Adaptive modelling of sustainable architecture design in entropy evolutionary

This paper argues a model of adaptive design for sustainable architecture within a framework of entropy evolution. The spectrum of sustainable architecture consists of efficient use of energy and material resource in the life-cycle of buildings, active involvement of the occupants into micro-climate control within the building, and the natural environment as the physical context. The interactions amongst all the parameters compose a complex system of sustainable architecture design, of which the conventional linear and fragmented design technologies are insufficient to indicate holistic and ongoing environmental performance. The latest interpretation of the Second Law of Thermodynamics states a microscopic formulation of an entropy evolution of complex open systems. It provides a design framework for an adaptive system evolves for the optimization in open systems, this adaptive system evolves for the optimization of building environmental performance. The paper concludes that adaptive modelling in entropy evolution is a design alternative for sustainable architecture.

Variability of input parameters related to pollutants build-up in stormwater quality modelling

The variability of input parameters is the most important source of overall model uncertainty. Therefore, an in-depth understanding of the variability is essential for uncertainty analysis of stormwater quality model outputs. This paper presents the outcomes of a research study which investigated the variability of pollutants build-up characteristics on road surfaces in residential, commercial and industrial land uses. It was found that build-up characteristics vary highly even within the same land use. Additionally, industrial land use showed relatively higher variability of maximum build-up, build-up rate and particle size distribution, whilst the commercial land use displayed a relatively higher variability of pollutant-solid ratio. Among the various build-up parameters analysed, D50 (volume-median-diameter) displayed the relatively highest variability for all three land uses.

Similarity metrics within a point of view

In vector space based approaches to natural language processing, similarity is commonly measured by taking the angle between two vectors representing words or documents in a semantic space. This is natural from a mathematical point of view, as the angle between unit vectors is, up to constant scaling, the only unitarily invariant metric on the unit sphere. However, similarity judgement tasks reveal that human subjects fail to produce data which satisfies the symmetry and triangle inequality requirements for a metric space. A possible conclusion, reached in particular by Tversky et al., is that some of the most basic assumptions of geometric models are unwarranted in the case of psychological similarity, a result which would impose strong limits on the validity and applicability vector space based (and hence also quantum inspired) approaches to the modelling of cognitive processes. This paper proposes a resolution to this fundamental criticism of of the applicability of vector space models of cognition. We argue that pairs of words imply a context which in turn induces a point of view, allowing a subject to estimate semantic similarity. Context is here introduced as a point of view vector (POVV) and the expected similarity is derived as a measure over the POVV's. Different pairs of words will invoke different contexts and different POVV's. Hence the triangle inequality ceases to be a valid constraint on the angles. We test the proposal on a few triples of words and outline further research.

Prognostic modelling options for remaining useful life estimation by industry

Over recent years a significant amount of research has been undertaken to develop prognostic models that can be used to predict the remaining useful life of engineering assets. Implementations by industry have only had limited success. By design, models are subject to specific assumptions and approximations, some of which are mathematical, while others relate to practical implementation issues such as the amount of data required to validate and verify a proposed model. Therefore, appropriate model selection for successful practical implementation requires not only a mathematical understanding of each model type, but also an appreciation of how a particular business intends to utilise a model and its outputs. This paper discusses business issues that need to be considered when selecting an appropriate modelling approach for trial. It also presents classification tables and process flow diagrams to assist industry and research personnel select appropriate prognostic models for predicting the remaining useful life of engineering assets within their specific business environment. The paper then explores the strengths and weaknesses of the main prognostics model classes to establish what makes them better suited to certain applications than to others and summarises how each have been applied to engineering prognostics. Consequently, this paper should provide a starting point for young researchers first considering options for remaining useful life prediction. The models described in this paper are Knowledge-based (expert and fuzzy), Life expectancy (stochastic and statistical), Artificial Neural Networks, and Physical models.

A prototype augmented reality collaborative process modelling tool

Identifying, modelling and documenting business processes usually requires the collaboration of many stakeholders that may be spread across companies in inter-organizational business settings. While there are many process modelling tools available, the support they provide for remote collaboration is still limited. This demonstration showcases a novel prototype application that implements collaborative virtual environment and augmented reality technologies to improve remote collaborative process modelling, with an aim to assisting common collaboration tasks by providing an increased sense of immersion in an intuitive shared work and task space. Our tool is easily deployed using open source software, and commodity hardware, and is expected to assist with saving money on travel costs for large scale process modelling projects covering national and international centres within an enterprise.

Identification of a cryptic Prokaryotic promoter within the cDNA encoding the 5′ End of Dengue Virus RNA Genome

Infectious cDNA clones of RNA viruses are important research tools, but flavivirus cDNA clones have proven difficult to assemble and propagate in bacteria. This has been attributed to genetic instability and/or host cell toxicity, however the mechanism leading to these difficulties has not been fully elucidated. Here we identify and characterize an efficient cryptic bacterial promoter in the cDNA encoding the dengue virus (DENV) 5′ UTR. Following cryptic transcription in E. coli, protein expression initiated at a conserved in-frame AUG that is downstream from the authentic DENV initiation codon, yielding a DENV polyprotein fragment that was truncated at the N-terminus. A more complete understanding of constitutive viral protein expression in E. coli might help explain the cloning and propagation difficulties generally observed with flavivirus cDNA.

Computational approaches for modelling intrinsic noise and delays in genetic regulatory networks

This chapter focuses on the interactions and roles between delays and intrinsic noise effects within cellular pathways and regulatory networks. We address these aspects by focusing on genetic regulatory networks that share a common network motif, namely the negative feedback loop, leading to oscillatory gene expression and protein levels. In this context, we discuss computational simulation algorithms for addressing the interplay of delays and noise within the signaling pathways based on biological data. We address implementational issues associated with efficiency and robustness. In a molecular biology setting we present two case studies of temporal models for the Hes1 gene (Monk, 2003; Hirata et al., 2002), known to act as a molecular clock, and the Her1/Her7 regulatory system controlling the periodic somite segmentation in vertebrate embryos (Giudicelli and Lewis, 2004; Horikawa et al., 2006).

Modelling contractor's and subcontractor's trust : a system dynamics approach

A general mistrust within the contactor and subcontractor companies has identified one of the significant barriers to derive benefits from true downstream supply chain integration. Using the general theory of trust in inter-organizational relations and conducting interviews, this research discusses factors that influence development of trust and cooperation in contractor– subcontractor relationships in construction projects. System dynamics is the simulation method is selected in this theory-building effort, based on qualitative data collected from two projects of a construction company in Thailand. Performance, permeability and system based trust are found to make significant contributions toward parties’ trust level. Three strategic policies such as best value contracting, management of subcontractors as internal team and semi project partnering approach are recommended to stimulate the trust factors as well as cooperative long term relationship.

Room ventilation and the risk of airborne infection transmission in three health care settings within a large teaching hospital

Background: Room ventilation is a key determinant of airborne disease transmission. Despite this, ventilation guidelines in hospitals are not founded on robust scientific evidence related to prevention of airborne transmission. Methods: We sought to assess the effect of ventilation rates on influenza, tuberculosis (TB) and rhinovirus infection risk within three distinct rooms in a major urban hospital; a Lung Function Laboratory, Emergency Department (ED) Negative-pressure Isolation Room and an Outpatient Consultation Room were investigated. Air exchange rate measurements were performed in each room using CO2 as a tracer. Gammaitoni and Nucci’s model was employed to estimate infection risk. Results: Current outdoor air exchange rates in the Lung Function Laboratory and ED Isolation Room limited infection risks to between 0.1 and 3.6%. Influenza risk for individuals entering an Outpatient Consultation Room after an infectious individual departed ranged from 3.6 to 20.7%, depending on the duration for which each person occupied the room. Conclusions: Given the absence of definitive ventilation guidelines for hospitals, air exchange measurements combined with modelling afford a useful means of assessing, on a case-by-case basis, the suitability of room ventilation at preventing airborne disease transmission.

Complex modelling in the primary/middle school years

The world’s increasing complexity, competitiveness, interconnectivity, and dependence on technology generate new challenges for nations and individuals that cannot be met by continuing education as usual (Katehi, Pearson, & Feder, 2009). With the proliferation of complex systems have come new technologies for communication, collaboration, and conceptualisation. These technologies have led to significant changes in the forms of mathematical and scientific thinking that are required beyond the classroom. Modelling, in its various forms, can develop and broaden children’s mathematical and scientific thinking beyond the standard curriculum. This paper first considers future competencies in the mathematical sciences within an increasingly complex world. Next, consideration is given to interdisciplinary problem solving and models and modelling. Examples of complex, interdisciplinary modelling activities across grades are presented, with data modelling in 1st grade, model-eliciting in 4th grade, and engineering-based modelling in 7th-9th grades.

Digital human modelling for vehicle design and manufacturing

Digital human modelling (DHM) has today matured from research into industrial application. In the automotive domain, DHM has become a commonly used tool in virtual prototyping and human-centred product design. While this generation of DHM supports the ergonomic evaluation of new vehicle design during early design stages of the product, by modelling anthropometry, posture, motion or predicting discomfort, the future of DHM will be dominated by CAE methods, realistic 3D design, and musculoskeletal and soft tissue modelling down to the micro-scale of molecular activity within single muscle fibres. As a driving force for DHM development, the automotive industry has traditionally used human models in the manufacturing sector (production ergonomics, e.g. assembly) and the engineering sector (product ergonomics, e.g. safety, packaging). In product ergonomics applications, DHM share many common characteristics, creating a unique subset of DHM. These models are optimised for a seated posture, interface to a vehicle seat through standardised methods and provide linkages to vehicle controls. As a tool, they need to interface with other analytic instruments and integrate into complex CAD/CAE environments. Important aspects of current DHM research are functional analysis, model integration and task simulation. Digital (virtual, analytic) prototypes or digital mock-ups (DMU) provide expanded support for testing and verification and consider task-dependent performance and motion. Beyond rigid body mechanics, soft tissue modelling is evolving to become standard in future DHM. When addressing advanced issues beyond the physical domain, for example anthropometry and biomechanics, modelling of human behaviours and skills is also integrated into DHM. Latest developments include a more comprehensive approach through implementing perceptual, cognitive and performance models, representing human behaviour on a non-physiologic level. Through integration of algorithms from the artificial intelligence domain, a vision of the virtual human is emerging.

Mathematical modelling of the drying of sol gel microspheres

This thesis presents a mathematical model of the evaporation of colloidal sol droplets suspended within an atmosphere consisting of water vapour and air. The main purpose of this work is to investigate the causes of the morphologies arising within the powder collected from a spray dryer into which the precursor sol for Synroc™ is sprayed. The morphology is of significant importance for the application to storage of High Level Liquid Nuclear Waste. We begin by developing a model describing the evaporation of pure liquid droplets in order to establish a framework. This model is developed through the use of continuum mechanics and thermodynamic theory, and we focus on the specific case of pure water droplets. We establish a model considering a pure water vapour atmosphere, and then expand this model to account for the presence of an atmospheric gas such as air. We model colloidal particle-particle interactions and interactions between colloid and electrolyte using DLVO Theory and reaction kinetics, then incorporate these interactions into an expression for net interaction energy of a single particle with all other particles within the droplet. We account for the flow of material due to diffusion, advection, and interaction between species, and expand the pure liquid droplet models to account for the presence of these species. In addition, the process of colloidal agglomeration is modelled. To obtain solutions for our models, we develop a numerical algorithm based on the Control Volume method. To promote numerical stability, we formulate a new method of convergence acceleration. The results of a MATLAB™ code developed from this algorithm are compared with experimental data collected for the purposes of validation, and further analysis is done on the sensitivity of the solution to various controlling parameters.

Unsteady natural convection within a differentially heated enclosure of sinusoidal corrugated side walls

Numerically investigation of natural convection within a differentially heated modified square enclosure with sinusoidally corrugated side walls has been performed for different values of Rayleigh number. The fluid inside the enclosure considered is air and is quiescent, initially. The top and bottom surfaces are flat and considered as adiabatic. Results reveal three main stages: an initial stage, a transitory or oscillatory stage and a steady stage for the development of natural convection flow inside the corrugated cavity. The numerical scheme is based on the finite element method adapted to triangular non-uniform mesh element by a non-linear parametric solution algorithm. Investigation has been performed for the Rayleigh number, Ra ranging from 105 to 108 with variation of corrugation amplitude and frequency. Constant physical properties for the fluid medium have been assumed. Results have been presented in terms of the isotherms, streamlines, temperature plots, average Nusselt numbers, traveling waves and thermal boundary layer thickness plots, temperature and velocity profiles. The effects of sudden differential heating and its consequent transient behavior on fluid flow and heat transfer characteristics have been observed for the range of governing parameters. The present results show that the transient phenomena are greatly influenced by the variation of the Rayleigh Number with corrugation amplitude and frequency.

Differential expression of chemokine and matrix re-modelling genes is associated with contrasting schistosome-induced hepatopathology in murine models

The pathological outcomes of schistosomiasis are largely dependent on the molecular and cellular mechanisms of the host immune response. In this study, we investigated the contribution of variations in host gene expression to the contrasting hepatic pathology observed between two inbred mouse strains following Schistosoma japonicum infection. Whole genome microarray analysis was employed in conjunction with histological and immunohistochemical analysis to define and compare the hepatic gene expression profiles and cellular composition associated with the hepatopathology observed in S. japonicum-infected BALB/c and CBA mice. We show that the transcriptional profiles differ significantly between the two mouse strains with high statistical confidence. We identified specific genes correlating with the more severe pathology associated with CBA mice, as well as genes which may confer the milder degree of pathology associated with BALB/c mice. In BALB/c mice, neutrophil genes exhibited striking increases in expression, which coincided with the significantly greater accumulation of neutrophils at granulomatous regions seen in histological sections of hepatic tissue. In contrast, up-regulated expression of the eosinophil chemokine CCL24 in CBA mice paralleled the cellular influx of eosinophils to the hepatic granulomas. Additionally, there was greater down-regulation of genes involved in metabolic processes in CBA mice, reflecting the more pronounced hepatic damage in these mice. Profibrotic genes showed similar levels of expression in both mouse strains, as did genes associated with Th1 and Th2 responses. However, imbalances in expression of matrix metalloproteinases (e.g. MMP12, MMP13) and tissue inhibitors of metalloproteinases (TIMP1) may contribute to the contrasting pathology observed in the two strains. Overall, these results provide a more complete picture of the molecular and cellular mechanisms which govern the pathological outcome of hepatic schistosomiasis. This improved understanding of the immunopathogenesis in the murine model schistosomiasis provides the basis for a better appreciation of the complexities associated with chronic human schistosomiasis.