Neural-based Compression Scheme for Solar Image Data

Studying the solar system and especially the Sun relies on the data gathered daily from space missions. These missions are data-intensive and compressing this data to make them efficiently transferable to the ground station is a twofold decision to make. Stronger compression methods, by distorting the data, can increase data throughput at the cost of accuracy which could affect scientific analysis of the data. On the other hand, preserving subtle details in the compressed data requires a high amount of data to be transferred, reducing the desired gains from compression. In this work, we propose a neural network-based lossy compression method to be used in NASA's data-intensive imagery missions. We chose NASA's SDO mission which transmits 1.4 terabytes of data each day as a proof of concept for the proposed algorithm. In this work, we propose an adversarially trained neural network, equipped with local and non-local attention modules to capture both the local and global structure of the image resulting in a better trade-off in rate-distortion (RD) compared to conventional hand-engineered codecs. The RD variational autoencoder used in this work is jointly trained with a channel-dependent entropy model as a shared prior between the analysis and synthesis transforms to make the entropy coding of the latent code more effective. Our neural image compression algorithm outperforms currently-in-use and state-of-the-art codecs such as JPEG and JPEG-2000 in terms of the RD performance when compressing extreme-ultraviolet (EUV) data. As a proof of concept for use of this algorithm in SDO data analysis, we have performed coronal hole (CH) detection using our compressed images, and generated consistent segmentations, even at a compression rate of $\sim0.1$ bits per pixel (compared to 8 bits per pixel on the original data) using EUV data from SDO.Comment: Accepted for publication in IEEE Transactions on Aerospace and Electronic Systems (TAES). arXiv admin note: text overlap with arXiv:2210.0647

A cross-sectional study of determinants of indoor environmental exposures in households with and without chronic exposure to biomass fuel smoke

BACKGROUND: Burning biomass fuels indoors for cooking is associated with high concentrations of particulate matter (PM) and carbon monoxide (CO). More efficient biomass-burning stoves and chimneys for ventilation have been proposed as solutions to reduce indoor pollution. We sought to quantify indoor PM and CO exposures in urban and rural households and determine factors associated with higher exposures. A secondary objective was to identify chronic vs. acute changes in cardiopulmonary biomarkers associated with exposure to biomass smoke. METHODS: We conducted a census survey followed by a cross-sectional study of indoor environmental exposures and cardiopulmonary biomarkers in the main household cook in Puno, Peru. We measured 24-hour indoor PM and CO concentrations in 86 households. We also measured PM(2.5) and PM(10) concentrations gravimetrically for 24 hours in urban households and during cook times in rural households, and generated a calibration equation using PM(2.5) measurements. RESULTS: In a census of 4903 households, 93% vs. 16% of rural vs. urban households used an open-fire stove; 22% of rural households had a homemade chimney; and <3% of rural households participated in a national program encouraging installation of a chimney. Median 24-hour indoor PM(2.5) and CO concentrations were 130 vs. 22 μg/m(3) and 5.8 vs. 0.4 ppm (all p<0.001) in rural vs. urban households. Having a chimney did not significantly reduce median concentrations in 24-hour indoor PM(2.5) (119 vs. 137 μg/m(3); p=0.40) or CO (4.6 vs. 7.2 ppm; p=0.23) among rural households with and without chimneys. Having a chimney did not significantly reduce median cook-time PM(2.5) (360 vs. 298 μg/m(3), p=0.45) or cook-time CO concentrations (15.2 vs. 9.4 ppm, p=0.23). Having a thatched roof (p=0.007) and hours spent cooking (p=0.02) were associated with higher 24-hour average PM concentrations. Rural participants had higher median exhaled CO (10 vs. 6 ppm; p=0.01) and exhaled carboxyhemoglobin (1.6% vs. 1.0%; p=0.04) than urban participants. CONCLUSIONS: Indoor air concentrations associated with biomass smoke were six-fold greater in rural vs. urban households. Having a homemade chimney did not reduce environmental exposures significantly. Measures of exhaled CO provide useful cardiopulmonary biomarkers for chronic exposure to biomass smoke

Molecular Epidemiology of Multidrug-Resistant Uropathogenic Escherichia coli O25b Strains Associated with Complicated Urinary Tract Infection in Children.

BACKGROUND: Uropathogenic Escherichia coli (UPEC) has increased the incidence of urinary tract infection (UTI). It is the cause of more than 80% of community-acquired cystitis cases and more than 70% of uncomplicated acute pyelonephritis cases. AIM: The present study describes the molecular epidemiology of UPEC O25b clinical strains based on their resistance profiles, virulence genes, and genetic diversity. METHODS: Resistance profiles were identified using the Kirby-Bauer method, including the phenotypic production of extended-spectrum β-lactamases (ESBLs) and metallo-β-lactamases (MBLs). The UPEC serogroups, phylogenetic groups, virulence genes, and integrons were determined via multiplex PCR. Genetic diversity was established using pulsed-field gel electrophoresis (PFGE), and sequence type (ST) was determined via multilocus sequence typing (MLST). RESULTS: UPEC strains (n = 126) from hospitalized children with complicated UTIs (cUTIs) were identified as O25b, of which 41.27% were multidrug resistant (MDR) and 15.87% were extensively drug resistant (XDR). The O25b strains harbored the fimH (95.23%), csgA (91.26%), papGII (80.95%), chuA (95.23%), iutD (88.09%), satA (84.92%), and intl1 (47.61%) genes. Moreover, 64.28% were producers of ESBLs and had high genetic diversity. ST131 (63.63%) was associated primarily with phylogenetic group B2, and ST69 (100%) was associated primarily with phylogenetic group D. CONCLUSION: UPEC O25b/ST131 harbors a wide genetic diversity of virulence and resistance genes, which contribute to cUTIs in pediatrics

Seroprevalence of IgA and IgG against SARS-CoV-2 and Risk Factors in Workers from Public Markets of Guatemala

Public market workers may be disproportionally exposed to SARS-CoV-2 due to interactions with shoppers. We aimed to estimate the seroprevalence of SARS-CoV-2 and determine whether occupation or adherence to preventive practices were associated with exposure. From July to December 2021, we longitudinally surveyed two Guatemalan markets twice. We collected blood to detect anti-S IgA, anti-S IgG, and anti-N IgG using ELISA, and a nasopharyngeal swab to detect SARS-CoV-2 using rRT-PCR. We estimated seroprevalences and assessed associations using generalized estimating equations. Of 229 workers, 109 (48%) participated in the first survey and 87 (38%) in the second. At baseline, 77% were female, 64% were aged <40, and 81% were vendors. Overall, the seroprevalence increased between surveys (61% to 89% for anti-S IgA, 53% to 91% for anti-S IgG, and 22% to 29% for anti-N IgG), but the magnitude differed by vaccination status and antibody type. The prevalence of infections decreased from 13% to 1% and most were asymptomatic. Vendor occupation was associated with IgA and IgG anti-S in males but not females. Using a mask was a protective measure. Most market workers had been exposed to SARS-CoV-2, possibly through asymptomatic individuals. Masking is a protective measure to be prioritized during high transmission

Availability of over-the-counter antibiotics in Guatemalan corner stores.

Widespread availability of antibiotics without prescription potentially facilitates overuse and contributes to selection pressure for antimicrobial resistant bacteria. Prior to this study, anecdotal observations in Guatemala identified corner stores as primary antibiotic dispensaries, where people purchase antibiotics without prescriptions. We carried out a cross sectional study to document the number and types of antibiotics available in corner stores, in four study areas in Guatemala. A total of 443 corner stores were surveyed, of which 295 (67%) sold antibiotics. The most commonly available antibiotics were amoxicillin, found in 246/295 (83%) stores, and tetracycline, found in 195/295 (66%) stores. Over the counter sales result from laissez-faire enforcement of antibiotic dispensing regulations in Guatemala combined with patient demand. This study serves as a baseline to document changes in the availability of antibiotics in informal establishments in light of new pharmacy regulations for antibiotic dispensing, which were adopted after this study was completed

Molecular Epidemiology of Multidrug-Resistant Uropathogenic Escherichia coli O25b Strains Associated with Complicated Urinary Tract Infection in Children

Background: Uropathogenic Escherichia coli (UPEC) has increased the incidence of urinary tract infection (UTI). It is the cause of more than 80% of community-acquired cystitis cases and more than 70% of uncomplicated acute pyelonephritis cases. Aim: The present study describes the molecular epidemiology of UPEC O25b clinical strains based on their resistance profiles, virulence genes, and genetic diversity. Methods: Resistance profiles were identified using the Kirby–Bauer method, including the phenotypic production of extended-spectrum β-lactamases (ESBLs) and metallo-β-lactamases (MBLs). The UPEC serogroups, phylogenetic groups, virulence genes, and integrons were determined via multiplex PCR. Genetic diversity was established using pulsed-field gel electrophoresis (PFGE), and sequence type (ST) was determined via multilocus sequence typing (MLST). Results: UPEC strains (n = 126) from hospitalized children with complicated UTIs (cUTIs) were identified as O25b, of which 41.27% were multidrug resistant (MDR) and 15.87% were extensively drug resistant (XDR). The O25b strains harbored the fimH (95.23%), csgA (91.26%), papGII (80.95%), chuA (95.23%), iutD (88.09%), satA (84.92%), and intl1 (47.61%) genes. Moreover, 64.28% were producers of ESBLs and had high genetic diversity. ST131 (63.63%) was associated primarily with phylogenetic group B2, and ST69 (100%) was associated primarily with phylogenetic group D. Conclusion: UPEC O25b/ST131 harbors a wide genetic diversity of virulence and resistance genes, which contribute to cUTIs in pediatrics

Seroprevalence of high incidence congenital infections among pregnant women in Coatepeque, Guatemala and surrounding areas, 2017-2018.

Maternal infections during pregnancy can potentially cause birth defects and severe adverse effects in infants. From 2017 to 2018, we investigated the seroprevalence of five antibodies among 436 mother-infant pairs enrolled in a pregnancy cohort study in Coatepeque, Guatemala. Upon enrollment (< 20 weeks gestational age) and shortly after delivery, we measured the prevalence of IgG and IgM antibodies against Toxoplasma gondii (T. gondii), rubella, and cytomegalovirus (CMV) in mothers and newborns and used rapid tests to detect HIV and syphilis (Treponema pallidum) in mothers. The mean cohort age was 24.5 years. Maternal T. gondii IgM and IgG seropositivity was 1.9% and 69.7%, respectively. No women were positive for HIV, syphilis, or rubella IgM. Maternal rubella IgG seropositivity was 80.8% and significantly increased with age. Maternal CMV IgM and IgG seropositivity were 2.3% and 99.5%, respectively. Of the 323 women tested at both timepoints, IgM reactivation occurred in one woman for T. gondii infection and in eight for CMV. No newborn was seropositive for CMV IgM or rubella IgM. One newborn was seropositive for T. gondii IgM. Congenital T. gondii and CMV infections are important public health issues for pregnant women, newborns, and healthcare providers in Coatepeque and Guatemala

A community dataset for comparing automated coronal hole detection schemes

Automated detection schemes are nowadays the standard approach for locating coronal holes in extreme-UV images from the Solar Dynamics Observatory (SDO). However, factors such as the noisy nature of solar imagery, instrumental effects, and others make it challenging to identify coronal holes using these automated schemes. While discrepancies between detection schemes have been noted in the literature, a comprehensive assessment of these discrepancies is still lacking. The contribution of the Coronal Hole Boundary Working Team in the COSPAR ISWAT initiative to close this gap is threefold. First, we present the first community data set for comparing automated coronal hole detection schemes. This data set consists of 29 SDO images, all of which were selected by experienced observers to challenge automated schemes. Second, we use this community data set as input to 14 widely applied automated schemes to study coronal holes and collect their detection results. Third, we study three SDO images from the data set that exemplify the most important lessons learned from this effort. Our findings show that the choice of the automated detection scheme can have a significant effect on the physical properties of coronal holes, and we discuss the implications of these findings for open questions in solar and heliospheric physics. We envision that this community data set will serve the scientific community as a benchmark data set for future developments in the field.Peer reviewe