Comparison of variables measured with a Scheimpflug device for evaluation of progression and detection of keratoconus

Keratoconus is a progressive ectatic corneal disorder, which can result in severe visual impairment. The new ABCD keratoconus classification system allows differentiated description of the disease. Aim of the study was to evaluate the components of this novel staging system (ARC, PRC, thinnest pachymetry) as well as topometric indices, deviation of normality indices, and other parameters in terms of repeatability and reliability. 317 eyes with keratoconus were examined twice with a Scheimpflug device (Pentacam, Oculus). Bland Altman analysis and intraclass correlations were carried out to evaluate the parameters repeatability and reliability. Apart from IHA (ICC=0.730), all parameters showed excellent reliability (ICC>0.900). ARC, PRC, thinnest pachymetry, Kmax, CKI, KI, Rmin, and Progression Avg were the best repeatable parameters with relative repeatability values<2.5%. Other parameters performing well in terms of repeatability were IHD, ISV, IVA, and final D (RR<13%). Regression analysis revealed consistently high repeatability along all stages of keratoconus for PRC, thinnest pachymetry, and CKI. All parameters of the ABCD staging system showed excellent reliability and repeatability, PRC and thinnest pachymetry even at all stages of keratoconus and can consequently be reliably used in the determination of keratoconus progression

Sensitivity of fluvial sediment source apportionment to mixing model assumptions: A Bayesian model comparison

Mixing models have become increasingly common tools for apportioning fluvial sediment load to various sediment sources across catchments using a wide variety of Bayesian and frequentist modeling approaches. In this study, we demonstrate how different model setups can impact upon resulting source apportionment estimates in a Bayesian framework via a one-factor-at-a-time (OFAT) sensitivity analysis. We formulate 13 versions of a mixing model, each with different error assumptions and model structural choices, and apply them to sediment geochemistry data from the River Blackwater, Norfolk, UK, to apportion suspended particulate matter (SPM) contributions from three sources (arable topsoils, road verges, and subsurface material) under base flow conditions between August 2012 and August 2013. Whilst all 13 models estimate subsurface sources to be the largest contributor of SPM (median ∼76%), comparison of apportionment estimates reveal varying degrees of sensitivity to changing priors, inclusion of covariance terms, incorporation of time-variant distributions, and methods of proportion characterization. We also demonstrate differences in apportionment results between a full and an empirical Bayesian setup, and between a Bayesian and a frequentist optimization approach. This OFAT sensitivity analysis reveals that mixing model structural choices and error assumptions can significantly impact upon sediment source apportionment results, with estimated median contributions in this study varying by up to 21% between model versions. Users of mixing models are therefore strongly advised to carefully consider and justify their choice of model structure prior to conducting sediment source apportionment investigations

2-(4-Fluorophenyl)-3-methyl-1H-indole

Funding: University of St Andrews and the Engineering and Physical Science Research Council (EPSRC, UK).The indole N-H hydrogen in the title compound, C15H12FN, does not display classical hydrogen bonding. Rather it forms an interaction with the pi system of an adjacent indole, resulting in weakly interacting chains along the [001] direction.Publisher PDFPeer reviewe

Toward learning realizable scenario-based, formal requirements specifications

Distributed, software-intensive systems such as fully automated cars have to handle various situations employing message-based coordination. The growing complexity of such systems results in an increasing difficulty to achieve a high quality of the systems' requirements specifications, particularly w.r.t. the realizability of the specifications. Scenario-based requirements engineering addresses the message-based coordination of such systems and enables, if underpinned with formal languages, automatic requirements validation techniques for proving the realizability of a requirements specification. However, formal requirements modeling languages require a deep knowledge of requirements engineers and typically require many manual iterations until they find a realizable specification. In order to support requirements engineers in the stepwise development of scenario-based requirements specifications, we propose to evolve a high-quality specification from a (presumably unrealizable) manually created specification employing an evolutionary algorithm. In this paper, we show our results on automatically evolving new assumptions on the systems' environment behavior that guarantee a realizable requirements specification. Based on this contribution, we outline our research roadmap toward our long-term goal of automatically supporting requirements engineers in finding high-quality requirements specifications

Formal, model- and scenario-based requirement patterns

Distributed, software-intensive systems such as automotive electronic control units have to handle various situations employing message-based coordination. The growing complexity of such systems results in an increasing difficulty to achieve a high quality of the systemsâ requirements specifications. Scenario-based requirements engineering addresses the message-based coordination of such systems and enables, if underpinned with formal modeling languages, automatic analyses for ensuring the quality of requirements specifications. However, formal requirements modeling languages require high expertise of the requirements engineers and many manual iterations until specifications reach high quality. Patterns provide a constructive means for assembling high-quality solutions by applying reusable and established building blocks. Thus, they also gained momentum in requirements documentation. In order to support the requirements engineers in the systematic conception of formal , scenario-based requirements specification models, we hence introduce in this paper a requirement pattern catalog for a requirements modeling language. We illustrate and discuss the application of the requirement patterns with an example of requirements for an automotive electronic control unit

Implementation of communication model and web services for cluster-based power system operation in smart grids

The penetration of distributed energy resources in distribution networks leads to the decentralisation of the power generation. This is contrary to the traditional centralized power generation where the power is fed from transmission systems. To cope with the impact of the decentralised power generation, clustering power systems approach (CPSA) is proposed. It is an approach that coexists operations of the distribution networks and the transmission systems by allowing the use of conventional control scheme and action of the transmission systems in the distribution networks. In addition, the CPSA is also aimed to realise the smart grid concept. Information and communication technology is hence applied to the CPSA. In this paper, a communication model and web services concept including its relevant technologies are proposed to enable power system operation based on the CPSA. The implementation of the communication model and web services for the CPSA is presented at the end

Hybrid framework of management systems supporting cluster-oriented smart grid operations

The concept of smart grids has been widely introduced to cope with energy transition towards sustainable energy system, which results in decentralization of the energy supply system. Among various solutions to accomplish the smart grids, clustering power systems approach (CPSA) has been proposed. Based on this approach, active interconnected cluster areas, operating similar to interconnected grids in transmission systems, are created in bottom-up direction from distribution level upwards to the upstream systems. In order to manage emerging cluster areas and concurrently facilitate their cooperation, this paper proposes hybrid framework of management systems. That is, both centralized and decentralized management systems are employed for operations under the CPSA. Besides, to add a level of cyber security, this paper also presents the integration of the adapted access control mechanism based on XACML data-flow model to the management systems. Lastly, the applications of the proposed hybrid framework are illustrated and discussed in use cases

Data management and visualization for cluster-based grid operations

The increase of electricity demand has raised requirements of more reliable and efficient grid operations as well as higher security of supply. Meanwhile, the transition towards clean and sustainable energy supply systems in the present power systems is under the spotlight [1]–[3]. High penetration of renewable energy sources (RESs), which are usually in the form of distributed generation (DG), can be expected. The RESs-based DG units can reside in distribution level, whose original purpose is to distribute power from electricity utilities to end users. Presently, to cope with the power penetration in distribution level, conventional power grids are being evolved into the smarter ones, known as smart grids. A smart grid is proposed to overcome the arising environmental and technical challenges [4], [5]. To smarten the grid, information and communication technologies are incorporated into the conventional power grids. They allow the cooperation of heterogeneous grid components, e.g. control centers and DG units, or users, e.g. operators and customers. Decentralization of grid control architecture is possible [6], and many actors can actively participate in the operation of the grid