Sharing Mobility Data for Planning and Policy Research

A California Public Utilities Commission (CPUC) rulemaking and possible legislative action in 2020 could affect data sharing requirements, with implications for shared mobility providers. The purpose of this brief is to inform this regulatory and legislative decision-making. We solicited policy and planning questions and data needs for shared mobility from within the University of California Institute of Transportation Studies research network. We defined shared mobility as including shared mobility devices, such as e-bikes and e-scooters, and transportation network companies (TNCs). We evaluated whether data shared in accordance with each of six mobility data specifications could be used to support analyses that would answer these questions. We then defined three approaches to data sharing and analysis to address these and other questions, presenting the advantages and disadvantages of each. This brief does not address the full breadth of the questions raised in the CPUC rulemaking nor does it introduce the complexities of this topic. Beyond the scope of this brief are issues of user privacy, the legal authority for sharing data, and contractual or requirements for each possible model of data sharing and analysis

An institutional framework to guide the comparison of work-integrated learning

Work-based placements, site visits, field trips and embedded industry-informed curriculum are employability strategies frequently applied by universities, and clustered under the umbrella term – work-integrated learning (WIL). Referring to each of these strategies as WIL can complicate comparisons (e.g. long-term placements vs. field trips) and can lead WIL related research to diverge in multiple directions. To support comparison and help guide institutional decision-making relating to WIL, the positioning of this article aligns with a recent stream of literature that attempts to outline, contrast and differentiate between various activities aimed at enhancing graduate employability. Four distinct WIL case studies from three Australian universities are described in this article: (a) students working in teams with industry partners (n=23), (b) students co-creating learning resources (n=7), (c) a student-staff partnership (n=2), and (d) students acting as peer-learning advisors (n=5). The cases were considered across five key factors: 1) ease of implementation, 2) barriers, 3) scalability, 4) authenticity, and 5) proximity. Using empirical data, the findings within the article contribute an institutional framework that highlights the benefits and drawbacks associated with differences across WIL types, intended to support good WIL practice among administrators, teachers and staff

Outlier detection for multivariate categorical data

This is an Accepted Manuscript of an article published by Taylor & Francis in “ Quality and Reliability Engineering International ” on 06th June 2018, available online: https://onlinelibrary.wiley.com/doi/abs/10.1002/qre.2339The detection of outlying rows in a contingency table is tackled from a Bayesian perspective, by adapting the framework adopted by Box and Tiao for normal models to multinomial models with random effects. The solution assumes a 2–component mixture model of 2 multinomial continuous mixtures for them, one for the nonoutlier rows and the second one for the outlier rows. The method starts by estimating the distributional characteristics of nonoutlier rows, and then it does cluster analysis to identify which rows belong to the outlier group and which do not. The method applies to any type of contingency table, and in particular, it could be used on the analysis of multivariate categorical control charts. Here, the use of the method is illustrated through a simulated example and by applying it to help identify heterogeneities of style among the acts in the plays of the First Folio edition of Shakespeare dramaPeer ReviewedPostprint (author's final draft

Social Deprivation, Inequality, and the Neighborhood-Level Incidence of Psychotic Syndromes in East London

licenses/by-nc/3.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited

Post-intervention Status in Patients With Refractory Myasthenia Gravis Treated With Eculizumab During REGAIN and Its Open-Label Extension

OBJECTIVE: To evaluate whether eculizumab helps patients with anti-acetylcholine receptor-positive (AChR+) refractory generalized myasthenia gravis (gMG) achieve the Myasthenia Gravis Foundation of America (MGFA) post-intervention status of minimal manifestations (MM), we assessed patients' status throughout REGAIN (Safety and Efficacy of Eculizumab in AChR+ Refractory Generalized Myasthenia Gravis) and its open-label extension. METHODS: Patients who completed the REGAIN randomized controlled trial and continued into the open-label extension were included in this tertiary endpoint analysis. Patients were assessed for the MGFA post-intervention status of improved, unchanged, worse, MM, and pharmacologic remission at defined time points during REGAIN and through week 130 of the open-label study. RESULTS: A total of 117 patients completed REGAIN and continued into the open-label study (eculizumab/eculizumab: 56; placebo/eculizumab: 61). At week 26 of REGAIN, more eculizumab-treated patients than placebo-treated patients achieved a status of improved (60.7% vs 41.7%) or MM (25.0% vs 13.3%; common OR: 2.3; 95% CI: 1.1-4.5). After 130 weeks of eculizumab treatment, 88.0% of patients achieved improved status and 57.3% of patients achieved MM status. The safety profile of eculizumab was consistent with its known profile and no new safety signals were detected. CONCLUSION: Eculizumab led to rapid and sustained achievement of MM in patients with AChR+ refractory gMG. These findings support the use of eculizumab in this previously difficult-to-treat patient population. CLINICALTRIALSGOV IDENTIFIER: REGAIN, NCT01997229; REGAIN open-label extension, NCT02301624. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that, after 26 weeks of eculizumab treatment, 25.0% of adults with AChR+ refractory gMG achieved MM, compared with 13.3% who received placebo

Minimal Symptom Expression' in Patients With Acetylcholine Receptor Antibody-Positive Refractory Generalized Myasthenia Gravis Treated With Eculizumab

The efficacy and tolerability of eculizumab were assessed in REGAIN, a 26-week, phase 3, randomized, double-blind, placebo-controlled study in anti-acetylcholine receptor antibody-positive (AChR+) refractory generalized myasthenia gravis (gMG), and its open-label extension

Mobility Data Sharing: Challenges and Policy Recommendations

Dynamic and responsive transportation systems are a core pillar of equitable and sustainable communities. Achieving such systems requires comprehensive mobility data, or data that reports the movement of individuals and vehicles. Such data enable planners and policymakers to make informed decisions and enable researchers to model the effects of various transportation solutions. However, collecting mobility data also raises concerns about privacy and proprietary interests. We argue that a middle-ground approach, in which data are shared in specific contexts and managed by a trusted third party, can capture the benefits of data sharing while minimizing risks. This brief provides an overview of the top needs and challenges surrounding mobility data sharing and presents relevant policy strategies

Sharing Mobility Data for Planning and Policy Research

A California Public Utilities Commission (CPUC) rulemaking and possible legislative action in 2020 could affect data sharing requirements, with implications for shared mobility providers. The purpose of this brief is to inform this regulatory and legislative decision-making. We solicited policy and planning questions and data needs for shared mobility from within the University of California Institute of Transportation Studies research network. We defined shared mobility as including shared mobility devices, such as e-bikes and e-scooters, and transportation network companies (TNCs). We evaluated whether data shared in accordance with each of six mobility data specifications could be used to support analyses that would answer these questions. We then defined three approaches to data sharing and analysis to address these and other questions, presenting the advantages and disadvantages of each. This brief does not address the full breadth of the questions raised in the CPUC rulemaking nor does it introduce the complexities of this topic. Beyond the scope of this brief are issues of user privacy, the legal authority for sharing data, and contractual or requirements for each possible model of data sharing and analysis