947 research outputs found
A Paler Shade of Green: Suburban Nature in Margaret Atwood’s Cat's Eye
Critics of Canadian literature such as Cheryl Cowdy, Frank Davey, and Franca Bellarsi construe suburbia as existing somewhere in between the concrete jungle and the verdant wilderness. The ecocritical implications of this geographic and critical positioning, however, have not yet been thoroughly examined. Common images of suburbanites portray people in the “enclosed private worlds of fences, parlours and automobiles,” cut off from their larger communities and environments in collective isolation. Margaret Atwood’s Cat’s Eye (1988) depicts how this separate-from-nature culture is fostered. As Elaine Risley faces the repressed, traumatizing experiences of her childhood, she confronts her and her society’s various interrelationships with the natural world, showing how a suburban upbringing can produce unsatisfactory relationships with both human and non-human nature. In so doing, Cat’s Eye critiques common, urbane conceptions of nature from a point of view that is quintessentially ecocritical. Aside from the obvious environmental concerns vocalized by Elaine’s biologist father, ecological issues are relevant to three other aspects of the novel: Elaine’s early childhood in northern Ontario, her later summer vacations there, and the social pressures and cultural practices that Elaine experiences in suburbia. Through these elements of the narrative, Cat’s Eye articulates some of the fundamental relationships with nature experienced by those living in suburban Canada and seeks to move beyond conventional portrayals of this relationship
Learning by Asking Questions
We introduce an interactive learning framework for the development and
testing of intelligent visual systems, called learning-by-asking (LBA). We
explore LBA in context of the Visual Question Answering (VQA) task. LBA differs
from standard VQA training in that most questions are not observed during
training time, and the learner must ask questions it wants answers to. Thus,
LBA more closely mimics natural learning and has the potential to be more
data-efficient than the traditional VQA setting. We present a model that
performs LBA on the CLEVR dataset, and show that it automatically discovers an
easy-to-hard curriculum when learning interactively from an oracle. Our LBA
generated data consistently matches or outperforms the CLEVR train data and is
more sample efficient. We also show that our model asks questions that
generalize to state-of-the-art VQA models and to novel test time distributions
Parallel netCDF: A Scientific High-Performance I/O Interface
Dataset storage, exchange, and access play a critical role in scientific
applications. For such purposes netCDF serves as a portable and efficient file
format and programming interface, which is popular in numerous scientific
application domains. However, the original interface does not provide an
efficient mechanism for parallel data storage and access. In this work, we
present a new parallel interface for writing and reading netCDF datasets. This
interface is derived with minimum changes from the serial netCDF interface but
defines semantics for parallel access and is tailored for high performance. The
underlying parallel I/O is achieved through MPI-IO, allowing for dramatic
performance gains through the use of collective I/O optimizations. We compare
the implementation strategies with HDF5 and analyze both. Our tests indicate
programming convenience and significant I/O performance improvement with this
parallel netCDF interface.Comment: 10 pages,7 figure
Are You Going to Dance?
https://digitalcommons.library.umaine.edu/mmb-vp/4646/thumbnail.jp
Improving statistical models for flood risk assessment
Widespread flooding, such as the events in the winter of 2013/2014 in the UK and early summer 2013 in Cent ral Europe, demonst rate clearly how important it is to understand the characterist ics of floods in which mult iple locat ions experience ext reme river flows. Recent developments in mult ivariate stat ist ical modelling help to place such events in a probabilist ic framework. It is now possible to perform joint probability analysis of events defined in terms of physical variables at hundreds of locat ions simultaneously, over mult iple variables (including river flows, rainfall and sea levels), combined with analysis of temporal dependence to capture the evolut ion of events over a large domain. Crit ical const raints on such data-driven methods are the problems of missing data, especially where records over a network are not all concurrent , the joint analysis of several different physical variables, and the choice of suitable t ime scales when combining informat ion from those variables. This paper presents new developments of a high-dimensional condit ional probability model for ext reme river flow events condit ioned on flow and r ainfall observat ions. These are: a new computat ionally efficient paramet ric approach to account for missing data in the joint analysis of ext remes over a large hydromet ric network; a robust approach for the spat ial interpolation of extreme events throughout a large river network,; generat ion of realist ic est imates of ext remes at ungauged locat ions; and, exploit ing rainfall information rat ionally within the stat ist ical model to help improve efficiency. These methodological advances will be illust rated with data from the UK river network and recent events to show how they cont ribute to a flexible and effective framework for flood risk assessment, with applicat ions in the insurance sector and for nat ional-scale emergency planning
Nature is a rich source of medicine - if we can protect it
First paragraph: The Pacific yew tree is a fairly small and slow growing conifer native to the Pacific Northwest. The Gila monster is a lizard with striking orange and black markings from the drylands of the Southwestern US and Mexico. Two very different organisms, but with a fascinating connection. They've both given us drugs that have saved and improved the lives of millions of people. Paclitaxel, originally isolated in 1971 from the bark of the Pacific Yew tree, is so important for treating various cancers that it is one of the World Health Organisation’s "Essential Medicines". This compound has been studied in more than 3,000 clinical trials. It's safe and effective and it generates sales of around US$80-100m per year.https://theconversation.com/nature-is-a-rich-source-of-medicine-if-we-can-protect-it-10747
Today’s advanced is tomorrow’s basic
https://deepblue.lib.umich.edu/bitstream/2027.42/145431/1/13089_2018_Article_100.pd
Feasibility study of advanced focused cardiac measurements within the emergency department
Abstract
Background
This study aims to compare the increased time needed to perform advanced focused cardiac measurements in the emergency department, including diastolic heart failure evaluation via E/E′, and cardiac output with LVOT/VTI. Patients with pertinent cardiopulmonary symptoms in the emergency department had a focused cardiac ultrasound performed by the emergency department ultrasound team. The ability to obtain basic cardiac windows, evaluate for effusion, systolic ejection fraction, and right-sided heart pressures were recorded. Advanced measurements, along with time to obtain all images and the training level of the provider, were recorded.
Results
Fifty-three patients were enrolled. Basic focused cardiac windows were able to be obtained in 80% of patients. The average 4-window focused cardiac ultrasound took 4Â min and 49Â s to perform. Diastolic measurements were able to be obtained in 51% of patients, taking an average of 3Â min and 17Â s. Cardiac output measurements were able to be obtained in 53% of patients, taking an average of 3Â min and 8Â s.
Conclusion
The ability to obtain these images improved with increasing level of training. Performing both cardiac output and diastolic measurements increased the time with bedside ultrasound by 6Â min and 25Â s, and were able to be obtained in slightly over half of all ED patients.https://deepblue.lib.umich.edu/bitstream/2027.42/143847/1/13089_2018_Article_93.pd
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