Two dynamic discrete choice estimation problems and simulation method solutions

This paper considers two problems that frequently arise in dynamic discrete choice problems but have not received much attention with regard to simulation methods. The first problem is how to simulate unbiased simulators of probabilities conditional on past history. The second is simulating a discrete transition probability model when the underlying dependent variable is really continuous. Both methods work well relative to reasonable alternatives in the application discussed. However, in both cases, for this application, simpler methods also provide reasonably good results.

A framework to analyze the impact of sustainable infrastructure on human productivity

The built environment has a profound impact on our natural environment, economy, health and productivity. As the majority of the people spent most of their time inside buildings, the environment in which they perform their daily activities will have an impact on their health and productivity. Studies have been conducted about the negative impacts of presence of non-favorable conditions to human health and well being. The term "Sick Building Syndrome" (SBS) is used to describe situations in which building occupants experience acute health and comfort problems that appear to be linked to their time spent in a building. Sustainable infrastructure rating systems have requirements intended to improve occupant productivity and health.While the impact of Sustainable Infrastructure in energy consumption and waste/water reduction can be measured using available tools, the impact on productivity remained as an assumption that is not clearly measured. The purpose of this research is to develop a framework to assess whether the impacts of the incorporation of features intended to improve occupants’ performance and health such as: increased ventilation, lightning and thermal comfort serve their intended purpose.

A survey in mathematics for industry: Two-timing and matched asymptotic expansions for singular perturbation problems

Following the derivation of amplitude equations through a new two-time-scale method [O'Malley, R. E., Jr. & Kirkinis, E (2010) A combined renormalization group-multiple scale method for singularly perturbed problems. Stud. Appl. Math. 124, 383-410], we show that a multi-scale method may often be preferable for solving singularly perturbed problems than the method of matched asymptotic expansions. We illustrate this approach with 10 singularly perturbed ordinary and partial differential equations. © 2011 Cambridge University Press.

A Combined Renormalization Group-Multiple Scale Method for Singularly Perturbed Problems

This paper introduces a straightforward method to asymptotically solve a variety of initial and boundary value problems for singularly perturbed ordinary differential equations whose solution structure can be anticipated. The approach is simpler than conventional methods, including those based on asymptotic matching or on eliminating secular terms. © 2010 by the Massachusetts Institute of Technology.

Amplitude equations and asymptotic expansions for multi-scale problems

In this paper we introduce a new technique to obtain the slow-motion dynamics in nonequilibrium and singularly perturbed problems characterized by multiple scales. Our method is based on a straightforward asymptotic reduction of the order of the governing differential equation and leads to amplitude equations that describe the slowly-varying envelope variation of a uniformly valid asymptotic expansion. This may constitute a simpler and in certain cases a more general approach toward the derivation of asymptotic expansions, compared to other mainstream methods such as the method of Multiple Scales or Matched Asymptotic expansions because of its relation with the Renormalization Group. We illustrate our method with a number of singularly perturbed problems for ordinary and partial differential equations and recover certain results from the literature as special cases. © 2010 - IOS Press and the authors. All rights reserved.

Increased size selectivity of Si quantum dots on SiC at low substrate temperatures : an ion-assisted self-organization approach

A simple, effective, and innovative approach based on ion-assisted self-organization is proposed to synthesize size-selected Si quantum dots (QDs) on SiC substrates at low substrate temperatures. Using hybrid numerical simulations, the formation of Si QDs through a self-organization approach is investigated by taking into account two distinct cases of Si QD formation using the ionization energy approximation theory, which considers ionized in-fluxes containing Si3+ and Si1+ ions in the presence of a microscopic nonuniform electric field induced by a variable surface bias. The results show that the highest percentage of the surface coverage by 1 and 2 nm size-selected QDs was achieved using a bias of -20 V and ions in the lowest charge state, namely, Si1+ ions in a low substrate temperature range (227-327 °C). As low substrate temperatures (≤500 °C) are desirable from a technological point of view, because (i) low-temperature deposition techniques are compatible with current thin-film Si-based solar cell fabrication and (ii) high processing temperatures can frequently cause damage to other components in electronic devices and destroy the tandem structure of Si QD-based third-generation solar cells, our results are highly relevant to the development of the third-generation all-Si tandem photovoltaic solar cells.

Tailoring microplasma nanofabrication : from nanostructures to nanoarchitectures

An innovative approach to fabricate tailored Mo-oxide nanostructures and composite nanoarchitectures using atmospheric microplasmas sustained in a gap between a Mo wire and a Si substrate is reported. It is shown that at smaller gap distances spherical nanoparticles are produced whereas sheet-like structures emerge when the gap is increased. When the wire is consumed continuously, it is possible to synthesize complex nanoarchitectures made of nanoparticles decorated with nanosheets. These processes can be applied for other metal and metal oxide materials and suggest a way to improve control and predictability, common problems in high-yield nanofabrication.

Series in vector spherical harmonics : an efficient tool for solution of nonlinear problems in spherical plasmas

The series expansion of the plasma fields and currents in vector spherical harmonics has been demonstrated to be an efficient technique for solution of nonlinear problems in spherically bounded plasmas. Using this technique, it is possible to describe the nonlinear plasma response to the rotating high-frequency magnetic field applied to the magnetically confined plasma sphere. The effect of the external magnetic field on the current drive and field configuration is studied. The results obtained are important for continuous current drive experiments in compact toruses. © 2000 American Institute of Physics.

Quantitative analysis of survivin in colorectal adenocarcinoma : increased expression and correlation with telomerase activity

The aims of the present study are to quantitatively analyze survivin expression, its clinicopathologic roles, and correlation with telomerase activity in a large cohort of patients with colorectal adenocarcinoma. Real-time polymerase chain reaction was used to quantitate expression level of survivin messenger RNA and human telomerase reverse transcriptase messenger RNA (telomerase activity) in 51 patients with colorectal adenocarcinomas. The findings were correlated with the clinicopathologic features of patients, which were prospectively collected into a computerized database. Survivin messenger RNA was expressed in all tumor samples. The level of expression in tumor tissues was increased in comparison with matched nontumor mucosa in the same patient (P = .01). The level of expression of survivin was significantly correlated with the level of human telomerase reverse transcriptase expression (P = .008) and size of the colorectal adenocarcinomas (P = .004). Survival of the patients with colorectal adenocarcinoma was associated with the TNM stages (P = .001) and not with the level of expression of survivin. Thus, survivin activity was altered in colorectal adenocarcinoma. The high prevalence of survivin expression and correlation with telomerase activity are important factors for consideration in gene targeting therapy for colorectal adenocarcinoma.

Using enterprise information architecture methods to model wicked problems in information systems design research

Design Science is the process of solving ‘wicked problems’ through designing, developing, instantiating, and evaluating novel solutions (Hevner, March, Park and Ram, 2004). Wicked problems are described as agent finitude in combination with problem complexity and normative constraint (Farrell and Hooker, 2013). In Information Systems Design Science, determining that problems are ‘wicked’ differentiates Design Science research from Solutions Engineering (Winter, 2008) and is a necessary part of proving the relevance to Information Systems Design Science research (Hevner, 2007; Iivari, 2007). Problem complexity is characterised as many problem components with nested, dependent and co-dependent relationships interacting through multiple feedback and feed-forward loops. Farrell and Hooker (2013) specifically state for wicked problems “it will often be impossible to disentangle the consequences of specific actions from those of other co-occurring interactions”. This paper discusses the application of an Enterprise Information Architecture modelling technique to disentangle the wicked problem complexity for one case. It proposes that such a modelling technique can be applied to other wicked problems and can lay the foundations for proving relevancy to DSR, provide solution pathways for artefact development, and aid to substantiate those elements required to produce Design Theory.

Influence and increased funding in Canadian public libraries : the case of Alberta in fiscal year 2009–10

This exploratory case study examined the role of social influence in the decision-making process to increase public library funding in the Canadian province of Alberta in the 2009–10 fiscal year. Using Robert Cialdini’s theory of factors of influence (i.e., commitment and consistency, authority, liking, social proof, scarcity, and reciprocity) as a framework for analysis, findings show that consistency and commitment and authority were relevant and that liking was also important. These findings are consistent with Cialdini’s theory, which suggests that the quality of relationships is one factor that can most strongly influence a decision maker. This study gives insight into the factors motivating those involved in public library funding allocation decisions. No prior studies have examined the construct of influence in decision making about funding for public libraries at any level of government.

Review and future options for computer modelling in the sugar industry

Computer modelling has been used extensively in some processes in the sugar industry to achieve significant gains. This paper reviews the investigations carried out over approximately the last twenty five years,including the successes but also areas where problems and delays have been encountered. In that time the capability of both hardware and software have increased dramatically. For some processes such as cane cleaning, cane billet preparation, and sugar drying, the application of computer modelling towards improved equipment design and operation has been quite limited. A particular problem has been the large number of particles and particle interactions in these applications, which, if modelled individually, is computationally very intensive. Despite the problems, some attempts have already been made and knowledge gained on tackling these issues. Even if the detailed modelling is wanting, a model can provide some useful insights into the processes. Some options to attack these more intensive problems include the use of commercial software packages, which are usually very robust and allow the addition of user-supplied subroutines to adapt the software to particular problems. Suppliers of such software usually charge a fee per CPU licence, which is often problematic for large problems that require the use of many CPUs. Another option to consider is using open source software that has been developed with the capability to access large parallel resources. Such software has the added advantage of access to the full internal coding. This paper identifies and discusses the detail of software options with the potential capability to achieve improvements in the sugar industry.

The educational design ladder : creation of a multi-discipline design thinking program

As global industries change and technology advances, traditional education systems may no longer be able to supply companies with graduates possessing an appropriate mix of skills and experience. The recent increased interest in Design Thinking as an approach to innovation has resulted in its adoption by non-design trained professionals. This necessitates a new method of teaching Design Thinking related skills and processes. This research investigates what (content) and how (assessment and learning modes) Design Thinking is being taught from fifty-one (51) selected courses across twenty-eight (28) international universities. Their approaches differ, with some universities specifically investing in design schools and programs, while others embed Design Thinking holistically throughout the university. Business, engineering and design schools are all expanding their efforts to teach students how to innovate, often through multi-disciplinary classes. This paper presents ‘The Educational Design Ladder’ a resource model, which suggests a process for the organisation and structuring of units for a multi-disciplinary Design Thinking program. The intention is to provide 21st century graduates with the right combination of skills and experience to solve workplace design problems regardless of their core discipline.

A review of modern computational algorithms for Bayesian optimal design

Bayesian experimental design is a fast growing area of research with many real-world applications. As computational power has increased over the years, so has the development of simulation-based design methods, which involve a number of algorithms, such as Markov chain Monte Carlo, sequential Monte Carlo and approximate Bayes methods, facilitating more complex design problems to be solved. The Bayesian framework provides a unified approach for incorporating prior information and/or uncertainties regarding the statistical model with a utility function which describes the experimental aims. In this paper, we provide a general overview on the concepts involved in Bayesian experimental design, and focus on describing some of the more commonly used Bayesian utility functions and methods for their estimation, as well as a number of algorithms that are used to search over the design space to find the Bayesian optimal design. We also discuss other computational strategies for further research in Bayesian optimal design.

The impact of diabetic ketoacidosis and age on behavior six months post-diagnosis in children with type 1 diabetes

Objectives: Children with type 1 diabetes mellitus (DM1) may be at increased risk of psychosocial and adjustment difficulties. We examined behavioral outcomes six months post-diagnosis in a group of children with newly diagnosed DM1. Methods: This study formed part of a larger longitudinal project examining pathophysiology and neuropsychological outcomes in diabetic patients with or without diabetic ketoacidosis (DKA). Participants were 61 children (mean age 11.8 years, SD 2.7 years) who presented with a new diagnosis of DM1 at the Royal Children’s Hospital, Melbourne. Twenty-three (11 female) presented in DKA and 38 (14 female) without DKA. Parents completed the behavior assessment system for children, second edition six months post-diagnosis. Results: There was a non-linear relationship between age and behavior. Internalising problems (i.e. anxiety depression, withdrawal) peaked in the transition from childhood to adolescence; children aged 10–13 years had elevated rates relative to the normal population (t = 2.55, P = 0.018). There was a non-significant trend for children under 10 to display internalising problems (P = 0.052), but rates were not elevated in children over 13 (P = 0.538). Externalising problems were not significantly elevated in any age group. Interestingly, children who presented in DKA were at lower risk of internalising problems than children without DKA (t = 3.83, P < 0.001). There was no effect of DKA on externalising behaviors. Conclusions: Children transitioning from childhood to adolescence are at significant risk for developing internalising problems such as anxiety and lowered mood after diagnosis of DM1. Somewhat counter-intuitively, parents of children presenting in DKA reported fewer internalising symptoms than parents of children without DKA. These results highlight the importance of monitoring and supporting psychosocial adjustment in newly diagnosed children even when they seem physically well.