Adult mosquito traps are commonly used in biosecurity surveillance for the detection of exotic mosquito incursions or for the demonstration of elimination. However, traps are typically deployed without knowledge of how many are required for detecting differing numbers of the target species. The aim of this study was to determine the sensitivity (i.e., detection probability) provided by carbon dioxide-baited EVS traps for adult female Australian southern saltmarsh mosquitoes, Aedes camptorhynchus, a recent biosecurity problem for New Zealand. A mark-release-recapture study of three concurrently released cohorts (sized 56, 296, and 960), recaptured over four days with a matrix of 20 traps, was conducted in Australia. The detection probability for different numbers of traps and cohorts of different sizes was determined by random sampling of recapture data. Detection probability ranged from approximately 0.3 for a single trap detecting a cohort of 56 mosquitoes to 1.0 (certainty of detection) when seven or more traps were used. For detection of adult Ae. camptorhynchus around a known source, a matrix of traps provides a strong probability of detection. Conversely, the use of single traps deployed over very large areas to detect mosquitoes of unknown entry pathway is unlikely to be successful. These findings have implications for the design of mosquito surveillance for biosecurity.
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http://dx.doi.org/10.1111/j.1948-7134.2012.00207.x | DOI Listing |
Sleep
January 2025
Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, CO USA.
Study Objectives: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) may improve sleep dysfunction, a common non-motor symptom of Parkinson disease (PD). Improvement in motor symptoms correlates with DBS-suppressed local field potential (LFP) activity, particularly in the beta frequency (13 - 30 Hz). Although well-characterized in the short term, little is known about the innate progression of these oscillations across the sleep-wake cycle.
View Article and Find Full Text PDFCurr Microbiol
January 2025
Razi Vaccine and Serum Research Institute (RVSRI), Agricultural Research, Education and Organization (AREEO), Karaj, Iran.
Brucella spp. is the bacterium responsible for brucellosis, a zoonotic infection that affects humans. This disease poses significant health challenges and contributes to poverty, particularly in developing countries.
View Article and Find Full Text PDFBMJ
December 2024
Department of Preventive Medicine, Hanyang University College of Medicine, Seoul, Republic of Korea.
Objective: To identify clusters of women with similar trajectories of breast density change over four longitudinal assessments and to examine the association between these trajectories and the subsequent risk of breast cancer.
Design: Retrospective cohort study.
Setting: Data from the national breast cancer screening programme, which is embedded in the National Health Insurance Service database in Korea.
Clin Chem
January 2025
Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, United States.
Background: Multianalyte machine learning (ML) models can potentially identify previously undetectable wrong blood in tube (WBIT) errors, improving upon current single-analyte delta check methodology. However, WBIT detection model performance has not been assessed in a real-world, low-prevalence context. To estimate real-world positive predictive values, we propose a methodology to assess WBIT detection models by evaluating the impact of missing data and by using a "low prevalence" validation data set.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Laboratory Engineering System, Hassania School of Public Works, Casablanca BP 8108, Morocco.
This paper presents a systematic review that explores the latest advancements in predictive maintenance methods and cybersecurity for solar panel systems, shedding light on the advantages and challenges of the most recent developments in predictive maintenance techniques for solar plants. Numerous important research studies, reviews, and empirical studies published between 2018 and 2023 are examined. These technologies help in detecting defects, degradation, and anomalies in solar panels by facilitating early intervention and reducing the probability of inverter failures.
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