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10 results for “Radio Frequency Identification”
Data for: Using radio frequency identification (RFID) technology to characterize nest site selection in wild Japanese tits (Parus minor)
<p>Selecting a suitable nest site is critical to the survival and reproduction of birds. Prospecting allows individuals to gather information on the local quality of potential future breeding sites, which may help them make the best nest site selection decision. However, few studies have focused on the direct links between the prospecting activity of breeders and subsequent nest site selection. In this study, we investigated the prospecting pattern of Japanese tits (<em>Parus minor</em>) during the pre-breeding period of the first breeding attempt and whether nest site characteristics influence their nest box visiting behaviour and occupied nest site. We used radio frequency identification (RFID) to track the movements of Japanese tits visiting nest boxes and compared nest site characteristics between visited and unvisited (control) nest boxes, as well as between visited and occupied nest boxes. We found that Japanese tits started visiting nest boxes approximately 20 days before breeding, visited an average of 6 nest boxes and eventually chose the most visited nest box for breeding activities. Japanese tits were more likely to visit nest boxes that had less canopy cover and lower shrub density but a greater total number of surrounding trees and ultimately chose breeding nest boxes with a smaller entrance inclination, in nesting trees with a larger diameter at breast height (DBH) which were surrounded by trees with a larger DBH. Our results suggest that Japanese tits visit several potential breeding sites before choosing breeding nest boxes and that nest site characteristics can influence their prospecting activity and nest site selection.</p>
Data for: Using radio frequency identification (RFID) technology to characterize nest site selection in wild Japanese tits (Parus minor)
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Data from: How to quantify animal activity from radio-frequency identification (RFID) recordings
Automated animal monitoring via radio-frequency identification (RFID) technology allows efficient and extensive data sampling of individual activity levels, and is therefore commonly used for ecological research. However, processing RFID data is still a largely unresolved problem, which potentially leads to inaccurate estimates for behavioural activity. One of the major challenges during data processing is to isolate independent behavioural actions from a set of superfluous, non-independent detections. As a case study, individual blue tits (Cyanistes caeruleus) were simultaneously monitored during reproduction with both video recordings and RFID technology. We demonstrated how RFID data can be processed based on the time spent in- and outside a nest box. We then validated the number and timing of nest visits obtained from the processed RFID dataset by calibration against video recordings. The video observations revealed a limited overlap between the time spent in- and outside the nest box, with the least overlap at 23 seconds for both sexes. We then isolated exact arrival times from redundant RFID registrations by erasing all successive registrations within 23 seconds after the preceding registration. After aligning the processed RFID data with the corresponding video recordings, we observed a high accuracy in three behavioural estimates of parental care (individual nest visit rates, within-pair alternation and synchronization of nest visits). We provide a clear guideline for future studies that aim to implement RFID technology in their research. We argue that our suggested RFID data processing procedure improves the precision of behavioural estimates, despite some inevitable drawbacks inherent to the technology. Our method is useful, not only for other cavity breeding birds, but for a wide range of (in)vertebrate species that are large enough to be fitted with a tag and that regularly pass near or through a fixed antenna.
Measuring intraoperative surgical instrument use with radio-frequency identification
<p><strong>Objective:</strong> Surgical instrument oversupply drives cost, confusion, and workload in the operating room (OR). With an estimated 78-87% of instruments being unused, many health systems have recognized the need for supply refinement. By manually recording instrument use and tasking surgeons to review instrument trays, previous quality improvement initiatives have achieved an average 52% reduction in supply. While demonstrating the degree of instrument oversupply, previous methods for identifying required instruments are qualitative, expensive, lack scalability and sustainability, and are prone to human error. In this work, we aim to develop and evaluate an automated system for measuring surgical instrument use.</p> <p><strong>Materials and Methods:</strong> We present the first system to our knowledge that automates the collection of real-time instrument use data with radio-frequency identification (RFID). Over 15 breast surgeries, ten carpometacarpal (CMC) arthroplasties, and four craniotomies, instrument use was tracked by both a trained observer manually recording instrument use and the RFID system.</p> <p><strong>Results:</strong> The average Cohen's Kappa agreement between the system and the observer was 0.81 (near perfect agreement), and the system enabled a supply reduction of 50.8% in breast and orthopedic surgery. Over 10 monitored breast surgeries and one CMC arthroplasty with reduced trays, no eliminated instruments were requested, and both trays continue to be used as the supplied standard. Setup time in breast surgery decreased from 23 minutes to 17 minutes with the reduced supply.</p> <p><strong>Conclusion:</strong> The RFID system presented herein achieves a novel data stream that enables accurate instrument supply optimization.</p>
Measuring intraoperative surgical instrument use with radio-frequency identification
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Data from: How to quantify animal activity from radio-frequency identification (RFID) recordings
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Data from: An active-radio-frequency-identification system capable of identifying co-locations and social-structure: validation with a wild free-ranging animal
Behavioural events that are important for understanding sociobiology and movement ecology are often rare, transient and localised, but can occur at spatially distant sites e.g. territorial incursions and co-locating individuals. Existing animal tracking technologies, capable of detecting such events, are limited by one or more of: battery life; data resolution; location accuracy; data security; ability to co-locate individuals both spatially and temporally. Technology that at least partly resolves these limitations would be advantageous. European badgers (Meles meles L.), present a challenging test-bed, with extra-group paternity (apparent from genotyping) contradicting established views on rigid group territoriality with little social-group mixing. In a proof of concept study we assess the utility of a fully automated active-radio-frequency-identification (aRFID) system combining badger-borne aRFID-tags with static, wirelessly-networked, aRFID-detector base-stations to record badger co-locations at setts (burrows) and near notional border latrines. We summarise the time badgers spent co-locating within and between social-groups, applying network analysis to provide evidence of co-location based community structure, at both these scales. The aRFID system co-located animals within 31.5 m (adjustable) of base-stations. Efficient radio transmission between aRFIDs and base-stations enables a 20 g tag to last for 2–5 years (depending on transmission interval). Data security was high (data stored off tag), with remote access capability. Badgers spent most co-location time with members of their own social-groups at setts; remaining co-location time was divided evenly between intra- and inter-social-group co-locations near latrines and inter-social-group co-locations at setts. Network analysis showed that 20–100% of tracked badgers engaged in inter-social-group mixing per week, with evidence of trans-border super-groups, that is, badgers frequently transgressed notional territorial borders. aRFID occupies a distinct niche amongst established tracking technologies. We validated the utility of aRFID to identify co-locations, social-structure and inter-group mixing within a wild badger population, leading us to refute the conventional view that badgers (social-groups) are territorial and to question management strategies, for controlling bovine TB, based on this model. Ultimately aRFID proved a versatile system capable of identifying social-structure at the landscape scale, operating for years and suitable for use with a range of species.
Data from: An active-radio-frequency-identification system capable of identifying co-locations and social-structure: validation with a wild free-ranging animal
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Enhancing Upper Limb Prostheses With Radio Frequency Identification
ClinicalTrials.gov study NCT01967004. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Radio-frequency Identification (RFID) Osteoporosis Pilot Study
ClinicalTrials.gov study NCT03385941. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
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