Self-assembled low-dimensional nanomaterials via low-temperature plasma processing

Examples of successful fabrication of low-dimensional semiconducting nanomaterials in the Integrated Plasma-Aided Nanofabrication Facility are shown. Self-assembled size-uniform ZnO nanoparticles, ultra-high-aspect ratio Si nanowires, vertically aligned cadmium sulfide nanostructures, and quarternary semiconducting SiCAlN nanomaterial have been synthesized using inductively coupled plasma-assisted RF magnetron sputtering deposition. The observed increase in crystallinity and growth rates of the nanostructures are explained by using a model of plasma-enhanced adatom surface diffusion under conditions of local energy exchange between the ion flux and the growth surface. Issues related to plasma-based growth of low-dimensional semiconducting nanomaterials are discussed as well. © 2007 Elsevier B.V. All rights reserved.

Lattice-based threshold-changeability for standard CRT secret-sharing schemes

We consider the problem of increasing the threshold parameter of a secret-sharing scheme after the setup (share distribution) phase, without further communication between the dealer and the shareholders. Previous solutions to this problem require one to start off with a non-standard scheme designed specifically for this purpose, or to have secure channels between shareholders. In contrast, we show how to increase the threshold parameter of the standard CRT secret-sharing scheme without secure channels between the shareholders. Our method can thus be applied to existing CRT schemes even if they were set up without consideration to future threshold increases. Our method is a positive cryptographic application for lattice reduction algorithms, and we also use techniques from lattice theory (geometry of numbers) to prove statements about the correctness and information-theoretic security of our constructions.

Lattice-based threshold-changeability for standard Shamir secret-sharing schemes

We consider the problem of increasing the threshold parameter of a secret-sharing scheme after the setup (share distribution) phase, without further communication between the dealer and the shareholders. Previous solutions to this problem require one to start off with a non-standard scheme designed specifically for this purpose, or to have communication between shareholders. In contrast, we show how to increase the threshold parameter of the standard Shamir secret-sharing scheme without communication between the shareholders. Our technique can thus be applied to existing Shamir schemes even if they were set up without consideration to future threshold increases. Our method is a new positive cryptographic application for lattice reduction algorithms, inspired by recent work on lattice-based list decoding of Reed-Solomon codes with noise bounded in the Lee norm. We use fundamental results from the theory of lattices (Geometry of Numbers) to prove quantitative statements about the information-theoretic security of our construction. These lattice-based security proof techniques may be of independent interest.

Integrated chronic disease management in primary-secondary care : a systematic literature review of the evidence

Introduction: Diabetes has traditionally been managed as a single chronic disease state, but it exists with co-morbidities such as depression and metabolic syndrome. Treatment is multifaceted, requiring both primary and secondary care, however, the delivery of diabetes care is often fragmented. Integrated chronic disease management is a growing model of interest, and is underpinned by the chronic care model (CCM), devised as a guide for primary care management of patients with chronic conditions. The model identifies six key elements for effective care, and has shown promise in improving the management of diabetes. Aim: To find empirical evidence of integrated care interventions targeted at co-morbidities including diabetes, across primary/secondary care. Method: A systematic review of peer reviewed literature from PubMed, CINAHL, Embase, Cochrane Library and Joanna Briggs was performed. Studies were reviewed according to inclusion criteria- studies published in English, between 2004-2014, empirical studies, studies with evidence of primary/secondary implementation, and those dealing with chronic co-morbid disease states. Results: 51 studies met the inclusion criteria. Included studies were mostly from the US (38), with five from Australia, UK (2), Canada (2), Netherlands (1), Norway (1), Ireland (1), and one multi-country study. It was found that all interventions adopted at least one (average 3-4) of the chronic care model, with the majority implementing delivery system redesign activities within the primary care practice/s. We found evidence of interventions which significantly reduced emergency department and hospital admissions, improved processes of care, patient health outcomes such as HbA1c, improved patient satisfaction, and reduced costs. Conclusion/Implications for practice: Diabetes exists as a co-morbid disease, requiring both primary and secondary care. We found that integrated care interventions adopting elements of the chronic care model positively impacted on patient outcomes, service utilisation, as well as costs. This review has highlighted that it may not be necessary to adopt all CCM elements to improve clinical outcomes, patient satisfaction and costs.

Minimizing the effects of overfitting and collinearity in construction cost estimation : a new hybird approach

Research problem: Overfitting and collinearity problems commonly exist in current construction cost estimation applications and obstruct researchers and practitioners in achieving better modelling results. Research objective and method: A hybrid approach of Akaike information criterion (AIC) stepwise regression and principal component regression (PCR) is proposed to help solve overfitting and collinearity problems. Utilization of this approach in linear regression is validated by comparing it with other commonly used approaches. The mean square error obtained by leave-one-out cross validation (MSELOOCV) is used in model selection in deciding predictive variables.

Choosing an appropriate modelling framework for analysing multispecies co-culture cell biology experiments

In vitro cell biology assays play a crucial role in informing our understanding of the migratory, proliferative and invasive properties of many cell types in different biological contexts. While mono-culture assays involve the study of a population of cells composed of a single cell type, co-culture assays study a population of cells composed of multiple cell types (or subpopulations of cells). Such co-culture assays can provide more realistic insights into many biological processes including tissue repair, tissue regeneration and malignant spreading. Typically, system parameters, such as motility and proliferation rates, are estimated by calibrating a mathematical or computational model to the observed experimental data. However, parameter estimates can be highly sensitive to the choice of model and modelling framework. This observation motivates us to consider the fundamental question of how we can best choose a model to facilitate accurate parameter estimation for a particular assay. In this work we describe three mathematical models of mono-culture and co-culture assays that include different levels of spatial detail. We study various spatial summary statistics to explore if they can be used to distinguish between the suitability of each model over a range of parameter space. Our results for mono-culture experiments are promising, in that we suggest two spatial statistics that can be used to direct model choice. However, co-culture experiments are far more challenging: we show that these same spatial statistics which provide useful insight into mono-culture systems are insuffcient for co-culture systems. Therefore, we conclude that great care ought to be exercised when estimating the parameters of co-culture assays.

Collaborative learning model of infrastructure construction: A capability perspective

Purpose Performance heterogeneity between collaborative infrastructure projects is typically examined by considering procurement systems and their governance mechanisms at static points in time. The literature neglects to consider the impact of dynamic learning capability, which is thought to reconfigure governance mechanisms over time in response to evolving market conditions. This conceptual paper proposes a new model to show how continuous joint learning of participant organisations improves project performance. Design/methodology/approach There are two stages of conceptual development. In the first stage, the management literature is analysed to explain the Standard Model of dynamic learning capability that emphasises three learning phases for organisations. This Standard Model is extended to derive a novel Circular Model of dynamic learning capability that shows a new feedback loop between performance and learning. In the second stage, the construction management literature is consulted, adding project lifecycle, stakeholder diversity and three organisational levels to the analysis, to arrive at the Collaborative Model of dynamic learning capability. Findings The Collaborative Model should enable construction organisations to successfully adapt and perform under changing market conditions. The complexity of learning cycles results in capabilities that are imperfectly imitable between organisations, explaining performance heterogeneity on projects. Originality/value The Collaborative Model provides a theoretically substantiated description of project performance, driven by the evolution of procurement systems and governance mechanisms. The Model’s empirical value will be tested in future research.

Memory of past random wave conditions in submarine groundwater discharge

Submarine groundwater discharge (SGD) is an integral part of the hydrological cycle and represents an important aspect of land-ocean interactions. We used a numerical model to simulate flow and salt transport in a nearshore groundwater aquifer under varying wave conditions based on yearlong random wave data sets, including storm surge events. The results showed significant flow asymmetry with rapid response of influxes and retarded response of effluxes across the seabed to the irregular wave conditions. While a storm surge immediately intensified seawater influx to the aquifer, the subsequent return of intruded seawater to the sea, as part of an increased SGD, was gradual. Using functional data analysis, we revealed and quantified retarded, cumulative effects of past wave conditions on SGD including the fresh groundwater and recirculating seawater discharge components. The retardation was characterized well by a gamma distribution function regardless of wave conditions. The relationships between discharge rates and wave parameters were quantifiable by a regression model in a functional form independent of the actual irregular wave conditions. This statistical model provides a useful method for analyzing and predicting SGD from nearshore unconfined aquifers affected by random waves

Tax principles and tax harmonization under imperfect competition: A cautionary example

This paper shows that under imperfect competition, the welfare effects of indirect tax harmonization may depend crucially on whether taxes are levied by the destination or the origin principle. In a standard model of imperfect competition, while harmonization always makes at least one country better off, and may be Pareto-improving, when taxes are levied under the destination principle (which currently applies in the European Union), harmonization of origin-based taxes (as recently proposed by the European Commission) is certain to be Pareto-worsening when the preferences in the two countries are identical, and is likely to be so even when they differ.