4,708 research outputs found
Effects of low level military training flights on wading bird colonies in Florida
During 1983 and 1984 the effect of low level military training
flights on the establishment. size and reproductive success of wading
bird colonies was studied in Florida. Based on the indirect evidence
of colony distributions and turnover rates in relation to military
areas (training routes designated to 500 feet or less above ground
level and military operations areas). there was no demonstrated effect
of military activity on wading bird colony establishment or size on a
statewide basis. Colony distributions were random with respect to
military areas and turnover rates were within 2% when military and
non-military areas were compared. Colony distributions and turnover
rates, however. were related to the amount and type.Les tuer-tne or
freshwater) of wetland. respectively.
During two breeding seasons the behavioral responses and
reproductive success of selected species were monitored in a
non-habituated treatment colony (military overflights) and a control
colony (no overflights). Breeding wading birds responded to F-16
overflights at 420 knots indicated airspeed. 82-84% maximum rpm. 500
feet above ground level and sound levels ranging from 55-100 dBA by
exhibiting no response. looking up or changing position (usually to an
alert posture): no productivity limiting responses were observed.
High-nesting Great Egrets responded more than other species, nestling
Great Egrets and Cattle Egrets responded significantly (r <.05) more
intensely than adults of their respective species, and adults
responded less during incubation and late chick-rearing than at other
times. In addition, no differences in adult attendance, aggressive
interactions or chick feeding rates were observed to result from F-16 overflights. No evidence of habituation to overflights was noted.
Humans entering the colony or airboats approaching the colony vicinity
elicited the most severe responses (flushing and panic flights)
observed at both sites.
Since relatively little coastal military activity occurs at low
levels ( ~500 ft) and only one Brown Pelican colony (5-6% of the
breeding population) was located in such an area, the reproductive
success of five, more lIexposedll study species (Great Egrets, Snowy
Egrets, Tricolored Herons, Little Blue Herons, Cattle Egrets) nesting
in interior freshwater colonies was studied. Reproductive activity
including such factors as nest success, nestling survival, nestling
mortality, and nesting chronology was independent of F-16 overflights
but related to ecological factors including colony location, colony
characteristics and climatology. The responses to and effects of F-16
overflights, as reported here, should not be considered representative
of military aircraft at lower altitudes or greater noise levels. (194 pages
CALCULATION OF THE MINIMUM NUMBER OF REPLICATE SPOTS REQUIRED FOR DETECTION OF SIGNIFICANT GENE EXPRESSION FOLD CHANGE IN MICROARRA Y EXPERIMENTS
Calculations for the number of per gene replicate spots in microarray experiments are presented for the purpose of obtaining estimates of the sampling variability present in microarray data, and for determining the minimum number of replicate spots required to achieve a high probability of detecting a significant fold change in gene expression. Our approach is based on data from control microarrays, and employs standard statistical estimation techniques. We have demonstrated the usefulness of our framework by analyzing two experimental data sets containing control array data. The minimum number of replicate spots required on a treatment array were calculated to achieve detection of a 3-fold increase in expression with 90%, 95% or 99% confidence. The inclusion of replicate spots on microarrays not only allows more accurate estimation of the variability present in an experiment, but more importantly increases the probability of detecting genes undergoing significant fold changes in expression, while substantially decreasing the probability of observing fold changes due to chance rather than true differential expression
Expressive Body Capture: 3D Hands, Face, and Body from a Single Image
To facilitate the analysis of human actions, interactions and emotions, we
compute a 3D model of human body pose, hand pose, and facial expression from a
single monocular image. To achieve this, we use thousands of 3D scans to train
a new, unified, 3D model of the human body, SMPL-X, that extends SMPL with
fully articulated hands and an expressive face. Learning to regress the
parameters of SMPL-X directly from images is challenging without paired images
and 3D ground truth. Consequently, we follow the approach of SMPLify, which
estimates 2D features and then optimizes model parameters to fit the features.
We improve on SMPLify in several significant ways: (1) we detect 2D features
corresponding to the face, hands, and feet and fit the full SMPL-X model to
these; (2) we train a new neural network pose prior using a large MoCap
dataset; (3) we define a new interpenetration penalty that is both fast and
accurate; (4) we automatically detect gender and the appropriate body models
(male, female, or neutral); (5) our PyTorch implementation achieves a speedup
of more than 8x over Chumpy. We use the new method, SMPLify-X, to fit SMPL-X to
both controlled images and images in the wild. We evaluate 3D accuracy on a new
curated dataset comprising 100 images with pseudo ground-truth. This is a step
towards automatic expressive human capture from monocular RGB data. The models,
code, and data are available for research purposes at
https://smpl-x.is.tue.mpg.de.Comment: To appear in CVPR 201
A Bayesian model for classifying all differentially expressed proteins simultaneously in 2D PAGE gels
Background: Two-dimensional polyacrylamide gel electrophoresis (2D PAGE) is commonly used to identify differentially expressed proteins under two or more experimental or observational conditions. Wu et al (2009) developed a univariate probabilistic model which was used to identify differential expression between Case and Control groups, by applying a Likelihood Ratio Test (LRT) to each protein on a 2D PAGE. In contrast to commonly used statistical approaches, this model takes into account the two possible causes of missing values in 2D PAGE: either (1) the non-expression of a protein; or (2) a level of expression that falls below the limit of detection.Results: We develop a global Bayesian model which extends the previously described model. Unlike the univariate approach, the model reported here is able treat all differentially expressed proteins simultaneously. Whereas each protein is modelled by the univariate likelihood function previously described, several global distributions are used to model the underlying relationship between the parameters associated with individual proteins. These global distributions are able to combine information from each protein to give more accurate estimates of the true parameters. In our implementation of the procedure, all parameters are recovered by Markov chain Monte Carlo (MCMC) integration. The 95% highest posterior density (HPD) intervals for the marginal posterior distributions are used to determine whether differences in protein expression are due to differences in mean expression intensities, and/or differences in the probabilities of expression.Conclusions: Simulation analyses showed that the global model is able to accurately recover the underlying global distributions, and identify more differentially expressed proteins than the simple application of a LRT. Additionally, simulations also indicate that the probability of incorrectly identifying a protein as differentially expressed (i.e., the False Discovery Rate) is very low. The source code is available at https://github.com/stevenhwu/BIDE-2D
Context-specific gene regulatory networks subdivide intrinsic subtypes of breast cancer
<p>Abstract</p> <p>Background</p> <p>Breast cancer is a highly heterogeneous disease with respect to molecular alterations and cellular composition making therapeutic and clinical outcome unpredictable. This diversity creates a significant challenge in developing tumor classifications that are clinically reliable with respect to prognosis prediction.</p> <p>Results</p> <p>This paper describes an unsupervised context analysis to infer context-specific gene regulatory networks from 1,614 samples obtained from publicly available gene expression data, an extension of a previously published methodology. We use the context-specific gene regulatory networks to classify the tumors into clinically relevant subgroups, and provide candidates for a finer sub-grouping of the previously known intrinsic tumors with a focus on Basal-like tumors. Our analysis of pathway enrichment in the key contexts provides an insight into the biological mechanism underlying the identified subtypes of breast cancer.</p> <p>Conclusions</p> <p>The use of context-specific gene regulatory networks to identify biological contexts from heterogenous breast cancer data set was able to identify genomic drivers for subgroups within the previously reported intrinsic subtypes. These subgroups (contexts) uphold the clinical relevant features for the intrinsic subtypes and were associated with increased survival differences compared to the intrinsic subtypes. We believe our computational approach led to the generation of novel rationalized hypotheses to explain mechanisms of disease progression within sub-contexts of breast cancer that could be therapeutically exploited once validated.</p
Cerumen Composition by Flash Pyrolysis-Gas Chromatography/Mass Spectrometry
Objective: To assess the chemical composition of cerumen by flash pyrolysis-gas chromatography/mass spectrometry.
Study Design: Collected earwax specimens were fractionated into residue and supernatant by means of deoxycholate. This natural bile acid produces significantly better disintegration of earwax in vitro than do presently available ceruminolytic preparations, and also has demonstrated excellent clinical results in vivo to date.
Patients: The sample for analysis was obtained from a patient with clinical earwax impaction.
Results: The supernatant is composed of simple aromatic hydrocarbons, C5-Cl 7 straight-chain hydrocarbons, a complex mixture of compounds tentatively identified as diterpenoids, and steroids, in particular cholesterol. The residue, on the other hand, produced simple aromatic compounds (including benzenes, phenols, and benzonitriles), C5-C25 straight-chain hydrocarbons, greater relative quantities of nitrogen compounds and phenol, and lesser importance of the (tentatively identified) diterpenoids.
Conclusions: Through the use of the detergent deoxycholate, squalene and a tentatively identified diterpenoid were revealed to be present in a free, unbound state, whereas some steroids and hydrocarbons appeared to be bound to a macromolecular structure by nitrogen linkages or other bonds. Additionally, this study reintroduces detergents as a viable method of earwax removal, specifically the bile acids
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