An algorithm for unsteady flows with strong convection

An implicit ADI numerical method for the calculation of 2-D unsteady flows with strong convection effects is described. The method is based on the conventional Crank-Nicholson approach for parabolic equations but an upwind-downwind differencing is used for the first order spatial derivatives associated with convection. The differencing is carried out in the current and previous time plane in such a way that the algorithm is second order accurate in both space and time. The difference equations are factored into sequential operators, one in each independent spatial variable; the solution at each time step may then be computed as a sequence of tridiagonal matrix problems. The method may be used in a noniterative manner although iteration at each time step is recommended in situations where the effects of convection are strong

Hierarchical strategies for efficient fault recovery on the reconfigurable PAnDA device

A novel hierarchical fault-tolerance methodology for reconfigurable devices is presented. A bespoke multi-reconfigurable FPGA architecture, the programmable analogue and digital array (PAnDA), is introduced allowing fine-grained reconfiguration beyond any other FPGA architecture currently in existence. Fault blind circuit repair strategies, which require no specific information of the nature or location of faults, are developed, exploiting architectural features of PAnDA. Two fault recovery techniques, stochastic and deterministic strategies, are proposed and results of each, as well as a comparison of the two, are presented. Both approaches are based on creating algorithms performing fine-grained hierarchical partial reconfiguration on faulty circuits in order to repair them. While the stochastic approach provides insights into feasibility of the method, the deterministic approach aims to generate optimal repair strategies for generic faults induced into a specific circuit. It is shown that both techniques successfully repair the benchmark circuits used after random faults are induced in random circuit locations, and the deterministic strategies are shown to operate efficiently and effectively after optimisation for a specific use case. The methods are shown to be generally applicable to any circuit on PAnDA, and to be straightforwardly customisable for any FPGA fabric providing some regularity and symmetry in its structure

Glucocorticoid programming of neuroimmune function

Work attributed to the ideas presented within this manuscript was supported by the BBSRC (Biotechnology and Biological Sciences Research Council, UK) under the EASTBIO doctoral training program [grant no. BB/J01446X/1], awarded to DJW. KAS was also part funded by a BBSRC grant [no. BB/L002264/1].Throughout life physiological systems strive to maintain homeostasis and these systems are susceptible to exposure to maternal or environmental perturbations, particularly during embryonic development. In some cases, these perturbations may influence genetic and physiological processes that permanently alter the functioning of these physiological systems; a process known as developmental programming. In recent years, the neuroimmune system has garnered attention for its fundamental interactions with key hormonal systems, such as the hypothalamic pituitary adrenal (HPA) axis. The ultimate product of this axis, the glucocorticoid hormones, play a key role in modulating immune responses within the periphery and the CNS as part of the physiological stress response. It is well-established that elevated glucocorticoids induced by developmental stress exert profound short and long-term physiological effects, yet there is relatively little information of how these effects are manifested within the neuroimmune system. Pre and post-natal periods are prime candidates for manipulation in order to uncover the physiological mechanisms that underlie glucocorticoid programming of neuroimmune responses. Understanding the potential programming role of glucocorticoids may be key in uncovering vulnerable windows of CNS susceptibility to stressful experiences during embryonic development and improve our use of glucocorticoids as therapeutics in the treatment of neurodegenerative diseases.Publisher PDFPeer reviewe

Logistic Regression Under Sparse Data Conditions

The impact of sparse data conditions was examined among one or more predictor variables in logistic regression and assessed the effectiveness of the Firth (1993) procedure in reducing potential parameter estimation bias. Results indicated sparseness in binary predictors introduces bias that is substantial with small sample sizes, and the Firth procedure can effectively correct this bias

JMASM36: Nine Pseudo R^2 Indices for Binary Logistic Regression Models (SPSS)

This syntax program is an applied complement to Veall and Zimmermann (1994), Menard (2000), and Smith and McKenna (2013) and produces nine pseudo R2 indices, not readily accessible in statistical software such as SPSS, which are used to describe the results from binary logistic regression analyses

In Pursuit of Economies of Scope: Credit Unions’ Acquisitions of Banks and Thrifts

Between 2012 and 2018, 19 credit unions acquired 23 banks and thrifts. 12 in 2017 and 2018; 17 are in process. Acquiring credit unions are pursuing economies of scope via traditional bank products. They are matched to and contrasted with peer credit unions that are not acquirers. Acquired institutions are matched and contrasted with peers that were not acquired. Performance is measured by CAMEL ratios. Acquiring credit unions have greater ROE and ROA, than nonacquirers, but are less liquid. Acquired institutions have lower capital adequacy, returns, and earnings than matches. Regulators should not discourage credit unions from economies of scope through acquisitions

An Exploration of Link Functions Used in Ordinal Regression

The purpose of this study is to examine issues involved with choice of a link function in generalized linear models with ordinal outcomes, including distributional appropriateness, link specificity, and palindromic invariance are discussed and an exemplar analysis provided using the Pew Research Center 25th anniversary of the Web Omnibus Survey data. Simulated data are used to compare the relative palindromic invariance of four distinct indices of determination/discrimination, including a newly proposed index by Smith et al. (2017)

Professional Development for Educational Leaders in the Era of Performance Evaluation Reform

The word “accountability” has become a mantra in public education. Arguably, this one word, and the movement it has produced, has shaped the direction of our field in the past decade more than any other (Harris, 2011). This movement has led to many positive changes including an examination of gaps in student achievement, the types of assessments used in schools, and the strength of the performance evaluation systems for principals and teachers. Many large urban school districts, as well as entire states, have revamped the way public school principals and teachers are evaluated. In fact many, including the State of Tennessee, Dallas Independent School District, Milwaukee Public Schools, Houston Independent School District, and the State of Illinois, have started or will start using some sort of student achievement metric as part of teacher and/or principal performance evaluations. The ideas surrounding using student growth seem simple enough: If student test scores improve, it means the teacher or principal is doing his or her job well and therefore should be rewarded. This seemingly simple idea is in fact quite complex. Many school administrators may not have the background or training to implement growth models as part of performance evaluations (Mitgang, 2012), which could lead to potentially unethical and incorrect implementation of newer forms of accountability such as growth modeling. Such problems have already arisen in a number of districts across the nation (Harris, 2011)