Transparent Support Research Articles

NoSQL technologies for the CMS Conditions Database

With the restart of the LHC in 2015, the growth of the CMS Conditions dataset will continue, therefore the need of consistent and highly available access to the Conditions makes a great cause to revisit different aspects of the current data storage solutions.We present a study of alternative data storage backends for the Conditions Databases, by evaluating some of the most popular NoSQL databases to support a key-value representation of the CMS Conditions. The definition of the database infrastructure is based on the need of storing the conditions as BLOBs. Because of this, each condition can reach the size that may require special treatment (splitting) in these NoSQL databases. As big binary objects may be problematic in several database systems, and also to give an accurate baseline, a testing framework extension was implemented to measure the characteristics of the handling of arbitrary binary data in these databases. Based on the evaluation, prototypes of a document store, using a column-oriented and plain key-value store, are deployed. An adaption layer to access the backends in the CMS Offline software was developed to provide transparent support for these NoSQL databases in the CMS context. Additional data modelling approaches and considerations in the software layer, deployment and automatization of the databases are also covered in the research. In this paper we present the results of the evaluation as well as a performance comparison of the prototypes studied.

Developing Effective Decision Support for the Application of “Gentle” Remediation Options: The GREENLAND Project

Gentle remediation options (GRO) are risk management strategies/technologies that result in a net gain (or at least no gross reduction) in soil function as well as risk management. They encompass a number of technologies, including the use of plant (phyto‐), fungi (myco‐), and/or bacteria‐based methods, with or without chemical soil additives or amendments, for reducing contaminant transfer to local receptors by in situ stabilization, or extraction, transformation, or degradation of contaminants. Despite offering strong benefits in terms of risk management, deployment costs, and sustainability for a range of site problems, the application of GRO as practical on‐site remedial solutions is still in its relative infancy, particularly for metal(loid)‐contaminated sites. A key barrier to wider adoption of GRO relates to general uncertainties and lack of stakeholder confidence in (and indeed knowledge of) the feasibility or reliability of GRO as practical risk management solutions. The GREENLAND project has therefore developed a simple and transparent decision support framework for promoting the appropriate use of gentle remediation options and encouraging participation of stakeholders, supplemented by a set of specific design aids for use when GRO appear to be a viable option. The framework is presented as a three phased model or Decision Support Tool (DST), in the form of a Microsoft Excel‐based workbook, designed to inform decision‐making and options appraisal during the selection of remedial approaches for contaminated sites. The DST acts as a simple decision support and stakeholder engagement tool for the application of GRO, providing a context for GRO application (particularly where soft end‐use of remediated land is envisaged), quick reference tables (including an economic cost calculator), and supporting information and technical guidance drawing on practical examples of effective GRO application at trace metal(loid) contaminated sites across Europe. This article introduces the decision support framework. ©2015 Wiley Periodicals, Inc.

The conceptual foundation of environmental decision support

Environmental decision support intends to use the best available scientific knowledge to help decision makers find and evaluate management alternatives. The goal of this process is to achieve the best fulfillment of societal objectives. This requires a careful analysis of (i) how scientific knowledge can be represented and quantified, (ii) how societal preferences can be described and elicited, and (iii) how these concepts can best be used to support communication with authorities, politicians, and the public in environmental management. The goal of this paper is to discuss key requirements for a conceptual framework to address these issues and to suggest how these can best be met. We argue that a combination of probability theory and scenario planning with multi-attribute utility theory fulfills these requirements, and discuss adaptations and extensions of these theories to improve their application for supporting environmental decision making. With respect to (i) we suggest the use of intersubjective probabilities, if required extended to imprecise probabilities, to describe the current state of scientific knowledge. To address (ii), we emphasize the importance of value functions, in addition to utilities, to support decisions under risk. We discuss the need for testing “non-standard” value aggregation techniques, the usefulness of flexibility of value functions regarding attribute data availability, the elicitation of value functions for sub-objectives from experts, and the consideration of uncertainty in value and utility elicitation. With respect to (iii), we outline a well-structured procedure for transparent environmental decision support that is based on a clear separation of scientific prediction and societal valuation. We illustrate aspects of the suggested methodology by its application to river management in general and with a small, didactical case study on spatial river rehabilitation prioritization.

Fabrication and characterization of an all optically addressed micromirror array

We describe the fabrication process for an optically addressed adaptive optics array. The device consists of a micromirror array cascaded directly on wafer fused gallium arsenide (GaAs)-gallium phosphide (GaP) photodiodes. Optically addressing a photodiode generates a photocurrent which in turn causes a voltage drop across the cascaded mirror via an integrated thin film resistor. This architecture allows parallel optical addressing of individual elements without the need for wire bonding each pixel, which can enable higher density segmented type arrays. We first describe a fabrication process for releasing a free-standing array of low stress SixN micromirrors on an indium phosphide (InP) support substrate. We then present a process for transferring GaAs p-i-n photodiodes on a transparent GaP support substrate using a specially designed wafer fusion fixture. The two samples when stacked together and electrically connected via a specially formulated and patterned semiconductive SU-8 resist form the final device. We report mirror displacements of up to 500 nm using this technique while requiring an optical signal as low as 150 μW.

Informed actions: where to cost effectively manage multiple threats to species to maximize return on investment.

Conservation practitioners, faced with managing multiple threats to biodiversity and limited funding, must prioritize investment in different management actions. From an economic perspective, it is routine practice to invest where the highest rate of return is expected. This return-on-investment (ROI) thinking can also benefit species conservation, and researchers are developing sophisticated approaches to support decision-making for cost-effective conservation. However, applied use of these approaches is limited. Managers may be wary of “black-box” algorithms or complex methods that are difficult to explain to funding agencies. As an alternative, we demonstrate the use of a basic ROI analysis for determining where to invest in cost-effective management to address threats to species. This method can be applied using basic geographic information system and spreadsheet calculations. We illustrate the approach in a management action prioritization for a biodiverse region of eastern Australia. We use ROI to prioritize management actions for two threats to a suite of threatened species: habitat degradation by cattle grazing, and predation by invasive red foxes (Vulpes vulpes). We show how decisions based on cost-effective threat management depend upon how expected benefits to species are defined and how benefits and costs co-vary. By considering a combination of species richness, restricted habitats, species vulnerability, and costs of management actions, small investments can result in greater expected benefit compared with management decisions that consider only species richness. Furthermore, a landscape management strategy that implements multiple actions is more efficient than managing only for one threat, or more traditional approaches that don't consider ROI. Our approach provides transparent and logical decision support for prioritizing different actions intended to abate threats associated with multiple species; it is of use when managers need a justifiable and repeatable approach to investment.

Need for Large-Area EDS Detectors for Imaging Nanoparticles in a SEM Operating in Transmission Mode

Accurate characterization of nanoparticles (NPs) with a high-resolution SEM with respect to morphology, shape and size distribution is carried out meanwhile routinely in more and more laboratories [1,2]. The valuable result of the metrological measurement of the NP size distribution -including traceability to the SI length unit was also recently demonstrated by exploiting the transmission mode in a SEM, i.e. TSEM [1,3]. Especially for NPs prepared on thin foil supports like the typical TEM grids the transmission mode at low voltages (up to 30 kV) supplies a high imaging contrast so that sharp boarders of the NPs enable accurate lateral dimensional measurements of NPs size. There are just a few analytical methods which are able to characterize physico-chemical properties of individual NPs. In most cases a SEM has attached an EDS detector so that information on the elemental composition of the sample to be analyzed becomes possible. The addressed sample volume typically in the micrometer range for bulk specimens is considerably reduced if thin, electron transparent support films are used. Hence, one improves the spatial resolution however, at the cost of lower signal-to-noise ratios of the X-ray spectra, due to the tiny amount of substance excited [2,4,5]. One decisive technological development in the manufacturing of EDS detectors, namely the large-area SDD EDS, meanwhile available commercially in various designs, compensates this analytical drawback. If collection solid angles of 1-2 msr have been typically available for almost four decades, recent technological improvements in SDD EDS size and design have resulted in solid angles in the sr range.

Three immobilized enzymes acting in series in layer by layer assemblies: Exploiting the trehalase-glucose oxidase-horseradish peroxidase cascade reactions for the optical determination of trehalose

A new optical biosensor for trehalose determination has been realized immobilizing three glycoenzymes on a transparent support. Trehalase, glucose oxidase and horseradish peroxidase have been alternated with layers of Concanavalin A by a “layer-by-layer” (LbL) deposition. The driving force of this assembly is the biospecific complexation between Concanavalin A and sugar residues in the glycoenzymes. As confirmed by UV–vis spectroscopy, the LbL deposition allowed a high ordinate architecture with high loading of enzymes. After the assembly, the functionality of immobilized enzymes was spectrophotometrically proven, demonstrating also that they can act in series catalyzing cascade reactions.The prepared biosensor was used to optically detect trehalose, giving a LOD of 10μM and a linear response up to 4mM, and it showed also good time stability. The trehalose content in a real sample (eyewash) was successfully determined by the biosensor.

Individualized Gaussian process-based prediction and detection of local and global gray matter abnormalities in elderly subjects

Structural imaging based on MRI is an integral component of the clinical assessment of patients with potential dementia. We here propose an individualized Gaussian process-based inference scheme for clinical decision support in healthy and pathological aging elderly subjects using MRI. The approach aims at quantitative and transparent support for clinicians who aim to detect structural abnormalities in patients at risk of Alzheimer's disease or other types of dementia. Firstly, we introduce a generative model incorporating our knowledge about normative decline of local and global gray matter volume across the brain in elderly. By supposing smooth structural trajectories the models account for the general course of age-related structural decline as well as late-life accelerated loss. Considering healthy subjects' demography and global brain parameters as informative about normal brain aging variability affords individualized predictions in single cases. Using Gaussian process models as a normative reference, we predict new subjects' brain scans and quantify the local gray matter abnormalities in terms of Normative Probability Maps (NPM) and global z-scores. By integrating the observed expectation error and the predictive uncertainty, the local maps and global scores exploit the advantages of Bayesian inference for clinical decisions and provide a valuable extension of diagnostic information about pathological aging. We validate the approach in simulated data and real MRI data. We train the GP framework using 1238 healthy subjects with ages 18–94years, and predict in 415 independent test subjects diagnosed as healthy controls, Mild Cognitive Impairment and Alzheimer's disease.

Разработка масштабируемой программной инфраструктуры для хранения и обработки данных в задачах вычислительной биологии

This article is an overview of scalable infrastructure for storage and processing of genome data in genetics problems. The overview covers used technologies descriptions, the organization of unified access to genome processing API of different underlying services. The article also covers methods for scalable and cloud computing technologies support. The first service in virtual genome processing laboratory is provided and presented. The service solves transcription factors bindning sites prediction problem. The main principles of service construction are provided. Basic requirements for underlying comptutaion software in virtual laboratory environments are provided. Overview describes the implemented web-service (https://api.ispras.ru/demo/gen) for transcription factors binding site prediction. Provided solution is based on ISPRAS API project as an API gateway and load-balancer; the middle-ware task-manager software for pool of workers support and for communications with Openstack infrastructure; OpenZFS as an intermediate storage with transparent compression support. The described solution is easy to extend with new services fitting the basic requirements.

3D hierarchical architectures based on self-rolled-up silicon nitride membranes

This study presents the superior structural versatility of strained silicon nitride (SiNx) membranes as a platform for three-dimensional (3D) hierarchical tubular architectures. The effects of compressive and tensile stressed SiNx layer thickness on the self-rolled-up tube curvature, the sacrificial layer etching anisotropy on rolling direction and chirality, and stress engineering by localized thickness control or thermal treatment, are explored systematically. Using strained SiNx membranes as an electrically insulating and optically transparent mechanical support, compact 3D hierarchical architectures involving carbon nanotube arrays and passive electronic components are demonstrated by releasing the functional structures deposited and patterned in 2D. These examples highlight the uniqueness of this platform that exploits 2D processing and self-assembly to achieve highly functional 3D structures.

A solution for transparent mobility with route optimization in the IP multimedia subsystem

This paper presents TRIM+, an architecture for transparent mobility management with route optimization in IMS based networks. The design of our architecture is based on a previous work referred to as TRIM. TRIM was originally devised to provide transparent mobility support in the IMS, although transparency came at the cost of using a suboptimal data path between communicating end points. TRIM+ maintains transparency as a design criterium, and thus end-user applications, running at the mobile node and its correspondent communication peers, are unaware of mobility management procedures. Additionally, the proposed design defines a set of route optimization procedures, allowing compliant devices to use the optimal data path for media communications. Furthermore, TRIM+ addresses packet loss management in scenarios where the media path cannot be maintained during the handover of the MN. To this end, our architecture enables the MN to request buffering capacity in its home network to temporarily store incoming media traffic during the handover, which would otherwise be dropped. This mechanism, as well as route optimization procedures, are executed transparently to the end-user applications running at the communicating end points. As a proof-of-concept, we have implemented a software prototype of the TRIM+ architecture, deploying it over a real IMS testbed. By means of a set of experiments, we have validated the mechanisms proposed in this paper, considering both UDP and TCP user traffic.

Land change modelling: moving beyond projections

During the last decades, there has been an increasing interest from the academic and policy communities to monitor and model changes of the earth surface. Modeling environmental dynamics helps to understand changes that are taking place currently and to anticipate future evolutions. Prospective simulation supports decision-making for environmental management and land planning. This special issue is dedicated to advances in land change modeling. Land Use / Land Cover Change, also called LUCC, is certainly a prominent interface between natural and social dynamics because anthropogenic LUCC has a profound impact on Earth. LUCC impacts a large amount of highly relevant topics such as resource exploitation, climate change, biodiversity loss, etc. Land change modeling can provide transparent, efficient and sustainable decision support to these current and rising environmental problems

Ordered Arrays of Native Chromatin Molecules for High-Resolution Imaging and Analysis

Individual chromatin molecules contain valuable genetic and epigenetic information. To date, there have not been reliable techniques available for the controlled stretching and manipulation of individual chromatin fragments for high-resolution imaging and analysis of these molecules. We report the controlled stretching of single chromatin fragments extracted from two different cancerous cell types (M091 and HeLa) characterized through fluorescence microscopy and atomic force microscopy (AFM). Our method combines soft lithography with molecular stretching to form ordered arrays of more than 250,000 individual chromatin fragments immobilized into a beads-on-a-string structure on a solid transparent support. Using fluorescence microscopy and AFM, we verified the presence of histone proteins after the stretching and transfer process.

A hybrid fuzzy group decision support framework for advanced-technology prioritization at NASA

The prioritization of advanced-technology projects at the National Aeronautic and Space Administration (NASA) is a difficult task. This difficulty is due to the multiple and often conflicting objectives in addition to the inherent technical complexities and valuation uncertainties involved in the assessment process. As such, a systematic and transparent decision support framework is needed to guide the assessment process, shape the decision outcomes and enable confident choices to be made. Methods for solving Multi-Criteria Decision Making (MCDM) problems have been widely used to select a finite number of alternatives generally characterized by multiple conflicting criteria. However, applying these methods is becoming increasingly difficult for technology assessment in the space industry because there are many emerging risks for which information is not available and decisions are made under significant uncertainty. In this paper, we propose a hybrid fuzzy group decision support framework for technology assessment at NASA. The proposed objective framework is comprised of two modules. In the first module, the complicated structure of the assessment criteria and alternatives are represented and evaluated with the Analytic Network Process (ANP). In the second module, the alternative advanced-technology projects are ranked using a customized fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). We demonstrate the applicability of the proposed framework through a case study at the Kennedy Space Center.

Focus on Citizens: Public Engagement with Online and Face-to-Face Participation—A Case Study

The main objective of this paper is to focus on how an integrated system based on Information Communication Technology (ICT) and face-to-face communication can increase participation in order to have a positive effect on quality of life, plans and decisions, and to discuss the many benefits which web-based public participation can bring to the planning process through a set of improvements to relations, quality and structure of cities in general and in this case example specifically. With the development of a transparent support system for collaborative decision-making processes, it is possible to identify a strategy for addressing gaps to reach collaborative decisions.

A web service application to support distributed manufacturing

Manufacturing as an industrial activity that starts with the conceptual project and ends with proper material disposal or its reuse has evolved from a centralized to a distributed process. The several components of the process are distributed according to space and time. This evolution was possible due to the support of information technology, which allows manufacturing data management. However, this evolution happened in an independent way in each process phase, creating isolated solutions and consequently a high heterogeneity in data management. The development of a Federative Factory Data Management offers a solution of a transparent support to the users who need to obtain information from different proprietary systems. As an example of a service that demonstrates the possibility of federative management of manufacturing data in service oriented architecture within a heterogeneous and flexible environment, this article presents the estimated calculation of the manufacturing time for a complex surface.

A spatio‐temporal absorbing state model for disease and syndromic surveillance

Reliable surveillance models are an important tool in public health because they aid in mitigating disease outbreaks, identify where and when disease outbreaks occur, and predict future occurrences. Although many statistical models have been devised for surveillance purposes, none are able to simultaneously achieve the important practical goals of good sensitivity and specificity, proper use of covariate information, inclusion of spatio-temporal dynamics, and transparent support to decision-makers. In an effort to achieve these goals, this paper proposes a spatio-temporal conditional autoregressive hidden Markov model with an absorbing state. The model performs well in both a large simulation study and in an application to influenza/pneumonia fatality data.

Physical model for the laser induced forward transfer process

This paper presents a numerical model which describes the underlying physical processes during laser induced forward transfer. The laser induced forward transfer uses a pulsed laser to transfer thin layers from a transparent support to a substrate. The model predicts the threshold energies Eth as well as the blow-off time tblow, thus allowing a profound physical understanding of the transfer process. The good agreement of simulated with measured Eth and tblow of thin nickel layers demonstrates the accuracy of the model. The model shows that gasification of the soda-lime glass support is the main driving force of the transfer process.

A simple method to reduce optical cross‐talk effects in chemical imaging with planar optodes

A simple and universal method to minimize optical cross‐talk in chemical imaging with planar optodes used for metabolic investigation of benthic interfaces is presented. Cross‐talk can lead to smeared images and flattened gradients and therefore to erroneous analytical results. To minimize the cross‐talk effect, an additional optical filter layer is coated on the downside of the transparent support. Cross‐talk light traveling in the support and decoupled by scattering media is absorbed to a higher extent than the virtual signal. The extent of cross‐talk and its reduction was evaluated by imaging the luminescence intensity of sensor layers with sharp edges and isolated points. The influence of cross‐talk on the accuracy of oxygen determination by lifetime measurements was investigated by analyzing aerated and de‐aerated zones of a planar optode placed on a scattering media. The presented method is compared qualitatively with methods previously described to reduce optical cross‐talk effects.

Are general practitioners prepared to end life on request in a country where euthanasia is legalised?

BackgroundIn 2002, Belgium set a legal framework for euthanasia, whereby granting and performing euthanasia is entrusted entirely to physicians, and—as advised by Belgian Medical Deontology—in the context of a trusted...