161 research outputs found

    Urban planning law in Liberia: the case for a transformational approach

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    This article discusses the need for a fundamental rethinking of urban planning in Liberia with special reference to Monrovia, the capital. Liberia is a post-conflict country and is facing a multitude of problems. One is the very rapid urbanisation of the country. Well over 50% of the population live in urban areas, and over one million people—one third of the population—live in Monrovia, for the most part in informal ‘illegal’ settlements with few facilities. Despite land issues being acknowledged as in need of being tackled as a matter of urgency, little has been done by the Johnson-Sirleaf government since it came to power in 2006. What is needed and what this article argues for is a plan for the development of Monrovia based on the Right to the City with residents given clear rights to land and to participate in the governance of their city. The approach is denominated as a transformational one, taking its inspiration from van der Walt’s approach set out in his Property in the Margins. The need for and the outline of an Urban Transformation Act are set out in the article which concludes with a warning that it cannot be supposed that the residents of Monrovia will continue indefinitely to put up with their very poor living conditions

    A case study of a new tool to identify good performing pavements in New Zealand

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    With the advancement of digital technology, the collection of pavement performance data has become commonplace. The improvement of tools to extract useful information from pavement databases has become a priority to justify expenditures. This paper presents a case study of PaveMD, a tool that integrates multi-dimensional data structures with a data-driven fuzzy approach to identify good performing pavement sections. Combining this tool with an innovative paradigm where the focus is on repeating success can bring additional value to existing pavement databases. The case study shows that PaveMD can identify pavement sections that are performing well by comparing performance measures for the New Zealand context. In this paper, PaveMD's development is described, and its implementation is showcased using data from the New Zealand Long-Term Pavement Performance (LTPP) database. It is recommended that this approach be further developed and extended to other infrastructure databases internationally

    Assessing Levels of Attention Using Low Cost Eye Tracking

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    The emergence of mobile eye trackers embedded in next generation smartphones or VR displays will make it possible to trace not only what objects we look at but also the level of attention in a given situation. Exploring whether we can quantify the engagement of a user interacting with a laptop, we apply mobile eye tracking in an in-depth study over 2 weeks with nearly 10.000 observations to assess pupil size changes, related to attentional aspects of alertness, orientation and conflict resolution. Visually presenting conflicting cues and targets we hypothesize that it's feasible to measure the allocated effort when responding to confusing stimuli. Although such experiments are normally carried out in a lab, we are able to differentiate between sustained alertness and complex decision making even with low cost eye tracking "in the wild". From a quantified self perspective of individual behavioral adaptation, the correlations between the pupil size and the task dependent reaction time and error rates may longer term provide a foundation for modifying smartphone content and interaction to the users perceived level of attention.Comment: 12 pages, 6 figures, 2 tables. The final publication will be available at Springer via http://dx.doi.org/DOIxxx, when published as part of the HCI International 2016 Conference Proceeding

    Recognizing Intimate Partner Violence in Primary Care: Western Cape, South Africa

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    Introduction: Interpersonal violence in South Africa is the second highest contributor to the burden of disease after HIV/ AIDS and 62 % is estimated to be from intimate partner violence (IPV). This study aimed to evaluate how women experiencing IPV present in primary care, how often IPV is recognized by health care practitioners and what other diagnoses are made. Methods: At two urban and three rural community health centres, health practitioners were trained to screen all women fo

    A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic

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    This study presents two simulation modelling tools to support the organisation of networks of dialysis services during the COVID-19 pandemic. These tools were developed to support renal services in the South of England (the Wessex region caring for 650 dialysis patients), but are applicable elsewhere. A discrete-event simulation was used to model a worst case spread of COVID-19, to stress-test plans for dialysis provision throughout the COVID-19 outbreak. We investigated the ability of the system to manage the mix of COVID-19 positive and negative patients, the likely effects on patients, outpatient workloads across all units, and inpatient workload at the centralised COVID-positive inpatient unit. A second Monte-Carlo vehicle routing model estimated the feasibility of patient transport plans. If current outpatient capacity is maintained there is sufficient capacity in the South of England to keep COVID-19 negative/recovered and positive patients in separate sessions, but rapid reallocation of patients may be needed. Outpatient COVID-19 cases will spillover to a secondary site while other sites will experience a reduction in workload. The primary site chosen to manage infected patients will experience a significant increase in outpatients and inpatients. At the peak of infection, it is predicted there will be up to 140 COVID-19 positive patients with 40 to 90 of these as inpatients, likely breaching current inpatient capacity. Patient transport services will also come under considerable pressure. If patient transport operates on a policy of one positive patient at a time, and two-way transport is needed, a likely scenario estimates 80 ambulance drive time hours per day (not including fixed drop-off and ambulance cleaning times). Relaxing policies on individual patient transport to 2-4 patients per trip can save 40-60% of drive time. In mixed urban/rural geographies steps may need to be taken to temporarily accommodate renal COVID-19 positive patients closer to treatment facilities.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.This article presents independent research funded by the National Institute for Health Research (NIHR) Applied Research Collaboration (ARC) South West Peninsula (MA, SL). The views expressed in this publication are those of the author(s) and not necessarily those of the National Health Service, the NIHR or the Department of Health and Social Care. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

    Frequent new particle formation over the high Arctic pack ice by enhanced iodine emissions

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    In the central Arctic Ocean the formation of clouds and their properties are sensitive to the availability of cloud condensation nuclei (CCN). The vapors responsible for new particle formation (NPF), potentially leading to CCN, have remained unidentified since the first aerosol measurements in 1991. Here, we report that all the observed NPF events from the Arctic Ocean 2018 expedition are driven by iodic acid with little contribution from sulfuric acid. Iodic acid largely explains the growth of ultrafine particles (UFP) in most events. The iodic acid concentration increases significantly from summer towards autumn, possibly linked to the ocean freeze-up and a seasonal rise in ozone. This leads to a one order of magnitude higher UFP concentration in autumn. Measurements of cloud residuals suggest that particles smaller than 30 nm in diameter can activate as CCN. Therefore, iodine NPF has the potential to influence cloud properties over the Arctic Ocean

    Farseer-NMR: automatic treatment, analysis and plotting of large, multi-variable NMR data

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    We present Farseer-NMR (https://git.io/vAueU), a software package to treat, evaluate and combine NMR spectroscopic data from sets of protein-derived peaklists covering a range of experimental conditions. The combined advances in NMR and molecular biology enable the study of complex biomolecular systems such as flexible proteins or large multibody complexes, which display a strong and functionally relevant response to their environmental conditions, e.g. the presence of ligands, site-directed mutations, post translational modifications, molecular crowders or the chemical composition of the solution. These advances have created a growing need to analyse those systems’ responses to multiple variables. The combined analysis of NMR peaklists from large and multivariable datasets has become a new bottleneck in the NMR analysis pipeline, whereby information-rich NMR-derived parameters have to be manually generated, which can be tedious, repetitive and prone to human error, or even unfeasible for very large datasets. There is a persistent gap in the development and distribution of software focused on peaklist treatment, analysis and representation, and specifically able to handle large multivariable datasets, which are becoming more commonplace. In this regard, Farseer-NMR aims to close this longstanding gap in the automated NMR user pipeline and, altogether, reduce the time burden of analysis of large sets of peaklists from days/weeks to seconds/minutes. We have implemented some of the most common, as well as new, routines for calculation of NMR parameters and several publication-quality plotting templates to improve NMR data representation. Farseer-NMR has been written entirely in Python and its modular code base enables facile extension

    Social, Structural and Behavioral Determinants of Overall Health Status in a Cohort of Homeless and Unstably Housed HIV-Infected Men

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    Background: Previous studies indicate multiple influences on the overall health of HIV-infected persons; however, few assess and rank longitudinal changes in social and structural barriers that are disproportionately found in impoverished populations. We empirically ranked factors that longitudinally impact the overall health status of HIV-infected homeless and unstably housed men. Methods and Findings: Between 2002 and 2008, a cohort of 288 HIV+ homeless and unstably housed men was recruited and followed over time. The population was 60 % non-Caucasian and the median age was 41 years; 67 % of study participants reported recent drug use and 20 % reported recent homelessness. At baseline, the median CD4 cell count was 349 cells/ml and 18 % of eligible persons (CD4,350) took antiretroviral therapy (ART). Marginal structural models were used to estimate the population-level effects of behavioral, social, and structural factors on overall physical and mental health status (measured by the SF-36), and targeted variable importance (tVIM) was used to empirically rank factors by their influence. After adjusting for confounding, and in order of their influence, the three factors with the strongest negative effects on physical health were unmet subsistence needs, Caucasian race, and no reported source of instrumental support. The three factors with the strongest negative effects on mental health were unmet subsistence needs, not having a close friend/confidant, and drug use. ART adherence.90 % ranked 5th for its positive influence on mental health, and viral loa
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