Populations in statistical genetic modelling and inference

What is a population? This review considers how a population may be defined in terms of understanding the structure of the underlying genetics of the individuals involved. The main approach is to consider statistically identifiable groups of randomly mating individuals, which is well defined in theory for any type of (sexual) organism. We discuss generative models using drift, admixture and spatial structure, and the ancestral recombination graph. These are contrasted with statistical models for inference, principle component analysis and other `non-parametric' methods. The relationships between these approaches are explored with both simulated and real-data examples. The state-of-the-art practical software tools are discussed and contrasted. We conclude that populations are a useful theoretical construct that can be well defined in theory and often approximately exist in practice

A Sectoral Model of the Australian Economy

We use a structural vector autoregression (SVAR) to examine the effect of unanticipated changes in monetary policy on the expenditure and production components of GDP over the period from 1983 to 2007. We find that dwelling investment and machinery & equipment investment are the most interest-sensitive expenditure components of activity, and that construction and retail trade are the most interest-sensitive production components of activity. We subject our model to a range of sensitivity checks and find that our results are robust to omitted variables, alternative identification schemes and the time period over which our model is estimated.Australian economy; sectoral macroeconomic model; monetary policy

Distributive inverse semigroups and non-commutative Stone dualities

We develop the theory of distributive inverse semigroups as the analogue of distributive lattices without top element and prove that they are in a duality with those etale groupoids having a spectral space of identities, where our spectral spaces are not necessarily compact. We prove that Boolean inverse semigroups can be characterized as those distributive inverse semigroups in which every prime filter is an ultrafilter; we also provide a topological characterization in terms of Hausdorffness. We extend the notion of the patch topology to distributive inverse semigroups and prove that every distributive inverse semigroup has a Booleanization. As applications of this result, we give a new interpretation of Paterson's universal groupoid of an inverse semigroup and by developing the theory of what we call tight coverages, we also provide a conceptual foundation for Exel's tight groupoid.Comment: arXiv admin note: substantial text overlap with arXiv:1107.551

Accelerated Neural Networks on OpenCL Devices Using SYCL-DNN

Over the past few years machine learning has seen a renewed explosion of interest, following a number of studies showing the effectiveness of neural networks in a range of tasks which had previously been considered incredibly hard. Neural networks' effectiveness in the fields of image recognition and natural language processing stems primarily from the vast amounts of data available to companies and researchers, coupled with the huge amounts of compute power available in modern accelerators such as GPUs, FPGAs and ASICs. There are a number of approaches available to developers for utilizing GPGPU technologies such as SYCL, OpenCL and CUDA, however many applications require the same low level mathematical routines. Libraries dedicated to accelerating these common routines allow developers to easily make full use of the available hardware without requiring low level knowledge of the hardware themselves, however such libraries are often provided by hardware manufacturers for specific hardware such as cuDNN for Nvidia hardware or MIOpen for AMD hardware. SYCL-DNN is a new open-source library dedicated to providing accelerated routines for neural network operations which are hardware and vendor agnostic. Built on top of the SYCL open standard and written entirely in standard C++, SYCL-DNN allows a user to easily accelerate neural network code for a wide range of hardware using a modern C++ interface. The library is tested on AMD's OpenCL for GPU, Intel's OpenCL for CPU and GPU, ARM's OpenCL for Mali GPUs as well as ComputeAorta's OpenCL for R-Car CV engine and host CPU. In this talk we will present performance figures for SYCL-DNN on this range of hardware, and discuss how high performance was achieved on such a varied set of accelerators with such different hardware features.Comment: 4 pages, 3 figures. In International Workshop on OpenCL (IWOCL '19), May 13-15, 2019, Bosto

Peer Observation, Reflection, and evaluation Practices in the Writing Center: A Genre Pedagogy Approach

In this essay, the author shares the results of a local assessment conducted on his center’s peer observation, reflection, and evaluation practices for graduate assistants (GAs), focusing especially on the form used to facilitate these practices. The author interviewed the participants and analyzed completed “Writing Center Graduate Assistant Observation” forms. The interviews focused on three major areas: 1) what they perceived the purpose of the observation and reflection exercise to be, 2) how they felt and what they learned about observing their peers and being observed, and 3) how they felt the form affected the observation and reflection. In brief, the author argues that melding evaluation and consultant self-reflection is fraught because the rhetorical situation of each requires markedly different social action. Two critical lenses guide this examination: reflective practice and genre pedagogy. Ultimately, the author cautions those who use observation and reflection in their assessments to consider carefully the documents and genres surrounding those assessments because these genres may (intentionally or not) draw on antecedent genres that are inappropriate for the social action they intend to facilitate. Perhaps more troubling, some of these genres may implicitly draw on and/or perpetuate ideologies that are fundamentally at odds with reflective practice.University Writing Cente

Invariant means on Boolean inverse monoids

The classical theory of invariant means, which plays an important role in the theory of paradoxical decompositions, is based upon what are usually termed `pseudogroups'. Such pseudogroups are in fact concrete examples of the Boolean inverse monoids which give rise to etale topological groupoids under non-commutative Stone duality. We accordingly initiate the theory of invariant means on arbitrary Boolean inverse monoids. Our main theorem is a characterization of when a Boolean inverse monoid admits an invariant mean. This generalizes the classical Tarski alternative proved, for example, by de la Harpe and Skandalis, but using different methods