Browsing by Subject "tracking"
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Item Open Access Academic Peer Effects with Different Group Assignment Policies: Residential Tracking versus Random Assignment(Economic Research Initiatives at Duke (ERID), 2016-03-03) Garlick, RJI study the relative academic performance of students tracked or randomly assigned to South African university dormitories. Tracking reduces low-scoring students' GPAs but has little effect on high-scoring students. This lowers mean GPA and raises GPA dispersion. I also directly estimate peer effects using random variation in peer groups across dormitories. Living with higher-scoring peers raises students' GPAs and this effect is larger for low-scoring students. Peer effects operate largely within race groups but operate both within and across programs of study. This suggests that spatial proximity alone does not generate peer effects. Interaction of some sort is required, but direct academic collaboration is not the relevant form of interaction. I integrate the results from variation in group assignment policies and variation in group composition by drawing on the matching and sorting literatures. Both sets of results imply that own and peer academic performance are substitutes in GPA production and that GPA may be a concave function of peer group performance. The cross-dormitory results correctly predict a negative effect of tracking on low-scoring students but understate the magnitude of the observed effect. I show that this understatement reflects both policy-sensitive parameter estimates and problems with extrapolation outside the support of the data observed under random assignment. This underlines the value of using both cross-policy and cross-group variation to study peer effects.Item Embargo Expanding Applications of Active-Feedback Single-Molecule Tracking Microscopy in Complex Background Environments Such as Cells.(2024) Niver, AnastasiaActive-feedback single-particle tracking methods are increasingly being applied to in vivo studies. Cellular heterogeneity is both a contributor to anomalous biomolecule behavior (when compared to behavior in dilute solutions) and an ongoing challenge to stable observation using active-feedback methods. Here we develop combined online Bayesian estimation with windowed estimation of background and signal (COBWEBS) in an effort to achieve active-feedback tracking in heterogeneous background environments. In 2D and 3D simulations, COBWEBS stabilizes tracking in complex environments with changing signal and background intensities. Additionally, COBWEBS (and alternative post-processing methods) are applied to experimental data to extract improved particle localizations. Once appropriately calibrated, COBWEBS, along the imaging XY plane, shows accuracy improvements when compared to the current experimentally implemented particle localization algorithm. Evidence suggests that real-time implementation of COBWEBS is possible, and a framework for future development of real-time estimation is presented. An alternative Gaussian fitting post-processing leads to higher accuracy improvements than the COBWEBS approach but cannot be implemented as a real-time particle localization strategy. Next, it is demonstrated that the increased response speed of a galvo scanning mirror in place of the traditional piezoelectric feedback increases overlap of trackable particle speeds with diffusive speeds of intracellular proteins. Finally, 3D active feedback tracking is used to read out static FRET efficiencies from freely-diffusing single molecules, suggesting potential for applications in probing protein dynamics using FRET as a molecular ruler.
Item Open Access Network analysis of sea turtle movements and connectivity: A tool for conservation prioritization(Diversity and Distributions, 2022-04-01) Kot, CY; Åkesson, S; Alfaro-Shigueto, J; Amorocho Llanos, DF; Antonopoulou, M; Balazs, GH; Baverstock, WR; Blumenthal, JM; Broderick, AC; Bruno, I; Canbolat, AF; Casale, P; Cejudo, D; Coyne, MS; Curtice, C; DeLand, S; DiMatteo, A; Dodge, K; Dunn, DC; Esteban, N; Formia, A; Fuentes, MMPB; Fujioka, E; Garnier, J; Godfrey, MH; Godley, BJ; González Carman, V; Harrison, AL; Hart, CE; Hawkes, LA; Hays, GC; Hill, N; Hochscheid, S; Kaska, Y; Levy, Y; Ley-Quiñónez, CP; Lockhart, GG; López-Mendilaharsu, M; Luschi, P; Mangel, JC; Margaritoulis, D; Maxwell, SM; McClellan, CM; Metcalfe, K; Mingozzi, A; Moncada, FG; Nichols, WJ; Parker, DM; Patel, SH; Pilcher, NJ; Poulin, S; Read, AJ; Rees, AF; Robinson, DP; Robinson, NJ; Sandoval-Lugo, AG; Schofield, G; Seminoff, JA; Seney, EE; Snape, RTE; Sözbilen, D; Tomás, J; Varo-Cruz, N; Wallace, BP; Wildermann, NE; Witt, MJ; Zavala-Norzagaray, AA; Halpin, PNAim: Understanding the spatial ecology of animal movements is a critical element in conserving long-lived, highly mobile marine species. Analyzing networks developed from movements of six sea turtle species reveals marine connectivity and can help prioritize conservation efforts. Location: Global. Methods: We collated telemetry data from 1235 individuals and reviewed the literature to determine our dataset's representativeness. We used the telemetry data to develop spatial networks at different scales to examine areas, connections, and their geographic arrangement. We used graph theory metrics to compare networks across regions and species and to identify the role of important areas and connections. Results: Relevant literature and citations for data used in this study had very little overlap. Network analysis showed that sampling effort influenced network structure, and the arrangement of areas and connections for most networks was complex. However, important areas and connections identified by graph theory metrics can be different than areas of high data density. For the global network, marine regions in the Mediterranean had high closeness, while links with high betweenness among marine regions in the South Atlantic were critical for maintaining connectivity. Comparisons among species-specific networks showed that functional connectivity was related to movement ecology, resulting in networks composed of different areas and links. Main conclusions: Network analysis identified the structure and functional connectivity of the sea turtles in our sample at multiple scales. These network characteristics could help guide the coordination of management strategies for wide-ranging animals throughout their geographic extent. Most networks had complex structures that can contribute to greater robustness but may be more difficult to manage changes when compared to simpler forms. Area-based conservation measures would benefit sea turtle populations when directed toward areas with high closeness dominating network function. Promoting seascape connectivity of links with high betweenness would decrease network vulnerability.