Access 3 project protocol: Young people and health system navigation in the digital age: A multifaceted, mixed methods study

© 2017 Article author(s). Background: The integration of digital technology into everyday lives of young people has become widespread. It is not known whether and how technology influences barriers and facilitators to healthcare, and whether and how young people navigate between face-to-face and virtual healthcare. To provide new knowledge essential to policy and practice, we designed a study that would explore health system access and navigation in the digital age. The study objectives are to: (1) describe experiences of young people accessing and navigating the health system in New South Wales (NSW), Australia; (2) identify barriers and facilitators to healthcare for young people and how these vary between groups; (3) describe health system inefficiencies, particularly for young people who are marginalised; (4) provide policy-relevant knowledge translation of the research data. Methods and analysis: This mixed methods study has four parts, including: (1) a cross-sectional survey of young people (12-24 years) residing in NSW, Australia; (2) a longitudinal, qualitative study of a subsample of marginalised young people (defined as young people who: identify as Aboriginal and/or Torres Strait Islander; are experiencing homelessness; identify as sexuality and/or gender diverse; are of refugee or vulnerable migrant background; and/or live in rural or remote NSW); (3) interviews with professionals; (4) a knowledge translation forum. Ethics and dissemination: Ethics approvals were sought and granted. Data collection commenced in March 2016 and will continue until June 2017. This study will gather practice and policy-relevant intelligence about contemporary experiences of young people and health services, with a unique focus on five different groups of marginalised young people, documenting their experiences over time. Access 3 will explore navigation around all levels of the health system, determine whether digital technology is integrated into this, and if so how, and will translate findings into policy-relevant recommendations

Real Time Global Tests of the ALICE High Level Trigger Data Transport Framework

The High Level Trigger (HLT) system of the ALICE experiment is an online event filter and trigger system designed for input bandwidths of up to 25 GB/s at event rates of up to 1 kHz. The system is designed as a scalable PC cluster, implementing several hundred nodes. The transport of data in the system is handled by an object-oriented data flow framework operating on the basis of the publisher-subscriber principle, being designed fully pipelined with lowest processing overhead and communication latency in the cluster. In this paper, we report the latest measurements where this framework has been operated on five different sites over a global north-south link extending more than 10,000 km, processing a ``real-time'' data flow.Comment: 8 pages 4 figure

Intersectionality: Social Marginalisation and Self-Reported Health Status in Young People.

BACKGROUND:The aim of this study was to measure young people's health status and explore associations between health status and belonging to one or more socio-culturally marginalised group. METHODS:part of the Access 3 project, this cross-sectional survey of young people aged 12-24 years living in New South Wales, Australia, oversampled young people from one or more of the following groups: Aboriginal and or Torres Strait Islander; living in rural and remote areas; homeless; refugee; and/or, sexuality and/or gender diverse. This paper reports on findings pertaining to health status, presence of chronic health conditions, psychological distress, and wellbeing measures. RESULTS:1416 participants completed the survey; 897 (63.3%) belonged to at least one marginalised group; 574 (40.5%) to one, 281 (19.8%) to two and 42 (3.0%) to three or four groups. Belonging to more marginalised groups was significantly associated with having more chronic health conditions (p = 0.001), a greater likelihood of high psychological distress (p = 0.001) and of illness or injury related absence from school or work (p < 0.05). CONCLUSIONS:increasing marginalisation is associated with decreasing health status. Using an intersectional lens can to be a useful way to understand disadvantage for young people belonging to multiple marginalised groups

Building evidence into youth health policy: a case study of the Access 3 knowledge translation forum.

BACKGROUND: Effective integration of evidence and youth perspectives into policy is crucial for supporting the future health and well-being of young people. The aim of this project was to translate evidence from the Access 3 project to support development of a new state policy on youth health and well-being within New South Wales (NSW), Australia. Ensuring the active contribution of young people within policy development was a key objective of the knowledge translation (KT) process. METHODS: The KT activity consisted of a 1-day facilitated forum with 64 purposively sampled stakeholders. Participants included eight young people, 14 policy-makers, 15 academics, 22 clinicians or managers from NSW health services, four general practitioners and one mental health service worker. Research to be translated came from the synthesized findings of the NSW Access 3 project. The design of the forum included stakeholder presentations and group workshops, guided by the 2003 Lavis et al. KT framework that was improved by the Grimshaw et al. KT framework in 2012. Members of the Access 3 research team took on the role of knowledge brokers throughout the KT process. Participant satisfaction with the workshop was evaluated using a brief self-report survey. Policy uptake was determined through examination of the subsequent NSW Youth Health Framework 2017-2024. RESULTS: A total of 25 policy recommendations were established through the workshop, and these were grouped into six themes that broadly aligned with the synthesized findings from the Access 3 project. The six policy themes were (1) technology solutions, (2) integrated care and investment to build capacity, (3) adolescent health checks, (4) workforce, (5) youth participation and (6) youth health indicators. Forum members were asked to vote on the importance of individual recommendations. These policy recommendations were subsequently presented to the NSW Ministry of Health, with some evidence of policy uptake identified. The majority of participants rated the forum positively. CONCLUSIONS: The utilization of KT theories and active youth engagement led to the successful translation of research evidence and youth perspectives into NSW youth health policy. Future research should examine the implementation of policy arising from these KT efforts

Calculation of magnetic anisotropy energy in SmCo5

SmCo5 is an important hard magnetic material, due to its large magnetic anisotropy energy (MAE). We have studied the magnetic properties of SmCo5 using density functional theory (DFT) calculations where the Sm f-bands, which are difficult to include in DFT calculations, have been treated within the LDA+U formalism. The large MAE comes mostly from the Sm f-shell anisotropy, stemming from an interplay between the crystal field and the spin-orbit coupling. We found that both are of similar strengths, unlike some other Sm compounds, leading to a partial quenching of the orbital moment (f-states cannot be described as either pure lattice harmonics or pure complex harmonics), an optimal situation for enhanced MAE. A smaller portion of the MAE can be associated with the Co-d band anisotropy, related to the peak in the density of states at the Fermi energy. Our result for the MAE of SmCo5, 21.6 meV/f.u., agrees reasonably with the experimental value of 13-16 meV/f.u., and the calculated magnetic moment (including the orbital component) of 9.4 mu_B agrees with the experimental value of 8.9 mu_B.Comment: Submitted to Phys. Rev.

KNIME-CDK: Workflow-driven cheminformatics

BACKGROUND: Cheminformaticians have to routinely process and analyse libraries of small molecules. Among other things, that includes the standardization of molecules, calculation of various descriptors, visualisation of molecular structures, and downstream analysis. For this purpose, scientific workflow platforms such as the Konstanz Information Miner can be used if provided with the right plug-in. A workflow-based cheminformatics tool provides the advantage of ease-of-use and interoperability between complementary cheminformatics packages within the same framework, hence facilitating the analysis process. RESULTS: KNIME-CDK comprises functions for molecule conversion to/from common formats, generation of signatures, fingerprints, and molecular properties. It is based on the Chemistry Development Toolkit and uses the Chemical Markup Language for persistence. A comparison with the cheminformatics plug-in RDKit shows that KNIME-CDK supports a similar range of chemical classes and adds new functionality to the framework. We describe the design and integration of the plug-in, and demonstrate the usage of the nodes on ChEBI, a library of small molecules of biological interest. CONCLUSIONS: KNIME-CDK is an open-source plug-in for the Konstanz Information Miner, a free workflow platform. KNIME-CDK is build on top of the open-source Chemistry Development Toolkit and allows for efficient cross-vendor structural cheminformatics. Its ease-of-use and modularity enables researchers to automate routine tasks and data analysis, bringing complimentary cheminformatics functionality to the workflow environment

Many-body GW calculations of ground-state properties: Quasi-2D electron systems and van der Waals forces

We present GW many-body results for ground-state properties of two simple but very distinct families of inhomogeneous systems in which traditional implementations of density-functional theory (DFT) fail drastically. The GW approach gives notably better results than the well-known random-phase approximation, at a similar computational cost. These results establish GW as a superior alternative to standard DFT schemes without the expensive numerical effort required by quantum Monte Carlo simulations

Diagrammatic self-energy approximations and the total particle number

There is increasing interest in many-body perturbation theory as a practical tool for the calculation of ground-state properties. As a consequence, unambiguous sum rules such as the conservation of particle number under the influence of the Coulomb interaction have acquired an importance that did not exist for calculations of excited-state properties. In this paper we obtain a rigorous, simple relation whose fulfilment guarantees particle-number conservation in a given diagrammatic self-energy approximation. Hedin's G(0)W(0) approximation does not satisfy this relation and hence violates the particle-number sum rule. Very precise calculations for the homogeneous electron gas and a model inhomogeneous electron system allow the extent of the nonconservation to be estimated

Self-consistent calculation of total energies of the electron gas using many-body perturbation theory

The performance of many-body perturbation theory for calculating ground-state properties is investigated. We present fully numerical results for the electron gas in three and two dimensions in the framework of the GW approximation. The overall agreement with very accurate Monte Carlo data is excellent, even for those ranges of densities for which the GW approach is often supposed to be unsuitable. The latter seems to be due to the fulfillment of general conservation rules. These results open further prospects for accurate calculations of ground-state properties circumventing the limitations of standard density-functional theory

Self-organizing ontology of biochemically relevant small molecules

<p>Abstract</p> <p>Background</p> <p>The advent of high-throughput experimentation in biochemistry has led to the generation of vast amounts of chemical data, necessitating the development of novel analysis, characterization, and cataloguing techniques and tools. Recently, a movement to publically release such data has advanced biochemical structure-activity relationship research, while providing new challenges, the biggest being the curation, annotation, and classification of this information to facilitate useful biochemical pattern analysis. Unfortunately, the human resources currently employed by the organizations supporting these efforts (e.g. ChEBI) are expanding linearly, while new useful scientific information is being released in a seemingly exponential fashion. Compounding this, currently existing chemical classification and annotation systems are not amenable to automated classification, formal and transparent chemical class definition axiomatization, facile class redefinition, or novel class integration, thus further limiting chemical ontology growth by necessitating human involvement in curation. Clearly, there is a need for the automation of this process, especially for novel chemical entities of biological interest.</p> <p>Results</p> <p>To address this, we present a formal framework based on Semantic Web technologies for the automatic design of chemical ontology which can be used for automated classification of novel entities. We demonstrate the automatic self-assembly of a structure-based chemical ontology based on 60 MeSH and 40 ChEBI chemical classes. This ontology is then used to classify 200 compounds with an accuracy of 92.7%. We extend these structure-based classes with molecular feature information and demonstrate the utility of our framework for classification of functionally relevant chemicals. Finally, we discuss an iterative approach that we envision for future biochemical ontology development.</p> <p>Conclusions</p> <p>We conclude that the proposed methodology can ease the burden of chemical data annotators and dramatically increase their productivity. We anticipate that the use of formal logic in our proposed framework will make chemical classification criteria more transparent to humans and machines alike and will thus facilitate predictive and integrative bioactivity model development.</p