Search

This paper describes three exemplars of practice inspired by emerging evidence that student-staff partnerships have the potential to significantly enhance many areas of higher education. Students and academics at the University of Adelaide have successfully implemented this collaborative approach across a range of learning and teaching contexts. The Design Thinking Framework, developed by the Hasso Plattner Institute of Design at Stanford University, was utilised at a faculty, program, and course level to frame each of the exemplars, due to its implicit approach to creativity, collaborative development, and achievement of solutions. The iterative nature of the framework facilitated a review cycle for continuous improvement in each Students-as-Partners’ initiative. Analysing the outcomes of each exemplar has identified common hallmarks of successful partnership, and these indicators have the potential to contribute to the growing body of evidence that defines best practice in this pedagogy

Young adults who experienced child abuse and neglect (CAN) are at significant risk for callous-unemotional traits and substance use problems. Research shows that compromised self-regulation may increase risk for these maladaptive outcomes. In the present cross-sectional study, we examined the moderating role of self-regulation, indexed by heart rate variability reactivity, in the indirect link between CAN and alcohol and other drug use problems via callous-unemotional traits. We utilized a sample of mostly female undergraduate students (N = 130, 81% Female; M(age) = 20.72). We hypothesized that (a) CAN and alcohol or other drug use problems would be associated indirectly via elevations in callous-unemotional traits, and (b) that this indirect association would be exacerbated by elevated heart rate variability reactivity. Results indicated that increased callous-unemotional traits underlain in the link between CAN and alcohol or other drug use problems. Further, this indirect link was exacerbated among youth with elevated heart rate variability reactivity. These findings have significant implications for prevention by demonstrating that physiological self-regulation is important to target in substance use prevention among collegiate samples.

We present a case of atrial flutter in a patient post Mustard atrial switch for d-TGA. The approach to arrhythmias following such surgery is discussed in detail.

In 1958 Modigliani and Miller published one of the most significant papers in finance on the cost of capital. It presented the capital structure irrelevance theorem which states that the cost of capital is independent of capital structure. It implies that there is no optimal structure and consequently denies the existence of non-optimal structures. If there are no non-optimal structures then there is no such thing as a business firm having too much leverage or debt. We disagree with that conclusion on both theoretical and empirical grounds supported by the evidence provided by the Financial Crisis Inquiry Commission plus the basic logic behind Basel III. The model of this paper comes from Brigham and Houston’s Bigbee case using beta, the Hamada transformation and an interest rate function which is crucial, concepts not available to M&M in 1958. We show how the minimization of WACC (weighted average cost of capital) and maximization of stock price give identical solutions and their similarity to M&M Propositions I and II. It also shows the simple mechanism that causes non-optimality. M&M missed non optimal structures partly because their data base from 1948 and 1953 had only low and moderate debt/equity ratios. Non-optimal behavior appears at high (double digit) D/E ratios. We have examples of the consequences of excessive leverage not available to M&M, including RJR, Houdaille Industries, the casualties of the 2008 crisis and others. The RJR LBO is examined in detail because it is as close to a laboratory experiment as can be expected in economics. The analysis shows how extremely high leverage put RJR on the path to bankruptcy and how the Roberts-Gerstner plan restored profitability following the logic of Brigham’s Bigbee model.

The recovery from the 2008-2009 recession has been much slower than the average recovery since the 1924 recession. As analysts who believe that the St. Louis model created by Leonall Andersen and Jerry Jordan still has relevance we believe that the slow rate of M2 growth since 2Q2009 is a major reason why GDP growth has been so slow. At the 9th Annual Missouri Economics Conference on March 27, 2009 we presented a paper, “Interwar Hoarding, Liquidity Traps, and the 2008 Solvency Trap” in which we recommended that the Federal Reserve attempt to maintain a 10% growth rate for M2 (or a growth rate of 6.80% on an inflation adjusted basis similar to the 1960, 1970, 1982 recoveries) with the hope that the plan would lead to a real GDP growth rate of 7% with an inflation rate of 3%.The title of that paper indicates two other factors hindering both M2 and GDP growth. Bank hoarding of excess reserves far in excess of ratios seen in the 1930s put the US into a liquidity trap. But in 2008 this was not an ordinary trap. We tried to coin the term “solvency trap” to indicate our belief that, using mark to market accounting, the financial system was insolvent. As Reinhart and Rogoff have noted, recoveries from financial crises tend to be slower than those from ordinary recessions. Analyses of each downturn since 1922 are conducted along with what has happened after the economy bottomed in 2Q09 including money supply analysis. Three years have passed. We continue to believe our original recommendation was correct.

We demonstrate that IOER should make the excess reserves even larger, continuing the problem of monetary policy control and rewarding the banks for their policy errors fostering the Great Recession by giving them risk free returns on the $2.5 trillion of idle funds that are benefiting no one except the banks themselves, or having the banks invest those idle funds in some useful manner such as helping finance the government deficit and fix our roads and bridges. The number 1 priority should be to get rid of the troublesome excess reserves and utilizing open market operations (OMO).

A model previously developed by Lackman (C. L. Lackman, Forecasting commercial paper rates. Journal of Business Finance and Accounting15 (1988) 499–524) for the period 1960 to 1985 is updated to include the 1990s and incorporate statistical techniques relating to tests for stationary conditions not available in 1988. As in the previous model, the demand for commercial paper by each institution (Households (HH), Life Insurance Companies (LIC), Non-Financial Corporations (CRP) and Finance Corporations (FC)) and the total demand is simulated. Simulations of the commercial paper rate are also generated—using just the demand equations (total supply exogenous) and then employing the entire model (supply endogenous) to determine the rate. Simulation periods are from 1960:2 to 2001:4 for all demand simulations. The dynamic simulation of the total demand for commercial paper performs well. The resulting root mean square error, 3.485, compares favourably with the Federal Reserve Boston–Massachusetts Institute of Technology (FRB–MIT) estimate of the commercial paper rate (deLeeuw and Granlich, 1968). Copyright © 2004 John Wiley & Sons, Ltd.

There has been renewed interest in the 1937-8 recession because analysts have mentioned that a Fed engineered increase in interest rates in 2016-7 might stop the 2009-16 recovery much as the 1937-8 recession interrupted the Great Depression recovery. There is interest in finding out whom or what caused the 1937-8 recession. Milton Friedman blamed the Fed for doubling reserve requirements and also said that the Treasury was equally to blame for its gold sterilization program. More recently Douglas Irwin came to the conclusion that gold sterilization was the main culprit. Velde finds that the sterilization of gold halted the growth of the monetary base in 1937 and that the effect of the reserve requirement increases was probable but less clear. Calomiris, Mason, and Wheelock find that the Fed, responsibility was minimal. None of these articles mention inventories being a significant problem. Meltzer (2003) said it was too small to be a major factor. Our inventory data are not only for 1935-8 but for accumulations in front of all post WWII recessions. It indicates that an inventory bubble was a major problem.

Exascale computing systems are essential for the scientific fields that will transform the 21st century global economy, including energy, biotechnology, nanotechnology, and materials science. Progress in these fields is predicated on the ability to perform advanced scientific and engineering simulations, and analyze the deluge of data. On July 29, 2013, ASCAC was charged by Patricia Dehmer, the Acting Director of the Office of Science, to assemble a subcommittee to provide advice on exascale computing. This subcommittee was directed to return a list of no more than ten technical approaches (hardware and software) that will enable the development of a system that achieves the Department's goals for exascale computing. Numerous reports over the past few years have documented the technical challenges and the non¬-viability of simply scaling existing computer designs to reach exascale. The technical challenges revolve around energy consumption, memory performance, resilience, extreme concurrency, and big data. Drawing from these reports and more recent experience, this ASCAC subcommittee has identified the top ten computing technology advancements that are critical to making a capable, economically viable, exascale system.

For several decades invasive coronary angiography has been the reference standard test for the assessment of coronary artery disease. The proper delineation of coronary artery disease extent and lesion quantification on invasive coronary angiography requires attention on the part of the operator to clearly display the entire coronary arterial tree and coronary artery disease lesions, while avoiding artifact, vessel overlap and/or foreshortening using this 2-dimensional imaging technique. The majority of coronary artery lesions visualized is assessed by visual estimation of lumen diameter stenosis. However, while visual estimation of diameter stenosis is practical and generally accurate, coronary artery disease lesion severity may be improved with use of quantitative coronary angiography (QCA), intravascular ultrasound or with the use of fractional flow reserve to assess hemodynamic effects related to the stenosis in question. Although not a high risk procedure on a per-patient basis with a risk of major complications below 1 %, serious complications from invasive coronary angiography do occur, including arterial injury, arrhythmia, myocardial infarction, stroke and death. More common but less morbid risks include renal dysfunction, allergy to contrast media, bleeding, hematoma, arteriovenous fistula, peripheral nerve injury, or risks of conscious sedation such as aspiration. Because of these risks noninvasive approaches to diagnostic coronary angiography have evolved, but do not allow for additional diagnostic or therapeutic maneuvers such as intravascular ultrasound, fractional flow reserve, or percutaneous coronary intervention (Table 6.1). Angiographic data including lesion location, severity, and anatomy correlate with prognosis for future events both with and without coronary intervention using scales such as the Duke Prognostic Score and Syntax scale. For all these reasons, invasive coronary angiography remains vitally important for visualization of coronary artery disease.

The exploitation of today's high-performance computer systems requires the effective use of parallelism in many forms and at numerous levels. This survey article discusses program analysis and restructuring techniques that target parallel architectures. We first describe various categories of architectures that are oriented toward parallel computation models: vector architectures, shared-memory multiprocessors, massively parallel machines, message-passing architectures, VLIWs, and multithreaded architectures. We then describe a variety of optimization techniques that can be applied to sequential programs to effectively utilize the vector and parallel processing units. After an overview of basic dependence analysis, we present restructuring transformations on DO loops targeted both to vectorization and to concurrent execution, interprocedural and pointer analysis, task scheduling, instruction-level parallelization, and compiler-assisted data placement. We conclude that although tremendous advances have been made in dependence theory and in the development of a “toolkit” of transformations, parallel systems are used most effectively when the programmer interacts in the optimization process.

Bit--level repetition of the sequences generated by the C library procedure random() have been observed as a function of seed. This note documents that observation. The effect has not been observed in drand48().

We study the set of probability distributions visited by a continuous-time quantum walk on graphs. An edge-weighted graph G is universal mixing if the instantaneous or average probability distribution of the quantum walk on G ranges over all probability distributions on the vertices as the weights are varied over non-negative reals. The graph is uniform mixing if it visits the uniform distribution. Our results include the following: (a) All weighted complete multipartite graphs are instantaneous universal mixing. This is in contrast to the fact that no unweighted complete multipartite graphs are uniform mixing (except for the four-cycle). (b) The weighted claw or star graph is a minimally connected instantaneous universal mixing graph. In fact, as a corollary, the unweighted claw is instantaneous uniform mixing. This adds a new family of uniform mixing graphs to a list that so far contains only the hypercubes. (c) Any weighted graph is average almost-uniform mixing unless its spectral type is sublinear in the size of the graph. This provides a nearly tight characterization for average uniform mixing on circulant graphs. (d) No weighted graphs are average universal mixing. This shows that weights do not help to achieve average universal mixing, unlike the instantaneous case. Our proofs exploit the spectra of the underlying weighted graphs and path collapsing arguments., 14 pages, 4 figures

This chapter describes CSP (Chip Scale Package) variations used in Folded, Stacked, and SIP (System-In-Package) structures. Tape-based CSPs are used for designs requiring folding of the substrate. We will describe examples of production packages, as well as designs existing only as prototypes. Thermal issues are discussed in some detail. Cost considerations are discussed, including breakdown of typical flex tape CSP cost.

Preface. 1. Introductory Tutorial. 1.1 Getting Started. 1.2 Private and Shared Data. 1.3 Shared Arrays and Affinity of Shared Data. 1.4 Synchronization and Memory Consistency. 1.5 Work Sharing. 1.6 UPC Pointers. 1.7 Summary. Exercises. 2. Programming View and UPC Data Types. 2.1 Programming Models. 2.2 UPC Programming Model. 2.3 Shared and Private Variables. 2.4 Shared and Private Arrays. 2.5 Blocked Shared Arrays. 2.6 Compiling Environments and Shared Arrays. 2.7 Summary. Exercises. 3. Pointers and Arrays. 3.1 UPC Pointers. 3.2 Pointer Arithmetic. 3.3 Pointer Casting and Usage Practices. 3.4 Pointer Information and Manipulation Functions. 3.5 More Pointer Examples. 3.6 Summary. Exercises. 4. Work Sharing and Domain Decomposition. 4.1 Basic Work Distribution. 4.2 Parallel Iterations. 4.3 Multidimensional Data. 4.4 Distributing Trees. 4.5 Summary. Exercises. 5. Dynamic Shared Memory Allocation. 5.1 Allocating a Global Shared Memory Space Collectively. 5.2 Allocating Multiple Global Spaces. 5.3 Allocating Local Shared Spaces. 5.4 Freeing Allocated Spaces. 5.5 Summary. Exercises. 6. Synchronization and Memory Consistency. 6.1 Barriers. 6.2 Split-Phase Barriers. 6.3 Locks. 6.4 Memory Consistency. 6.5 Summary. Exercises. 7. Performance Tuning and Optimization. 7.1 Parallel System Architectures. 7.2 Performance Issues in Parallel Programming. 7.3 Role of Compilers and Run-Time Systems. 7.4 UPC Hand Optimization. 7.5 Case Studies. 7.6 Summary. Exercises. 8. UPC Libraries. 8.1 UPC Collective Library. 8.2 UPC-IO Library. 8.3 Summary. References. Appendix A: UPC Language Specifications, v1.1.1. Appendix B: UPC Collective Operations Specifications, v1.0. Appendix C: UPC-IO Specifications, v1.0. Appendix D: How to Compile and Run UPC Programs. Appendix E: Quick UPC Reference. Index.

We have modified the C language to support a programming model based on a shared address space with physically distributed memory. With this model users can write programs in which the nodes of a massively parallel processor can access remote memory without message passing. AC provides support for distributed arrays as well as pointers to distributed data. Simple array references and pointer dereferencing are sufficient to generate low-overhead remote reads and writes. We have implemented these ideas in a compiler based on the GNU C compiler and targeted at Cray Research's T3D. Initial performance measurements show that AC generates code for remote accesses which is considerably faster than that of the native compiler for structures up to about 16 words in size and virtually equivalent for larger transfers.