University of Windsor

About: University of Windsor is a education organization based out in Windsor, Ontario, Canada. It is known for research contribution in the topics: Population & Argumentation theory. The organization has 10654 authors who have published 22307 publications receiving 435906 citations. The organization is also known as: UWindsor & Assumption University of Windsor.

Brominated and chlorinated flame retardants in Lake Ontario, Canada, lake trout (Salvelinus namaycush) between 1979 and 2004 and possible influences of food-web changes

Abstract: Concentrations of non-polybrominated diphenyl ether (PBDE) brominated (hexabromocyclododecane [HBCD], 1,2-bis[2,4,6-tribromophenoxy]ethane [BTBPE], and pentabromoethylbenzene [PEB]) and chlorinated (Dechlorane Plus [DP] as well as short- and medium-chain chlorinated paraffins [SCCP and MCCP, respectively]) flame retardants were evaluated in archived Lake Ontario, Canada, lake trout (Salvelinus namaycush) samples collected between 1979 and 2004. Polybrominated diphenyl ethers also were analyzed to provide a point of reference for comparison to previous studies. Concentrations of the dominant PBDE congeners (BDEs 28, 47, 99, 100, 153, and 154) increased significantly from 1979 until the mid-1990s, then either leveled off or decreased significantly between 1998 and 2004, a result that corresponds to those of previous studies. In contrast, BDE 209 increased approximately fourfold between 1998 and 2004. The temporal trends of the non-PBDE flame retardants varied, with sum (Σ) HBCD and DP showing significant overall decreases; BTBPE, ΣSCP, and ΣMCP showing parabolic trends; and PEB showing no overall change during the study period. Because many of the non-PBDE chemicals may be used as replacements for penta- and octa-BDE mixtures, these results will provide a baseline to evaluate future usage patterns. Possible changes in food-web structure, evaluated through stable nitrogen isotopes (δ15N), may be influencing our interpretations of contaminant trends in lake trout and are hypothesized to be partially responsible for the observed decrease in concentrations of BDEs 28, 47, 99, 100, 153, and 154 between 1998 and 2004. Retrospective analyses evaluating temporal trends in stable isotope values at the base of the food web, however, are recommended to test this hypothesis further.

Ten years tracking the migrations of small landbirds: Lessons learned in the golden age of bio-logging

Abstract: In 2007, the first miniature light-level geolocators were deployed on small landbirds, revolutionizing the study of migration. In this paper, we review studies that have used geolocators to track small landbirds with the goal of summarizing research themes and identifying remaining important gaps in understanding. We also highlight research and opportunities using 2 recently developed tracking technologies: archival GPS tags and automated radio-telemetry systems. In our review, we found that most (54%) geolocator studies focused on quantifying natural history of migration, such as identifying migration routes, nonbreeding range, and migration timing. Studies of behavioral ecology (20%) uncovered proximate drivers of movements, including en route habitat quality; that migration routes, but not timing, may be flexible in some species; and different age and sex classes show significant differences in migration strategy. Studies of the evolution of migration (9%) have illustrated that migration is a ...

Unified relativistic theory for 1s2p P13-1s2 S01 and 1s2p P11-1s2 S01 frequencies and transition rates in heliumlike ions

Abstract: The aim of this paper is to test a simple method for converting accurate nonrelativistic predictions of atomic properties into accurate relativistic predictions with a minimum of additional computational effort. The method connects smoothly the exact nonrelativistic $\mathrm{LS}$-coupling results appropriate at small $Z$ with the relativistic $\mathrm{jj}$-coupling results appropriate at large $Z$. For the processes stated in the title, the method appears to offer a significant improvement in accuracy over relativistic Hartree-Fock or random-phase-approximation calculations, particularly in the low and intermediate range of nuclear charge. For large $Z$, the present results agree well with the relativistic random-phase approximation.

Learning in the Air: Secure Federated Learning for UAV-Assisted Crowdsensing

Abstract: Unmanned aerial vehicles (UAVs) combined with artificial intelligence (AI) have opened a revolutionized way for mobile crowdsensing (MCS). Conventional AI models, built on aggregation of UAVs’ sensing data (typically contain private and sensitive user information), may arise severe privacy and data misuse concerns. Federated learning, as a promising distributed AI paradigm, has opened up possibilities for UAVs to collaboratively train a shared global model without revealing their local sensing data. However, there still exist potential security and privacy threats for UAV-assisted crowdsensing with federated learning due to vulnerability of central curator, unreliable contribution recording, and low-quality shared local models. In this paper, we propose SFAC, a s ecure f ederated learning framework for U A V-assisted M C S. Specifically, we first introduce a blockchain-based collaborative learning architecture for UAVs to securely exchange local model updates and verify contributions without the central curator. Then, by applying local differential privacy, we design a privacy-preserving algorithm to protect UAVs’ privacy of updated local models with desirable learning accuracy. Furthermore, a two-tier reinforcement learning-based incentive mechanism is exploited to promote UAVs’ high-quality model sharing when explicit knowledge of network parameters are not available in practice. Extensive simulations are conducted, and the results demonstrate that the proposed SFAC can effectively improve utilities for UAVs, promote high-quality model sharing, and ensure privacy protection in federated learning, compared with existing schemes.