Visibility-reducing organic aerosols in the vicinity of Grand Canyon National Park: Properties observed by high resolution gas chromatography

Fine particle and total airborne particle samples were collected during August 1989 within the Grand Canyon (Indian Gardens (IG)) and on its south rim (Hopi Point (HP)) to define summertime organic aerosol concentration and composition as a function of elevation at Grand Canyon National Park. Inorganic chemical constituents were analyzed also to help place the relative importance of organics in perspective. Fine particle organic aerosols were approximately equal in concentration to sulfate aerosols at both sites. Monthly average mass concentrations for fine aerosol organics ranged from 1.1 μg m(−3) (IG) to 1.3 μg m^(−3) (HP), while the organic aerosol concentration within total suspended particulate matter samples ranged from 1.9 μg m^(−3) (IG) to 2.1 μg m^(−3) (HP). Aerosol organics that could be evaluated by gas chromatography with flame ionization detection (GC-FID) (elutable organics) constituted 27% to 53% of the total organics mass collected as fine or total aerosol. At each site, roughly half of the elutable organics fine aerosol fraction was composed of highly polar organic compounds. Distributions of the elutable organics were compared to Los Angeles fine aerosol samples and to distributions of authentic sources of aerosol organics. It was found that the Grand Canyon organic aerosol during August 1989 did not resemble diluted aged Los Angeles organic aerosol, indicating that most of the organic particulate matter at the Grand Canyon at the time studied originated from other sources

Community-Centered Responses to Ebola in Urban Liberia: The View from Below

The West African Ebola epidemic has demonstrated that the existing range of medical and epidemiological responses to emerging disease outbreaks is insufficient, especially in post-conflict contexts with exceedingly poor healthcare infrastructures. This study provides baseline information on community-based epidemic control priorities and identifies innovative local strategies for containing EVD in Liberia.In this study the authors analyzed data from the 2014 Ebola outbreak in Monrovia and Montserrado County, Liberia. The data were collected for the purposes of program design and evaluation by the World Health Organization (WHO) and the Government of Liberia (GOL), in order to identify: (1) local knowledge about EVD, (2) local responses to the outbreak, and (3) community based innovations to contain the virus. At the time of data collection, the international Ebola response had little insight into how much local Liberian communities knew about Ebola, and how communities managed the epidemic when they could not get access to care due to widespread hospital and clinic closures. Methods included 15 focus group discussions with community leaders from areas with active Ebola cases. Participants were asked about best practices and what they were currently doing to manage EVD in their respective communities, with the goal of developing conceptual models of local responses informed by local narratives. Findings reveal that communities responded to the outbreak in numerous ways that both supported and discouraged formal efforts to contain the spread of the disease. This research will inform global health policy for both this, and future, epidemic and pandemic responses

Genome assembly and population genomic analysis provide insights into the evolution of modern sweet corn.

Sweet corn is one of the most important vegetables in the United States and Canada. Here, we present a de novo assembly of a sweet corn inbred line Ia453 with the mutated shrunken2-reference allele (Ia453-sh2). This mutation accumulates more sugar and is present in most commercial hybrids developed for the processing and fresh markets. The ten pseudochromosomes cover 92% of the total assembly and 99% of the estimated genome size, with a scaffold N50 of 222.2 Mb. This reference genome completely assembles the large structural variation that created the mutant sh2-R allele. Furthermore, comparative genomics analysis with six field corn genomes highlights differences in single-nucleotide polymorphisms, structural variations, and transposon composition. Phylogenetic analysis of 5,381 diverse maize and teosinte accessions reveals genetic relationships between sweet corn and other types of maize. Our results show evidence for a common origin in northern Mexico for modern sweet corn in the U.S. Finally, population genomic analysis identifies regions of the genome under selection and candidate genes associated with sweet corn traits, such as early flowering, endosperm composition, plant and tassel architecture, and kernel row number. Our study provides a high-quality reference-genome sequence to facilitate comparative genomics, functional studies, and genomic-assisted breeding for sweet corn

EarCV: An open‐source, computer vision package for maize ear phenotyping

Abstract Fresh market sweet corn (Zea mays L.) is a row crop commercialized as a vegetable, resulting in strict expectations for ear size, color, and shape. Ear phenotyping in breeding programs is typically done manually and can be subjective, time consuming, and unreliable. Computer vision tools have enabled an inexpensive, high‐throughput, and quantitative alternative to phenotyping in agriculture. Here we present a computer vision tool using open‐source Python and OpenCV to measure yield component and quality traits relevant to sweet corn from photographs. This tool increases accuracy and efficiency in phenotyping through high‐throughput, quantitative feature extraction of traits typically measured qualitatively. EarCV worked in variable lighting and background conditions, such as under full sun and shade and against grass and dirt backgrounds. The package compares ears in images taken at varying distances and accurately measures ear length and ear width. It can measure traits that were previously difficult to quantify such as color, tip fill, taper, and curvature. EarCV allows users to phenotype any number of ears, dried or fresh, in any orientation while tolerating some debris and silk noise. The tool can categorize husked ears according to the predefined USDA quality grades based on length and tip fill. We show that the information generated from this computer vision approach can be incorporated into breeding programs by analyzing hybrid ears, capturing heritability of yield component traits, and detecting phenotypic differences between cultivars that conventional yield measurements cannot. Ultimately, computer vision can reduce the cost and resources dedicated to phenotyping in breeding programs