Study objective: The three-dimensional shape of the ultrasound beam produces a thicker scan plane than most users assume. Viewed longitudinally, a needle placed lateral to a vessel just outside the central scanning plane can be displayed incorrectly in the ultrasound image as if placed intravascularly. This phenomenon is called the beam width artefact, also known as the elevation or slice thickness artefact. The goal of this study was to demonstrate the potential negative effect of the beam width artefact on the performance of in-plane ultrasound- guided vascular access procedures, and to provide a solution. Design: Randomized, double-blinded study Setting: Department of anaesthesiology and intensive care of a teaching hospital Participants: 31 experienced (anesthesiologists and intensivists) and 36 inexperienced (anesthetic nurses) ultrasound users Interventions: We developed an acoustic lens that narrows the scan plane to reduce the beam width artefact. The lens was tested in a simulated vascular access study. Measurements: The primary endpoint was first pass success. Secondary endpoints were the number of punctures and needle withdrawals, procedure time, needle visibility and operator satisfaction. Main results: First pass success was highly enhanced using the acoustic lens, with a success rate of 92.5% versus 68.7% without the lens (difference 23.8, 95% confidence interval 11.0–35.3, p <0.001). The total number of punctures needed to obtain intravenous access was also reduced using the lens (1.10 versus 1.38, difference 0.27, 95% CI 0.11–0.43, p =0.002). Procedure time, needle withdrawals, needle visibility and satisfaction were similar. Both inexperienced and experienced users benefited from the acoustic lens. Conclusions: The beam width artefact has a significant effect on the performance of ultrasound-guided needle- based procedures. The efficacy of in-plane superficial vascular access procedures can be enhanced by narrowing the imaging plane using an acoustic lens.
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INTRODUCTION: In the Netherlands, Diagnostic Reference Levels (DRLs) have not been based on a national survey as proposed by ICRP. Instead, local exposure data, expert judgment and the international scientific literature were used as sources. This study investigated whether the current DRLs are reasonable for Dutch radiological practice.METHODS: A national project was set up, in which radiography students carried out dose measurements in hospitals supervised by medical physicists. The project ran from 2014 to 2017 and dose values were analysed for a trend over time. In the absence of such a trend, the joint yearly data sets were considered a single data set and were analysed together. In this way the national project mimicked a national survey.RESULTS: For six out of eleven radiological procedures enough data was collected for further analysis. In the first step of the analysis no trend was found over time for any of these procedures. In the second step the joint analysis lead to suggestions for five new DRL values that are far below the current ones. The new DRLs are based on the 75 percentile values of the distributions of all dose data per procedure.CONCLUSION: The results show that the current DRLs are too high for five of the six procedures that have been analysed. For the other five procedures more data needs to be collected. Moreover, the mean weights of the patients are higher than expected. This introduces bias when these are not recorded and the mean weight is assumed to be 77 kg.IMPLICATIONS FOR PRACTICE: The current checking of doses for compliance with the DRLs needs to be changed. Both the procedure (regarding weights) and the values of the DRLs should be updated.
Lecture in PhD Programme Life Science Education Research UMCU. Course Methods of Life Science Education Research. Utrecht, The Netherlands. abstract Audit trail procedures are applied as a way to check the validity of qualitative research designs, qualitative analyses, and the claims that are made. Audit trail procedures can be conducted based on the three criteria of visibility, comprehensibility, and acceptability (Akkerman et al., 2008). During an audit trail procedure, all documents and materials resulting from the data gathering and the data analysis are assessed by an auditor. In this presentation, we presented a summative audit trail procedure (Agricola, Prins, Van der Schaaf & Van Tartwijk, 2021), whereas in a second study we used a formative one (Agricola, Van der Schaaf, Prins & Van Tartwijk, 2022). For both studies, two different auditors were chosen. For the study presented in Agricola et al. (2021) the auditor was one of the PhD supervisors, while in that presented Agricola et al. (2022) was a junior researcher not involved in the project. The first auditor had a high level of expertise in the study’s topic and methodology. As a result, he was able to provide a professional and critical assessment report. Although the second auditor might be considered to be more objective than the first, as she was not involved in the project, more meetings were needed to explain the aim of the study and the aim of the audit trail procedure. There are many ideas about the criteria that qualitative studies should meet (De Kleijn en Van Leeuwen, 2018). I argue that procedures of checking for interrater agreement and understanding, the triangulation, and audit trail procedures can increase the internal validity of qualitative studies. Agricola, B. T., Prins, F. J., van der Schaaf, M. F., & van Tartwijk, J. (2021). Supervisor and Student Perspectives on Undergraduate Thesis Supervision in Higher Education. Scandinavian Journal of Educational Research, 65(5), 877-897. doi: https://doi.org/10.1080/00313831.2020.1775115 Agricola, B. T., van der Schaaf, M. F., Prins, F. J., & van Tartwijk, J. (2022). The development of research supervisors’ pedagogical content knowledge in a lesson study project. Educational Action Research. doi: https://doi.org/10.1080/09650792.2020.1832551 de Kleijn, R. A. M., & Van Leeuwen, A. (2018). Reflections and review on the audit procedure: Guidelines for more transparency. International Journal of Qualitative Methods, 17(1), 1-8. doi: https://doi.org/10.1177/1609406918763214 Akkerman, S., Admiraal, W., Brekelmans, M., & Oost, H. (2008). Auditing quality of research in social sciences. Quality & Quantity, 42(2), 257-274. doi: https://doi.org/10.1007/s11135-006-9044-4
The increasing amount of electronic waste (e-waste) urgently requires the use of innovative solutions within the circular economy models in this industry. Sorting of e-waste in a proper manner are essential for the recovery of valuable materials and minimizing environmental problems. The conventional e-waste sorting models are time-consuming processes, which involve laborious manual classification of complex and diverse electronic components. Moreover, the sector is lacking in skilled labor, thus making automation in sorting procedures is an urgent necessity. The project “AdapSort: Adaptive AI for Sorting E-Waste” aims to develop an adaptable AI-based system for optimal and efficient e-waste sorting. The project combines deep learning object detection algorithms with open-world vision-language models to enable adaptive AI models that incorporate operator feedback as part of a continuous learning process. The project initiates with problem analysis, including use case definition, requirement specification, and collection of labeled image data. AI models will be trained and deployed on edge devices for real-time sorting and scalability. Then, the feasibility of developing adaptive AI models that capture the state-of-the-art open-world vision-language models will be investigated. The human-in-the-loop learning is an important feature of this phase, wherein the user is enabled to provide ongoing feedback about how to refine the model further. An interface will be constructed to enable human intervention to facilitate real-time improvement of classification accuracy and sorting of different items. Finally, the project will deliver a proof of concept for the AI-based sorter, validated through selected use cases in collaboration with industrial partners. By integrating AI with human feedback, this project aims to facilitate e-waste management and serve as a foundation for larger projects.
The maximum capacity of the road infrastructure is being reached due to the number of vehicles that are being introduced on Dutch roads each day. One of the plausible solutions to tackle congestion could be efficient and effective use of road infrastructure using modern technologies such as cooperative mobility. Cooperative mobility relies majorly on big data that is generated potentially by millions of vehicles that are travelling on the road. But how can this data be generated? Modern vehicles already contain a host of sensors that are required for its operation. This data is typically circulated within an automobile via the CAN bus and can in-principle be shared with the outside world considering the privacy aspects of data sharing. The main problem is, however, the difficulty in interpreting this data. This is mainly because the configuration of this data varies between manufacturers and vehicle models and have not been standardized by the manufacturers. Signals from the CAN bus could be manually reverse engineered, but this process is extremely labour-intensive and time-consuming. In this project we investigate if an intelligent tool or specific test procedures could be developed to extract CAN messages and their composition efficiently irrespective of vehicle brand and type. This would lay the foundations that are required to generate big data-sets from in-vehicle data efficiently.
De energietransitie van fossiele naar duurzame energie krijgt brede maatschappelijk aandacht. Er zijn projecten voor het plaatsen van zonnepanelen en windturbines. Dit betreft zowel nationale projecten (zoals windparken op de Noordzee en de discussies over waterstof) als kleinere lokale projecten in huizen in woonwijken en bedrijfsgebouwen op bedrijventerreinen. Netcongestie is een recente ontwikkeling, wat betekent dat het elektriciteitsnet niet meer genoeg transportcapaciteit heeft om afspraken te kunnen maken voor nieuwe aansluitingen. Netcongestie beperkt de uitbreiding en vestiging van nieuwe bedrijven in sterke mate. De opschaling van de installatie van duurzame bronnen zoals zon- en windenergie wordt er door onmogelijk. Dit leidt tot een sterke vermindering van de toekomstige economische activiteiten en brengt het halen van duurzame-energiedoelstellingen in gevaar. Op korte termijn is volledig fysieke versterking van het net onmogelijk door gebrek aan mankracht en trage vergunningsprocedures. Een tussentijdse oplossing is het optimaal benutten van de netcapaciteit door de werkelijke vraag en aanbod te meten en beter op elkaar af te stemmen. In deze aanvraag stellen wij een onderzoeksaanpak voor om op lokaal bedrijventerreinenniveau deze sturing, vanuit een nauwe samenwerking tussen de netbeheerder, de parkorganisatie en de lokale (MKB) bedrijven op een bedrijvenpark, vorm te geven. Dit verkennend onderzoek begint met het in kaart te brengen van lokale (energie-)behoeftes en oplossingsmogelijkheden op laagspanningsniveau. Dit gebeurt door de informatie van slimme meters en de laagspanningstrafo’s momentaan uit te lezen en met AI de te verwachtte belasting te bepalen. Als bekend is wat de lokale regelmogelijkheden zijn, kan er met de bedrijven worden nagegaan hoe het huidige laagspanningsnet beter kan worden benut voorafgaand aan grote netverzwaring. Wij inventariseren hoe de opties en de voordelen voor de ondernemers op een begrijpelijke manier kunnen worden gepresenteerd, bijvoorbeeld met behulp van een dashboard.
