6,088 research outputs found
Pilot study of vegetation in the Alchichica-Perote region by remote sensing
A study of the application of satellite images to the identification of vegetation in a small area corresponding to the arid zone of Veracruz and part of Puebla is presented. This study is accomplished by means of images from the LANDSAT satellite obtained on January 19 and May 23, 1973. The interpretation of the different maps is made on the basis of information from the data bank of the Flora de Veracruz program, and various surveys made by land and air
Fast Bayesian estimation of brain activation with cortical surface fMRI data using EM
Task functional magnetic resonance imaging (fMRI) is a type of neuroimaging
data used to identify areas of the brain that activate during specific tasks or
stimuli. These data are conventionally modeled using a massive univariate
approach across all data locations, which ignores spatial dependence at the
cost of model power. We previously developed and validated a spatial Bayesian
model leveraging dependencies along the cortical surface of the brain in order
to improve accuracy and power. This model utilizes stochastic partial
differential equation spatial priors with sparse precision matrices to allow
for appropriate modeling of spatially-dependent activations seen in the
neuroimaging literature, resulting in substantial increases in model power. Our
original implementation relies on the computational efficiencies of the
integrated nested Laplace approximation (INLA) to overcome the computational
challenges of analyzing high-dimensional fMRI data while avoiding issues
associated with variational Bayes implementations. However, this requires
significant memory resources, extra software, and software licenses to run. In
this article, we develop an exact Bayesian analysis method for the general
linear model, employing an efficient expectation-maximization algorithm to find
maximum a posteriori estimates of task-based regressors on cortical surface
fMRI data. Through an extensive simulation study of cortical surface-based fMRI
data, we compare our proposed method to the existing INLA implementation, as
well as a conventional massive univariate approach employing ad-hoc spatial
smoothing. We also apply the method to task fMRI data from the Human Connectome
Project and show that our proposed implementation produces similar results to
the validated INLA implementation. Both the INLA and EM-based implementations
are available through our open-source BayesfMRI R package.Comment: 29 pages, 10 figures. arXiv admin note: text overlap with
arXiv:2203.0005
Improving Reliability of Subject-Level Resting-State fMRI Parcellation with Shrinkage Estimators
A recent interest in resting state functional magnetic resonance imaging
(rsfMRI) lies in subdividing the human brain into anatomically and functionally
distinct regions of interest. For example, brain parcellation is often used for
defining the network nodes in connectivity studies. While inference has
traditionally been performed on group-level data, there is a growing interest
in parcellating single subject data. However, this is difficult due to the low
signal-to-noise ratio of rsfMRI data, combined with typically short scan
lengths. A large number of brain parcellation approaches employ clustering,
which begins with a measure of similarity or distance between voxels. The goal
of this work is to improve the reproducibility of single-subject parcellation
using shrinkage estimators of such measures, allowing the noisy
subject-specific estimator to "borrow strength" in a principled manner from a
larger population of subjects. We present several empirical Bayes shrinkage
estimators and outline methods for shrinkage when multiple scans are not
available for each subject. We perform shrinkage on raw intervoxel correlation
estimates and use both raw and shrinkage estimates to produce parcellations by
performing clustering on the voxels. Our proposed method is agnostic to the
choice of clustering method and can be used as a pre-processing step for any
clustering algorithm. Using two datasets---a simulated dataset where the true
parcellation is known and is subject-specific and a test-retest dataset
consisting of two 7-minute rsfMRI scans from 20 subjects---we show that
parcellations produced from shrinkage correlation estimates have higher
reliability and validity than those produced from raw estimates. Application to
test-retest data shows that using shrinkage estimators increases the
reproducibility of subject-specific parcellations of the motor cortex by up to
30%.Comment: body 21 pages, 11 figure
Anomalous metamagnetic-like transition in a FeRh/FePt interface occurring at T120 K in the field-cooled-cooling curves for low magnetic fields
We report on the magnetic properties of a special configuration of a FeRh
thin film. An anomalous behavior on the magnetisation vs. temperature was
observed when low magnetic fields are applied in the plane of a thin layer of
FeRh deposited on ordered FePt. The anomalous effect resembles a
metamagnetic transition and occur only in the field-cooled-cooling
magnetisation curve at temperatures near 120 K in samples without any heat
treatment.Comment: 7 pages, 5 figures. arXiv admin note: text overlap with
arXiv:1008.195
320-to-10 Gbit/s all-optical demultiplexing using sum-frequency generation in PPLN waveguide
A 320-to-10 Gbit/s all-optical demultiplexer based on sum-frequency generation in a periodically-poled lithium niobate (PPLN) waveguide is demonstrated. A bit-error-rate of 10-9 is achieved with a power penalty of 1.5 dB
A Single-Block TRL Test Fixture for the Cryogenic Characterization of Planar Microwave Components
The High-Temperature-Superconductivity (HTS) group of the RF Technology Branch, Space Electronics Division, is actively involved in the fabrication and cryogenic characterization of planar microwave components for space applications. This process requires fast, reliable, and accurate measurement techniques not readily available. A new calibration standard/test fixture that enhances the integrity and reliability of the component characterization process has been developed. The fixture consists of 50 omega thru, reflect, delay, and device under test gold lines etched onto a 254 microns (0.010 in) thick alumina substrate. The Thru-Reflect-Line (TRL) fixture was tested at room temperature using a 30 omega, 7.62 mm (300 mil) long, gold line as a known standard. Good agreement between the experimental data and the data modelled using Sonnet's em(C) software was obtained for both the return (S(sub 11)) and insertion (S( 21)) losses. A gold two-pole bandpass filter with a 7.3 GHz center frequency was used as our Device Under Test (DUT), and the results compared with those obtained using a Short-Open-Load-Thru (SOLT) calibration technique
Bacterial-foraging optimization algorithm for non-hazardous plant layouts
PresentationThe following article approaches a safe plant layout design problem based on a bacterial-foraging optimization algorithm. Our approach finds the position in the two dimensional plane for each main process unit and evaluates the possibility of secondary contention for pertinent units, in order to minimize capital costs associated to equipment loss, piping, secondary contention, and usage of area. Fire and Explosion hazard is considered as the relevant safety aspect for distribution, and it is assessed through Dow’s Fire and Explosion Index. The proposed solution approach provides an alternative to hard-optimization methods, by allowing greater flexibility in accounting for both safety and economic aspects, while providing high quality solutions in a limited computation time. The aim of our proposed solution approach is to provide support to expert decision-making during the early plant layout design steps. A case study based on an acrylic-acid production plant, which has been used by several other papers that appeared in the literature, serves the purposes of showing the appropriateness and effectiveness of the method
Lean Manufacturing Production Management Model using the Johnson Method Approach to Reduce Delivery Delays for Printing Production Lines in the Digital Graphic Design Industry
Several factors compel graphic design companies to improve efficiency and competitiveness in their production lines. However, these companies are not prepared to take on this challenge, as they report delays in 20% of their deliveries, caused by high setup times, low machine availability, and poor work scheduling. In this context, this study proposes a new production management model fed by the interaction of lean manufacturing tools and the Johnson scheduling method. This model has been validated by direct application at the SISSA. The results obtained were the reduction of the setup time to 15 minutes, increased machine availability up to 24%, and an efficient scheduling of its tasks. All of these reduced the percentage of delivery delays from 20% to 6%
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