The implementation of a polymerase chain reaction-based pneumonia panel was associated with actionable results in 87% of 384 cases. In a population of mostly elderly non-intensive care unit patients with sputum samples, opportunities for antibiotic stewardship included streamlining for atypical bacteria, Pseudomonas aeruginosa, and methicillin-resistant Staphylococcus aureus coverage, with occasional opportunities to escalate antibiotic therapy.

The presented research investigates the impact of interference on the performance of aircraft Global Navigation Satellite System (GNSS) receivers with a specific focus on the behaviour of Automatic Dependent Surveillance-Broadcast (ADS-B) position quality indicators. Several experiments were performed with different aircraft types, such as Airbus, Boeing, Beechcraft King Air B350 or Tecnam, and using various intensities of GNSS jamming. The behaviour of various quality indicators, such as the Navigation Integrity Category, Navigation Accuracy Category, Source Integrity Level and System Design Assurance transmitted in different types of ADS-B messages, is analysed. We investigate not only situations where the quality indicators drop to zero, but also the complete evolution of the changes in the indicators as a function of the increasing power of the jamming signal. Based on the analysis of changes in the ADS-B quality indicators, the estimation of the most likely interference signal power required to discontinue the tracking of an already acquired GPS L1 Coarse/Acquisition signal is made. Additionally, the interference signal power to prevent re-acquisition is also estimated. The findings improve the understanding of interference effects and can support the development of robust interference mitigation techniques in aviation applications.

Clostridioides difficile infection (CDI) research relies upon accurate identification of cases when using electronic health record (EHR) data. We developed and validated a multi-component algorithm to identify hospital-associated CDI using EHR data and determined that the tandem of CDI-specific treatment and laboratory testing has 97% accuracy in identifying HA-CDI cases.

More than ever the welfare of horses in equestrian sport is in the spotlight. In response to this scrutiny, one peak body, the Federation Equestre Internationale (FEI) has created an Equine Ethics and Wellbeing Commission to protect their sport’s longevity. However, for welfare-based strategies to be successful, the conceptualisation of horse welfare must align across various stakeholders, including the general public. The value-laden nature of welfare makes agreement on its definition, even among scientists, difficult. Given little is known about how equestrians conceptualise horse welfare, we interviewed 19 Australian amateur equestrians using a semi-structured format. Systems thinking and the Five Domains Model provided the theoretical framework and informed our methods. Using reflexive thematic analysis, three themes were identified: (1) good horse welfare is tangible; (2) owners misinterpret unwanted horse behaviour; and (3) equestrians publicly minimise horse welfare issues but are privately concerned. Our results highlight participants’ conceptualisations of horse welfare do not align with the Five Domains Model; participants’ ideal of prioritising horse welfare does not align with their practice; and there is inconsistency between what participants share publicly and what they think privately about horse welfare. These findings can inform the development of programmes to improve ridden horse welfare throughout the horse industry. As a starting point, programmes that provide a safe space for equestrians to explore their private horse welfare concerns, and programmes that build a partnership mindset to facilitate knowledge exchange between all stakeholders are needed.

Oil palm is one of Southeast Asia’s most common crops, and its expansion has caused substantial modification of natural habitats and put increasing pressure on biodiversity. Rising global demand for vegetable oil, coupled with oil palm’s high yield per unit area and the versatility of the palm oil product, has driven the expansion of oil palm agriculture in the region. Therefore, it is critical to identify management practices that can support biodiversity in plantations without exacerbating negative impacts on the environment. This study focuses on day-flying Lepidoptera (butterflies and moths), which contribute to the ecosystem functioning as pollinators, prey, and herbivore species. We assessed whether density and behaviours of day-flying Lepidoptera varied between different habitats within oil palm plantations and across seasons. We surveyed the density and behaviours of Lepidoptera communities in mature industrial oil palm plantations within the Biodiversity and Ecosystem Function in Tropical Agriculture (BEFTA) Programme sites, in Riau, Indonesia. We surveyed two distinct habitats within the plantations in March and September 2013: Edge habitats, which were bordered by plantation roads on one side, and Core habitats in the centre of oil palm planting blocks. We conducted analyses on the effect of habitat type and season on both the overall density and behaviour of Lepidoptera communities and, independently, on the most common species. In our surveys, we observed 1464 individuals across 41 species, with a significantly higher density in Edge than in Core habitats. While there was no significant difference between overall density in March and September surveys, there was an interaction between season and habitat, with density increasing more markedly in Edge than Core areas in September. There was also a significant effect of habitat and season on behavioural time budget for the community as a whole, with more active behaviours, such as foraging and mating, being recorded more frequently in Edge than Core habitats, and more commonly in September than March. The effect of habitat type, season, and their interaction differed between the six most common species. Our findings indicate that Lepidoptera abundance is affected by habitat characteristics in a plantation and can therefore be influenced by plantation management practices. In particular, our study highlights the value of road edges and paths in plantations for day-flying Lepidoptera. We suggest that increased non-crop vegetation in these areas, achieved through reduced clearing practices or planting of flowering plants, could foster abundant and active butterfly communities in plantations. These practices could form part of sustainability management recommendations for oil palm, such as those of the Roundtable on Sustainable Palm Oil.

OBJECTIVES/GOALS: The rates of computational phenotyping algorithm reuse across health systems are low, leading to a proliferation of algorithms for the same trait. We propose a framework for reusing computational phenotyping algorithms and describe the real-world deployment of this framework for the development of the Colorado Diabetes EHR Research Repository. METHODS/STUDY POPULATION: The novel phenotype reuse framework consists of 4 steps: select algorithms that are appropriate for reuse by assessing whether they are fit for purpose; extend the algorithm to account for changes in data and care practice standards; localize the algorithm to use local database standards and terminologies; optimize the algorithm by applying a data driven approach to achieve the desired local performance. To identify individuals with type 1 diabetes (T1D) or type 2 diabetes (T2D), we selected and implemented T2D algorithms in a cohort of adults with any diabetes or pre-diabetes related diagnosis code, medication, or abnormal glucose-related laboratory test in the clinical data warehouse for UCHealth and the University of Colorado. RESULTS/ANTICIPATED RESULTS: We included a total of 926,290 patients who were identified by initial filters. Patients were more likely to be female (53%), identify as non-Hispanic white (69%) and had a median age of 58 years (IQR: 41, 70). Implementation, extension, localization, & optimization through iterative chart review prioritized high sensitivity for all-cause diabetes and high specificity for T1D and T2D. Of the original cohort, 252,946 (27%) were identified by the all-cause diabetes algorithm. Of these 11,688 were identified as T1D and 135,588 as T2D. After optimization the all-cause diabetes algorithm had 88% sensitivity, 90% specificity, 74% positive predictive value (PPV), and 96% negative predictive value (NPV). Our algorithms for T1D and T2D had high specificity (100% and 99%, respectively) and PPV (100 and 96% respectively). DISCUSSION/SIGNIFICANCE: Developing computational phenotyping algorithms is expensive and time consuming, yet algorithm reuse is low due to a lack of practical approaches for reusing algorithms. We demonstrate application of a novel framework for algorithm reuse, yielding good alignment of algorithm performance with study goals for identifying individuals with diabetes.

Earth is rapidly losing free-living species. Is the same true for parasitic species? To reveal temporal trends in biodiversity, historical data are needed, but often such data do not exist for parasites. Here, parasite communities of the past were reconstructed by identifying parasites in fluid-preserved specimens held in natural history collections. Approximately 2500 macroparasites were counted from 109 English Sole (Parophrys vetulus) collected between 1930 and 2019 in the Salish Sea, Washington, USA. Alpha and beta diversity were measured to determine if and how diversity changed over time. Species richness of parasite infracommunities and community dispersion did not vary over time, but community composition of decadal component communities varied significantly over the study period. Community dissimilarity also varied: prior to the mid-20th century, parasites shifted in abundance in a seemingly stochastic manner and, after this time period, a canalization of community change was observed, where species' abundances began to shift in consistent directions. Further work is needed to elucidate potential drivers of these changes and to determine if these patterns are present in the parasite communities of other fishes of the Salish Sea.

Adherence to the Dietary Approaches to Stop Hypertension (DASH) diet is inversely associated with type 2 diabetes mellitus (T2DM) risk. Metabolic changes due to DASH adherence and their potential relationship with incident T2DM have not been described. The objective is to determine metabolite clusters associated with adherence to a DASH-like diet in the Insulin Resistance Atherosclerosis Study cohort and explore if the clusters predicted 5-year incidence of T2DM. The current study included 570 non-diabetic multi-ethnic participants aged 40–69 years. Adherence to a DASH-like diet was determined a priori through an eighty-point scale for absolute intakes of the eight DASH food groups. Quantitative measurements of eighty-seven metabolites (acylcarnitines, amino acids, bile acids, sterols and fatty acids) were obtained at baseline. Metabolite clusters related to DASH adherence were determined through partial least squares (PLS) analysis using R. Multivariable-adjusted logistic regression was used to explore the associations between metabolite clusters and incident T2DM. A group of acylcarnitines and fatty acids loaded strongly on the two components retained under PLS. Among strongly loading metabolites, a select group of acylcarnitines had over 50 % of their individual variance explained by the PLS model. Component 2 was inversely associated with incident T2DM (OR: 0·89; (95 % CI 0·80, 0·99), P-value = 0·043) after adjustment for demographic and metabolic covariates. Component 1 was not associated with T2DM risk (OR: 1·02; (95 % CI 0·88, 1·19), P-value = 0·74). Adherence to a DASH-type diet may contribute to reduced T2DM risk in part through modulations in acylcarnitine and fatty acid physiology.

Optical tracking systems typically trade off between astrometric precision and field of view. In this work, we showcase a networked approach to optical tracking using very wide field-of-view imagers that have relatively low astrometric precision on the scheduled OSIRIS-REx slingshot manoeuvre around Earth on 22 Sep 2017. As part of a trajectory designed to get OSIRIS-REx to NEO 101955 Bennu, this flyby event was viewed from 13 remote sensors spread across Australia and New Zealand to promote triangulatable observations. Each observatory in this portable network was constructed to be as lightweight and portable as possible, with hardware based off the successful design of the Desert Fireball Network. Over a 4-h collection window, we gathered 15 439 images of the night sky in the predicted direction of the OSIRIS-REx spacecraft. Using a specially developed streak detection and orbit determination data pipeline, we detected 2 090 line-of-sight observations. Our fitted orbit was determined to be within about 10 km of orbital telemetry along the observed 109 262 km length of OSIRIS-REx trajectory, and thus demonstrating the impressive capability of a networked approach to Space Surveillance and Tracking.

Brine beneath Taylor Glacier has been proposed to enter the proglacial west lobe of Lake Bonney (WLB) as well as from Blood Falls, a surface discharge point at the Taylor Glacier terminus. The brine strongly influences the geochemistry of the water column of WLB. Year-round measurements from this study are the first to definitively identify brine intrusions from a subglacial entry point into WLB. Furthermore, we excluded input from Blood Falls by focusing on winter dynamics when the absence of an open water moat prevents surface brine entry. Due to the extremely high salinities below the chemocline in WLB, density stratification is dominated by salinity, and temperature can be used as a passive tracer. Cold brine intrusions enter WLB at the glacier face and intrude into the water column at the depth of neutral buoyancy, where they can be identified by anomalously cold temperatures at that depth. High-resolution measurements also reveal under-ice internal waves associated with katabatic wind events, a novel finding that challenges long-held assumptions about the stability of the WLB water column.

Surface melt on the coastal Antarctic ice sheet (AIS) determines the viability of its ice shelves and the stability of the grounded ice sheet, but very few in situ melt rate estimates exist to date. Here we present a benchmark dataset of in situ surface melt rates and energy balance from nine sites in the eastern Antarctic Peninsula (AP) and coastal Dronning Maud Land (DML), East Antarctica, seven of which are located on AIS ice shelves. Meteorological time series from eight automatic and one staffed weather station (Neumayer), ranging in length from 15 months to almost 24 years, serve as input for an energy-balance model to obtain consistent surface melt rates and energy-balance results. We find that surface melt rates exhibit large temporal, spatial and process variability. Intermittent summer melt in coastal DML is primarily driven by absorption of shortwave radiation, while non-summer melt events in the eastern AP occur during föhn events that force a large downward directed turbulent flux of sensible heat. We use the in situ surface melt rate dataset to evaluate melt rates from the regional atmospheric climate model RACMO2 and validate a melt product from the QuikSCAT satellite.