Systematic Usage of Embedded Modelling Languages in Automated Model Transformation Chains

Annotation of programs using embedded Domain-Specific Languages (embedded DSLs), such as the program annotation facility for the Java programming language, is a well-known practice in computer science. In this paper we argue for and propose a specialized approach for the usage of embedded Domain-Specific Modelling Languages (embedded DSMLs) in Model-Driven Engineering (MDE) processes that in particular supports automated many-step model transformation chains. It can happen that information defined at some point, using an embedded DSML, is not required in the next immediate transformation step, but in a later one. We propose a new approach of model annotation enabling flexible many-step transformation chains. The approach utilizes a combination of embedded DSMLs, trace models and a megamodel. We demonstrate our approach based on an example MDE process and an industrial case study.

Decoherence-based exploration of d-dimensional one-way quantum computation: Information transfer and basic gates

We study the effects of amplitude and phase damping decoherence in d-dimensional one-way quantum computation. We focus our attention on low dimensions and elementary unidimensional cluster state resources. Our investigation shows how information transfer and entangling gate simulations are affected for d >= 2. To understand motivations for extending the one-way model to higher dimensions, we describe how basic qudit cluster states deteriorate under environmental noise of experimental interest. In order to protect quantum information from the environment, we consider encoding logical qubits into qudits and compare entangled pairs of linear qubit-cluster states to single qudit clusters of equal length and total dimension. A significant reduction in the performance of cluster state resources for d > 2 is found when Markovian-type decoherence models are present.

Quantum state transfer via temporal kicking of information

We propose a strategy for perfect state transfer in spin chains based on the use of an unmodulated coupling Hamiltonian whose coefficients are explicitly time dependent. We show that, if specific and nondemanding conditions are satisfied by the temporal behavior of the coupling strengths, our model allows perfect state transfer. The paradigm put forward by our proposal holds the promises to set an alternative standard to the use of clever encoding and coupling-strength engineering for perfect state transfer.

A Bayesian Network Hybrid Model for Representing Accident and Emergency Waiting Times

The paper introduces a new modeling approach that represents the waiting times in an Accident and Emergency (A&E) Department in a UK based National Health Service (NHS) hospital. The technique uses Bayesian networks to capture the heterogeneity of arriving patients by representing how patient covariates interact to influence their waiting times in the department. Such waiting times have been reviewed by the NHS as a means of investigating the efficiency of A&E departments (Emergency Rooms) and how they operate. As a result activity targets are now established based on the patient total waiting times with much emphasis on trolley waits.

A Tower-Shadow Model for Wind Turbines Using a Wavelet-Prony Method

The increasing penetration of wind generation on the Island of Ireland has been accompanied by close investigation of low-frequency pulsations contained within active power flow. A primary concern is excitation of low-frequency oscillation modes already present on the system, particularly the 0.75 Hz mode as a consequence of interconnection between the Northern and Southern power system networks. In order to determine whether the prevalence of wind generation has a negative effect (excites modes) or positive impact (damping of modes) on the power system, oscillations must be measured and characterised. Using time – frequency methods, this paper presents work that has been conducted to extract features from low-frequency active power pulsations to determine the composition of oscillatory modes which may impact on dynamic stability. The paper proposes a combined wavelet-Prony method to extract modal components and determine damping factors. The method is exemplified using real data obtained from wind farm measurements.

Dynamic pricing model and algorithm for perishable products with fuzzy demand (ABS 2* Journal)

This paper studies the dynamic pricing problem of selling fixed stock of perishable items over a finite horizon, where the decision maker does not have the necessary historic data to estimate the distribution of uncertain demand, but has imprecise information about the quantity demand. We model this uncertainty using fuzzy variables. The dynamic pricing problem based on credibility theory is formulated using three fuzzy programming models, viz.: the fuzzy expected revenue maximization model, a-optimistic revenue maximization model, and credibility maximization model. Fuzzy simulations for functions with fuzzy parameters are given and embedded into a genetic algorithm to design a hybrid intelligent algorithm to solve these three models. Finally, a real-world example is presented to highlight the effectiveness of the developed model and algorithm.

Spatial Allocation of Material Flow Analysis: A Geographic Information System Application of Material Flow Analysis in Ireland

This study concerns the spatial allocation of material flows, with emphasis on construction material in the Irish housing sector. It addresses some of the key issues concerning anthropogenic impact on the environment through spatial temporal visualisation of the flow of materials, wastes and emissions at different spatial levels. This is presented in the form of a spatial model, Spatial Allocation of Material Flow Analysis (SAMFA), which enables the simulation of construction material flows and associated energy use. SAMFA parallels the Island Limits project (EPA funded under 2004-SD-MS-22-M2), which aimed to create a material flow analysis of the Irish economy classified by industrial sector. SAMFA further develops this by attempting to establish the material flows at the subnational geographical scale that could be used in the development of local authority (LA) sustainability strategies and spatial planning frameworks by highlighting the cumulative environmental impacts of the development of the built environment. By drawing on the idea of planning support systems, SAMFA also aims to provide a cross-disciplinary, integrative medium for involving stakeholders in strategies for a sustainable built environment and, as such, would help illustrate the sustainability consequences of alternative The pilot run of the model in Kildare has shown that the model can be successfully calibrated and applied to develop alternative material flows and energy-use scenarios at the ED level. This has been demonstrated through the development of an integrated and a business-as-usual scenario, with the former integrating a range of potential material efficiency and energysaving policy options and the latter replicating conditions that best describe the current trend. Their comparison shows that the former is better than the latter in terms of both material and energy use. This report also identifies a number of potential areas of future research and areas of broader application. This includes improving the accuracy of the SAMFA model (e.g. by establishing actual life expectancy of buildings in the Irish context through field surveys) and the extension of the model to other Irish counties. This would establish SAMFA as a valuable predicting and monitoring tool that is capable of integrating national and local spatial planning objectives with actual environmental impacts. Furthermore, should the model prove successful at this level, it then has the potential to transfer the modelling approach to other areas of the built environment, such as commercial development and other key contributors of greenhouse emissions. The ultimate aim is to develop a meta-model for predicting the consequences of consumption patterns at the local scale. This therefore offers the possibility of creating critical links between socio technical systems with the most important challenge of all the limitations of the biophysical environment.

A Cluster Randomized Controlled Trial of an Adapted U.S. Model of Pharmaceutical Care for Nursing Home Residents in Northern Ireland (Fleetwood Northern Ireland Study): A Cost-Effectiveness Analysis

OBJECTIVES: To evaluate the cost-effectiveness of an adapted U.S. model of pharmaceutical care to improve psychoactive prescribing for nursing home residents in Northern Ireland (Fleetwood NI Study).
DESIGN: Economic evaluation alongside a cluster randomized controlled trial.
SETTING: Nursing homes in NI randomized to intervention (receipt of the adapted model of care; n511) or control (usual care continued; n511).
PARTICIPANTS: Residents aged 65 and older who provided informed consent (N5253; 128 intervention, 125 control) and who had full resource use data at 12 months.
INTERVENTION: Trained pharmacists reviewed intervention home residents’ clinical and prescribing information for 12 months, applied an algorithm that guided them in assessing the appropriateness of psychoactive medication, and worked with prescribers (general practitioners) to make changes. The control homes received usual care in which there was no pharmacist intervention.
MEASUREMENTS: The proportion of residents prescribed one or more inappropriate psychoactive medications (according to standardized protocols), costs, and a cost-effectiveness acceptability curve. The latter two outcomes are the focus for this article.
RESULTS: The proportions of residents receiving inappropriate psychoactive medication at 12 months in the intervention and control group were 19.5% and 50.4%, respectively. The mean cost of healthcare resources used per resident per year was $4,923 (95% con?dence interval.

Physical model for the generation of ideal resources in multipartite quantum networking

We propose a physical model for generating multipartite entangled states of spin-s particles that have important applications in distributed quantum information processing. Our protocol is based on a process where mobile spins induce the interaction among remote scattering centers. As such, a major advantage lies in the management of stationary and well-separated spins. Among the generable states, there is a class of N-qubit singlets allowing for optimal quantum telecloning in a scalable and controllable way. We also show how to prepare Aharonov, W, and Greenberger-Horne-Zeilinger states.

An evaluation of an adapted United States model of pharmaceutical care to improve psychoactive prescribing for nursing home residents in Northern Ireland (Fleetwood NI Study).

OBJECTIVES: To test the effect of an adapted U.S. model of pharmaceutical care on prescribing of inappropriate psychoactive (anxiolytic, hypnotic, and antipsychotic) medications and falls in nursing homes for older people in Northern Ireland (NI).

DESIGN: Cluster randomized controlled trial.

SETTING: Nursing homes randomized to intervention (receipt of the adapted model of care; n=11) or control (usual care continued; n=11).

PARTICIPANTS: Residents aged 65 and older who provided informed consent (N=334; 173 intervention, 161 control).

INTERVENTION: Specially trained pharmacists visited intervention homes monthly for 12 months and reviewed residents' clinical and prescribing information, applied an algorithm that guided them in assessing the appropriateness of psychoactive medication, and worked with prescribers (general practitioners) to improve the prescribing of these drugs. The control homes received usual care.

MEASUREMENTS: The primary end point was the proportion of residents prescribed one or more inappropriate psychoactive medicine according to standardized protocols; falls were evaluated using routinely collected falls data mandated by the regulatory body for nursing homes in NI.

RESULTS: The proportion of residents taking inappropriate psychoactive medications at 12 months in the intervention homes (25/128, 19.5%) was much lower than in the control homes (62/124, 50.0%) (odds ratio=0.26, 95% confidence interval=0.14–0.49) after adjustment for clustering within homes. No differences were observed at 12 months in the falls rate between the intervention and control groups.

CONCLUSION: Marked reductions in inappropriate psychoactive medication prescribing in residents resulted from pharmacist review of targeted medications, but there was no effect on falls.

Quantifying, characterizing, and controlling information flow in ultracold atomic gases

We study quantum information flow in a model comprised of a trapped impurity qubit immersed in a Bose-Einstein-condensed reservoir. We demonstrate how information flux between the qubit and the condensate can be manipulated by engineering the ultracold reservoir within experimentally realistic limits. We show that this system undergoes a transition from Markovian to non-Markovian dynamics, which can be controlled by changing key parameters such as the condensate scattering length. In this way, one can realize a quantum simulator of both Markovian and non-Markovian open quantum systems, the latter ones being characterized by a reverse flow of information from the background gas (reservoir) to the impurity (system).

Combining multisensory temporal information for movement synchronisation

The ability to synchronise actions with environmental events is a fundamental skill supporting a variety of group activities. In such situations, multiple sensory cues are usually available for synchronisation, yet previous studies have suggested that auditory cues dominate those from other modalities. We examine the control of rhythmic action on the basis of auditory and haptic cues and show that performance is sensitive to both sources of information for synchronisation. Participants were required to tap the dominant hand index finger in synchrony with a metronome defined by periodic auditory tones, imposed movements of the non-dominant index finger, or both cues together. Synchronisation was least variable with the bimodal metronome as predicted by a maximum likelihood estimation (MLE) model. However, increases in timing variability of the auditory cue resulted in some departures from the MLE model. Our findings indicate the need for further investigation of the MLE account of the integration of multisensory signals in the temporal control of action.