The ultraviolet imager (UVI) has been developed for the spacecraft (Venus Climate Orbiter mission). The UVI takes ultraviolet (UV) images of the solar radiation reflected by the Venusian clouds with narrow bandpass filters centered at the 283 and 365 nm wavelengths. There are absorption bands of SO and unknown absorbers in these wavelength regions. The UV images provide the spatial distribution of SO and the unknown absorber around cloud top altitudes. The images also allow us to understand the cloud top morphologies and haze properties. Nominal sequential images with 2-h intervals are used to understand the dynamics of the Venusian atmosphere by estimating the wind vectors at the cloud top altitude, as well as the mass transportation of UV absorbers. The UVI is equipped with off-axial catadioptric optics, two bandpass filters, a diffuser installed in a filter wheel moving with a step motor, and a high sensitivity charge-coupled device with UV coating. The UVI images have spatial resolutions ranging from 200 m to 86 km at sub-spacecraft points. The UVI has been kept in good condition during the extended interplanetary cruise by carefully designed operations that have maintained its temperature maintenance and avoided solar radiation damage. The images have signal-to-noise ratios of over 100 after onboard desmear processing.
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http://dx.doi.org/10.1186/s40623-017-0772-6 | DOI Listing |
Surv Geophys
May 2024
NOAA/Pacific Marine Environmental Laboratory, Seattle, WA 98115 USA.
Satellite observations from the Clouds and the Earth's Radiant Energy System show that Earth's energy imbalance has doubled from 0.5 ± 0.2 Wm during the first 10 years of this century to 1.
View Article and Find Full Text PDFSurv Geophys
October 2024
European Space Agency (ESA-ESRIN), 00044 Frascati, Italy.
This study uses an oceanic energy budget to estimate the ocean heat transport convergence in the North Atlantic during 2005-2018. The horizontal convergence of the ocean heat transport is estimated using ocean heat content tendency primarily derived from satellite altimetry combined with space gravimetry. The net surface energy fluxes are inferred from mass-corrected divergence of atmospheric energy transport and tendency of the ECMWF ERA5 reanalysis combined with top-of-the-atmosphere radiative fluxes from the clouds and the Earth's radiant energy system project.
View Article and Find Full Text PDFFront Chem
November 2024
African Society for Bioinformatics and Computational Biology, Cape Town, South Africa.
Introduction: Homology modeling is a widely used computational technique for predicting the three-dimensional (3D) structures of proteins based on known templates,evolutionary relationships to provide structural insights critical for understanding protein function, interactions, and potential therapeutic targets. However, existing tools often require significant expertise and computational resources, presenting a barrier for many researchers.
Methods: Prostruc is a Python-based homology modeling tool designed to simplify protein structure prediction through an intuitive, automated pipeline.
BMC Anesthesiol
December 2024
Department of Anesthesiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, 510030, Guangdong, China.
Aim: The study aimed to develop a predictive model with machine learning (ML) algorithm, to predict and manage the need for red blood cell (RBC) transfusion during hip fracture surgery.
Methods: Data of 2785 cases that underwent hip fracture surgery from April 2016 to May 2022 were collected, covering demographics, medical history and comorbidities, type of surgery and preoperative laboratory results. The primary outcome was the intraoperative RBC transfusion.
Arthritis Res Ther
December 2024
Department of Orthopaedic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Qingchun Road No. 79, Hangzhou, China.
Objective: To use routine demographic and clinical data to develop an interpretable individual-level machine learning (ML) model to diagnose knee osteoarthritis (KOA) and to identify highly ranked features.
Methods: In this retrospective, population-based cohort study, anonymized questionnaire data was retrieved from the Wu Chuan KOA Study, Inner Mongolia, China. After feature selections, participants were divided in a 7:3 ratio into training and test sets.
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