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As the frequency of rocket launches increases, accurately predicting their noise is necessary to assess structural, environmental, and societal impacts. NASA’s Space Launch System (SLS) is a challenging vehicle to model because it has both solid-fuel rocket boosters and liquid-fueled engines that contribute to its thrust at launch. This paper discusses measured aeroacoustic properties of this super heavy-lift rocket in the context of supersonic jet theory and measurements of other rockets. Using four measured aeroacoustic properties: directivity, spectral peak frequency, maximum overall sound pressure level, and overall sound power level, an equivalent rocket based on merged plumes is created for SLS. With the constraint that the effective thrust and mass flow rates should match those of the actual vehicle, a method using weighted averages of the disparate plume parameters successfully reproduces SLS’s desired aeroacoustic properties, yielding a relatively simple model for the complex vehicle. 

Abstract Rust fungi (Pucciniales, Basidiomycota) are a species-rich (ca. 8000 species), globally distributed order of obligate plant pathogens. Rust species are host-specific, and as a group they cause disease on many of our most economically and/or ecologically significant plants. As such, the ability to accurately and rapidly identify these fungi is of particular interest to mycologists, botanists, agricultural scientists, farmers, quarantine officials, and associated stakeholders. However, the complexities of the rust life cycle, which may include production of up to five different spore types and alternation between two unrelated host species, have made standard identifications, especially of less-documented spore states or alternate hosts, extremely difficult. The Arthur Fungarium (PUR) at Purdue University is home to one of the most comprehensive collections of rust fungi in the world. Using material vouchered in PUR supplemented with fresh collections we generated DNA barcodes of the 28S ribosomal repeat from > 3700 rust fungal specimens. Barcoded material spans 120 genera and > 1100 species, most represented by several replicate sequences. Barcodes and associated metadata are hosted in a publicly accessible, BLAST searchable database called Rust HUBB (Herbarium-based Universal Barcode Blast) and will be continuously updated. 

Abstract Serological assays used to estimate the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) often rely on manufacturers’ cutoffs established on the basis of severe cases. We conducted a household-based serosurvey of 4,677 individuals in Chennai, India, from January to May 2021. Samples were tested for SARS-CoV-2 immunoglobulin G (IgG) antibodies to the spike (S) and nucleocapsid (N) proteins. We calculated seroprevalence, defining seropositivity using manufacturer cutoffs and using a mixture model based on measured IgG level. Using manufacturer cutoffs, there was a 5-fold difference in seroprevalence estimated by each assay. This difference was largely reconciled using the mixture model, with estimated anti-S and anti-N IgG seroprevalence of 64.9% (95% credible interval (CrI): 63.8, 66.0) and 51.5% (95% CrI: 50.2, 52.9), respectively. Age and socioeconomic factors showed inconsistent relationships with anti-S and anti-N IgG seropositivity using manufacturer cutoffs. In the mixture model, age was not associated with seropositivity, and improved household ventilation was associated with lower seropositivity odds. With global vaccine scale-up, the utility of the more stable anti-S IgG assay may be limited due to the inclusion of the S protein in several vaccines. Estimates of SARS-CoV-2 seroprevalence using alternative targets must consider heterogeneity in seroresponse to ensure that seroprevalence is not underestimated and correlates are not misinterpreted.