Masculinity, modernist form and the ends of Empire in Virginia's Woolf's fiction

The study traces the development of Woolf's methods for fictional representation of masculinity; it argues that chief among her narrative strategies for defamiliarising the public world of men and for bringing male characters into critical perspective is her use of autoethnography (Pratt 1992). The most explicit statement of Woolf's construction of masculinity is in the polemical, pacifist essay Three Guineas (1938), which makes direct connections between masculinity, war and the rise of Fascism in Europe, and between masculine dominance in the domestic sphere and tyrannical dictatorship in the international sphere of imperial rivalry and war. The study explores connections between the work of Bourdieu, especially his analysis in Masculine Domination (2001) of the persistence in the present of archaic gender divisions and relations of dominance and subordination between men and women, and Woolf's analysis and representation of relations of gender and power in the modern, early twentieth-century world. A reading of the novels shows how Woolf's outside perspective on men and masculinity shapes her thematic focus and formal style, and the development of the autoethnographic method is traced from its early manifestations to a more systematic deployment in the later work. The sequence of novels depicts the slow demise of a Victorian/Edwardian hegemonic model of colonial/imperial masculinity reflecting British imperial decline and the catastrophiC impact of the First World War upon the old order; in the later novels an uncertain new gender order is glimpsed as Woolf demonstrates both continuity and change in the acquisition of gender identities. The study also reviews recent developments in the continuing evolution of Woolf's literary and political reputation with an account of her steadily emerging reputation as a public intellectual

Lupin stubbles : getting the best with weaner sheep

Sweet lupins are now grown on about a million hectares in Western Australia each year. If half of the State\u27s seven million weaners were grazed as recommended on half of the lupin stubbles, it could generate about $15 million from reduced supplementary feeding, greater wool production and other advantages. But correct management is important, particularly knowing when to take weaners out. Research by the Department over the last five years is now indicating how this should be done

Phomopsis-resistant lupin stubbles as feed for weaner sheep

The breeding of sweet, narrow-leafed lupins with increased resistance to Phomopsis leptostromiformis, the fungus that causes lupinosis in sheep, is a breakthrough for the summer nutrition of weaner sheep. The new resistant varieties, Gungurru for the medium (325 to 450 mm) rainfall areas and Yorrel for low rainfall areas (less than 325 mm), were released by the Department of Agriculture in 1988. This article discusses progress in a four-year project which is examining liveweight and wool production of weaners grazing Gungurru stubbles

PROFILE OF PARTICIPANTS IN FISH AND WILDLIFE RELATED OUTDOOR RECREATIONAL ACTIVITIES IN THE UNITED STATES

Resource /Energy Economics and Policy,

Instructional leadership and student achievement: the role of Catholic identity in supporting instructional leadership

This study examined the relationship between strong instructional leadership, as measured by the Principal Instructional Measurement Rating Scale (PIMRS) and high student academic outcomes in 35 Mid-Atlantic Catholic elementary schools. In addition, the research explored the role of Catholic identity in supporting instructional leadership behaviors in Catholic elementary schools. The purpose of the study was to examineA) instructional leadership behaviors in principals with high versus low student academic outcomes, and B) to use a measure of Catholic identity to differentiate the extent to which principals can focus on instructional leadership This research focused on ways Catholic schools can both improve themselves and inform charter and traditional public schools. The study consisted of over 100 principals and teachers in Mid-Atlantic Catholic elementary schools. The participants completed the PIMRS and Framework for Catholic Identity (FCI) to identify instructional leadership behaviors and level of Catholic identity. To document student academic achievement in aggregate, the research used a value added growth model. Using factor analysis, the researcher identified behaviors associated with schools in different levels of student growth and performance on standardized assessment in relation to outcomes on the PIMRS and FCI.Research on principal leadership behavior is extensive and focuses on either traditional public schools, using an instructional leadership model supported by top-down leadership or public charter schools that focus on transformational leadership. The research provided evidence that Catholic schools reside in between instructional and transformational leadership, with Catholic culture supporting instructional leadership. Since Catholic schools lack an organized and systemic top-down leadership model, there is a gap in knowledge of the unique environment of site-based leadership management in Catholic schools. In addition, the research informs school improvement across all sectors of K-12 education. This research is designed to identify best practices in site-based leadership, as practiced in Catholic (P)K-8 elementary schools, to help improve education in public, charter, and non-public schools.With many organizations, such as the Bill and Melinda Gates Foundation, supporting transformational leadership model to expand charter school across the country, there is a need to understand in what context it is possible to scale a site-based leadership model. Catholic schools benefit from having a Catholic culture drive their goals and purpose, which unlike charter schools, is not dependent on a single person or group. The implications of this study will inform Catholic school central offices on principal behaviors within its unique structure. In addition, the research will inform school reformers on how to harness the most effective elements of both instructional and transformational leadership to improve student academic outcomes for all students.Ed.D., Educational Leadership and Management -- Drexel University, 201

Biodiversity benefits of an ecosystem engineer are negated by an invasive predator

Ecosystem engineers play a vital role in community assembly by modifying the environment to create novel habitat features. Woodrats (Neotoma sp.) build and maintain intricate stick-nests that stockpile organic materials and create habitat for other small species. The Key Largo woodrat (Neotoma floridana smalli) is an endangered subspecies endemic to Key Largo, Florida, USA, that has undergone substantial declines due to habitat loss and predation by invasive predators. We leveraged data from a camera trap monitoring grid at supplemental woodrat nest structures to survey bird communities to evaluate the role of woodrat nest use and stick-nest building related to bird abundance using generalized linear models. We predicted that woodrat occurrence and stick-nest building would positively correlate with bird species richness and abundance due to the creation of habitat structures that support prey for birds. To test this, we analyzed the relationship that bird abundance and species richness have with several indicators of woodrat activity along with other environmental and predator variables. Bird abundance was positively associated with woodrat supplemental nest use and stick-nest building. However, these positive associations were largely negated by the presence of free-roaming cats (Felis catus), an invasive predator, and dampened by proximity to human development. We provide evidence that woodrats may have cascading effects on their local food webs by creating foraging grounds for birds, but this positive relationship is disrupted by the presence of an introduced predator

Estimating the total incidence of kidney failure in australia including individuals who are not treated by dialysis or transplantation

Background: To date, incidence data for kidney failure in Australia have been available for only those who start renal replacement therapy (RRT). Information about the total incidence of kidney failure, including non-RRT-treated cases, is important to help understand the burden of kidney failure in the community and the characteristics of patients who die without receiving treatment

Automatic Spectroscopic Data Categorization by Clustering Analysis (ASCLAN): A Data-Driven Approach for Distinguishing Discriminatory Metabolites for Phenotypic Subclasses

We propose a novel data-driven approach aiming to reliably distinguish discriminatory metabolites from nondiscriminatory metabolites for a given spectroscopic data set containing two biological phenotypic subclasses. The automatic spectroscopic data categorization by clustering analysis (ASCLAN) algorithm aims to categorize spectral variables within a data set into three clusters corresponding to noise, nondiscriminatory and discriminatory metabolites regions. This is achieved by clustering each spectral variable based on the r(2) value representing the loading weight of each spectral variable as extracted from a orthogonal partial least-squares discriminant (OPLS-DA) model of the data set. The variables are ranked according to r(2) values and a series of principal component analysis (PCA) models are then built for subsets of these spectral data corresponding to ranges of r(2) values. The Q(2)X value for each PCA model is extracted. K-means clustering is then applied to the Q(2)X values to generate two clusters based on minimum Euclidean distance criterion. The cluster consisting of lower Q(2)X values is deemed devoid of metabolic information (noise), while the cluster consists of higher Q(2)X values is then further subclustered into two groups based on the r(2) values. We considered the cluster with high Q(2)X but low r(2) values as nondiscriminatory, while the cluster with high Q(2)X and r(2) values as discriminatory variables. The boundaries between these three clusters of spectral variables, on the basis of the r(2) values were considered as the cut off values for defining the noise, nondiscriminatory and discriminatory variables. We evaluated the ASCLAN algorithm using six simulated (1)H NMR spectroscopic data sets representing small, medium and large data sets (N = 50, 500, and 1000 samples per group, respectively), each with a reduced and full resolution set of variables (0.005 and 0.0005 ppm, respectively). ASCLAN correctly identified all discriminatory metabolites and showed zero false positive (100% specificity and positive predictive value) irrespective of the spectral resolution or the sample size in all six simulated data sets. This error rate was found to be superior to existing methods for ascertaining feature significance: univariate t test by Bonferroni correction (up to 10% false positive rate), Benjamini-Hochberg correction (up to 35% false positive rate) and metabolome wide significance level (MWSL, up to 0.4% false positive rate), as well as by various OPLS-DA parameters: variable importance to projection, (up to 15% false positive rate), loading coefficients (up to 35% false positive rate), and regression coefficients (up to 39% false positive rate). The application of ASCLAN was further exemplified using a widely investigated renal toxin, mercury II chloride (HgCl2) in rat model. ASCLAN successfully identified many of the known metabolites related to renal toxicity such as increased excretion of urinary creatinine, and different amino acids. The ASCLAN algorithm provides a framework for reliably differentiating discriminatory metabolites from nondiscriminatory metabolites in a biological data set without the need to set an arbitrary cut off value as applied to some of the conventional methods. This offers significant advantages over existing methods and the possibility for automation of high-throughput screening in "omics" data

Abundant Weirdness: Our Journey to Breaking a World Record

In Fall 2013, the Math Honors Seminar at Central Washington University broke the world record for largest primitive weird number ever discovered. A weird number is a number N whose set of proper divisors sums to be larger than itself, but which has no subset of proper divisors exactly equal to N. Take, for example, the number 70, which has proper divisors {1, 2, 5, 7, 10, 14, 35}. The sum of these numbers is 74, a number that is larger than our original number. Though, this only satisfies one of the qualifications for the number 70 to be considered “weird.” In particular, 70 is a weird number because no subset sum of {1, 2, 5, 7, 10, 14, 35} equals 70. The most important class of weird numbers is the primitive weird numbers – those not divisible by any others. Thousands of primitive weird numbers are known, but there is no efficient way to find them all. By early 2013, the record for the largest known primitive number was held by Dr. Sidney Kravitz, who discovered a 53-digit weird number. Using a generalization of Kravitz’s ideas, the class broke this record, finding weird numbers with 74, 127, and 226 decimal digits