Proceedings of an Embassy to the King of Ava, Pegu, &c. in 1757 by Robert Lester, edited by Michael W. Charney

Ensign’s Robert Lester’s account of his embassy to Ava in 1757 was originally published in Alexander Dalrymple’s Oriental Repertory. It provides one of the few first-hand accounts of Alaung-hpaya and thus remains a valuable source on the reign and the beginnings of the Kon-baung Dynasty. Dalrymple’s italicization has been removed and dates have been expanded to include the month and year in order to avoid confusion

Changing Criminal Thinking: An Examination of Heterogeneity in Treatment Effects in a Sample of Justice-Involved Persons with Dual Diagnoses

Recent studies have indicated variability in cognitive change for justice-involved persons with mental illness exposed to treatments for criminal thinking and psychiatric risk factors. Research suggests that proactive styles of criminal thinking may be more difficult to change than impulsive or reactive styles. To date, however, no studies have identified risk factors for a limited response or modeled observed disparities in responsivity to interventions aimed at reducing criminal thinking. Using an archival dataset comprising 206 probationers with a dual diagnosis who were exposed to active CBT-based treatment, a latent profile analysis modeled unobserved heterogeneity in treatment response per observed changes in criminal thinking. Results found that a majority of participants endorsed significant changes in reactive criminal thinking with minimal changes in reported proactive criminal thinking. Neither pre-treatment severity of psychopathology nor compliance with psychotropic medication predicted response to treatment. While diagnosis largely did not predict responsiveness, a self-reported previous diagnosis of a psychotic spectrum disorder predicted increased criminal thinking post-treatment. Moreover, those expressing greater levels of criminal thinking after treatment were also found to express more attitudes supportive of violence. Limitations and treatment recommendations are discussed, including the need for correctional treatments to improve the responsiveness of treatment to individual factors

Do Frictions Matter in the Labor Market? Accessions, Separations and Minimum Wage Effects

We measure labor market frictions using a strategy that bridges design-based and structural approaches: estimating an equilibrium search model using reduced-form minimum wage elasticities identified from border discontinuities and fitted with Bayesian and LIML methods. We begin by providing the first test of U.S. minimum wage effects on labor market flows and find negative effects on employment flows, but not levels. Separations and accessions fall among restaurants and teens, especially those with low tenure. Our estimated parameters of a search model with wage posting and heterogeneous workers and firms imply that frictions help explain minimum wage effects.minimum wage, labor market flows, monopsony, Bayesian estimation

Stochastic rounding and reduced-precision fixed-point arithmetic for solving neural ordinary differential equations

Although double-precision floating-point arithmetic currently dominates high-performance computing, there is increasing interest in smaller and simpler arithmetic types. The main reasons are potential improvements in energy efficiency and memory footprint and bandwidth. However, simply switching to lower-precision types typically results in increased numerical errors. We investigate approaches to improving the accuracy of reduced-precision fixed-point arithmetic types, using examples in an important domain for numerical computation in neuroscience: the solution of Ordinary Differential Equations (ODEs). The Izhikevich neuron model is used to demonstrate that rounding has an important role in producing accurate spike timings from explicit ODE solution algorithms. In particular, fixed-point arithmetic with stochastic rounding consistently results in smaller errors compared to single precision floating-point and fixed-point arithmetic with round-to-nearest across a range of neuron behaviours and ODE solvers. A computationally much cheaper alternative is also investigated, inspired by the concept of dither that is a widely understood mechanism for providing resolution below the least significant bit (LSB) in digital signal processing. These results will have implications for the solution of ODEs in other subject areas, and should also be directly relevant to the huge range of practical problems that are represented by Partial Differential Equations (PDEs).Comment: Submitted to Philosophical Transactions of the Royal Society

Optical properties of synthetic diamond of different synthesis origin.

A research report submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg in partial fulfilment of the requirements for the degree of Master of ScienceThe aim of this work was to evaluate the measurement of the optical properties as a means of obtaining information on the growth history of synthetic diamond. A suite of sample! of known synthesis origin representing the different types of commercially produced synthetic diamond was analysed hy photoluminescence. The photoluminescence intensity was normalising by using the area of tbe Raman peak. This allowed a semi-quantitative comparison of the defect concentration. Three photoluminescent centres were identified, H3, 575 run and 1.945 eV (with zero-phonon lines at 2.463 eV, 2.156 eV, and 1.945 eV respectively). Differences between the intensities of the luminescence due to these centres were observed as a function of the type ot diamond. The H3 amd the 1.945 eV intensity was found to increase with the proporticn of cubic growth sector, In addition the 1.945 eV intensity was found to increase with heat treatment and was higher in {lOO}than in {111} growth sectors. as all three defects detected involve vacancies and nitrogen impurity, an analysis was done to quantify any correlation between the luminescent intensities from the different defects in the same SDA powder sample. The 1.945 eV and 575 nm intensities were observed to be correlated. An additional correlation was found between the 575 nm and the H3 intensities in the case of finer particle size samples. The luminescence intensity for all three defect types was observed to be a function of the particle size of the sample. The shapes and widths of zero-phonon lines were related to the types and concentration of lattice defects present in a crystal according to line broadening theory. An attempt was made to explain the results in the context of the known synthesis origin and growth conditions.AC201

WO 655 Getting Premodern to go Post Modern: Wisdom from the Early Church for Preaching and Worship Today

Allen, Diogenes. Spiritual Theology: The Theology of Yesterday for Spiritual Help Today. Cowley Publications, 1997. Cuming, Geoffrey. Hippolytus: A Text for Students. Grove Books Limited, 1987. Greer, Rowan A. Broken Lights and Mended Lives. Pennsylvania State University Press, 1986. Harmless, William. Augustine and the Catechumenate. Pueblo, 1995. Kelly, J. N. D. Golden Mouth: The Story of John Chrysostom: Ascetic, Preacher, Bishop. Cornell University Press, 1995. McLaren, Brian. A New Kind of Christian. Jossey-Bass, 2001https://place.asburyseminary.edu/syllabi/2705/thumbnail.jp

Distributed Low-rank Subspace Segmentation

Vision problems ranging from image clustering to motion segmentation to semi-supervised learning can naturally be framed as subspace segmentation problems, in which one aims to recover multiple low-dimensional subspaces from noisy and corrupted input data. Low-Rank Representation (LRR), a convex formulation of the subspace segmentation problem, is provably and empirically accurate on small problems but does not scale to the massive sizes of modern vision datasets. Moreover, past work aimed at scaling up low-rank matrix factorization is not applicable to LRR given its non-decomposable constraints. In this work, we propose a novel divide-and-conquer algorithm for large-scale subspace segmentation that can cope with LRR's non-decomposable constraints and maintains LRR's strong recovery guarantees. This has immediate implications for the scalability of subspace segmentation, which we demonstrate on a benchmark face recognition dataset and in simulations. We then introduce novel applications of LRR-based subspace segmentation to large-scale semi-supervised learning for multimedia event detection, concept detection, and image tagging. In each case, we obtain state-of-the-art results and order-of-magnitude speed ups