Research Infrastructure Network Research Articles

Automatic spatial metadata systems – the case of Australian urban research infrastructure network

ABSTRACTThe increasing amount of spatial data demands effective and efficient methods for managing them in spatial data infrastructures (SDIs). Metadata standards have been developed in response to the needs of data custodians who manage these ever-growing resources and in recognition of the end users’ need for easy access and discovery of spatial data. Data custodians prepare metadata records and allow SDIs to harvest them. The harvesting can be undertaken through metadata standards or data service standards. The metadata updating processes are not efficient and, therefore, create a disjoint between the data and its metadata. As a result, end users cannot realize the full potential of metadata records. In addressing this issue, the paper presents an automatic spatial metadata system with a suite of functions including metadata monitoring, enrichment, and maintenance to enable the data custodians to manage the integrity of their metadata records in SDIs. These functions have been demonstrated and reviewed through a case study in the Australian Urban Infrastructure Network (AURIN). Using these functions, AURIN’s data custodians have been able to offer over 1200 coherent and consistent spatial metadata records to end users.

Intercomparison of 15 aerodynamic particle size spectrometers (APS 3321): uncertainties in particle sizing and number size distribution

Abstract. Aerodynamic particle size spectrometers are a well-established method to measure number size distributions of coarse mode particles in the atmosphere. Quality assurance is essential for atmospheric observational aerosol networks to obtain comparable results with known uncertainties. In a laboratory study within the framework of ACTRIS (Aerosols, Clouds, and Trace gases Research Infrastructure Network), 15 aerodynamic particle size spectrometers (APS model 3321, TSI Inc., St. Paul, MN, USA) were compared with a focus on flow rates, particle sizing, and the unit-to-unit variability of the particle number size distribution. Flow rate deviations were relatively small (within a few percent), while the sizing accuracy was found to be within 10 % compared to polystyrene latex (PSL) reference particles. The unit-to-unit variability in terms of the particle number size distribution during this study was within 10 % to 20 % for particles in the range of 0.9 up to 3 µm, which is acceptable for atmospheric measurements. For particles smaller than that, the variability increased up to 60 %, probably caused by differences in the counting efficiencies of individual units. Number size distribution data for particles smaller than 0.9 µm in aerodynamic diameter should only be used with caution. For particles larger than 3 µm, the unit-to-unit variability increased as well. A possible reason is an insufficient sizing accuracy in combination with a steeply sloping particle number size distribution and the increasing uncertainty due to decreasing counting. Particularly this uncertainty of the particle number size distribution must be considered if higher moments of the size distribution such as the particle volume or mass are calculated, which require the conversion of the aerodynamic diameter measured to a volume equivalent diameter. In order to perform a quantitative quality assurance, a traceable reference method for the particle number concentration in the size range 0.5–3 µm is needed.

An interlinked coastal observatory network for Europe

ABSTRACTExisting coastal observatories in European waters are complex systems consisting of different observational components, providing crucial operational data for assessment, model validation and assimilation purposes. However, the geographical, structural, functional and operational heterogeneities that characterise them pose an enormous challenge to their efficient exploitation as information providers on a broader, cross-border, regional scale. To address this problem, the European Union (EU) Seventh Framework Programme (FP7) Towards a Joint European Research Infrastructure Network for Coastal Observatories (JERICO) project is creating a shared, pan-European framework for the networking of such observatories, promoting the identification and dissemination of best practices for their design, implementation and maintenance, as well as common data distribution and transnational access protocols to enhance their performance and sustainability. In doing so, the project is also laying down the foundation for the coastal element of the nascent European Ocean Observing System.

The Australian Data-Driven Urban Research Platform: Systems Paper

Rapid urban growth is occurring across Australia. This has implications for planning and management of cities. Data is key to tackling this. Hitherto, an extensive range of organisations has held the data for Australian cities, crossing government, industry and academia. With the growing demand for open data and capabilities to support big data analytics, new opportunities now exist to rectify this situation. The Australian Urban Research Infrastructure Network (AURIN) project has been funded to provide seamless, secure access to data from definitive organisations of Australia. We describe the AURIN platform; it's data, together with a representative big data case study.

A European multi-language initiative to make the general population aware of independent clinical research: the European Communication on Research Awareness Need project.

BackgroundThe ECRAN (European Communication on Research Awareness Needs) project was initiated in 2012, with support from the European Commission, to improve public knowledge about the importance of independent, multinational, clinical trials in Europe.MethodsParticipants in the ECRAN consortium included clinicians and methodologists directly involved in clinical trials; researchers working in partnership with the public and patients; representatives of patients; and experts in science communication. We searched for, and evaluated, relevant existing materials and developed additional materials and tools, making them freely available under a Creative Commons licence.ResultsThe principal communication materials developed were:A website (http://ecranproject.eu) in six languages, including a Media centre section to help journalists to disseminate information about the ECRAN projectAn animated film about clinical trials, dubbed in the 23 official languages of the European Community, and an interactive tutorialAn inventory of resources, available in 23 languages, searchable by topic, author, and media typeTwo educational games for young people, developed in six languagesTesting Treatments interactive in a dozen languages, including five official European Community languagesAn interactive tutorial slide presentation testing viewers’ knowledge about clinical trialsConclusionsOver a 2-year project, our multidisciplinary and multinational consortium was able to produce, and make freely available in many languages, new materials to promote public knowledge about the importance of independent and international clinical trials. Sustained funding for the ECRAN information platform could help to promote successful recruitment to independent clinical trials supported through the European Clinical Research Infrastructure Network.

EARLINET Single Calculus Chain – overview on methodology and strategy

Abstract. In this paper we describe the EARLINET Single Calculus Chain (SCC), a tool for the automatic analysis of lidar measurements. The development of this tool started in the framework of EARLINET-ASOS (European Aerosol Research Lidar Network – Advanced Sustainable Observation System); it was extended within ACTRIS (Aerosol, Clouds and Trace gases Research InfraStructure Network), and it is continuing within ACTRIS-2. The main idea was to develop a data processing chain that allows all EARLINET stations to retrieve, in a fully automatic way, the aerosol backscatter and extinction profiles starting from the raw lidar data of the lidar systems they operate. The calculus subsystem of the SCC is composed of two modules: a pre-processor module which handles the raw lidar data and corrects them for instrumental effects and an optical processing module for the retrieval of aerosol optical products from the pre-processed data. All input parameters needed to perform the lidar analysis are stored in a database to keep track of all changes which may occur for any EARLINET lidar system over the time. The two calculus modules are coordinated and synchronized by an additional module (daemon) which makes the whole analysis process fully automatic. The end user can interact with the SCC via a user-friendly web interface. All SCC modules are developed using open-source and freely available software packages. The final products retrieved by the SCC fulfill all requirements of the EARLINET quality assurance programs on both instrumental and algorithm levels. Moreover, the manpower needed to provide aerosol optical products is greatly reduced and thus the near-real-time availability of lidar data is improved. The high-quality of the SCC products is proven by the good agreement between the SCC analysis, and the corresponding independent manual retrievals. Finally, the ability of the SCC to provide high-quality aerosol optical products is demonstrated for an EARLINET intense observation period.

EARLINET: potential operationality of a research network

Abstract. In the framework of ACTRIS (Aerosols, Clouds, and Trace Gases Research Infrastructure Network) summer 2012 measurement campaign (8 June–17 July 2012), EARLINET organized and performed a controlled exercise of feasibility to demonstrate its potential to perform operational, coordinated measurements and deliver products in near-real time. Eleven lidar stations participated in the exercise which started on 9 July 2012 at 06:00 UT and ended 72 h later on 12 July at 06:00 UT. For the first time, the single calculus chain (SCC) – the common calculus chain developed within EARLINET for the automatic evaluation of lidar data from raw signals up to the final products – was used. All stations sent in real-time measurements of a 1 h duration to the SCC server in a predefined netcdf file format. The pre-processing of the data was performed in real time by the SCC, while the optical processing was performed in near-real time after the exercise ended. 98 and 79 % of the files sent to SCC were successfully pre-processed and processed, respectively. Those percentages are quite large taking into account that no cloud screening was performed on the lidar data. The paper draws present and future SCC users' attention to the most critical parameters of the SCC product configuration and their possible optimal value but also to the limitations inherent to the raw data. The continuous use of SCC direct and derived products in heterogeneous conditions is used to demonstrate two potential applications of EARLINET infrastructure: the monitoring of a Saharan dust intrusion event and the evaluation of two dust transport models. The efforts made to define the measurements protocol and to configure properly the SCC pave the way for applying this protocol for specific applications such as the monitoring of special events, atmospheric modeling, climate research and calibration/validation activities of spaceborne observations.

A methodology for investigating dust model performance using synergistic EARLINET/AERONET dust concentration retrievals

Abstract. Systematic measurements of dust concentration profiles at a continental scale were recently made possible by the development of synergistic retrieval algorithms using combined lidar and sun photometer data and the establishment of robust remote-sensing networks in the framework of Aerosols, Clouds, and Trace gases Research InfraStructure Network (ACTRIS)/European Aerosol Research Lidar Network (EARLINET). We present a methodology for using these capabilities as a tool for examining the performance of dust transport models. The methodology includes considerations for the selection of a suitable data set and appropriate metrics for the exploration of the results. The approach is demonstrated for four regional dust transport models (BSC-DREAM8b v2, NMMB/BSC-DUST, DREAMABOL, DREAM8-NMME-MACC) using dust observations performed at 10 ACTRIS/EARLINET stations. The observations, which include coincident multi-wavelength lidar and sun photometer measurements, were processed with the Lidar-Radiometer Inversion Code (LIRIC) to retrieve aerosol concentration profiles. The methodology proposed here shows advantages when compared to traditional evaluation techniques that utilize separately the available measurements such as separating the contribution of dust from other aerosol types on the lidar profiles and avoiding model assumptions related to the conversion of concentration fields to aerosol extinction values. When compared to LIRIC retrievals, the simulated dust vertical structures were found to be in good agreement for all models with correlation values between 0.5 and 0.7 in the 1–6 km range, where most dust is typically observed. The absolute dust concentration was typically underestimated with mean bias values of -40 to -20 μg m−3 at 2 km, the altitude of maximum mean concentration. The reported differences among the models found in this comparison indicate the benefit of the systematic use of the proposed approach in future dust model evaluation studies.

A scalable Cloud-based system for data-intensive spatial analysis

Advances in Cloud computing technology and the availability of affordable and easy to use Cloud services are enabling a multitude of scientific applications to use these resources as primary or secondary computing infrastructure. The urban and built environment research domain is one area that can benefit greatly from Cloud computing. The global population growth and increase in the size and population of cities raise many challenges for governments, planners and researchers alike. The Australian Urban Research Infrastructure Network (AURIN— http://www.aurin.org.au ) project has been tasked with developing an advanced platform (e-Infrastructure) across Australia to tackle these challenges. The platform leverages large-scale Cloud resources to provide federated data access to, at present over 1100 data sets from major and often definitive government and industry data-rich organisations, and for scalable data processing and visualisation. The original AURIN tools were developed using the object modelling system (OMS) and supported integrated workflows to define and enact/re-enact scientific processes. More recently the work has evolved to focus more on delivery of a workbench offering a rich range of tools delivered through an extensible workflow environment. In this paper, we provide the background to AURIN including the scientific drivers that are shaping the work and the realisation of the Cloud-based AURIN environment. We focus in particular on the workflow environment and show how it seamlessly utilizes the Cloud for urban research processes focused especially on data-intensive spatial analysis. We illustrate the utilisation of this workflow environment across a range of case studies reflecting urban research activities.

'Cloud computing' and clinical trials: report from an ECRIN workshop.

Growing use of cloud computing in clinical trials prompted the European Clinical Research Infrastructures Network, a European non-profit organisation established to support multinational clinical research, to organise a one-day workshop on the topic to clarify potential benefits and risks. The issues that arose in that workshop are summarised and include the following: the nature of cloud computing and the cloud computing industry; the risks in using cloud computing services now; the lack of explicit guidance on this subject, both generally and with reference to clinical trials; and some possible ways of reducing risks. There was particular interest in developing and using a European ‘community cloud’ specifically for academic clinical trial data. It was recognised that the day-long workshop was only the start of an ongoing process. Future discussion needs to include clarification of trial-specific regulatory requirements for cloud computing and involve representatives from the relevant regulatory bodies.

ACTRIS non-methane hydrocarbon intercomparison experiment in Europe to support WMO GAW and EMEP observation networks

Abstract. The performance of 18 European institutions involved in long-term non-methane hydrocarbon (NMHC) measurements in ambient air within the framework of the Global Atmosphere Watch (GAW) and the European Monitoring and Evaluation Programme (EMEP) was assessed with respect to data quality objectives (DQOs) of ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) and GAW. Compared to previous intercomparison studies the DQOs define a novel approach to assess and ensure a high quality of the measurements. Having already been adopted by GAW, the ACTRIS DQOs are demanding with deviations to a reference value of less than 5 % and a repeatability of better than 2 % for NMHC mole fractions above 0.1 nmol mol−1. The participants of the intercomparison analysed two dry gas mixtures in pressurised cylinders, a 30-component NMHC mixture in nitrogen (NMHC_N2) at approximately 1 nmol mol−1 and a whole air sample (NMHC_air), following a standardised operation procedure including zero- and calibration gas measurements. Furthermore, participants had to report details on their instruments and assess their measurement uncertainties. The NMHCs were analysed either by gas chromatography–flame ionisation detection (GC-FID) or by gas chromatography–mass spectrometry (GC-MS). For the NMHC_N2 measurements, 62 % of the reported values were within the 5 % deviation class corresponding to the ACTRIS DQOs. For NMHC_air, generally more frequent and larger deviations to the assigned values were observed, with 50 % of the reported values within the 5 % deviation class. Important contributors to the poorer performance in NMHC_air compared to NMHC_N2 were a more complex matrix and a larger span of NMHC mole fractions (0.03–2.5 nmol mol−1). The performance of the participating laboratories were affected by the different measurement procedures such as the usage of a two-step vs. a one-step calibration, breakthroughs of C2–C3 hydrocarbons in the focussing trap, blank values in zero-gas measurements (especially for those systems using a Nafion® Dryer), adsorptive losses of aromatic compounds, and insufficient chromatographic separation.

Ecrin (European Clinical Research Infrastructure Network): The Added Value of Interoperability and Pan-European Interconnection on Clinical Research

Ecrin (European Clinical Research Infrastructure Network): The Added Value of Interoperability and Pan-European Interconnection on Clinical Research

Interacting microRNA and mRNA genes identify potential therapeutic targets for NSCLC

Lung cancer patients die from drug‐resistant, metastatic disease. Lung cancers have high mutation rates. We propose that analysis of gene expression data can uncover new drug targets and strategies to improve outcomes in Non‐Small Cell Lung Cancer (NSCLC). Partial Least Squares (PLS) regression analysis coupled with bioinformatics processing can identify microRNA(miR) and mRNA interactions with druggable potential.miR/mRNA signatures that predict NSCLC response to epidermal growth factor (EGFR) inhibitors were assembled using SAS. mRNA were regressed on miR genes for 8 samples. mRNA probesets that interacted at least 5 miR genes moved forward to biological validation by gene silencing. STRING used probeset/gene IDs to map protein‐protein interactions (PPIs). From the PPIs, the interactions of genes within two edges determined whether targets interact with the EGFR network.After cross‐validation, 8 interactions were retained, and one physical interaction was confirmed. EIF4B, RAB8A, and PPP1CB interact in the PI3K/AKT cascade while KLK8 and PRKX interact with TGFß signaling; both pathways intersect EGFR. We silenced EIF4B, RAB8a, and PPP1CB +/‐ EGFR inhibition in NSCLC cells. Silencing of EIF4B and RAB8A did not induce cell cycle arrest or death. PPP1CB is a potential novel target. PLS modeling and bioinformatics was used to build a logical and repeatable workflow with gene expression data to identify new drug targets/strategies. Of 14000 possible interactions, 8 genes were processed, and 3 were chosen for biological validation. PLS modeling and bioinformatics analyses will be optimized.KY Bioinformatics Research Infrastructure Network Pilot Project (NIH‐8 P20 GM103436‐12)

Editorial: Planning Support Systems

This special issue of the journal aims to provide a series of papers representing the state-of-the-art in terms of the development of planning support systems (PSS). Four contributions are included which illustrate not only different systems and applications but also the contextual drivers that underpin their development, such as technological changes including the emergence of cloud computing, and austerity measures that have pervaded public sector institutions as a consequence of national debt crises following the global recession. The applications exemplify the use of PSS in different thematic contexts in different parts of the world including Western Australia, Wyoming, the north of England and the Netherlands. The first paper by Chris Pettit and colleagues provides an excellent example of the way in which one well-known desktop planning support system, What If? (Klosterman 2001), is being transformed to take advantage of the benefits of cloud computing and offer users the opportunity online to generate future land-use predictions under alternative scenarios. The new Online What If? (OWI) system is being developed as part of the Australian Urban Research Infrastructure Network (AURIN) initiative and the paper outlines one of the tools available from this workbench that enables maps to be produced that show the relative suitability of grid squares for different types of land use. The methodology is illustrated with a case study of the anticipated growth rate in the North West Metro Perth sub-region, in collaboration with the Western Australia State Government. The results of two scenarios – one focussed on employment generation and the other on environmental conservation – are investigated and a comparison of the simulations reveals that that even under the more restrictive assumptions of the latter scenario, the sub-region can accommodate the predicted population growth whilst not compromising the environmental considerations. In the second paper, the focus moves from land-use planning per se to the relationship between infrastructure development, residential growth and the cost and efficiency of providing public services in Wyoming in the USA. Scott Lieske and his co-authors present a methodology that begins with a comparison of the population growth trends

Introducing a usability framework to support urban information discovery and analytics

One of the significant challenges facing the development of web portals is optimising the usability of such e-infrastructures for diverse, yet specialised, uses. This paper presents a usability framework for supporting the iterative testing and development of the Australian Urban Research Infrastructure Network (AURIN) portal. The portal serves as a securitised environment for data sharing, and as a repository of open-source analytical routines to support urban decision-making. Harmonisation, security, accessibility and discoverability are critical concerns at the data level as many different kinds of federated data are being referenced by the portal. Furthermore, urban researchers are accessing this portal across Australia as an advanced spatial decision support system. A further design consideration for the portal is that it needs to be able to be usable by non-experts to discover and access a broad spectrum of digital data and analytical tools relevant to human settlements. Managing the complexity across many areas and supporting a spectrum of naïve to expert users are significant challenges. In this research we present an overview of a usability framework, developed for the AURIN project, which elicits feedback from naïve users through to domain experts. This feedback is captured through hands-on workshops with participants and one-on-one user testing sessions. In this paper we report the findings from initial workshops with end-users and one-on-one testing sessions. We analyse this feedback to understand the current strengths and weaknesses of the system. The end-user feedback provides a dual purpose. Firstly, it is fed back to the technical development team as part of a cycle of continuous improvement. Secondly, the workshops also provide a vehicle for engaging end-users and raising awareness of the AURIN data search, interrogation and visualisation capabilities. We conclude the paper by discussing the next steps in developing and implementing the usability framework in relation to the AURIN portal.

The Online What if? Planning Support System: A Land Suitability Application in Western Australia

Recent advances in cloud computing and the ability to more easily deliver online tools and services provide exciting opportunities for the development and application of online planning support systems. This paper describes the application of an online open source land suitability tool which has been developed as one of the many tools available through the Australian Urban Research Infrastructure Network (AURIN) workbench. The tool is part of the larger open source online What if? planning support system (PSS) which implements the desktop What if? PSS developed by Klosterman (Environment and Planning B: Planning and Design 26:393–408, 1999; 2008). This paper describes the development of the online What if? suitability tool and the advantages and disadvantages of developing this novel solution. The paper focuses on a case study which used the tool for collaborative planning in the context of developing land suitability scenarios for the Metro North West sub-region in the Perth-Peel region undertaken by the Department of Planning in Western Australia. The paper concludes by discussing the lessons learned from formulating the land use suitability scenarios for Perth and outlines the next steps in the development and application of the online What if? tool.

First Clinical Research Informatics (CRI) Solutions Day: advanced IT support from EU projects for clinical trials

Necessity for a novel form of interactive conference Clinical trials are the foundation for the advancement of medical research, but they are also complex, time consuming and expensive. To ensure scientific validity, clinical trials must record large amounts of data on health and treatment of a carefully selected group of patients or trial participants. That is why a robust and highly flexible IT infrastructure that permits rapid reconfiguration to support different trials while maintaining consistent data models is needed to ensure that clinical data can be shared and used for analysis. Recently, EU projects, like TRANSFoRm, p-medicine, EHR4CR and BioMedBridges, are creating advanced clinical research information systems consisting of sets of tools that assist in the preparation and conduct of clinical trials and the re-use of care data for research purposes. These tools are also able to assemble data from heterogeneous sources to answer complex research questions, including functions for data mining and support of research process workflows to meet the needs of translational and personalized medical research [1]. Because the translation of biomedical discoveries into clinical applications is an aim of the EU Commission, clinical research support is expected to be a major component of EU funded projects [2]. In this context, the EU Framework Program 7 (FP7, http://ec.europa.eu/ research/fp7/index_en.cfm) has promoted translational research, the so-called ‘from bench-to-bedside’ approach, that is expected to have practical benefits and improvements of the quality of life for patients. In this context, it is planned that many of the tools developed in ESFRI (European Strategy Forum on Research Infrastructures) and IMI projects will be used by ECRIN, the European Clinical Research Infrastructures Network [3] to advance clinical trials. To provide information on these new research tools and to evaluate their usability for the clinical research community, the CRI Solutions Day was organised by ECRIN together with other EUfunded projects (TRANSFoRm, EHR4CR, p-medicine, BioMedBridges and ECRIN-IA) providing interactive “hands-on” sessions to allow visitors to see these tools in action. The necessity for such a solutions day was based on the experience of ECRIN that the conventional, class room style presentation of research tools is not sufficient to demonstrate comparability and usability to many researchers. Thus, presenters from academia, research infrastructures and EU projects presented their developments with interactive sessions embedded in a framework of presentations and joint discussions. The CRI solutions day took place at Heinrich-Heine University Dusseldorf, in Dusseldorf, Germany, 26-27 May 2014.

Developing a research and practice tool to measure walkability: a demonstration project.

Growing evidence shows that higher-density, mixed-use, pedestrian-friendly neighbourhoods encourage active transport, including transport-related walking. Despite widespread recognition of the benefits of creating more walkable neighbourhoods, there remains a gap between the rhetoric of the need for walkability and the creation of walkable neighbourhoods. Moreover, there is little objective data to benchmark the walkability of neighbourhoods within and between Australian cities in order to monitor planning and design intervention progress and to assess built environment and urban policy interventions required to achieve increased walkability. This paper describes a demonstration project that aimed to develop, trial and validate a 'Walkability Index Tool' that could be used by policy makers and practitioners to assess the walkability of local areas; or by researchers to access geospatial data assessing walkability. The overall aim of the project was to develop an automated geospatial tool capable of creating walkability indices for neighbourhoods at user-specified scales. The tool is based on open-source software architecture, within the Australian Urban Research Infrastructure Network (AURIN) framework, and incorporates key sub-component spatial measures of walkability (street connectivity, density and land use mix). Using state-based data, we demonstrated it was possible to create an automated walkability index. However, due to the lack of availability of consistent of national data measuring land use mix, at this stage it has not been possible to create a national walkability measure. The next stage of the project is to increase useability of the tool within the AURIN portal and to explore options for alternative spatial data sources that will enable the development of a valid national walkability index. AURIN's open-source Walkability Index Tool is a first step in demonstrating the potential benefit of a tool that could measure walkability across Australia. It also demonstrates the value of making accurate spatial data available for research purposes. SO WHAT?: There remains a gap between urban policy and practice, in terms of creating walkable neighbourhoods. When fully implemented, AURIN's walkability tool could be used to benchmark Australian cities against which planning and urban design decisions could be assessed to monitor progress towards achieving policy goals. Making cleaned data readily available for research purposes through a common portal could also save time and financial resources.

Assimilation of lidar signals: application to aerosol forecasting in the western Mediterranean basin

Abstract. This paper presents a new application of assimilating lidar signals to aerosol forecasting. It aims at investigating the impact of a ground-based lidar network on the analysis and short-term forecasts of aerosols through a case study in the Mediterranean basin. To do so, we employ a data assimilation (DA) algorithm based on the optimal interpolation method developed in the Polair3D chemistry transport model (CTM) of the Polyphemus air quality modelling platform. We assimilate hourly averaged normalised range-corrected lidar signals (PR2) retrieved from a 72 h period of intensive and continuous measurements performed in July 2012 by ground-based lidar systems of the European Aerosol Research Lidar Network (EARLINET) integrated into the Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS) network and an additional system in Corsica deployed in the framework of the pre-ChArMEx (Chemistry-Aerosol Mediterranean Experiment)/TRAQA (TRAnsport à longue distance et Qualité de l'Air) campaign. This lidar campaign was dedicated to demonstrating the potential operationality of a research network like EARLINET and the potential usefulness of assimilation of lidar signals to aerosol forecasts. Particles with an aerodynamic diameter lower than 2.5 μm (PM2.5) and those with an aerodynamic diameter higher than 2.5 μm but lower than 10 μm (PM10–2.5) are analysed separately using the lidar observations at each DA step. First, we study the spatial and temporal influences of the assimilation of lidar signals on aerosol forecasting. We conduct sensitivity studies on algorithmic parameters, e.g. the horizontal correlation length (Lh) used in the background error covariance matrix (50 km, 100 km or 200 km), the altitudes at which DA is performed (0.75–3.5 km, 1.0–3.5 km or 1.5–3.5 km a.g.l.) and the assimilation period length (12 h or 24 h). We find that DA with Lh = 100 km and assimilation from 1.0 to 3.5 km a.g.l. during a 12 h assimilation period length leads to the best scores for PM10 and PM2.5 during the forecast period with reference to available measurements from surface networks. Secondly, the aerosol simulation results without and with lidar DA using the optimal parameters (Lh = 100 km, an assimilation altitude range from 1.0 to 3.5 km a.g.l. and a 12 h DA period) are evaluated using the level 2.0 (cloud-screened and quality-assured) aerosol optical depth (AOD) data from AERONET, and mass concentration measurements (PM10 or PM2.5) from the French air quality (BDQA) network and the EMEP-Spain/Portugal network. The results show that the simulation with DA leads to better scores than the one without DA for PM2.5, PM10and AOD. Additionally, the comparison of model results to evaluation data indicates that the temporal impact of assimilating lidar signals is longer than 36 h after the assimilation period.

Proceedings of the Thirteenth Annual UT- KBRIN Bioinformatics Summit 2014.

The University of Tennessee (UT) and the Kentucky Biomedical Research Infrastructure Network (KBRIN) have collaborated over the past fourteen years to share research and educational expertise in bioinformatics. One result is an annual regional summit for researchers, educators and students. The Fourteenth Annual UT- KBRIN Bioinformatics Summit was held at Paris Landing State Park in Buchanan, Tennessee from March 20-22, 2015. A total of 200 participants pre-registered, with 115 from Tennessee, 69 from Kentucky, and the remainder from various states and international locales. Among the registrants were 70 faculty, 65 students, 40 staff, and 23 postdocs. The conference program consisted of a workshop on R and three days of presentations broken into plenary sessions: Where are They Now, Medical Informatics, and Epigenetics. In addition, a poster session with 42 posters was held on Saturday evening.