Caps, apps and other mobile traps

This report outlines the major policy and legal issues on mobile phone ownership for children and young people

Opportunities for information sharing: case studies

Personal information provided to government and non-government service providers is highly sensitive. Appropriate collection, management and storage of personal information are critical elements to citizen trust in the public sector. However, misconceptions about the frameworks governing sharing personal information can impact on the coordination of services, case management and policy development.   The NSW Department of Premier & Cabinet engaged the Social Policy Research Centre to develop three case studies that identified the challenges to sharing information appropriately, and the opportunities for better personal information sharing between government agencies and non-government organisations. Improved sharing of personal information in these areas can support more effective policy development, leading to improved service delivery performance and coordination.   The Social Policy Research Centre identified the legislative and policy framework for each case study, conducted qualitative research on the interpretation of this framework, and developed three case study reports

Session 2B Smart Cities Council: Creating an Impact Through SDG 11

Full text available. This presentation was created as a group project for my Biology of Global Change course at Boston University, where we were tasked with finding an organization that exemplified the SDG that we were assigned to. My group focused on the Smart Cities Council, a non-governmental organization that coincides with SDG 11, sustainable cities and communities

A Recommender Model for the Personalized Adaptive CHUNK Learning System

Recommender systems attempt to influence one’s behavior based on explicit and implicit information provided by the users of the system. Users who take part in e-commerce or watch cat videos online will be familiar with this concept. Different algorithms exist that determine what objects or concepts to recommend to users, but every one of them has the similar goal of providing a good recommendation. In this context, good means that the recommendation will be user relevant suggesting accurate topics, and will influence the user’s behavior. Additionally, a good recommendation system is adaptive, consistently seeking feedback from the user. Feedback is then used to make the next recommendation better. In this work, we develop a recommendation methodology for an existing personalized learning system, where both content and teaching methodology options are presented to the user. Our methodology provides solutions to both the user and the network coldstart problems, where little up-front information is available in order to make good recommendations. Using real system data, we show how our method recommends the most relevant learning topics and styles and incorporates user feedback to improve future recommendations.Do

Pharmacovigilance in hospice/palliative care: rapid report of net clinical effect of metoclopramide

Background: Understanding the performance of prescribed medications in day-to-day practice is important to minimize harm, maximize clinical benefits, and, eventually, better target the people who are most likely to benefit, especially in hospice/palliative care where there may be limited time to optimize prescribing. Metoclopramide, a benzamide prokinetic antiemetic, is widely used for a number of indications including nausea, vomiting, hiccups, and reflux. It has recently had a new ‘‘black box’’ warning issued by the Food and Drug Administration in relation to tardive dyskinesia to limit use to 12 weeks. Methods: A consecutive cohort of patients from 12 participating centers in two countries who were having metoclopramide initiated had data collected at three time points—baseline, 2 days (clinical benefit), and day 7 (clinical harm). Additionally, harms could be recorded at any time. Results: Of the 53 people included in the cohort, 23 (43%) reported benefit at 48 hours, but only 18 (34%) of these people were still using it one week after commencing it. For the other 5, the medication was ceased due to harms. The most frequent harms were akathisia (n = 4), headache (n = 4), and abdominal pain (n = 4). Nine people (17%) had no clinical benefit and experienced harms. Conclusion: Overall, one in three people gained net clinical benefit at one week. Limiting effects include sideeffects that need to be sought actively in clinical care

Patients' reports or clinicians' assessments: Which are better for prognosticating?

BACKGROUND: The Prognosis in Palliative care Scale (PiPS) predicts survival in advanced cancer patients more accurately than a doctor's or a nurse's estimate. PiPS scores are derived using observer ratings of symptom severity and performance status. The purpose of this study was to determine whether patient-rated data would provide better prognostic estimates than clinician observer ratings. PATIENTS AND METHODS: 1018 subjects with advanced cancer no longer undergoing tumour-directed therapy were recruited to a multi-centre study. Prognostic models were developed using observer ratings, patient ratings or a composite method that used patient ratings when available or else used observer ratings. The performance of the prognostic models was compared by determining the agreement between the models' predictions and the survival of study participants. RESULTS: All three approaches to model development resulted in prognostic scores that were able to differentiate between patients with a survival of 'days', 'weeks' or 'months+'. However, the observer-rated models were significantly (p<0.05) more accurate than the patient-rated models. CONCLUSIONS: A prognostic model derived using observer-rated data was more accurate at predicting survival than a similar model derived using patient self-report measures. This is clinically important because patient-rated data can be burdensome and difficult to obtain in patients with terminal illnesses

Algorithms for Olfactory Search across Species

Localizing the sources of stimuli is essential. Most organisms cannot eat, mate, or escape without knowing where the relevant stimuli originate. For many, if not most, animals, olfaction plays an essential role in search. While microorganismal chemotaxis is relatively well understood, in larger animals the algorithms and mechanisms of olfactory search remain mysterious. In this symposium, we will present recent advances in our understanding of olfactory search in flies and rodents. Despite their different sizes and behaviors, both species must solve similar problems, including meeting the challenges of turbulent airflow, sampling the environment to optimize olfactory information, and incorporating odor information into broader navigational systems

Nitric oxide biosensor uncovers diminished ferrous iron-dependency of cultured cells adapted to physiological oxygen levels

Iron is an essential metal for cellular metabolism and signaling, but it has adverse effects in excess. The physiological consequences of iron deficiency are well established, yet the relationship between iron supplementation and pericellular oxygen levels in cultured cells and their downstream effects on metalloproteins has been less explored. This study exploits the metalloprotein geNOps in cultured HEK293T epithelial and EA.hy926 endothelial cells to test the iron-dependency in cells adapted to standard room air (18 kPa O2) or physiological normoxia (5 kPa O2). We show that cells in culture require iron supplementation to activate the metalloprotein geNOps and demonstrate for the first time that cells adapted to physiological normoxia require significantly lower iron compared to cells adapted to hyperoxia. This study establishes an essential role for recapitulating oxygen levels in vivo and uncovers a previously unrecognized requirement for ferrous iron supplementation under standard cell culture conditions to achieve geNOps functionality.Integration Projects of Sabanci University ; Heart Research U.K. ; British Heart Foundation ; European Cooperation in Science and Technology (COST) ; King's Together Strategic Awar

Rapid feedback on hospital onset SARS-CoV-2 infections combining epidemiological and sequencing data.

BACKGROUND: Rapid identification and investigation of healthcare-associated infections (HCAIs) is important for suppression of SARS-CoV-2, but the infection source for hospital onset COVID-19 infections (HOCIs) cannot always be readily identified based only on epidemiological data. Viral sequencing data provides additional information regarding potential transmission clusters, but the low mutation rate of SARS-CoV-2 can make interpretation using standard phylogenetic methods difficult. METHODS: We developed a novel statistical method and sequence reporting tool (SRT) that combines epidemiological and sequence data in order to provide a rapid assessment of the probability of HCAI among HOCI cases (defined as first positive test >48 hr following admission) and to identify infections that could plausibly constitute outbreak events. The method is designed for prospective use, but was validated using retrospective datasets from hospitals in Glasgow and Sheffield collected February-May 2020. RESULTS: We analysed data from 326 HOCIs. Among HOCIs with time from admission ≥8 days, the SRT algorithm identified close sequence matches from the same ward for 160/244 (65.6%) and in the remainder 68/84 (81.0%) had at least one similar sequence elsewhere in the hospital, resulting in high estimated probabilities of within-ward and within-hospital transmission. For HOCIs with time from admission 3-7 days, the SRT probability of healthcare acquisition was >0.5 in 33/82 (40.2%). CONCLUSIONS: The methodology developed can provide rapid feedback on HOCIs that could be useful for infection prevention and control teams, and warrants further prospective evaluation. The integration of epidemiological and sequence data is important given the low mutation rate of SARS-CoV-2 and its variable incubation period. FUNDING: COG-UK HOCI funded by COG-UK consortium, supported by funding from UK Research and Innovation, National Institute of Health Research and Wellcome Sanger Institute.COG-UK HOCI funded by COG-UK consortium, supported by funding from UK Research and Innovation, National Institute of Health Research and Wellcome Sanger Institute

In Good Times and in Bad: Bank Capital Ratios and Lending Rates

This paper investigates the relationship between bank capital ratios and lending rates using data from 1998 to 2012 for 13 large banks accounting for 75% of total UK lending. We document a substantial change in the coefficient of the Tier 1 capital ratio in reduced-form regressions for secured household lending rates; the coefficient changes from positive pre-crisis to negative in crisis. Significant changes are also detected in the relationship for unsecured household and corporate lending. Such instability is difficult to reconcile with many well-established theories of financial intermediation but is consistent with the relatively recent theories of bank portfolio decisions emphasising cyclical variation in bank leverage and risk-appetite