Deployment and Performance Analyses of High-Resolution Iowa XPOL Radar System during the NASA IFloodS Campaign

Abstract This article presents the data collected and analyzed using the University of Iowa’s X-band polarimetric (XPOL) radars that were part of the spring 2013 hydrology-oriented Iowa Flood Studies (IFloodS) field campaign, sponsored by NASA’s Global Precipitation Measurement (GPM) Ground Validation (GV) program. The four mobile radars have full scanning capabilities that provide quantitative estimation of the rainfall at high temporal and spatial resolutions over experimental watersheds. IFloodS was the first extensive test of the XPOL radars, and the XPOL radars demonstrated their field worthiness during this campaign with 46 days of nearly uninterrupted, remotely monitored, and controlled operations. This paper presents detailed postcampaign analyses of the high-resolution, research-quality data that the XPOL radars collected. The XPOL dual-polarimetric products and rainfall are compared with data from other instruments for selected diverse meteorological events at high spatiotemporal resolutions from unprecedentedly unique and vast data generated during IFloodS operations. The XPOL data exhibit a detailed, complex structure of precipitation viewed at multiple range resolutions (75 and 30 m). The inter-XPOL comparisons within an overlapping scanned domain demonstrate consistency across different XPOL units. The XPOLs employed a series of heterogeneous scans and obtained estimates of the meteorological echoes up to a range oversampling of 7.5 m. A finer-resolution (30 m) algorithm is described to correct the polarimetric estimates for attenuation at the X band and obtain agreement of attenuation-corrected products with disdrometers and NASA S-band polarimetric (NPOL) radar. The paper includes hardware characterization of Iowa XPOL radars conducted prior to the deployment in IFloodS following the GPM calibration protocol.

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Synthesis of High-Resolution Research-Quality MRI Data from Clinical MRI Data in Patients with COVID-19

10.1101/2021.11.25.21266090 ◽

2021 ◽

Author(s):

Ryan J Cali ◽

Holly J Freeman ◽

Benjamin Billot ◽

Megan E Barra ◽

David Fischer ◽

...

Keyword(s):

White Matter ◽

High Resolution ◽

Neurological Disorders ◽

Grey Matter ◽

Brain Lesion ◽

Research Quality ◽

Quality Data ◽

Focal Lesions ◽

Mri Scans ◽

Clinical Mri

Pathophysiological mechanisms of neurological disorders in patients with coronavirus disease 2019 (COVID-19) are poorly understood, partly because of a lack of high-resolution neuroimaging data. We applied SynthSR, a convolutional neural network that synthesizes high-resolution isotropic research-quality data from thick-slice clinical MRI data, to a cohort of 11 patients with severe COVID-19. SynthSR successfully synthesized T1-weighted MPRAGE data at 1 mm spatial resolution for all 11 patients, each of whom had at least one brain lesion. Correlations between volumetric measures derived from synthesized and acquired MPRAGE data were strong for the cortical grey matter, subcortical grey matter, brainstem, hippocampus, and hemispheric white matter (r=0.84 to 0.96, p≤0.001), but absent for the cerebellar white matter and corpus callosum (r=0.04 to 0.17, p>0.61). SynthSR creates an opportunity to quantitatively study clinical MRI scans and elucidate the pathophysiology of neurological disorders in patients with COVID-19, including those with focal lesions.

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Computer processing of high-resolution images of periodic specimens

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100141834 ◽

1986 ◽

Vol 44 ◽

pp. 2-5

Author(s):

W. Chiu ◽

M.F. Schmid ◽

T.-W. Jeng

Keyword(s):

High Resolution ◽

Fourier Transforms ◽

Complex Structure ◽

Distribution Functions ◽

Multiple Image ◽

Cryo Electron Microscopy ◽

Structure Factors ◽

Unit Cells ◽

High Resolution Images ◽

Phase Probability Distribution

Cryo-electron microscopy has been developed to the point where one can image thin protein crystals to 3.5 Å resolution. In our study of the crotoxin complex crystal, we can confirm this structural resolution from optical diffractograms of the low dose images. To retrieve high resolution phases from images, we have to include as many unit cells as possible in order to detect the weak signals in the Fourier transforms of the image. Hayward and Stroud proposed to superimpose multiple image areas by combining phase probability distribution functions for each reflection. The reliability of their phase determination was evaluated in terms of a crystallographic “figure of merit”. Grant and co-workers used a different procedure to enhance the signals from multiple image areas by vector summation of the complex structure factors in reciprocal space.

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Experimental Validation of Conifer and Broad-Leaf Tree Classification Using High Resolution PolSAR Data above X-Band

IEICE Transactions on Communications ◽

10.1587/transcom.2018ebp3288 ◽

2019 ◽

Vol E102.B (7) ◽

pp. 1345-1350 ◽

Cited By ~ 1

Author(s):

Yoshio YAMAGUCHI ◽

Yuto MINETANI ◽

Maito UMEMURA ◽

Hiroyoshi YAMADA

Keyword(s):

High Resolution ◽

Experimental Validation ◽

X Band ◽

Broad Leaf

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High Resolution Measurements of Pollution Wash-Off from an Asphalt Surface

Hydrology Research ◽

10.2166/nh.1992.0017 ◽

1992 ◽

Vol 23 (4) ◽

pp. 245-256 ◽

Cited By ~ 3

Author(s):

Å. Spångberg ◽

J. Niemczynowicz

Keyword(s):

Water Quality ◽

High Resolution ◽

Time Resolution ◽

Quality Data ◽

Rainfall Runoff ◽

Water Quality Data ◽

Urban Catchment ◽

Complex Process ◽

Surface Measurements ◽

Fine Time

The paper describes a measurement project aiming at delivering water quality data with the very fine time resolution necessary to discover deterministic elements of the complex process of pollution wash-off from an urban surface. Measurements of rainfall, runoff, turbidity, pH, conductivity and temperature with 10 sec time resolution were performed on a simple urban catchment, i.e. a single impermeable 270 m2 surface drained by one inlet. The paper presents data collection and some preliminary results.

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Fabrication and Compressive Behavior of a Micro-Lattice Composite by High Resolution DLP Stereolithography

Polymers ◽

10.3390/polym13050785 ◽

2021 ◽

Vol 13 (5) ◽

pp. 785

Author(s):

Chow Shing Shin ◽

Yu Chia Chang

Keyword(s):

High Resolution ◽

Lattice Structure ◽

Low Cost ◽

Hierarchical Structures ◽

Dip Coating ◽

Unit Cell ◽

Digital Light Processing ◽

Unit Cell Size ◽

Wide Range ◽

And Performance

Lattice structures are superior to stochastic foams in mechanical properties and are finding increasing applications. Their properties can be tailored in a wide range through adjusting the design and dimensions of the unit cell, changing the constituent materials as well as forming into hierarchical structures. In order to achieve more levels of hierarchy, the dimensions of the fundamental lattice have to be small enough. Although lattice size of several microns can be fabricated using the two-photon polymerization technique, sophisticated and costly equipment is required. To balance cost and performance, a low-cost high resolution micro-stereolithographic system has been developed in this work based on a commercial digital light processing (DLP) projector. Unit cell lengths as small as 100 μm have been successfully fabricated. Decreasing the unit cell size from 150 to 100 μm increased the compressive stiffness by 26%. Different pretreatments to facilitate the electroless plating of nickel on the lattice structure have been attempted. A pretreatment of dip coating in a graphene suspension is the most successful and increased the strength and stiffness by 5.3 and 3.6 times, respectively. Even a very light and incomplete nickel plating in the interior has increase the structural stiffness and strength by more than twofold.

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A High Resolution Spectrograph at Weihai Observatory

Proceedings of the International Astronomical Union ◽

10.1017/s1743921313013252 ◽

2012 ◽

Vol 8 (S293) ◽

pp. 400-402

Author(s):

Dongyang Gao ◽

Dayong Ren

Keyword(s):

High Resolution ◽

Echelle Spectrograph ◽

Metal Abundance ◽

And Performance

AbstractWeihai Echelle Spectrograph (WES) is the first the fiber-fed echelle spectrograph in China. WES can provide data for the studies of metal abundance of stars, exoplanets researches and asteroseismology, etc. A brief description of its design and performance is given.

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High resolution Michelson interferometer for airborne infrared astronomical observations 1: Concept and performance

Applied Optics ◽

10.1364/ao.16.001834 ◽

1977 ◽

Vol 16 (7) ◽

pp. 1834 ◽

Cited By ~ 11

Author(s):

J. P. Baluteau ◽

M. Anderegg ◽

A. F. M. Moorwood ◽

N. Coron ◽

J. E. Beckman ◽

...

Keyword(s):

High Resolution ◽

Michelson Interferometer ◽

Astronomical Observations ◽

And Performance

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Design and performance of an ultra-high-resolution 300 kV microscope

Ultramicroscopy ◽

10.1016/0304-3991(96)00026-5 ◽

1996 ◽

Vol 64 (1-4) ◽

pp. 17-34 ◽

Cited By ~ 17

Author(s):

Hans Bakker ◽

Arno Bleeker ◽

Peter Mul

Keyword(s):

High Resolution ◽

And Performance

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MRA-SNet: Siamese Networks of Multiscale Residual and Attention for Change Detection in High-Resolution Remote Sensing Images

Remote Sensing ◽

10.3390/rs13224528 ◽

2021 ◽

Vol 13 (22) ◽

pp. 4528

Author(s):

Xin Yang ◽

Lei Hu ◽

Yongmei Zhang ◽

Yunqing Li

Keyword(s):

Remote Sensing ◽

High Resolution ◽

Change Detection ◽

Remote Sensing Image ◽

Image Features ◽

Remote Sensing Images ◽

The Rich ◽

The Difference ◽

Basic Network ◽

And Performance

Remote sensing image change detection (CD) is an important task in remote sensing image analysis and is essential for an accurate understanding of changes in the Earth’s surface. The technology of deep learning (DL) is becoming increasingly popular in solving CD tasks for remote sensing images. Most existing CD methods based on DL tend to use ordinary convolutional blocks to extract and compare remote sensing image features, which cannot fully extract the rich features of high-resolution (HR) remote sensing images. In addition, most of the existing methods lack robustness to pseudochange information processing. To overcome the above problems, in this article, we propose a new method, namely MRA-SNet, for CD in remote sensing images. Utilizing the UNet network as the basic network, the method uses the Siamese network to extract the features of bitemporal images in the encoder separately and perform the difference connection to better generate difference maps. Meanwhile, we replace the ordinary convolution blocks with Multi-Res blocks to extract spatial and spectral features of different scales in remote sensing images. Residual connections are used to extract additional detailed features. To better highlight the change region features and suppress the irrelevant region features, we introduced the Attention Gates module before the skip connection between the encoder and the decoder. Experimental results on a public dataset of remote sensing image CD show that our proposed method outperforms other state-of-the-art (SOTA) CD methods in terms of evaluation metrics and performance.

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