The National Science Foundation’s Arctic Data Center is the primary data repository for NSF-funded research conducted in the Arctic. There are major challenges in discovering and interpreting resources in a repository containing data as heterogeneous and interdisciplinary as those in the Arctic Data Center. This paper reports on advances in cyberinfrastructure at the Arctic Data Center that help address these issues by leveraging semantic technologies that enhance the repository’s adherence to the FAIR data principles and improve the Findability, Accessibility, Interoperability, and Reusability of digital resources in the repository. We describe the Arctic Data Center’s improvements. We use semantic annotation to bind metadata about Arctic data sets with concepts in web-accessible ontologies. The Arctic Data Center’s implementation of a semantic annotation mechanism is accompanied by the development of an extended search interface that increases the findability of data by allowing users to search for specific, broader, and narrower meanings of measurement descriptions, as well as through their potential synonyms. Based on research carried out by the DataONE project, we evaluated the potential impact of this approach, regarding the accessibility, interoperability, and reusability of measurement data. Arctic research often benefits from having additional data, typically from multiple, heterogeneous sources, that complement and extend the bases – spatially, temporally, or thematically – for understanding Arctic phenomena. These relevant data resources must be ‘found’, and ‘harmonized’ prior to integration and analysis. The findings of a case study indicated that the semantic annotation of measurement data enhances the capabilities of researchers to accomplish these tasks.

Abstract Background In response to the COVID-19 pandemic, bioMérieux has incorporated assays to detect SARS-CoV-2 into the BIOFIRE® Respiratory 2.1 (RP2.1) Panel, the BIOFIRE® SPOTFIRE® Respiratory (R) Panel and the BIOFIRE® SPOTFIRE® Respiratory (R) Panel Mini. All panels use two assays for SARS-CoV-2 detection, each targeting a different gene. Positive detection in only one of the two assays is required for a positive SARS-CoV-2 result. As new variants of SARS-CoV-2 emerge, in silico analysis remains crucial to ensure that both SARS-CoV-2 assays are reactive to circulating strains. Methods Sequence data (https://gisaid.org/) for SARS-CoV-2 variants deemed significant by the WHO and UKHSA are analyzed monthly. Assay primer regions are assessed for mismatches using Geneious Prime® as well as proprietary software tools. When primer mismatches with potential to affect the sensitivity of SARS-CoV-2 detection are identified (mismatches occurring in the 3’ half of a primer in both assays), and meet the testing criteria, the BIOFIRE RP2.1 Panel is used to empirically evaluate the impact by comparing synthetic templates with mismatches of concern to synthetic template without mismatches. Results As of March 21, 2023, nearly 1,000 variants and 12,744,136 sequences have been analyzed. Of these, only 481 sequences (0.0038%) contain paired mismatches of concern. Wet testing showed < 10x lower projected sensitivity for 288 (72 unique) sequences, 10-100x lower sensitivity for 16 (10 unique) sequences, and only 1 sequence had 100-1000x lower projected sensitivity. Lineage defining mutations were seen within a SARS-CoV-2 assay primer region in 27 variants. However, most lack mutations in the second assay, indicating no major risk for SARS-CoV-2 detection. Wet testing shows that the inclusion of two SARS-CoV-2 assays in the panels helps to mitigate the effect of mismatches of concern. Conclusion Based on the comprehensive in silico analysis of available sequences and variants, BIOFIRE RP2.1 Panel, SPOTFIRE R Panel and SPOTFIRE R Panel Mini continue to function as intended with >99.99% detection of SARS-CoV-2 sequences. Disclosures Eleanor K. Horrocks, bioMerieux: employee|bioMerieux: Stocks/Bonds Toma Todorov, n/a, bioMerieux: employee|bioMerieux: Stocks/Bonds Alexandra Debernardi, n/a, bioMerieux: employee|bioMerieux: Stocks/Bonds Usha Spaulding, n/a, bioMerieux: employee|bioMerieux: Stocks/Bonds Tanner Robinson, n/a, bioMerieux: employee|bioMerieux: Stocks/Bonds Jeremiah Antosch, n/a, bioMerieux: employee|bioMerieux: Stocks/Bonds Zhenmei Lu, n/a, bioMerieux: employee|bioMerieux: Stocks/Bonds Matthew Jones, MS, bioMerieux: employee|bioMerieux: Stocks/Bonds Joann Cloud, PhD, bioMerieux: employee|bioMerieux: Stocks/Bonds

BACKGROUND:Serology assays have the potential to support RT-PCR in the diagnosis of SARS-CoV-2 infection. We studied three commercially available immunoassays for their diagnostic accuracy from blood specimens collected from 93 patients.METHODS:Blood samples from patients with confirmed COVID-19 infection were analysed using three different Immunoassays (Roche total antibody assay, Abbott IgG assay and Euroimmun IgG assay). Sensitivity, specificity, precision and time of seroconversion were evaluated.RESULTS:The sensitivity of Roche, Abbott and Euroimmun assays was 38.7%, 35.5% and 25.0% respectively for specimens collected <10 days and 84.4%, 84.4% and 70.0% respectively for specimens collected ≥10 days after the first positive RT-PCR. The specificity of all the three assays in this study was 100%. The timing of seroconversion occurred at day 1, 7 or 14.CONCLUSIONS:The assays evaluated in this study have different sensitivities for detecting antibodies in SARS-CoV-2 infection. Sensitivity for detecting antibodies for all three assays was higher for specimens collected ≥10 days after first positive PCR compared with specimens collected <10 days. Time of seroconversion is variable and assay-dependent.

Abstract Background The US Food and Drug Administration (FDA) has granted Emergency Use Authorization (EUA) for multiple PCR-based tests to aid in the diagnosis and containment of COVID-19. A vast majority of these tests detect only SARS-CoV-2 which causes symptoms similar to those caused by other respiratory pathogens. Hence, other etiologies or co-infections requiring a different therapy may be missed. The prototype BioFire® Respiratory Panel 2.1 (RP2.1) continues the syndromic approach of the FDA-cleared BioFire® Respiratory Panel 2 (RP2), to provide the ability to simultaneously detect 22 common respiratory pathogens, including SARS-CoV-2, from nasopharyngeal swab (NPS) specimens. The goal of this study was to rapidly develop a RP2.1 prototype that contains high-performing SARS-CoV-2 assays and maintains the performance of assays retained from RP2. Methods Twelve assays designed for four SARS-CoV-2 genes were tested for compatibility with the RP2 assays and conditions. All retained RP2 assays were evaluated to verify established RP2 performance. The sensitivity of novel SARS-CoV-2 assays was estimated with nucleic acids at BioFire and contrived live virus NPS samples at MRIGlobal. Primer homology of SARS-CoV-2 assays to > 15,000 SARS-CoV-2 genomes from accessible databases was assessed for in silico inclusivity Results A prototype multiplexed PCR panel containing assays for 22 pathogens was developed in a 5-week period. Of the 12 SARS-CoV-2 assays, 7 were compatible with the RP2 conditions; 2 were selected for the prototype. No false positive results due to cross-reactivity with unintended analytes or non-specific amplification in negative samples were observed for any assays. All retained RP2 assays were detected at or near their established LoD. The SARS-CoV-2 LoD was estimated at 103 -102 genomes/mL with both nucleic acid and live virus spiked into NPS. Together, the assays are 100% inclusive for all 15,370 complete SARS-CoV-2 genomes assessed in silico for reactivity. Conclusion The results of this study indicate a strong potential for RP2.1 to serve as a sensitive comprehensive syndromic option to aid in the diagnosis of COVID-19 as well as respiratory syndromes caused by other pathogens, including co-infections. This study was performed with a test not cleared for diagnostic use. Disclosures All Authors: No reported disclosures

The main output of the FORCE11 Software Citation working group (https://www.force11.org/group/software-citation-working-group) was a paper on software citation principles (https://doi.org/10.7717/peerj-cs.86) published in September 2016. This paper laid out a set of six high-level principles for software citation (importance, credit and attribution, unique identification, persistence, accessibility, and specificity) and discussed how they could be used to implement software citation in the scholarly community. In a series of talks and other activities, we have promoted software citation using these increasingly accepted principles. At the time the initial paper was published, we also provided guidance and examples on how to make software citable, though we now realize there are unresolved problems with that guidance. The purpose of this document is to provide an explanation of current issues impacting scholarly attribution of research software, organize updated implementation guidance, and identify where best practices and solutions are still needed.

ABSTRACT The FilmArray Respiratory Panel 2 (RP2) is a multiplex in vitro diagnostic test for the simultaneous and rapid (∼45-min) detection of 22 pathogens directly from nasopharyngeal swab (NPS) samples. It contains updated (and in some instances redesigned) assays that improve upon the FilmArray Respiratory Panel (RP; version 1.7), with a faster run time. The organisms identified are adenovirus, coronavirus 229E, coronavirus HKU1, coronavirus NL63, coronavirus OC43, human metapneumovirus, human rhinovirus/enterovirus, influenza virus A, influenza virus A H1, influenza virus A H1-2009, influenza virus A H3, influenza virus B, parainfluenza virus 1, parainfluenza virus 2, parainfluenza virus 3, parainfluenza virus 4, respiratory syncytial virus, Bordetella pertussis, Chlamydia pneumoniae, and Mycoplasma pneumoniae. Two new targets are included in the FilmArray RP2: Middle East respiratory syndrome coronavirus and Bordetella parapertussis. This study provides data from a multicenter evaluation of 1,612 prospectively collected NPS samples, with performance compared to that of the FilmArray RP or PCR and sequencing. The overall percent agreement between the FilmArray RP2 and the comparator testing was 99.2%. The RP2 demonstrated a positive percent agreement of 91.7% or greater for detection of all but three analytes: coronavirus OC43, B. parapertussis, and B. pertussis. The FilmArray RP2 also demonstrated a negative percent agreement of ≥93.8% for all analytes. Of note, the adenovirus assay detects all genotypes, with a demonstrated increase in sensitivity. The FilmArray RP2 represents a significant improvement over the FilmArray RP, with a substantially shorter run time that could aid in the diagnosis of respiratory infections in a variety of clinical scenarios.

GeoLink has leveraged linked data principles to create a dataset that allows users to seamlessly query and reason over some of the most prominent geoscience metadata repositories in the United States. The GeoLink dataset includes such diverse information as port calls made by oceanographic cruises, physical sample metadata, research project funding and staffing, and authorship of technical reports. The data has been published according to best practices for linked data and is publicly available via a SPARQL Protocol and RDF Query Language (SPARQL) end point that at present contains more than 45 million Resource Description Framework (RDF) triples together with a collection of ontologies and geo-visualization tools. This article describes the geoscience datasets, the modeling and publication process, and current uses of the dataset. The focus is on providing enough detail to enable researchers, application developers and others who wish to leverage the GeoLink data in their own work to do so. The dataset is available at http://hdl.handle.net/1912/9524.

Heterogeneity is increasingly recognized as a foundational characteristic of ecological systems. Under global change, understanding temporal community heterogeneity is necessary for predicting the stability of ecosystem functions and services. Indeed, spatial heterogeneity is commonly used in alternative stable state theory as a predictor of temporal heterogeneity and therefore an early indicator of regime shifts. To evaluate whether spatial heterogeneity in species composition is predictive of temporal heterogeneity in ecological communities, we analyzed 68 community data sets spanning freshwater and terrestrial systems where measures of species abundance were replicated over space and time. Of the 68 data sets, 55 (81%) had a weak to strongly positive relationship between spatial and temporal heterogeneity, while in the remaining communities the relationship was weak to strongly negative (19%). Based on a mixed model analysis, we found a significant but weak overall positive relationship between spatial and temporal heterogeneity across all data sets combined, and within aquatic and terrestrial data sets separately. In addition, lifespan and successional stage were negatively and positively related to temporal heterogeneity, respectively. We conclude that spatial heterogeneity may be a predictor of temporal heterogeneity in ecological communities, and that this relationship may be a general property of many terrestrial and aquatic communities.

The FilmArray ® Respiratory Panel 2 (RP2) is a multiplex in vitro diagnostic test 20 for the simultaneous and rapid (~45 minutes) detection of 22 pathogens directly from 21 nasopharyngeal swab (NPS) samples. It contains updated (and in some instances redesigned) 22 assays that improve upon the FilmArray ® Respiratory Panel (RP; version 1.7), with a faster run 23 time. The organisms identified are adenovirus, coronavirus 229E, coronavirus HKU1, 24 coronavirus NL63, coronavirus OC43, human metapneumovirus, human rhinovirus/enterovirus, 25 influenza A, influenza A H1, influenza A H1-2009, influenza A H3, influenza B, parainfluenza 26 virus 1, parainfluenza virus 2, parainfluenza virus 3, parainfluenza virus 4, respiratory syncytial 27 virus, Bordetella pertussis , Chlamydia pneumoniae , and Mycoplasma pneumoniae. Two new 28 targets are included in the FilmArray RP2: Middle East respiratory syndrome coronavirus, and 29 Bordetella parapertussis . This study provides data from a multicenter evaluation of 1612 30 prospectively collected NPS samples with performance compared to FilmArray RP or PCR and 31 sequencing. The overall percent agreement between FilmArray RP2 and the comparator testing 32 was 99.2%. The RP2 demonstrated a positive percent agreement of 91.7% or greater for 33 detection of all but three analytes: coronavirus OC43, B. parapertussis , and B. pertussis . The 34 FilmArray RP2 also demonstrated a negative percent agreement of ≥93.8% for all analytes. Of 35 note, the adenovirus assay detects all genotypes with a demonstrated increase in sensitivity. The 36 FilmArray RP2 represents a significant improvement over FilmArray RP with a substantially 37 shorter run time that could aid in diagnosis of respiratory infections in a variety of clinical 38 scenarios.

The triboelectric nanogenerator (TENG) has attracted enormous amount of attention in the research community in recent years because of its simple design, high energy conversion efficiency, broad application areas, a wide materials spectrum, and low-temperature easy fabrication. A key factor that dictates the performance of the TENGs is the surface charge density, which can be taken as a standard to characterize the matrix of performance of a material for a TENG. The triboelectric charge density can be improved by increasing the effective contact area, and in order to increase the contact area in a limited device size, micro-/nano-structures are often designed at the contact surfaces. Expert knowledge in contact mechanics, especially in adhesion and detachment mechanisms of the micro-/nano-structured interface, is thus becoming essential for a better understanding of the impact of interfacial design on the power generation of TENGs. Such an emerging field provides a platform for electrical engineers, chemical engineers, and mechanicians to share knowledge and build collaborations, which will enable the TENG researchers to pursue new design philosophies to achieve enhanced performance. In this paper, systematical numerical studies on the adhesive contact at the micro-/nano-structured interface are presented. We use a numerical simulation package in which the adhesive interactions are represented by an interaction potential and the surface deformations are coupled by using half-space Green's functions discretized on the surface. The results confirmed that the deformation of interfacial structures directly determines the pressure-voltage relationship of TENG, and it can be seen that our numerical results provided a better fit with the experimental data than the previous studies.

The second annual NSF Software Infrastructure for Sustained Innovation (SI2) PI meeting took place in Arlington, VA February 24-25, 2014. It was hosted by Beth Plale, Indiana University; Douglas Thain, University of Notre Dame; and Matt Jones, National Center for Ecological Analysis and Synthesis. This report captures the challenges and outcomes emerging from the meeting over the four topic areas discussed i) Attribution and Citation, ii) Reproducibility, Reusability, and Preservation, iii) Project/Software Sustainability, and iv) Career Paths. The report is an academic synthesis with credit to all the participants and to the notetakers who took prodigious notes and synthesized the results upon which the conclusions of this report are derived.

We introduce and describe scientific workflows, i.e., executable descriptions of automatable scientific processes such as computational science simulations and data analyses. Scientific workflows are often expressed in terms of tasks and their (data ow) dependencies. This chapter first provides an overview of the characteristic features of scientific workflows and outlines their life cycle. A detailed case study highlights workflow challenges and solutions in simulation management. We then provide a brief overview of how some concrete systems support the various phases of the workflow life cycle, i.e., design, resource management, execution, and provenance management. We conclude with a discussion on community-based workflow sharing.