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Träfflista för sökning "WFRF:(Jack Bradley) "

Sökning: WFRF:(Jack Bradley)

  • Resultat 1-10 av 18
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1.
  • McCarrick, Heather, et al. (författare)
  • The Simons Observatory Microwave SQUID Multiplexing Detector Module Design
  • 2021
  • Ingår i: Astrophysical Journal. - : American Astronomical Society. - 0004-637X .- 1538-4357. ; 922:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Advances in cosmic microwave background (CMB) science depend on increasing the number of sensitive detectors observing the sky. New instruments deploy large arrays of superconducting transition-edge sensor (TES) bolometers tiled densely into ever larger focal planes. High multiplexing factors reduce the thermal loading on the cryogenic receivers and simplify their design. We present the design of focal-plane modules with an order of magnitude higher multiplexing factor than has previously been achieved with TES bolometers. We focus on the novel cold readout component, which employs microwave SQUID multiplexing (μmux). Simons Observatory will use 49 modules containing 70,000 bolometers to make exquisitely sensitive measurements of the CMB. We validate the focal-plane module design, presenting measurements of the readout component with and without a prototype detector array of 1728 polarization-sensitive bolometers coupled to feedhorns. The readout component achieves a 95% yield and a 910 multiplexing factor. The median white noise of each readout channel is 65 pA √Hz . This impacts the projected SO mapping speed by <8%, which is less than is assumed in the sensitivity projections. The results validate the full functionality of the module. We discuss the measured performance in the context of SO science requirements, which are exceeded.
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2.
  • Tan, Hung, et al. (författare)
  • No evidence that the widespread environmental contaminant caffeine alters energy balance or stress responses in fish
  • 2023
  • Ingår i: Ethology. - 0179-1613 .- 1439-0310. ; 129:12, s. 666-678
  • Tidskriftsartikel (refereegranskat)abstract
    • Anthropogenic sources of environmental pollution are ever-increasing as urban areas expand and more chemical compounds are used in daily life. The stimulant caffeine is one of the most consumed chemical compounds worldwide, and as a result, has been detected as an environmental contaminant in all types of major water sources on all continents. Exposure of wildlife to environmental pollutants can disrupt the energy balance of these organisms, as restoration of homeostasis is prioritised. In turn, energy allocated to other key biological processes such as growth or reproduction may be affected, consequently reducing the overall fitness of an individual. Therefore, we aimed to investigate if long-term exposure to environmentally relevant concentrations of caffeine had any energetic consequences on wildlife. Specifically, we exposed wild eastern mosquitofish (Gambusia holbrooki) to one of three nominal concentrations of caffeine (0, 100 and 10,000 ng/L) and assayed individuals for metabolic rate, general activity, antipredator and foraging behaviour and body size as measures of energy expenditure or energy intake. We found no differences in any measured traits between any of the given exposure treatments, indicating that exposure to caffeine at current environmental levels may not adversely affect the energy balance and fitness of vulnerable freshwater fish. 
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  • 2019
  • Tidskriftsartikel (refereegranskat)
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  • Bradley, Steven, et al. (författare)
  • A Methodology for Investigating Women's Module Choices in Computer Science
  • 2023
  • Ingår i: ITiCSE 2023. - : Association for Computing Machinery (ACM). - 9798400701399 ; , s. 569-570
  • Konferensbidrag (refereegranskat)abstract
    • At ITiCSE 2021, Working Group 3 examined the evidence for teaching practices that broaden participation for women in computing, based on the National Center for Women & Information Technology (NCWIT) Engagement Practices framework. One of the report's recommendations was "Make connections from computing to your students' lives and interests (Make it Matter) but don't assume you know what those interests are; find out!" The goal of this 2023 working group is to find out what interests women students by bringing together data from our institutions on undergraduate module enrollment, seeing how they differ for women and men, and what drives those choices. We will code published module content based on ACM curriculum guidelines and combine these data to build a hierarchical statistical model of factors affecting student choice. This model should be able to tell us how interesting or valuable different topics are to women, and to what extent topic affects choice of module - as opposed to other factors such as the instructor, the timetable, or the mode of assessment. Equipped with this knowledge we can advise departments how to focus curriculum development on areas that are of value to women, and hence work towards making the discipline more inclusive.
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9.
  • Bradley, Steven, et al. (författare)
  • Modeling Women's Elective Choices in Computing
  • 2023
  • Ingår i: ITiCSE-WGR '23. - : Association for Computing Machinery (ACM). - 9798400704055 ; , s. 196-226
  • Konferensbidrag (refereegranskat)abstract
    • Evidence-based strategies suggest ways to reduce the gender gap in computing. For example, elective classes are valuable in enabling students to choose in which directions to expand their computing knowledge in areas aligned with their interests. The availability of electives of interest may also make computing programs of study more meaningful to women. However, research on which elective computing topics are more appealing to women is often class or institution specific. In this study, we investigate differences in enrollment within undergraduate-level elective classes in computing to study differences between women and men. The study combined data from nine institutions from both Western Europe and North America and included 272 different classes with 49,710 student enrollments. These classes were encoded using ACM curriculum guidelines and combined with the enrollment data to build a hierarchical statistical model of factors affecting student choice. Our model shows which elective topics are less popular with all students (including fundamentals of programming languages and parallel and distributed computing), and which elective topics are more popular with women students (including mathematical and statistical foundations, human computer interaction and society, ethics, and professionalism). Understanding which classes appeal to different students can help departments gain insight of student choices and develop programs accordingly. Additionally, these choices can also help departments explore whether some students are less likely to choose certain classes than others, indicating potential barriers to participation in computing.
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10.
  • Czeszumski, Artur, et al. (författare)
  • #EEGManyLabs: Investigating the Replicability of Influential EEG Experiments
  • 2024
  • Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
    • There is growing awareness across the neuroscience community that the replicability of findings on the relationship between brain activity and cognitive phenomena can be improved by conducting studies with high statistical power that adhere to well-defined and standardized analysis pipelines. Inspired by efforts from the psychological sciences, and with the desire to examine some of the foundational findings using electroencephalography (EEG), we have launched #EEGManyLabs, a large-scale international collaborative replication effort. Since its discovery in the early 20th century, EEG has had a profound influence on our understanding of human cognition, but there is limited evidence on the replicability of some of the most highly cited discoveries. After a systematic search and selection process, we have identified 27 of the most influential and continually cited studies in the field. We plan to directly test the replicability of key findings from 20 of these studies in teams of at least three independent laboratories. The design and protocol of each replication effort will be submitted as a Registered Report and peer-reviewed prior to data collection. Prediction markets, open to all EEG researchers, will be used as a forecasting tool to examine which findings the community expects to replicate. This project will update our confidence in some of the most influential EEG findings and generate a large open access database that can be used to inform future research practices. Finally, through this international effort, we hope to create a cultural shift towards inclusive, high-powered multi-laboratory collaborations.
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