194 research outputs found
Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning
We introduce a new type of query mechanism for collecting human feedback,
called the perceptual adjustment query ( PAQ). Being both informative and
cognitively lightweight, the PAQ adopts an inverted measurement scheme, and
combines advantages from both cardinal and ordinal queries. We showcase the PAQ
in the metric learning problem, where we collect PAQ measurements to learn an
unknown Mahalanobis distance. This gives rise to a high-dimensional, low-rank
matrix estimation problem to which standard matrix estimators cannot be
applied. Consequently, we develop a two-stage estimator for metric learning
from PAQs, and provide sample complexity guarantees for this estimator. We
present numerical simulations demonstrating the performance of the estimator
and its notable properties.Comment: 42 pages, 6 figure
A Generative Deep Learning Approach to Stochastic Downscaling of Precipitation Forecasts
Despite continuous improvements, precipitation forecasts are still not as
accurate and reliable as those of other meteorological variables. A major
contributing factor to this is that several key processes affecting
precipitation distribution and intensity occur below the resolved scale of
global weather models. Generative adversarial networks (GANs) have been
demonstrated by the computer vision community to be successful at
super-resolution problems, i.e., learning to add fine-scale structure to coarse
images. Leinonen et al. (2020) previously applied a GAN to produce ensembles of
reconstructed high-resolution atmospheric fields, given coarsened input data.
In this paper, we demonstrate this approach can be extended to the more
challenging problem of increasing the accuracy and resolution of comparatively
low-resolution input from a weather forecasting model, using high-resolution
radar measurements as a "ground truth". The neural network must learn to add
resolution and structure whilst accounting for non-negligible forecast error.
We show that GANs and VAE-GANs can match the statistical properties of
state-of-the-art pointwise post-processing methods whilst creating
high-resolution, spatially coherent precipitation maps. Our model compares
favourably to the best existing downscaling methods in both pixel-wise and
pooled CRPS scores, power spectrum information and rank histograms (used to
assess calibration). We test our models and show that they perform in a range
of scenarios, including heavy rainfall.Comment: Submitted to JAMES 4/4/2
Inadequate reporting of research ethics review and informed consent in cluster randomized trials : review of random sample of published trials
Peer reviewedPublisher PD
A global analysis of management capacity and ecological outcomes in terrestrial protected areas
Protecting important sites is a key strategy for halting the loss of biodiversity. However, our understanding of the relationship between management inputs and biodiversity outcomes in protected areas (PAs) remains weak. Here, we examine biodiversity outcomes using species population trends in PAs derived from the Living Planet Database in relation to management data derived from the Management Effectiveness Tracking Tool (METT) database for 217 population time-series from 73 PAs. We found a positive relationship between our METT-based scores for Capacity and Resources and changes in vertebrate abundance, consistent with the hypothesis that PAs require adequate resourcing to halt biodiversity loss. Additionally, PA age was negatively correlated with trends for the mammal subsets and PA size negatively correlated with population trends in the global subset. Our study highlights the paucity of appropriate data for rigorous testing of the role of management in maintaining species populations across multiple sites, and describes ways to improve our understanding of PA performance
OH PLIF Visualization of the UVa Supersonic Combustion Experiment: Configuration A
Hydroxyl radical (OH) planar laser-induced fluorescence (PLIF) measurements were performed in the University of Virginia s dual-mode scramjet experiment. The test section was set up in configuration A, which includes a Mach 2 nozzle, combustor, and extender section. Hydrogen fuel was injected through an unswept compression ramp at two different equivalence ratios. Through the translation of the optical system and the use of two separate camera views, the entire optical range of the combustor was accessed. Single-shot, average, and standard deviation images of the OH PLIF signal are presented at several streamwise locations. The results show the development of a highly turbulent flame structure and provide an experimental database to be used for numerical model assessment
OH PLIF Visualization of the UVa Supersonic Combustion Experiment: Configuration C
Non-intrusive hydroxyl radical (OH) planar laser-induced fluorescence (PLIF) measurements were obtained in configuration C of the University of Virginia supersonic combustion experiment. The combustion of hydrogen fuel injected through an unswept compression ramp into a supersonic cross-flow was imaged over a range of streamwise positions. Images were corrected for optical distortion, variations in the laser sheet profile, and different camera views. Results indicate an effect of fuel equivalence ratio on combustion zone shape and local turbulence length scale. The streamwise location of the reaction zone relative to the fuel injector was also found to be sensitive to the fuel equivalence ratio. The flow boundary conditions in the combustor section, which are sensitive to the fuel flow rate, are believed to have caused this effect. A combination of laser absorption and radiative trapping effects are proposed to have caused asymmetry observed in the images. The results complement previously published OH PLIF data obtained for configuration A along with other non-intrusive measurements to form a database for computational fluid dynamics (CFD) model validation
Protein kinase A negatively regulates Ca2+ signalling in Toxoplasma gondii.
The phylum Apicomplexa comprises a group of obligate intracellular parasites that alternate between intracellular replicating stages and actively motile extracellular forms that move through tissue. Parasite cytosolic Ca2+ signalling activates motility, but how this is switched off after invasion is complete to allow for replication to begin is not understood. Here, we show that the cyclic adenosine monophosphate (cAMP)-dependent protein kinase A catalytic subunit 1 (PKAc1) of Toxoplasma is responsible for suppression of Ca2+ signalling upon host cell invasion. We demonstrate that PKAc1 is sequestered to the parasite periphery by dual acylation of PKA regulatory subunit 1 (PKAr1). Upon genetic depletion of PKAc1 we show that newly invaded parasites exit host cells shortly thereafter, in a perforin-like protein 1 (PLP-1)-dependent fashion. Furthermore, we demonstrate that loss of PKAc1 prevents rapid down-regulation of cytosolic [Ca2+] levels shortly after invasion. We also provide evidence that loss of PKAc1 sensitises parasites to cyclic GMP (cGMP)-induced Ca2+ signalling, thus demonstrating a functional link between cAMP and these other signalling modalities. Together, this work provides a new paradigm in understanding how Toxoplasma and related apicomplexan parasites regulate infectivity
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