Creative thinking experimentations for entrepreneurship with a disruptive, personalised and mobile game-based learning ecosystem

Based on an unprecedented need of stimulating creative capacities towards entrepreneurship to university students and young researchers, this paper introduces and analyses a smart learning ecosystem for encouraging teaching and learning on creative thinking as a distinct feature to be taught and learnt in universities. The paper introduces a mashed-up authoring architecture for designing lesson-plans and games with visual learning mechanics for creativity learning. The design process is facilitated by creativity pathways discerned across components. Participatory learning, networking and capacity building is a key aspect of the architecture, extending the learning experience and context from the classroom to outdoor (co-authoring of creative pathways by students, teachers and real-world entrepreneurs) and personal spaces. We anticipate that the smart learning ecosystem will be empirically evaluated and validated in future iterations for exploring the benefits of using games for enhancing creative mindsets, unlocking the imagination that lies within, practiced and transferred to multiple academic tribes and territories.

On-line puzzle game based assessment & training for ADHD

Attention-deficit hyperactivity disorder (ADHD) is the most prevalent and impairing neurodevelopmental disorder, with worldwide estimates of 5.29%. ADHD is clinically characterized by hyperactivity-impulsivity and inattention, with neuropsychological deficits in executive functions, attention, working memory and inhibition. These cognitive processes rely on prefrontal cortex function; cognitive training programs enhance performance of ADHD participants supporting the idea of neuronal plasticity. Here we propose the development of an on-line puzzle game based assessment and training tool in which participants must deduce the ‘winning symbol’ out of N distracters. To increase ecological validity of assessments strategically triggered Twitter/Facebook notifications will challenge the ability to ignore distracters. In the UK, significant cost for the disorder on health, social and education services, stand at £23m a year. Thus the potential impact of neuropsychological assessment and training to improve our understanding of the pathophysiology of ADHD, and hence our treatment interventions and patient outcomes, cannot be overstated.

A mathematical model for assembly line balancing model to consider disordering sequence of workstations

Purpose – A binary integer programming model for the simple assembly line balancing problem (SALBP), which is well known as SALBP-1, was formulated more than 30 years ago. Since then, a number of researchers have extended the model for the variants of assembly line balancing problem.The model is still prevalent nowadays mainly because of the lower and upper bounds on task assignment. These properties avoid significant increase of decision variables. The purpose of this paper is to use an example to show that the model may lead to a confusing solution. Design/methodology/approach – The paper provides a remedial constraint set for the model to rectify the disordered sequence problem. Findings – The paper presents proof that the assembly line balancing model formulated by Patterson and Albracht may lead to a confusing solution. Originality/value – No one previously has found that the commonly used model is incorrect.

Performance measurement based co-ordination of enterprise resource planning systems in a virtual enterprise

As the backbone of e-business, Enterprise Resource Planning (ERP)system plays an important role in today's competitive business environment. Few publications discuss the application of ERP systems in a virtual enterprise (VE). A VE is defined as a dynamic partnership among enterprises that can bring together complementary core competencies needed to achieve a business task. Since VE strongly emphasises partner cooperation, specific issues exist relative to the implementation of ERP systems in a VE. This paper discusses the use of VE Performance Measurement System(VEPMS) to coordinate ERP systems of VE partners. It also defines the framework of a `Virtual Enterprise Resource Planning (VERP) system', and identifies research avenues in this field.

Web based expert elicitation of uncertainties in environmental model inputs

When constructing and using environmental models, it is typical that many of the inputs to the models will not be known perfectly. In some cases, it will be possible to make observations, or occasionally physics-based uncertainty propagation, to ascertain the uncertainty on these inputs. However, such observations are often either not available or even possible, and another approach to characterising the uncertainty on the inputs must be sought. Even when observations are available, if the analysis is being carried out within a Bayesian framework then prior distributions will have to be specified. One option for gathering or at least estimating this information is to employ expert elicitation. Expert elicitation is well studied within statistics and psychology and involves the assessment of the beliefs of a group of experts about an uncertain quantity, (for example an input / parameter within a model), typically in terms of obtaining a probability distribution. One of the challenges in expert elicitation is to minimise the biases that might enter into the judgements made by the individual experts, and then to come to a consensus decision within the group of experts. Effort is made in the elicitation exercise to prevent biases clouding the judgements through well-devised questioning schemes. It is also important that, when reaching a consensus, the experts are exposed to the knowledge of the others in the group. Within the FP7 UncertWeb project (http://www.uncertweb.org/), there is a requirement to build a Webbased tool for expert elicitation. In this paper, we discuss some of the issues of building a Web-based elicitation system - both the technological aspects and the statistical and scientific issues. In particular, we demonstrate two tools: a Web-based system for the elicitation of continuous random variables and a system designed to elicit uncertainty about categorical random variables in the setting of landcover classification uncertainty. The first of these examples is a generic tool developed to elicit uncertainty about univariate continuous random variables. It is designed to be used within an application context and extends the existing SHELF method, adding a web interface and access to metadata. The tool is developed so that it can be readily integrated with environmental models exposed as web services. The second example was developed for the TREES-3 initiative which monitors tropical landcover change through ground-truthing at confluence points. It allows experts to validate the accuracy of automated landcover classifications using site-specific imagery and local knowledge. Experts may provide uncertainty information at various levels: from a general rating of their confidence in a site validation to a numerical ranking of the possible landcover types within a segment. A key challenge in the web based setting is the design of the user interface and the method of interacting between the problem owner and the problem experts. We show the workflow of the elicitation tool, and show how we can represent the final elicited distributions and confusion matrices using UncertML, ready for integration into uncertainty enabled workflows.We also show how the metadata associated with the elicitation exercise is captured and can be referenced from the elicited result, providing crucial lineage information and thus traceability in the decision making process.

A technique to randomise consecutive codons in a sequence of DNA using MAX oligonucleotides

Randomisation of DNA using conventional methodology requires an excess of genes to be cloned, since with randomised codons NNN or NNG/T 64 genes or 32 genes must be cloned to encode 20 amino acids respectively. Thus, as the number of randomised codons increases, the number of genes required to encode a full set of proteins increases exponentially. Various methods have been developed that address the problems associated with excess of genes that occurs due to the degeneracy of the genetic code. These range from chemical methodologies to biological methods. These all involve the replacement, insertion or deletion of codon(s) rather than individual nucleotides. The biological methods are however limited to random insertion/deletion or replacement. Recent work by Hughes et al., (2003) has randomised three binding residues of a zinc finger gene. The drawback with this is the fact that consecutive codons cannot undergo saturation mutagenesis. This thesis describes the development of a method of saturation mutagenesis that can be used to randomise any number of consecutive codons in a DNA strand. The method makes use of “MAX” oligonucleotides coding for each of the 20 amino acids that are ligated to a conserved sequence of DNA using T4 DNA ligase. The “MAX” oligonucleotides were synthesised in such a way, with an MlyI restriction site, that restriction of the oligonucleotides occurred after the three nucleotides coding for the amino acids. This use of the MlyI site and the restrict, purify, ligate and amplify method allows the insertion of “MAX” codons at any position in the DNA. This methodology reduces the number of clones that are required to produce a representative library and has been demonstrated to be effective to 7 amino acid positions.

An information foraging theory based user study of an adaptive user interaction framework for content-based image retrieval

This paper presents the design and results of a task-based user study, based on Information Foraging Theory, on a novel user interaction framework - uInteract - for content-based image retrieval (CBIR). The framework includes a four-factor user interaction model and an interactive interface. The user study involves three focused evaluations, 12 simulated real life search tasks with different complexity levels, 12 comparative systems and 50 subjects. Information Foraging Theory is applied to the user study design and the quantitative data analysis. The systematic findings have not only shown how effective and easy to use the uInteract framework is, but also illustrate the value of Information Foraging Theory for interpreting user interaction with CBIR. © 2011 Springer-Verlag Berlin Heidelberg.

Evidence based pharmacogenetics study of the use of anti-psychotics in treatment of schizophrenia

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Subject identification via ECG fiducial-based systems:influence of the type of QT interval correction

Electrocardiography (ECG) has been recently proposed as biometric trait for identification purposes. Intra-individual variations of ECG might affect identification performance. These variations are mainly due to Heart Rate Variability (HRV). In particular, HRV causes changes in the QT intervals along the ECG waveforms. This work is aimed at analysing the influence of seven QT interval correction methods (based on population models) on the performance of ECG-fiducial-based identification systems. In addition, we have also considered the influence of training set size, classifier, classifier ensemble as well as the number of consecutive heartbeats in a majority voting scheme. The ECG signals used in this study were collected from thirty-nine subjects within the Physionet open access database. Public domain software was used for fiducial points detection. Results suggested that QT correction is indeed required to improve the performance. However, there is no clear choice among the seven explored approaches for QT correction (identification rate between 0.97 and 0.99). MultiLayer Perceptron and Support Vector Machine seemed to have better generalization capabilities, in terms of classification performance, with respect to Decision Tree-based classifiers. No such strong influence of the training-set size and the number of consecutive heartbeats has been observed on the majority voting scheme.

Development of a physiologically-based pharmacokinetic model of the rat central nervous system

Central nervous system (CNS) drug disposition is dictated by a drug’s physicochemical properties and its ability to permeate physiological barriers. The blood–brain barrier (BBB), blood-cerebrospinal fluid barrier and centrally located drug transporter proteins influence drug disposition within the central nervous system. Attainment of adequate brain-to-plasma and cerebrospinal fluid-to-plasma partitioning is important in determining the efficacy of centrally acting therapeutics. We have developed a physiologically-based pharmacokinetic model of the rat CNS which incorporates brain interstitial fluid (ISF), choroidal epithelial and total cerebrospinal fluid (CSF) compartments and accurately predicts CNS pharmacokinetics. The model yielded reasonable predictions of unbound brain-to-plasma partition ratio (Kpuu,brain) and CSF:plasma ratio (CSF:Plasmau) using a series of in vitro permeability and unbound fraction parameters. When using in vitro permeability data obtained from L-mdr1a cells to estimate rat in vivo permeability, the model successfully predicted, to within 4-fold, Kpuu,brain and CSF:Plasmau for 81.5% of compounds simulated. The model presented allows for simultaneous simulation and analysis of both brain biophase and CSF to accurately predict CNS pharmacokinetics from preclinical drug parameters routinely available during discovery and development pathways.

Strategic supplier performance evaluation:a case-based action research of a UK manufacturing organisation

The main aim of this research is to demonstrate strategic supplier performance evaluation of a UK-based manufacturing organisation using an integrated analytical framework. Developing long term relationship with strategic suppliers is common in today's industry. However, monitoring suppliers' performance all through the contractual period is important in order to ensure overall supply chain performance. Therefore, client organisations need to measure suppliers' performance dynamically and inform them on improvement measures. Although there are many studies introducing innovative supplier performance evaluation frameworks and empirical researches on identifying criteria for supplier evaluation, little has been reported on detailed application of strategic supplier performance evaluation and its implication on overall performance of organisation. Additionally, majority of the prior studies emphasise on lagging factors (quality, delivery schedule and value/cost) for supplier selection and evaluation. This research proposes both leading (organisational practices, risk management, environmental and social practices) and lagging factors for supplier evaluation and demonstrates a systematic method for identifying those factors with the involvement of relevant stakeholders and process mapping. The contribution of this article is a real-life case-based action research utilising an integrated analytical model that combines quality function deployment and the analytic hierarchy process method for suppliers' performance evaluation. The effectiveness of the method has been demonstrated through number of validations (e.g. focus group, business results, and statistical analysis). Additionally, the study reveals that enhanced supplier performance results positive impact on operational and business performance of client organisation.

Microstructure-based inherent anisotropy of asphalt mixtures

Asphalt mixtures have been demonstrated to be anisotropic materials in both laboratory and field tests. The anisotropy of asphalt mixtures consists of inherent anisotropy and stress-induced anisotropy. In previous work, the inherent anisotropy of asphalt mixtures was quantified by using only the inclination angles of the coarse aggregate particles in the asphalt mixtures. However, the inclination of fine aggregates also has a contribution to the inherent anisotropy. Moreover, the contribution to the inherent anisotropy of each aggregate may not be the same as in the previous work but will depend on the size, orientation, and sphericity of the aggregate particle. This paper quantifies the internal microstructure of the aggregates in asphalt mixtures by using an aggregate-related geometric parameter, the vector magnitude. The original formulation of the vector magnitude, which addresses only the orientation of coarse aggregates, is modified to account for not only the coarse aggregate orientation, but also the size, orientation, and sphericity of coarse and fine aggregates. This formulation is applied to cylindrical lab-mixed lab-compacted asphalt mixture specimens varying in asphalt binder type, air void content, and aging period. The vertical modulus and the horizontal modulus are also measured by using nondestructive tests. A relationship between the modified vector magnitude and the modulus ratio of the vertical modulus to the horizontal modulus is developed to quantify the influence of the inherent microstructure of the aggregates on the anisotropy of the mixtures. The modulus ratio is found to depend solely on the aggregate characteristics including the inclination angle, size, and sphericity, and it is independent of the asphalt binder type, air void content, and aging period. The inclination angle, itself, proves to be insufficient to quantify the inherent anisotropy of the asphalt mixtures. © 2011 American Society of Civil Engineers.

Charting new territory for organizational ethnography:insights from a team-based video ethnography of reinsurance trading in Lloyd’s of London

An increasing interest in “bringing actors back in” and gaining a nuanced understanding of their actions and interactions across a variety of strands in the management literature, has recently helped ethnography to unknown prominence in the field of organizational studies. Yet, calls remain that ethnography should “play a much more central role in the organization and management studies repertoire than it currently does” (Watson, 2011: 202). Ironically, those organizational realities that ethnographers are called to examine have at the same time become less and less amenable to ethnographic study. In this paper, we respond to these calls for innovative ethnographic methods in two ways. First, we report on the practices and ethnographic experiences of conducting a year-long team-based video ethnography of reinsurance trading in Lloyd’s of London. Second, drawing on these experiences, we propose an initial framework for systematizing new approaches to organizational ethnography and visualizing the ways in which they are ‘expanding’ ethnography as it was traditionally practiced.

Changes in autofluorescence based organoid model of muscle invasive urinary bladder cancer

Muscle invasive urinary bladder cancer is one of the most lethal cancers and its detection at the time of transurethral resection remains limited and diagnostic methods are urgently needed. We have developed a muscle invasive transitional cell carcinoma (TCC) model of the bladder using porcine bladder scaffold and the human bladder cancer cell line 5637. The progression of implanted cancer cells to muscle invasion can be monitored by measuring changes in the spectrum of endogenous fluorophores such as reduced nicotinamide dinucleotide (NADH) and flavins. We believe this could act as a useful tool for the study of fluorescence dynamics of developing muscle invasive bladder cancer in patients.

The development of a computer aided system for adaptive budgeting in a confectionery manufacturing firm

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