health Organisation. VA documents contain both coded data and open narrative. The task is formulated as a Text Classification problem and explores various combinations of linguistic and statistical approaches to determine how these may improve on the standard bag-of-words approach using a dataset of over 6400 VA documents that were manually annotated with cause of death. We demonstrate that a significant improvement of prediction accuracy can be obtained through a novel combination of statistical and linguistic features derived from the VA text. The paper explores the methods by which ATC may leads to improved accuracy in Cause of Death prediction