Maryland Shared Open Access Repository
MD-SOAR is a shared digital repository platform for eleven colleges and universities in Maryland. It is currently funded by the University System of Maryland and Affiliated Institutions (USMAI) Library Consortium (usmai.org) and other participating partner institutions. MD-SOAR is jointly governed by all participating libraries, who have agreed to share policies and practices that are necessary and appropriate for the shared platform. Within this broad framework, each library provides customized repository services and collections that meet local institutional needs. Please follow the links below to learn more about each library's repository services and collections.
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Wastewater-based epidemiology in Beijing, China: Prevalence of antibiotic use in flu season and association of pharmaceuticals and personal care products with socioeconomic characteristics
(Elsevier Ltd, 2019-04)Wastewater-based epidemiology is an emerging field that has mostly been applied to investigate consumption of illicit drugs. In this study, the wastewater-based epidemiology approach was employed to study consumption of ... -
Nanoparticles for Environment, Engineering, and Nanomedicine
(Hindawi, 2019-01-30) -
Degradation of 2,4-dichlorophenoxyacetic acid by UV 253.7 and UV-H2O2: Reaction kinetics and effects of interfering substances
(Elsevier B.V., 2019)This work investigates the degradation of 2,4-dichlorophenoxy acetic acid (2,4-D) using UV irradiation and the UV-H₂O₂ advanced oxidation process (AOP). For UV irradiation at 253.7 nm, ∼66% degradation was observed for a ... -
The Elementary Education Act of 1870: Landmark or Transition
(Palgrave Macmillan, Cham, 2019-04-11)The Education Act of 1870 was only one of several factors contributing to the onset of universal schooling and literacy in England. Much of the growth of state involvement in the provision of elementary schooling occurred ... -
Generating Videos with Scene Dynamics
(2016)We capitalize on large amounts of unlabeled video in order to learn a model of scene dynamics for both video recognition tasks (e.g. action classification) and video generation tasks (e.g. future prediction). We propose a ...
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