Building a Stronger Regional Safety Net: Philanthropy's Role

Examines nonprofit organizations' capacity to serve the fast-growing low-income suburban populations in the Atlanta, Chicago, Denver, and Detroit areas and local philanthropic communities' strategies for boosting regional service capacity

Optimal discrimination of single-qubit mixed states

We consider the problem of minimum-error quantum state discrimination for single-qubit mixed states. We present a method which uses the Helstrom conditions constructively and analytically; this algebraic approach is complementary to existing geometric methods, and solves the problem for any number of arbitrary signal states with arbitrary prior probabilities.Comment: 8 pages, 1 figur

Optimal sequential measurements for bipartite state discrimination

State discrimination is a useful test problem with which to clarify the power and limitations of different classes of measurement. We consider the problem of discriminating between given states of a bipartite quantum system via sequential measurement of the subsystems, with classical feed-forward of measurement results. Our aim is to understand when sequential measurements, which are relatively easy to implement experimentally, perform as well, or almost as well, as optimal joint measurements, which are in general more technologically challenging. We construct conditions that the optimal sequential measurement must satisfy, analogous to the well-known Helstrom conditions for minimum error discrimination in the unrestricted case. We give several examples and compare the optimal probability of correctly identifying the state via global versus sequential measurement strategies

Harbour porpoises (Phocoena phocoena) and minke whales (Balaenoptera acutorostrata) observed during land-based surveys in The Minch, north-west Scotland

Peer reviewedPublisher PD

Learnersourcing Subgoal Labels for How-to Videos

Websites like YouTube host millions of how-to videos, but the interfaces are not optimized for learning. Previous research suggests that users learn more from how-to videos when the information from the video is presented in outline form, with individual steps and labels for groups of steps (subgoals) shown. We envision an alternative video player where the steps and subgoals are displayed alongside the video. To generate this information for existing videos, we propose a learnersourcing approach, where people actively learning from a video provide such information. To demonstrate this method, we created a workflow where learners contribute and refine subgoal labels for how-to videos. We deployed a live website with our workflow implemented on a set of introductory web programming videos. For the four videos with the highest participation, we found that a majority of learner-generated subgoals were comparable in quality to expert-generated ones. Learners commented that the system helped them grasp the material, suggesting that our workflow did not detract from the learning experience.Massachusetts Institute of Technology. Undergraduate Research Opportunities ProgramCisco Systems, Inc.Quanta Computer (Firm) (Qmulus Project)National Science Foundation (U.S.) (Award SOCS-1111124)Alfred P. Sloan Foundation (Sloan Research Fellowship)Samsung (Firm) (Fellowship

Crowdsourcing step-by-step information extraction to enhance existing how-to videos

Millions of learners today use how-to videos to master new skills in a variety of domains. But browsing such videos is often tedious and inefficient because video player interfaces are not optimized for the unique step-by-step structure of such videos. This research aims to improve the learning experience of existing how-to videos with step-by-step annotations. We first performed a formative study to verify that annotations are actually useful to learners. We created ToolScape, an interactive video player that displays step descriptions and intermediate result thumbnails in the video timeline. Learners in our study performed better and gained more self-efficacy using ToolScape versus a traditional video player. To add the needed step annotations to existing how-to videos at scale, we introduce a novel crowdsourcing workflow. It extracts step-by-step structure from an existing video, including step times, descriptions, and before and after images. We introduce the Find-Verify-Expand design pattern for temporal and visual annotation, which applies clustering, text processing, and visual analysis algorithms to merge crowd output. The workflow does not rely on domain-specific customization, works on top of existing videos, and recruits untrained crowd workers. We evaluated the workflow with Mechanical Turk, using 75 cooking, makeup, and Photoshop videos on YouTube. Results show that our workflow can extract steps with a quality comparable to that of trained annotators across all three domains with 77% precision and 81% recall

Decreases in Antimicrobial Use Associated With Multihospital Implementation of Electronic Antimicrobial Stewardship Tools.

BackgroundAntimicrobial stewards may benefit from comparative data to inform interventions that promote optimal inpatient antimicrobial use.MethodsAntimicrobial stewards from 8 geographically dispersed Veterans Affairs (VA) inpatient facilities participated in the development of antimicrobial use visualization tools that allowed for comparison to facilities of similar complexity. The visualization tools consisted of an interactive web-based antimicrobial dashboard and, later, a standardized antimicrobial usage report updated at user-selected intervals. Stewards participated in monthly learning collaboratives. The percent change in average monthly antimicrobial use (all antimicrobial agents, anti-methicillin-resistant Staphylococcus aureus [anti-MRSA] agents, and antipseudomonal agents) was analyzed using a pre-post (January 2014-January 2016 vs July 2016-January 2018) design with segmented regression and external comparison with uninvolved control facilities (n = 118).ResultsIntervention sites demonstrated a 2.1% decrease (95% confidence interval [CI], -5.7% to 1.6%) in total antimicrobial use pre-post intervention vs a 2.5% increase (95% CI, 0.8% to 4.1%) in nonintervention sites (absolute difference, 4.6%; P = .025). Anti-MRSA antimicrobial use decreased 11.3% (95% CI, -16.0% to -6.3%) at intervention sites vs a 6.6% decrease (95% CI, -9.1% to -3.9%) at nonintervention sites (absolute difference, 4.7%; P = .092). Antipseudomonal antimicrobial use decreased 3.4% (95% CI, -8.2% to 1.7%) at intervention sites vs a 3.6% increase (95% CI, 0.8% to 6.5%) at nonintervention sites (absolute difference, 7.0%; P = .018).ConclusionsComparative data visualization tool use by stewards at 8 VA facilities was associated with significant reductions in overall antimicrobial and antipseudomonal use relative to uninvolved facilities

Policy Feedback and the Politics of the Affordable Care Act

There is a large body of literature devoted to how “policies create politics” and how feedback effects from existing policy legacies shape potential reforms in a particular area. Although much of this literature focuses on self‐reinforcing feedback effects that increase support for existing policies over time, Kent Weaver and his colleagues have recently drawn our attention to self‐undermining effects that can gradually weaken support for such policies. The following contribution explores both self‐reinforcing and self‐undermining policy feedback in relationship to the Affordable Care Act, the most important health‐care reform enacted in the United States since the mid‐1960s. More specifically, the paper draws on the concept of policy feedback to reflect on the political fate of the ACA since its adoption in 2010. We argue that, due in part to its sheer complexity and fragmentation, the ACA generates both self‐reinforcing and self‐undermining feedback effects that, depending of the aspect of the legislation at hand, can either facilitate or impede conservative retrenchment and restructuring. Simultaneously, through a discussion of partisan effects that shape Republican behavior in Congress, we acknowledge the limits of policy feedback in the explanation of policy stability and change

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy