Adaptive Response Modeling Using GIS, Blog 3

Student blog posts from the Great VCU Bike Race Book

F. R. Leavis: the development of a critical vocabulary

This thesis demonstrates the development of F.R.Leavis's critical vocabulary through an examination of his critical practice. The socia] and political dimension of his critical orientation is examined by means of a reading of his own early pamphlets and articles; and of Q.D.Leavis's Fiction and the Reading Public (1932). This chapter indicates the nature of Leavis's approach to literature and criticism. An analysis of Leavis's preliminary considerations on poetry illustrates the gradual advancement of his critical terminology under the influence of T.S.Eliot. The judgements produced are examined and their value and reasoning are ,accounted for. Leavis's work on the novel is examined, showing how the critical terminology was transferred from criticism of the poetry to criticism of the novel. The source and function of Leavis's categories of 'tradition' and 'morality' are analysed. The ensuing critical judgements are assessed to show how and why such judgements were of ambiguous value. Leavis's study of Lawrence demonstrates centrally the advantages and disadvantages of Leavis's critical method. A discussion of the 'two cultures' debate illustrates Leavis's continuing polemical engagements and how this affects his critical priorities. Finally. an examination of Leavis's later work on Dickens and T.S.Eliot shows how Leavis's critical vocabulary matured a metaphysical, almost 'religious', dimension in its striving to maintain a connection between his concepts of 'art' and 'life'. Throughout this thesis, Leavis's criticism is examined by means of a rehearsal of his major arguments. This is combined with a discussion and assessment of the integrity of and sources for those arguments and an analysis of their resultant literary judgements. The thesis presents an objective account of the nature and function of Leavis's critical vocabulary, with a demonstration of its sources and an assessment of its achievements

BioSimulator.jl: Stochastic simulation in Julia

Biological systems with intertwined feedback loops pose a challenge to mathematical modeling efforts. Moreover, rare events, such as mutation and extinction, complicate system dynamics. Stochastic simulation algorithms are useful in generating time-evolution trajectories for these systems because they can adequately capture the influence of random fluctuations and quantify rare events. We present a simple and flexible package, BioSimulator.jl, for implementing the Gillespie algorithm, $\tau$-leaping, and related stochastic simulation algorithms. The objective of this work is to provide scientists across domains with fast, user-friendly simulation tools. We used the high-performance programming language Julia because of its emphasis on scientific computing. Our software package implements a suite of stochastic simulation algorithms based on Markov chain theory. We provide the ability to (a) diagram Petri Nets describing interactions, (b) plot average trajectories and attached standard deviations of each participating species over time, and (c) generate frequency distributions of each species at a specified time. BioSimulator.jl's interface allows users to build models programmatically within Julia. A model is then passed to the simulate routine to generate simulation data. The built-in tools allow one to visualize results and compute summary statistics. Our examples highlight the broad applicability of our software to systems of varying complexity from ecology, systems biology, chemistry, and genetics. The user-friendly nature of BioSimulator.jl encourages the use of stochastic simulation, minimizes tedious programming efforts, and reduces errors during model specification.Comment: 27 pages, 5 figures, 3 table

Selecting hybrid pine clones for deployment - The pointy end of wood quality improvement

A clonal forestry research programme on Pinus elliottii Engelm. (slash pine) x P. caribaea Morelet var. hondurensis Barrett & Golfari (Caribbean pine) hybrids commenced in Queensland in 1986. Each cycle of clonal tests covered about 5 calendar years from field planting, and studies of wood quality variation have so far been used in selecting superior clones from the first three series of tests for commercial plantation deployment. Experience from the Series III clonal selection round is used to highlight the difficulties of ranking elite clones given a large number of growth, form, and wood property traits. Three to six ramets were felled from the best 32 clones in the Series III trials at age 6.8 years and a 3-m butt log from each was sawn into 70 × 35-mm structural boards. The clones sawn were ranked for routine deployment using data on growth, form, and wood traits. All recovered boards were assessed for distortion and tested for modulus of elasticity and modulus of rupture. Various non-destructive wood evaluation methods were used to estimate modulus of elasticity (wood stiffness) in these trees. Standing tree acoustic velocity assessed with an ST300 tool was slightly less strongly correlated phenotypically with the average modulus of elasticity of the recovered boards (r = 0.88**) than with predictions of modulus of elasticity from resonance vibration test samples and SilviScan estimates (both r = 0.89**). Moderate phenotypic relationships were found for individual tree means between average twist of the sawn boards and the average spiral grain angle of growth rings 2, 3, and 4 (r = 0.70**) assessed using a breast-height 12-mm increment core, and between average bow in the boards and average microfibril angle (r = 0.64**) from SilviScan assessments of core samples

Iterative hard thresholding in genome-wide association studies: Generalized linear models, prior weights, and double sparsity.

BackgroundConsecutive testing of single nucleotide polymorphisms (SNPs) is usually employed to identify genetic variants associated with complex traits. Ideally one should model all covariates in unison, but most existing analysis methods for genome-wide association studies (GWAS) perform only univariate regression.ResultsWe extend and efficiently implement iterative hard thresholding (IHT) for multiple regression, treating all SNPs simultaneously. Our extensions accommodate generalized linear models, prior information on genetic variants, and grouping of variants. In our simulations, IHT recovers up to 30% more true predictors than SNP-by-SNP association testing and exhibits a 2-3 orders of magnitude decrease in false-positive rates compared with lasso regression. We also test IHT on the UK Biobank hypertension phenotypes and the Northern Finland Birth Cohort of 1966 cardiovascular phenotypes. We find that IHT scales to the large datasets of contemporary human genetics and recovers the plausible genetic variants identified by previous studies.ConclusionsOur real data analysis and simulation studies suggest that IHT can (i) recover highly correlated predictors, (ii) avoid over-fitting, (iii) deliver better true-positive and false-positive rates than either marginal testing or lasso regression, (iv) recover unbiased regression coefficients, (v) exploit prior information and group-sparsity, and (vi) be used with biobank-sized datasets. Although these advances are studied for genome-wide association studies inference, our extensions are pertinent to other regression problems with large numbers of predictors

Ten Simple Rules for Getting Help from Online Scientific Communities

The increasing complexity of research requires scientists to work at the intersection of multiple fields and to face problems for which their formal education has not prepared them. For example, biologists with no or little background in programming are now often using complex scripts to handle the results from their experiments; vice versa, programmers wishing to enter the world of bioinformatics must know about biochemistry, genetics, and other fields. In this context, communication tools such as mailing lists, web forums, and online communities acquire increasing importance. These tools permit scientists to quickly contact people skilled in a specialized field. A question posed properly to the right online scientific community can help in solving difficult problems, often faster than screening literature or writing to publication authors. The growth of active online scientific communities, such as those listed in Table S1, demonstrates how these tools are becoming an important source of support for an increasing number of researchers. Nevertheless, making proper use of these resources is not easy. Adhering to the social norms of World Wide Web communication—loosely termed “netiquette”—is both important and non-trivial. In this article, we take inspiration from our experience on Internet-shared scientific knowledge, and from similar documents such as “Asking the Questions the Smart Way” and “Getting Answers”, to provide guidelines and suggestions on how to use online communities to solve scientific problems

OPENMENDEL: A Cooperative Programming Project for Statistical Genetics

Statistical methods for genomewide association studies (GWAS) continue to improve. However, the increasing volume and variety of genetic and genomic data make computational speed and ease of data manipulation mandatory in future software. In our view, a collaborative effort of statistical geneticists is required to develop open source software targeted to genetic epidemiology. Our attempt to meet this need is called the OPENMENDELproject (https://openmendel.github.io). It aims to (1) enable interactive and reproducible analyses with informative intermediate results, (2) scale to big data analytics, (3) embrace parallel and distributed computing, (4) adapt to rapid hardware evolution, (5) allow cloud computing, (6) allow integration of varied genetic data types, and (7) foster easy communication between clinicians, geneticists, statisticians, and computer scientists. This article reviews and makes recommendations to the genetic epidemiology community in the context of the OPENMENDEL project.Comment: 16 pages, 2 figures, 2 table

The changing culture of silviculture

Changing climates are altering the structural and functional components of forest ecosystems at an unprecedented rate. Simultaneously, we are seeing a diversification of public expectations on the broader sustainable use of forest resources beyond timber production. As a result, the science and art of silviculture needs to adapt to these changing realities. In this piece, we argue that silviculturists are gradually shifting from the application of empirically derived silvicultural scenarios to new sets of approaches, methods and practices, a process that calls for broadening our conception of silviculture as a scientific discipline. We propose a holistic view of silviculture revolving around three key themes: observe, anticipate and adapt. In observe, we present how recent advances in remote sensing now enable silviculturists to observe forest structural, compositional and functional attributes in near-real-time, which in turn facilitates the deployment of efficient, targeted silvicultural measures in practice that are adapted to rapidly changing constraints. In anticipate, we highlight the importance of developing state-of-the-art models designed to take into account the effects of changing environmental conditions on forest growth and dynamics. In adapt, we discuss the need to provide spatially explicit guidance for the implementation of adaptive silvicultural actions that are efficient, cost-effective and socially acceptable. We conclude by presenting key steps towards the development of new tools and practical knowledge that will ensure meeting societal demands in rapidly changing environmental conditions. We classify these actions into three main categories: reexamining existing silvicultural trials to identify key stand attributes associated with the resistance and resilience of forests to multiple stressors, developing technological workflows and infrastructures to allow for continuous forest inventory updating frameworks, and implementing bold, innovative silvicultural trials in consultation with the relevant communities where a range of adaptive silvicultural strategies are tested. In this holistic perspective, silviculture can be defined as the science of observing forest condition and anticipating its development to apply tending and regeneration treatments adapted to a multiplicity of desired outcomes in rapidly changing realities