Ontology modeling for generation of clinical pathways

Purpose: Increasing costs of health care, fuelled by demand for high quality, cost-effective healthcare has drove hospitals to streamline their patient care delivery systems. One such systematic approach is the adaptation of Clinical Pathways (CP) as a tool to increase the quality of healthcare delivery. However, most organizations still rely on are paper-based pathway guidelines or specifications, which have limitations in process management and as a result can influence patient safety outcomes. In this paper, we present a method for generating clinical pathways based on organizational semiotics by capturing knowledge from syntactic, semantic and pragmatic to social level. Design/methodology/approach: The proposed modeling approach to generation of CPs adopts organizational semiotics and enables the generation of semantically rich representation of CP knowledge. Semantic Analysis Method (SAM) is applied to explicitly represent the semantics of the concepts, their relationships and patterns of behavior in terms of an ontology chart. Norm Analysis Method (NAM) is adopted to identify and formally specify patterns of behavior and rules that govern the actions identified on the ontology chart. Information collected during semantic and norm analysis is integrated to guide the generation of CPs using best practice represented in BPMN thus enabling the automation of CP. Findings: This research confirms the necessity of taking into consideration social aspects in designing information systems and automating CP. The complexity of healthcare processes can be best tackled by analyzing stakeholders, which we treat as social agents, their goals and patterns of action within the agent network. Originality/value: The current modeling methods describe CPs from a structural aspect comprising activities, properties and interrelationships. However, these methods lack a mechanism to describe possible patterns of human behavior and the conditions under which the behavior will occur. To overcome this weakness, a semiotic approach to generation of clinical pathway is introduced. The CP generated from SAM together with norms will enrich the knowledge representation of the domain through ontology modeling, which allows the recognition of human responsibilities and obligations and more importantly, the ultimate power of decision making in exceptional circumstances.

(PDF, 406 KB) On L3 acquisition and phonological permeability: a new test case for debates on the mental representation of non-native phonological systems

The goal of this article is to make an epistemological and theoretical contribution to the nascent field of third language (L3) acquisition and show how examining L3 development can offer a unique view into longstanding debates within L2 acquisition theory. We offer the Phonological Permeability Hypothesis (PPH), which maintains that examining the development of an L3/Ln phonological system and its effects on a previously acquired L2 phonological system can inform contemporary debates regarding the mental constitution of postcritical period adult phonological acquisition. We discuss the predictions and functional significance of the PPH for adult SLA and multilingualism studies, detailing a methodology that examines the effects of acquiring Brazilian Portuguese on the Spanish phonological systems learned before and after the so-called critical period (i.e., comparing simultaneous versus successive adult English-Spanish bilinguals learning Brazilian Portuguese as an L3).

CASCADE: An Agent Based Framework For Modeling The Dynamics Of Smart Electricity Systems

The Complex Adaptive Systems, Cognitive Agents and Distributed Energy (CASCADE) project is developing a framework based on Agent Based Modelling (ABM). The CASCADE Framework can be used both to gain policy and industry relevant insights into the smart grid concept itself and as a platform to design and test distributed ICT solutions for smart grid based business entities. ABM is used to capture the behaviors of diff erent social, economic and technical actors, which may be defi ned at various levels of abstraction. It is applied to understanding their interactions and can be adapted to include learning processes and emergent patterns. CASCADE models ‘prosumer’ agents (i.e., producers and/or consumers of energy) and ‘aggregator’ agents (e.g., traders of energy in both wholesale and retail markets) at various scales, from large generators and Energy Service Companies down to individual people and devices. The CASCADE Framework is formed of three main subdivisions that link models of electricity supply and demand, the electricity market and power fl ow. It can also model the variability of renewable energy generation caused by the weather, which is an important issue for grid balancing and the profi tability of energy suppliers. The development of CASCADE has already yielded some interesting early fi ndings, demonstrating that it is possible for a mediating agent (aggregator) to achieve stable demandfl attening across groups of domestic households fi tted with smart energy control and communication devices, where direct wholesale price signals had previously been found to produce characteristic complex system instability. In another example, it has demonstrated how large changes in supply mix can be caused even by small changes in demand profi le. Ongoing and planned refi nements to the Framework will support investigation of demand response at various scales, the integration of the power sector with transport and heat sectors, novel technology adoption and diffusion work, evolution of new smart grid business models, and complex power grid engineering and market interactions.

Unified framework for construction of rule based classification systems

Automatic generation of classification rules has been an increasingly popular technique in commercial applications such as Big Data analytics, rule based expert systems and decision making systems. However, a principal problem that arises with most methods for generation of classification rules is the overfit-ting of training data. When Big Data is dealt with, this may result in the generation of a large number of complex rules. This may not only increase computational cost but also lower the accuracy in predicting further unseen instances. This has led to the necessity of developing pruning methods for the simplification of rules. In addition, classification rules are used further to make predictions after the completion of their generation. As efficiency is concerned, it is expected to find the first rule that fires as soon as possible by searching through a rule set. Thus a suit-able structure is required to represent the rule set effectively. In this chapter, the authors introduce a unified framework for construction of rule based classification systems consisting of three operations on Big Data: rule generation, rule simplification and rule representation. The authors also review some existing methods and techniques used for each of the three operations and highlight their limitations. They introduce some novel methods and techniques developed by them recently. These methods and techniques are also discussed in comparison to existing ones with respect to efficient processing of Big Data.

Introducing "ecoputation": a universal systems design process

A universal systems design process is specified, tested in a case study and evaluated. It links English narratives to numbers using a categorical language framework with mathematical mappings taking the place of conjunctions and numbers. The framework is a ring of English narrative words between 1 (option) and 360 (capital); beyond 360 the ring cycles again to 1. English narratives are shown to correspond to the field of fractional numbers. The process can enable the development, presentation and communication of complex narrative policy information among communities of any scale, on a software implementation known as the "ecoputer". The information is more accessible and comprehensive than that in conventional decision support, because: (1) it is expressed in narrative language; and (2) the narratives are expressed as compounds of words within the framework. Hence option generation is made more effective than in conventional decision support processes including Multiple Criteria Decision Analysis, Life Cycle Assessment and Cost-Benefit Analysis.The case study is of a participatory workshop in UK bioenergy project objectives and criteria, at which attributes were elicited in environmental, economic and social systems. From the attributes, the framework was used to derive consequences at a range of levels of precision; these are compared with the project objectives and criteria as set out in the Case for Support. The design process is to be supported by a social information manipulation, storage and retrieval system for numeric and verbal narratives attached to the "ecoputer". The "ecoputer" will have an integrated verbal and numeric operating system. Novel design source code language will assist the development of narrative policy. The utility of the program, including in the transition to sustainable development and in applications at both community micro-scale and policy macro-scale, is discussed from public, stakeholder, corporate, Governmental and regulatory perspectives.

Using reanalysis data to quantify extreme wind power generation statistics : a 33 year case study in Great Britain

With a rapidly increasing fraction of electricity generation being sourced from wind, extreme wind power generation events such as prolonged periods of low (or high) generation and ramps in generation, are a growing concern for the efficient and secure operation of national power systems. As extreme events occur infrequently, long and reliable meteorological records are required to accurately estimate their characteristics. Recent publications have begun to investigate the use of global meteorological “reanalysis” data sets for power system applications, many of which focus on long-term average statistics such as monthly-mean generation. Here we demonstrate that reanalysis data can also be used to estimate the frequency of relatively short-lived extreme events (including ramping on sub-daily time scales). Verification against 328 surface observation stations across the United Kingdom suggests that near-surface wind variability over spatiotemporal scales greater than around 300 km and 6 h can be faithfully reproduced using reanalysis, with no need for costly dynamical downscaling. A case study is presented in which a state-of-the-art, 33 year reanalysis data set (MERRA, from NASA-GMAO), is used to construct an hourly time series of nationally-aggregated wind power generation in Great Britain (GB), assuming a fixed, modern distribution of wind farms. The resultant generation estimates are highly correlated with recorded data from National Grid in the recent period, both for instantaneous hourly values and for variability over time intervals greater than around 6 h. This 33 year time series is then used to quantify the frequency with which different extreme GB-wide wind power generation events occur, as well as their seasonal and inter-annual variability. Several novel insights into the nature of extreme wind power generation events are described, including (i) that the number of prolonged low or high generation events is well approximated by a Poission-like random process, and (ii) whilst in general there is large seasonal variability, the magnitude of the most extreme ramps is similar in both summer and winter. An up-to-date version of the GB case study data as well as the underlying model are freely available for download from our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/.

Aspects of designing and evaluating seasonal-to-interannual Arctic sea-ice prediction systems

Using lessons from idealised predictability experiments, we discuss some issues and perspectives on the design of operational seasonal to inter-annual Arctic sea-ice prediction systems. We first review the opportunities to use a hierarchy of different types of experiment to learn about the predictability of Arctic climate. We also examine key issues for ensemble system design, such as: measuring skill, the role of ensemble size and generation of ensemble members. When assessing the potential skill of a set of prediction experiments, using more than one metric is essential as different choices can significantly alter conclusions about the presence or lack of skill. We find that increasing both the number of hindcasts and ensemble size is important for reliably assessing the correlation and expected error in forecasts. For other metrics, such as dispersion, increasing ensemble size is most important. Probabilistic measures of skill can also provide useful information about the reliability of forecasts. In addition, various methods for generating the different ensemble members are tested. The range of techniques can produce surprisingly different ensemble spread characteristics. The lessons learnt should help inform the design of future operational prediction systems.

Blending systems thinking approaches for organisational analysis: reviewing child protection in England

This paper concerns the innovative use of a blend of systems thinking ideas in the ‘Munro Review of Child Protection’, a high-profile examination of child protection activities in England, conducted for the Department for Education. We go ‘behind the scenes’ to describe the OR methodologies and processes employed. The circumstances that led to the Review are outlined. Three specific contributions that systems thinking made to the Review are then described. First, the systems-based analysis and visualisation of how a ‘compliance culture’ had grown up. Second the creation of a large, complex systems map of current operations and the effects of past policies on them. Third, how the map gave shape to the range of issues the Review addressed and acted as an organising framework for the systemically coherent set of recommendations made. The paper closes with an outline of the main implementation steps taken so far to create a child protection system with the critically reflective properties of a learning organisation, and methodological reflections on the benefits of systems thinking to support organisational analysis.

Diversity in a honey bee pathogen: first report of a third master variant of the Deformed Wing Virus quasispecies

Treatment of emerging RNA viruses is hampered by the high mutation and replication rates that enable these viruses to operate as a quasispecies. Declining honey bee populations have been attributed to the ectoparasitic mite Varroa destructor and its affiliation with Deformed Wing Virus (DWV). In the current study we use next-generation sequencing to investigate the DWV quasispecies in an apiary known to suffer from overwintering colony losses. We show that the DWV species complex is made up of three master variants. Our results indicate that a new DWV Type C variant is distinct from the previously described types A and B, but together they form a distinct clade compared with other members of the Iflaviridae. The molecular clock estimation predicts that Type C diverged from the other variants ~319 years ago. The discovery of a new master variant of DWV has important implications for the positive identification of the true pathogen within global honey bee populations.

Influence of rhBMP-2 on bone formation and osseointegration in different implant systems after sinus-floor elevation. An in vivo study on sheep

Background Several studies have reported certain bone morphogenic proteins (BMPs) to have positive effects on bone generation Although some investigators have studied the effects of human recombinant BMP (rhBMP-2) in sinus augmentation in sheep, none of these studies looked at the placement of implants at the time of sinus augmentation Furthermore, no literature could be found to report on the impact that different implant systems, as well as the positioning of the implants had on bone formation if rhBMP-2 was utilized in sinus-lift procedures Purpose The aim of this study was to compare sinus augmentation with rhBMP-2 on a poly-D, L-lactic-co-glycolic acid gelatine (PLPG) sponge with sinus augmentation with autologous pelvic cancellous bone in the maxillary sinus during the placement of different dental Implants Materials and methods Nine adult female sheep were submitted to bilateral sinus-floor elevation In one side (test group) the sinus lift was performed with rhBMP-2 on a PLPG-sponge, while the contralateral side served as the control by using cancellous bone from the iliac crest Three different implants (Branemark (R), 31 (R) and Straumann (R)) were inserted either simultaneously with the sinus augmentation or as a two staged procedure 6 weeks later The animals were sacrificed at 6 and 12 weeks for histological and histomorphometrical evaluations during which bone-to-implant contact (BIC) and bone density (BD) were evaluated Results BD and BIC were significantly higher at 12 weeks in the test group if the Implants were placed at the time of the sinus lift (p < 0 05) No difference was observed between the different implant systems or positions Conclusions The use of rhBMP-2 with PLPG-sponge increased BIC as well as BD in the augmented sinuses if compared to autologous bone Different implant systems and positions of the implants had no effect on BIC or BD (C) 2010 European Association for Cranio-Maxillo-Facial Surgery

On site flotation for recovering polluted aquatic systems: is it a feasible solution for a Brazilian urban river?

Pinheiros River (Brazil) plays a pivotal role in supplying water to Billings Reservoir, which presents multiple uses (human drinking, energy generation, irrigation, navigation, fishing and leisure) An intense monitoring program was performed during the years 2007 and 2008 to find out whether on site flotation is a feasible solution or not for improving the water quality of this urban river, attenuating the pollutants load caused by the water pumping to the reservoir (approximately 10 m(3)s(-1)) The monitoring of 18 variables (13,429 laboratorial analysis during the period of 490 days), suggested that despite the convenience of the on site approach for water treatment, especially for rivers located in fully urbanized areas, the flotation system is not enough itself to recover Pinheiros River water quality, given the several constraints that apply Total phosphorus removal was high in percentage terms (about 90%), although the remaining concentrations were not so low (mean of 0 05 mg L(-1)) The removal efficiency of some variables was insufficient, leading to high final mean concentrations of metals [e g aluminium (0 29 mg L(-1)), chromium (0 02 mg L(-1)) and iron (1 1 mg L(-1))] as well as nitrogen-ammonia (25 8 mg L(-1)) and total suspended solids (18 mg L(-1)) in the treated water

Reliability of orbital fits for resonant extrasolar planetary systems: the case of HD82943

We perform a statistical study of the process of orbital determination of the HD82943 extrasolar planetary system, using the current observational data set of N = 165 radial velocity (RV) measurements. Our aim is to analyse the dispersion of possible orbital fits leading to residuals compatible with the best solution, and to discuss the sensitivity of the results with respect to both the data set and the error distribution around the best fit. Although some orbital parameters (e.g. semimajor axis) appear well constrained, we show that the best fits for the HD82943 system are not robust, and at present it is not possible to estimate reliable solutions for these bodies. Finally, we discuss the possibility of a third planet, with a mass of 0.35M(Jup) and an orbital period of 900 d. Stability analysis and simulations of planetary migration indicate that such a hypothetical three-planet system could be locked in a double 2/1 mean-motion resonance, similar to the so-called Laplace resonance of the three inner Galilean satellites of Jupiter.

Reduced allergic lung inflammation in rats following formaldehyde exposure: Long-term effects on multiple effector systems

Clinical and experimental evidences show that formaldehyde (FA) exposure has an irritant effect on the upper airways. As being an indoor and outdoor pollutant, FA is known to be a causal factor of occupational asthma. This study aimed to investigate the repercussion of FA exposure on the course of a lung allergic process triggered by an antigen unrelated to FA. For this purpose, male Wistar rats were subjected to FA inhalation for 3 consecutive days (1%, 90-min daily), subsequently sensitized with ovalbumin (OVA)-alum via the intraperitoneal route, and 2 weeks later challenged with aerosolized OVA. The OVA challenge in rats after FA inhalation (FA/OVA group) evoked a low-intensity lung inflammation as indicated by the reduced enumerated number of inflammatory cells in bronchoalveolar lavage as compared to FA-untreated allergic rats (OVA/OVA group). Treatment with FA also reduced the number of bone marrow cells and blood leukocytes in sensitized animals challenged with OVA, which suggests that the effects of FA had not been only localized to the airways. As indicated by passive cutaneous anaphylactic reaction, FA treatment did not impair the anti-OVA IgE synthesis, but reduced the magnitude of OVA challenge-induced mast cell degranulation. Moreover, FA treatment was associated to a diminished lung expression of PECAM-1 (platelet-endothelial cell adhesion molecule 1) in lung endothelial cells after OVA challenge and an exacerbated release of nitrites by BAL-cultured cells. Keeping in mind that rats subjected solely to either FA or OVA challenge were able to significantly increase the cell influx into lung, our study shows that FA inhalation triggers long-lasting effects that affect multiple mediator systems associated to OVA-induced allergic lung such as the reduction of mast cells activation, PECAM-1 expression and exacerbation of NO generation, thereby contributing to the decrease of cell recruitment after the OVA challenge. In conclusion, repeated expositions to air-borne FA may impair the lung cell recruitment after an allergic stimulus, thereby leading to a non-responsive condition against inflammatory stimuli likely those where mast cells are involved. (C) 2008 Elsevier Ireland Ltd. All rights reserved.

Fault Coverage-Driven Incremental Test Generation

In this paper, we consider a classical problem of complete test generation for deterministic finite-state machines (FSMs) in a more general setting. The first generalization is that the number of states in implementation FSMs can even be smaller than that of the specification FSM. Previous work deals only with the case when the implementation FSMs are allowed to have the same number of states as the specification FSM. This generalization provides more options to the test designer: when traditional methods trigger a test explosion for large specification machines, tests with a lower, but yet guaranteed, fault coverage can still be generated. The second generalization is that tests can be generated starting with a user-defined test suite, by incrementally extending it until the desired fault coverage is achieved. Solving the generalized test derivation problem, we formulate sufficient conditions for test suite completeness weaker than the existing ones and use them to elaborate an algorithm that can be used both for extending user-defined test suites to achieve the desired fault coverage and for test generation. We present the experimental results that indicate that the proposed algorithm allows obtaining a trade-off between the length and fault coverage of test suites.