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9,302 results for “DETECT”
Data from: Brief in-hospital cognitive screening detects dementia and anticipates complex admissions
<p><strong>Objective</strong>: With the goal of improving community health by screening for dementia, we tested the utility of integrating the Six-Item Screener (SIS) into our emergency room neurology consultations.</p> <p><strong>Methods</strong>: In this cross-sectional observational study, we measured SIS performance within 24 hours of hospital arrival in one hundred consecutive English-speaking patients aged ≥ 45 years. Performance was compared to patient age, previously-charted cognitive impairment, and proxies for in-hospital complexity: whether or not a patient was admitted to the hospital and the number of medical studies ordered.</p> <p><strong>Results</strong>: Those with poor SIS performance were older (<em>p</em> = 0.02), more likely to have previously-charted cognitive impairment (<em>p</em> < 0.01; sensitivity 86%, specificity 77%). Poor performers were more likely to be admitted to the hospital (<em>p</em> = 0.04; odds ratio = 3.6) and were subjected to more tests once admitted (<em>p</em> < 0.01). These findings persisted after accounting for age and history of cognitive impairment.</p> <p><strong>Conclusions</strong>: Poor performance on the SIS was associated with previously charted cognitive impairment, justifying future study of its ability to detect unrecognized dementia cases. Until then, its ability to inexpensively anticipate medically complex hospital admissions motivates broader emergency department use of the SIS.</p>
A novel method for detecting extra-home range movements (EHRMs) by animals and recommendations for future EHRM studies
<p>Infrequent, long-distance animal movements outside of typical home range areas provide useful insights into resource acquisition, gene flow, and disease transmission within the fields of conservation and wildlife management, yet understanding of these movements is still limited across taxa. To detect these extra-home range movements (EHRMs) in spatial relocation datasets, most previous studies compare relocation points against fixed spatial and temporal bounds, typified by seasonal home ranges (referred to here as the "Fixed-Period" method). However, utilizing home ranges modelled over fixed time periods to detect EHRMs within those periods likely results in many EHRMs going undocumented, particularly when an animal's space use changes within that period of time. To address this, we propose a novel, "Moving-Window" method of detecting EHRMs through an iterative process, comparing each day's relocation data to the preceding period of space use only. We compared the number and characteristics of EHRM detections by both the Moving-Window and Fixed-Period methods using GPS relocations from 33 white-tailed deer (Odocoileus virginianus) in Alabama, USA. The Moving-Window method detected 1.5 times as many EHRMs as the Fixed-Period method and identified 120 unique movements that were undetected by the Fixed-Period method, including some movements that extended nearly 5 km outside of home range boundaries. Additionally, we utilized our EHRM dataset to highlight and evaluate potential sources of variation in EHRM summary statistics stemming from differences in definition criteria among previous EHRM literature. We found that this spectrum of criteria identified between 15.6% and 100.0% of the EHRMs within our dataset. We conclude that variability in terminology and definition criteria previously used for EHRM detection hinders useful comparisons between studies. The Moving-Window approach to EHRM detection introduced here, along with proposed methodology guidelines for future EHRM studies, should allow researchers to better investigate and understand these behaviors across a variety of taxa.</p>
Data from: Natural disturbances can produce misleading bioassessment results: identifying metrics to detect anthropogenic impacts in intermittent rivers
<p>Ecosystems experience natural disturbances and anthropogenic impacts that affect biological communities and ecological processes. When natural disturbance modifies anthropogenic impacts, current widely used bioassessment metrics can prevent accurate assessment of biological quality.</p> <p>Our aim was to assess the ability of biomonitoring metrics to detect anthropogenic impacts at both perennial and intermittent sites, and in the latter including both flowing and disconnected pool aquatic phases. Specifically, aquatic macroinvertebrates from 20 rivers were sampled along gradients of natural flow intermittence (natural disturbance) and anthropogenic impacts to investigate their combined effects on widely used river biomonitoring metrics (i.e. taxonomic richness and standard biological indices) and novel functional metrics, including functional redundancy (i.e. the number of taxa contributing similarly to an ecosystem function, here a trophic function) and response diversity (i.e. how functionally similar taxa respond to natural disturbance and anthropogenic impacts).</p> <p>Our results showed that natural flow intermittence can confound river bioassessment, and that a set of new functional metrics could be used as effective alternatives to standard metrics in naturally disturbed intermittent rivers.</p>
Detection and Estimation of Inundation and Associated Risks Using Traffic and Monitoring Cameras and Image Processing Under Extreme Flooding Conditions
<p>The main objective of this project is to develop an inundation detection and evaluation framework using images from traffic monitoring cameras and reliable flood monitoring under extreme precipitation conditions. This study presents a comparative assessment of image enhancement and segmentation techniques to automatically identify the flash flooding from the low-resolution images taken by traffic-monitoring cameras. Due to inaccurate equipment in severe weather conditions (e.g., raindrops or light refraction on camera lenses), low-resolution images are subject to noises that degrade the quality of information. De-noising procedures are carried out for the enhancement of images by removing different types of noises. After the de-noising, image segmentation is implemented to detect the inundation from the images automatically. In addition, the detection of the inundation using the image segmentation with and without de-noising techniques are compared. The results indicate that among de-noising methods, the Bayes shrink with the thresholding discrete wavelet transform shows the most reliable result. For the image segmentation, the Bayesian segmentation is superior to the others. The results demonstrate that the proposed image enhancement and segmentation methods can be effectively used to identify the inundation from low-resolution images taken in severe weather conditions. A new Bayesian filtering method will be devised and applied to estimate the inundation from low-resolution images that will allow traffic engineers to take preventive or proactive actions to improve the safety of drivers and protect and preserve the transportation infrastructure. This new observation with improved accuracy will enhance our understanding of dynamic urban flooding by filling an information gap in the locations where conventional observations have limitations.</p>
Sampling of common eiders for the detection of Pasteurella multocida infection at Mitivik Island, Nunavut
<p>From 2007-2014, pre-breeding common eiders were captured in flight nets when arriving and flying over Mitivik Island, Nunavut, banded, sexed and measured. Cloacal and oral samples were collected for detection of current <i>Pasteurella multocida</i> infection, and blood samples were collected for detection of antibodies to this bacterium. For more details, see van Dijk et al. (2020) Herd immunity drives the epidemic fadeout of avian cholera in Arctic-nesting seabirds.</p>
Data to accompany manuscript: Detection and tracking of cracks based on thermoelastic stress analysis
<p>Thermoelastic stress analysis datasets were collected during tensile loading of hole-in-plate aluminium alloy specimens, at both constant amplitude and frequency conditions, and at variable amplitude and frequency conditions - based on an idealised flight cycle. Data were collected during initiation and propagation of a fatigue crack and monitored using three types of infra-red detector at different price points.</p> <p> </p> <p>--------------------------</p> <p>This dataset accompanies the manuscript:</p> <p>Detection and tracking of cracks based on thermoelastic stress analysis</p> <p>Middleton C. A.1, Weihrauch, M.1, Christian, W. J. R.1, Greene, R. J.2, and Patterson, E. A.1</p> <p>1School of Engineering, University of Liverpool, The Quadrangle, Brownlow Hill, Liverpool, L69 3GH, U.K.<br> 2Strain Solutions Ltd, Dunston Innovation Centre, Dunston Road, Chesterfield, Derbyshire S41 8NG, U.K.</p> <p>Royal Society Open Science, Accepted: 26 November 2020</p> <p> </p> <p> </p>
Detection dogs in nature conservation: a database on their worldwide deployment with a review on breeds used and their performance compared to other methods
<p>Over the last century, dogs have been increasingly used to detect rare and elusive species or traces of them. The use of wildlife detection dogs (WDD) is particularly well established in North America, Europe and Oceania, and projects deploying them have increased worldwide. However, if they are to make a significant contribution to conservation and management, their strengths, abilities, and limitations should be fully identified. We reviewed the use of WDD with particular focus on the breeds used in different countries and for various targets, as well as their overall performance compared to other methods, by developing and analysing a database of 1220 publications, including 916 scientific ones, covering 2464 individual cases - most of them (1840) scientific. With the worldwide increase in the use of WDD, associated tasks have changed and become much more diverse. Since 1930, reports exist for 62 countries and 407 animal, 42 plant, 26 fungi and 6 bacteria species. Altogether, 108 FCI-classified and 20 non-FCI-classified breeds have worked as WDD. While certain breeds have been preferred on different continents and for specific tasks and targets, they were not generally better suited for detection tasks than others. Overall, WDD usually worked more effectively than other monitoring methods. For each species group, regardless of breed, detection dogs were better than other methods in 88.71% of all cases and only worse in 0.98%. It was only for arthropods that Pinshers and Schnauzers performed worse than other breeds. For mono- and dicotyledons, detection dogs did less often outperform other methods. Although every breed can be trained as a WDD, choosing the most suitable dog for the task and target may speed up training and increase the chance of success. Albeit selection of the most appropriate WDD is important, excellent training, knowledge about the target density and suitability, and a proper study design all appeared to have the highest impact on performance. Moreover, an appropriate area, habitat and weather are crucial for detection dog work. When these factors are taken into consideration, WDD can be an outstanding monitoring method.</p>
Detection of gene function - bioinformatics and molecular methods
<p>On December 28, 2020, we organized the first 1st IPANEMA Invited Scientific Online Lecture. The lecture was held by Mladen Petreš, from the Faculty of Agriculture, University of Novi Sad. Through this lecture, our researchers had a chance to learn more about the detection of gene function - bioinformatics and molecular methods.</p>
Porous Silicon Biosensor for the Detection of Bacteria Through Their Lysate: Data
<p>This file contains:</p> <p>- Characterization data of porous silicon layer based on different etching parameters</p> <p>- Relative EOT shift on PSi layers for different analytes</p> <p>- Relative EOT shift on PSi membranes for different analytes</p> <p>- EOT shift on PSi membranes with respect to refractive index changes</p>
Comparative evaluation of ten lateral flow immunoassays to detect SARS-CoV-2 antibodies
<p><b>Background: </b>Rapid mobilisation from industry and academia following the outbreak of the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), led to the development and availability of SARS-CoV-2 lateral flow immunoassays (LFAs). High-quality LFAs are urgently needed at the point of care to add to currently available diagnostic tools. In this study, we provide evaluation data for ten LFAs suitable for use at the point of care.</p> <p><b>Methods:</b> COVID-19 positive patients (N=45), confirmed by reverse transcription – quantitative polymerase chain reaction (RT-qPCR), were recruited through the International Severe Acute Respiratory and Emerging Infection Consortium - Coronavirus Clinical Characterisation Consortium (ISARIC4C) study. Sera collected from patients with influenza A (N=20), tuberculosis (N=5), individuals with previous flavivirus exposure (N=21), and healthy sera (N=4), collected pre-pandemic, were used as negative controls. Ten LFAs manufactured or distributed by ASBT Holdings Ltd, Cellex, Fortress Diagnostics, Nantong Egens Biotechnology, Mologic, NG Biotech, Nal von Minden, and Suzhou Herui BioMed Co. were evaluated.</p> <p><b>Results: </b>Compared to RT-qPCR, sensitivity of LFAs ranged from 87.0-95.7%. Specificity against pre-pandemic controls ranged between 92.0-100%. Compared to IgG ELISA, sensitivity and specificity ranged between 90.5-100% and 93.2-100%, respectively. Percentage agreement between LFAs and IgG ELISA ranged from 89.6-92.7%. Inter-test agreement between LFAs and IgG ELISA ranged between kappa=0.792-0.854.</p> <p><b>Conclusions: </b>LFAs may serve as a useful tool for rapid confirmation of ongoing or previous infection in conjunction with clinical suspicion of COVID-19 in patients attending hospital. Impartial validation prior to commercial sale provides users with data that can inform best use settings.</p>
AH-CID: A Tool to Automatically Detect Human-Centric Issues in App Reviews
<p>The keyword list used in the paper to pre-filter the app reviews.</p>
Occupancy and detection probability of American Three-toed Woodpecker in a heavily-managed boreal forest of eastern Canada
<p>The southern extent of the boreal forest in North America has experienced intensive human disturbance in recent decades. Among these, forest harvesting leads to the substantial loss of late-successional stands that include key habitat attributes for several avian species. The American Three-toed Woodpecker, <em>Picoides dorsalis</em>, is associated with continuous old spruce forests in the eastern part of its range. In this study, we assessed the influence of habitat characteristics at different scales on the occupancy of American Three-toed Woodpecker in a heavily-managed boreal landscape of northeastern Canada, and we inferred species occupancy at the regional scale. We conducted 185<br> playback stations over two breeding seasons and modelled the occupancy of the species while taking into account the probability of detection. American Three-toed Woodpecker occupancy was lower in stands with large areas recently clear-cut, and higher in landscapes with large extents of old-growth forest dominated by black spruce. At the regional scale, areas with high probability of occupancy were scarce and mostly within protected areas. Habitat requirements of the American Three-toed Woodpecker during the breeding season, coupled with overall low occupancy rate in our study area, challenge its long-term sustainability in such heavily managed landscapes. Additionally, the scarcity of areas of high probability of occupancy in the region suggests that the ecological role of old forest outside protected areas could be compromised.</p>
Prospects of gravitational-waves detections from common-envelope evolution with LISA
<p>Input and output files for the <a href="https://cosmic-popsynth.github.io/">COSMIC</a> simulations used in <a href="https://arxiv.org/abs/2102.00078">arXiv:2102.00078</a>.</p>
Accurate SNV detection in single cells by transposon-based whole-genome amplification of complementary strands
<p>Common SNPs from gnomAD</p>
Data from: Dead before detection: addressing the effects of left truncation on survival estimation and ecological inference for neonates
1. Neonate survival is a key life history trait, yet remains challenging to measure in wild populations because neonates can be difficult to capture at birth. Estimates of survival from neonates that are opportunistically captured might be inaccurate because some individuals die before sampling, resulting in data that are left truncated. The resulting overestimation of survival rates can further affect ecological inference through biased estimates of covariate effects in survival models, yet is not addressed in most studies of animal survival. Here, we quantify the effects of left truncation on survival estimates and subsequent ecological inference. 2. Vaginal implant transmitters (VITs) enable capture of ungulates at birth, yielding data without left truncation. The effects of left truncation on survival estimation were quantified using age-dependent survival models for VIT and opportunistically captured neonatal deer. Differences in daily survival rates (DSRs) and cumulative survival probability were calculated for the first 70 days of life. In addition, left truncation was simulated by removing fawns that died during the first 1 or 2 days of life from the VIT-caught sample, isolating the effect of left truncation. 3. Cumulative probability of survival during the first 70 days of life was overestimated by 7–23% for fawns caught opportunistically compared with those caught by VIT, depending on model design. Differences in DSRs were large at age 1 day, but had converged by age 30 days. Simulated left truncation resulted in overestimates of survival of up to 31%. Model selection and covariate coefficients were strongly affected by left truncation, producing spurious ecological inference, including changes to sign and/or magnitude of inferred effects of all covariates. 4. We recommend (i) every effort be made to capture neonates; (ii) consistent capture methods, using at least in part non-truncating techniques, be implemented across years and study areas; and (iii) exclusion of left-truncated data from survival estimates until DSRs converge with those calculated from non-truncated data. This work emphasizes the importance of accounting for left truncation in survival estimation for any species with strong age-dependent survival in order to prevent biased conclusions produced by sampling method rather than true ecological effects.
Data from: A method for detecting recent changes in contemporary effective population size from linkage disequilibrium at linked and unlinked loci
Estimation of contemporary effective population size (Ne) from linkage disequilibrium (LD) between unlinked pairs of genetic markers has become an important tool in the field of population and conservation genetics. If data pertaining to physical linkage or genomic position are available for genetic markers, estimates of recombination rate between loci can be combined with LD data to estimate contemporary Ne at various times in the past. We extend the well-known, LD-based method of estimating contemporary Ne to include linkage information and show via simulation that even relatively small, recent changes in Ne can be detected reliably with a modest number of SNP loci. We explore several issues important to interpretation of the results and quantify the bias in estimates of contemporary Ne associated with the assumption that all loci in a large SNP dataset are unlinked. The approach is applied to an empirical dataset of SNP genotypes from a population of a marine fish where a recent, temporary decline in Ne is known to have occurred.
Data from: Repurposing population genetics data to discern genomic architecture: a case study of linkage cohort detection in mountain pine beetle (Dendroctonus ponderosae)
Genetic surveys of the population structure of species can be used as resources for exploring their genomic architecture. By adjusting filtering assumptions, genome-wide single nucleotide polymorphism (SNP) datasets can be reused to give new insights into the genetic basis of divergence and speciation without targeted re-sampling of specimens. Filtering only for missing data and minor allele frequency, we used a combination of principle components analysis and linkage disequilibrium network analysis to distinguish three cohorts of variable SNPs in the mountain pine beetle in western Canada, including one that was sex-linked and one that was geographically associated. These marker cohorts indicate genomically localized differentiation, and their detection demonstrates an accessible and intuitive method for discovering potential islands of genomic divergence without a priori knowledge of a species' genomic architecture. Thus, this method has utility for directly addressing the genomic architecture of species and generating new hypotheses for functional research.
Data from: Redirection of ambient light improves predator detection in a diurnal fish
Cases where animals use controlled illumination to improve vision are rare and thus far limited to chemiluminescence, which only functions in darkness. This constraint was recently relaxed by studies on Tripterygion delaisi, a small triplefin that redirects sunlight instead. By reflecting light sideways with its iris, it has been suggested to induce and detect eyeshine in nearby microprey. Here, we test whether "diurnal active photolocation" also improves T. delaisi's ability to detect a cryptobenthic sit-and-wait predator Scorpaena porcus, a scorpionfish with strong daytime retroreflective eyeshine. Three independent experiments revealed that triplefins in which light redirection was artificially suppressed approached scorpionfish significantly closer than two control treatments before moving away to a safer distance. Visual modelling confirmed that ocular light redirection by a triplefin is sufficiently strong to generate a luminance increase in scorpionfish eyeshine that can be perceived by the triplefin over 6-8 cm under average conditions. These distances coincide well with the closest approaches observed. We conclude that light redirection by small, diurnal fish significantly contributes to their ability to visually detect cryptic predators, strongly widening the conditions under which active sensing with light is feasible. We discuss the consequences for fish eye evolution.
Data from: Ecologically diverse and distinct neighbourhoods trigger persistent phenotypic consequences, and amine metabolic profiling detects them
1.Global change triggers rapid alterations in the composition and diversity of plant communities which may change ecosystem functioning. Do changes in community diversity also change traits persistently, i.e. does coexistence with numerous or functionally or phylogenetically distinct species trigger, in a given focal species, trait shifts that persist? 2.We studied the grass Dactylis glomerata. Dactylis was grown in experimental plots with different species compositions for five years, sampled, cloned and grown in a common garden. We studied amines, regulators integrating growth responses of organisms to their environment. 3.We found that the mean levels and variances of most amines depended on the diversity of the source community, notably the species richness and the phylogenetic and functional distinctness from Dactylis, unbiased by species identity or biomass shifts. 4.Synthesis. Our results suggest that different levels of ambient diversity can, within a few years, select for different genotypes which have different compositions of growth regulators. Our study also suggests that a plant species can evolve in response to the diversity or distinctness of the surrounding plant community. Evolutionary changes of plant phenotypes might mediate an impact of past biological diversity on present ecosystem functioning.
Data from: The measurement of selection when detection is imperfect: how good are naïve methods?
The life spans of animals can be measured in natural populations by uniquely marking individuals and then releasing them into the field. Selection on survival (a component of fitness) can subsequently be quantified by regressing the life spans of these marked individuals on their trait values. However, marked individuals are not always seen on every subsequent catching occasion, and for this reason, imperfect detection is considered a problem when estimating survival selection in natural populations. Capture–mark–recapture methods have been advocated as a powerful means to correct for imperfect detection. Here, we use simulated and field data sets to evaluate the effect of assuming perfect detection ('naïve methods'), when detection is really imperfect. We compared the performance of the naïve methods with methods correcting for imperfect detection (mark–recapture methods, or MR). Although the effects of trait-dependent recapture probability are mitigated when recapture probability is high, mark–recapture methods still provide the safest choice when recapture probability might be trait-dependent. In our simulations, mark–recapture methods had a power advantage over naïve methods, but all methods lost statistical power at low recapture probabilities. The main advantage of mark–recapture methods over naïve methods is the ability to control for hidden trait-dependent recapture probability, as it is often hard to tell a priori if trait dependence is an issue in a particular study. However, when trait-dependent recapture probability is weak, naïve methods and mark–recapture methods perform similarly as long as recapture rates do not become too low, and the main problem of survival selection studies is still low statistical power. We provide a R package (EasyMARK) alongside with this paper to facilitate future integration between MR methods and classical selection studies. EasyMARK provides the opportunity to convert the regression coefficients from MR-approaches in to classical standardized selection gradients.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.