Open Educational Resources Textbook List

Discipline specific OER textbook list for departments at SHU, compiled by Zach Claybaugh and Chelsea Stone

Open Educational Resource 2017 Textbook List

This is an updated, discipline specific OER textbook list for departments at Sacred Heart University, compiled by Zach Claybaugh and Chelsea Stone

OER Awareness, Advocacy, and Adoption: An Institutional Approach

Sacred Heart University’s Open Educational Resources (OER) Task Force, an entity composed of the Office of the Provost, the Office of Digital Learning (ODL), Sacred Heart University Library, and faculty from across campus, has worked for the past two years to integrate OER into the educational culture of the university. To accomplish this we’ve employed a process that focuses on building awareness, identifying campus units for building strategic partnerships, assisting faculty in locating relevant resources, and, through pilot programs, onboarding OER into courses for trial

GLAM 3D

Review of GLAM 3D, Reviewed April 2021 by Chelsea Stone [email protected]

Copyright for Educators & Librarians

Review of Copyright for Educators & Librarians, Reviewed June 2019 by Chelsea M. Stone, Photo Research & Permissions Librarian History Colorado [email protected]

#dariahTeach

Review: Launched in 2015, #dariahTeach is an European based Open Education Resources (OER) platform for the digital arts and humanities. The target audience for this platform is higher education teachers, who can embed existing content or create new content for courses and learners, especially those who do not have access to formal courses or training. For European students working toward a degree, #dariahTeach is compliant with the European Credit Transfer and Accumulation System (ECTS), which enables students to accumulate credits from different universities in different countries. #dariahTeach promotes sharing and reuse, in order to develop a place for publishing and teaching material

Tilt West

Tilt West is a Denver-based non-profit that engages in publication activities as well as hosting community round tables. The board members are supported by a team from the region's budding arts and culture community. Founded to “elevate, amplify, and support the growing arts and culture scene in Colorado,” Tilt West believes in the essential role of critical discourse in supporting a healthy artistic ecosystem. Tilt West Journal is a manifestation of this goal and is complimented by open invitation community talks

Saturation of the magnetorotational instability in the unstratified shearing box with zero net flux: convergence in taller boxes

Previous studies of the non-linear regime of the magnetorotational instability in one particular type of shearing box model - unstratified with no net magnetic flux - find that without explicit dissipation (viscosity and resistivity) the saturation amplitude decreases with increasing numerical resolution. We show that this result is strongly dependent on the vertical aspect ratio of the computational domain Lz/Lx. When Lz/Lx ≲ 1, we recover previous results. However when the vertical domain is extended Lz/Lx ≳ 2.5, we find the saturation level of the stress is greatly increased (giving a ratio of stress to pressure α ≳ 0.1), and moreover the results are independent of numerical resolution. Consistent with previous results, we find that saturation of the magnetorotational (MRI) in this regime is controlled by a cyclic dynamo which generates patches of strong toroidal field that switches sign on scales of Lx in the vertical direction. We speculate that when Lz/Lx ≲ 1, the dynamo is inhibited by the small size of the vertical domain, leading to the puzzling dependence of saturation amplitude on resolution. We show that previous toy models developed to explain the MRI dynamo are consistent with our results and that the cyclic pattern of toroidal fields observed in stratified shearing box simulations (leading to the so-called butterfly diagram) may also be related. In tall boxes the saturation amplitude is insensitive to whether or not explicit dissipation is included in the calculations at least for large magnetic Reynolds and Prandtl number. Finally, we show MRI turbulence in tall domains has a smaller critical Pmc, and an extended lifetime compared to Lz/Lx ≲ 1 boxes

Open-World Object Manipulation using Pre-trained Vision-Language Models

For robots to follow instructions from people, they must be able to connect the rich semantic information in human vocabulary, e.g. "can you get me the pink stuffed whale?" to their sensory observations and actions. This brings up a notably difficult challenge for robots: while robot learning approaches allow robots to learn many different behaviors from first-hand experience, it is impractical for robots to have first-hand experiences that span all of this semantic information. We would like a robot's policy to be able to perceive and pick up the pink stuffed whale, even if it has never seen any data interacting with a stuffed whale before. Fortunately, static data on the internet has vast semantic information, and this information is captured in pre-trained vision-language models. In this paper, we study whether we can interface robot policies with these pre-trained models, with the aim of allowing robots to complete instructions involving object categories that the robot has never seen first-hand. We develop a simple approach, which we call Manipulation of Open-World Objects (MOO), which leverages a pre-trained vision-language model to extract object-identifying information from the language command and image, and conditions the robot policy on the current image, the instruction, and the extracted object information. In a variety of experiments on a real mobile manipulator, we find that MOO generalizes zero-shot to a wide range of novel object categories and environments. In addition, we show how MOO generalizes to other, non-language-based input modalities to specify the object of interest such as finger pointing, and how it can be further extended to enable open-world navigation and manipulation. The project's website and evaluation videos can be found at https://robot-moo.github.io/Comment: Accepted at the 7th Conference on Robot Learning (CoRL 2023

Parameterization of single-scattering albedo (SSA) and absorption Ångström exponent (AAE) with EC/OC for aerosol emissions from biomass burning

Single-scattering albedo (SSA) and absorption Ångström exponent (AAE) are two critical parameters in determining the impact of absorbing aerosol on the Earth\u27s radiative balance. Aerosol emitted by biomass burning represent a significant fraction of absorbing aerosol globally, but it remains difficult to accurately predict SSA and AAE for biomass burning aerosol. Black carbon (BC), brown carbon (BrC), and non-absorbing coatings all make substantial contributions to the absorption coefficient of biomass burning aerosol. SSA and AAE cannot be directly predicted based on fuel type because they depend strongly on burn conditions. It has been suggested that SSA can be effectively parameterized via the modified combustion efficiency (MCE) of a biomass burning event and that this would be useful because emission factors for CO and CO2, from which MCE can be calculated, are available for a large number of fuels. Here we demonstrate, with data from the FLAME-4 experiment, that for a wide variety of globally relevant biomass fuels, over a range of combustion conditions, parameterizations of SSA and AAE based on the elemental carbon (EC) to organic carbon (OC) mass ratio are quantitatively superior to parameterizations based on MCE. We show that the EC/OC ratio and the ratio of EC/(EC + OC) both have significantly better correlations with SSA than MCE. Furthermore, the relationship of EC/(EC + OC) with SSA is linear. These improved parameterizations are significant because, similar to MCE, emission factors for EC (or black carbon) and OC are available for a wide range of biomass fuels. Fitting SSA with MCE yields correlation coefficients (Pearson\u27s r) of ∼0.65 at the visible wavelengths of 405, 532, and 660 nm while fitting SSA with EC/OC or EC/(EC + OC) yields a Pearson\u27s r of 0.94-0.97 at these same wavelengths. The strong correlation coefficient at 405 nm (r = 0.97) suggests that parameterizations based on EC/OC or EC/(EC + OC) have good predictive capabilities even for fuels in which brown carbon absorption is significant. Notably, these parameterizations are effective for emissions from Indonesian peat, which have very little black carbon but significant brown carbon (SSA = 0.990 ± 0.001 at 532 and 660 nm, SSA = 0.937 ± 0.011 at 405 nm). Finally, we demonstrate that our parameterization based on EC/(EC + OC) accurately predicts SSA during the first few hours of plume aging with data from Yokelson et al. (2009) gathered during a biomass burning event in the Yucatán Peninsula of Mexico