Parameter estimation of structural commodity price models

Commodity price modeling is normally approached in terms of structural time-series models, in which the different components (states) have a financial interpretation. The parameters of these models can be estimated using maximum likelihood. This approach results in a non-linear parameter estimation problem and thus a key issue is how to obtain reliable initial estimates. In this paper, we focus on the initial parameter estimation problem for the Schwartz-Smith two-factor model commonly used in asset valuation. We propose the use of a two-step method. The first step considers a univariate model based only on the spot price and uses a transfer function model to obtain initial estimates of the fundamental parameters. The second step uses the estimates obtained in the first step to initialize a re-parameterized state-space-innovations based estimator, which includes information related to future prices. The second step refines the estimates obtained in the first step and also gives estimates of the remaining parameters in the model. This paper is part tutorial in nature and gives an introduction to aspects of commodity price modeling and the associated parameter estimation problem.

An approach for extending Building Information Models (BIM) to specifications

The Construction industry accounts for a tenth of global GDP. Still, challenges such as slow adoption of new work processes, islands of information, and legal disputes, remain frequent, industry-wide occurrences despite various attempts to address them. In response, IT-based approaches have been adopted to explore collaborative ways of executing construction projects. Building Information Modelling (BIM) is an exemplar of integrative technologies whose 3D-visualisation capabilities have fostered collaboration especially between clients and design teams. Yet, the ways in which specification documents are created and used in capturing clients' expectations based on industry standards have remained largely unchanged since the 18th century. As a result, specification-related errors are still common place in an industry where vast amounts of information are consumed as well as produced in the course project implementation in the built environment. By implication, processes such as cost planning which depend on specification-related information remain largely inaccurate even with the use of BIM-based technologies. This paper briefly distinguishes between non-BIM-based and BIM-based specifications and reports on-going efforts geared towards the latter. We review exemplars aimed at extending Building Information Models to specification information embedded within the objects in a product library and explore a viable way of reasoning about a semi-automated process of specification using our product library.

Paracrine interactions between LNCaP prostate cancer cells and bioengineered bone in 3D in vitro culture reflect molecular changes during bone metastasis

As microenvironmental factors such as three-dimensionality and cell–matrix interactions are increasingly being acknowledged by cancer biologists, more complex 3D in vitro models are being developed to study tumorigenesis and cancer progression. To better understand the pathophysiology of bone metastasis, we have established and validated a 3D indirect co-culture model to investigate the paracrine interactions between prostate cancer (PCa) cells and human osteoblasts. Co-culture of the human PCa, LNCaP cells embedded within polyethylene glycol hydrogels with human osteoblasts in the form of a tissue engineered bone construct (TEB), resulted in reduced proliferation of LNCaP cells. LNCaP cells in both monoculture and co-culture were responsive to the androgen analog, R1881, as indicated by an increase in the expression (mRNA and/or protein induction) of androgen-regulated genes including prostate specific antigen and fatty acid synthase. Microarray gene expression analysis further revealed an up-regulation of bone markers and other genes associated with skeletal and vasculature development and a significant activation of transforming growth factor β1 downstream genes in LNCaP cells after co-culture with TEB. LNCaP cells co-cultured with TEB also unexpectedly showed similar changes in classical androgen-responsive genes under androgen-deprived conditions not seen in LNCaP monocultures. The molecular changes of LNCaP cells after co-culturing with TEBs suggest that osteoblasts exert a paracrine effect that may promote osteomimicry and modulate the expression of androgen-responsive genes in LNCaP cells. Taken together, we have presented a novel 3D in vitro model that allows the study of cellular and molecular changes occurring in PCa cells and osteoblasts that are relevant to metastatic colonization of bone. This unique in vitro model could also facilitate cancer biologists to dissect specific biological hypotheses via extensive genomic or proteomic assessments to further our understanding of the PCa-bone crosstalk.

Human breast cancer cell metastasis to long bone and soft organs of nude mice : a quantitative assay

Bone is a common metastatic site in human breast cancer (HBC). Since bone metastasis occurs very rarely from current spontaneous or experimental metastasis models of HBC cells in nude mice, an arterial seeding model involving the direct injection of the cells into the left ventricle has been developed to better understand the mechanisms involved in this process. We present here a sensitive polymerase chain reaction (PCR) method to detect and quantitate bone and soft organ metastasis in nude mice which have been intracardially inoculated with Lac Z transduced HBC cells. Amplification of genomically incorporated Lac Z sequences in MDA-MB-231-BAG HBC cells enables us to specifically detect these cells in mouse organs and bones. We have also created a competitive template to use as an internal standard in the PCR reactions, allowing us to better quantitate levels of HBC metastasis. The results of this PCR detection method correlate well with cell culture detection from alternate long bones from the same mice, and are more sensitive than gross Lac Z staining with X-gal or routine histology. Comparable qualitative results were obtained with PCR and culture in a titration experiment in which mice were inoculated with increasing numbers of cells, but PCR is more quantifiable, less time consuming, and less expensive. This assay can be employed to study the molecular and cellular aspects of bone metastasis, and could easily be used in conjunction with RT-PCR-based analyses of gene products which may be involved with HBC metastasis.

EMT and MET in carcinoma : clinical observations, regulatory pathways and new models

The articles collected here in this special edition Epithelial-Mesenchymal (EMT) and Mesenchymal-Epithelial Transitions (MET) in Cancer provide a snapshot of the very rapidly progressing cinemascope of the involvement of these transitions in carcinoma progression. Pubmed analysis of EMT and cancer shows an exponential increase in the last few years in the number of papers and reviews published under these terms (Fig. 1). The last few years have seen these articles appearing in high calibre journals including Nature, Nature Cell Biology, Cancer Cell, PNAS, JNCI, JCI, and Cell, signaling the acceptance and quality of work in this field.

An MMP13-selective inhibitor delays primary tumor growth and the onset of tumor-associated osteolytic lesions in experimental models of breast cancer

We investigated the effects of the matrix metalloproteinase 13 (MMP13)-selective inhibitor, 5-(4-{4-[4-(4-fluorophenyl)-1,3-oxazol-2-yl]phenoxy}phenoxy)-5-(2-methoxyethyl) pyrimidine-2,4,6(1H,3H,5H)-trione (Cmpd-1), on the primary tumor growth and breast cancer-associated bone remodeling using xenograft and syngeneic mouse models. We used human breast cancer MDA-MB-231 cells inoculated into the mammary fat pad and left ventricle of BALB/c Nu/Nu mice, respectively, and spontaneously metastasizing 4T1.2-Luc mouse mammary cells inoculated into mammary fat pad of BALB/c mice. In a prevention setting, treatment with Cmpd-1 markedly delayed the growth of primary tumors in both models, and reduced the onset and severity of osteolytic lesions in the MDA-MB-231 intracardiac model. Intervention treatment with Cmpd-1 on established MDA-MB-231 primary tumors also significantly inhibited subsequent growth. In contrast, no effects of Cmpd-1 were observed on soft organ metastatic burden following intracardiac or mammary fat pad inoculations of MDA-MB-231 and 4T1.2-Luc cells respectively. MMP13 immunostaining of clinical primary breast tumors and experimental mice tumors revealed intra-tumoral and stromal expression in most tumors, and vasculature expression in all. MMP13 was also detected in osteoblasts in clinical samples of breast-to-bone metastases. The data suggest that MMP13-selective inhibitors, which lack musculoskeletal side effects, may have therapeutic potential both in primary breast cancer and cancer-induced bone osteolysis.

Mechanics of microfilaments networks : a cross-scales study

The mechanical properties of microfilament networks are systematically summarized at different special scales in this paper. We have presented the mechanical models of single microfilaments and microfilament networks at microscale. By adopting a coarse-grained simulation strategy, the mechanical stability of microfilaments related cellular structures are analysed. Structural analysis is conducted to microfilament networks to understand the stress relaxation under compression. The nanoscale molecular mechanisms of the microfilaments deformation is also summarized from the viewpoint of molecular dynamics simulation. This paper provides the fundaments of multiscale modelling framework for the mechanical behaviours simulation of hierarchical microfilament networks.

A comparison of mathematical models for phase separation in high-rate LiFePO4 cathodes

We construct a two-scale mathematical model for modern, high-rate LiFePO4cathodes. We attempt to validate against experimental data using two forms of the phase-field model developed recently to represent the concentration of Li+ in nano-sized LiFePO4crystals. We also compare this with the shrinking-core based model we developed previously. Validating against high-rate experimental data, in which electronic and electrolytic resistances have been reduced is an excellent test of the validity of the crystal-scale model used to represent the phase-change that may occur in LiFePO4material. We obtain poor fits with the shrinking-core based model, even with fitting based on “effective” parameter values. Surprisingly, using the more sophisticated phase-field models on the crystal-scale results in poorer fits, though a significant parameter regime could not be investigated due to numerical difficulties. Separate to the fits obtained, using phase-field based models embedded in a two-scale cathodic model results in “many-particle” effects consistent with those reported recently.

Simulation-based fully Bayesian experimental design for mixed effects models

In this paper, we present fully Bayesian experimental designs for nonlinear mixed effects models, in which we develop simulation-based optimal design methods to search over both continuous and discrete design spaces. Although Bayesian inference has commonly been performed on nonlinear mixed effects models, there is a lack of research into performing Bayesian optimal design for nonlinear mixed effects models that require searches to be performed over several design variables. This is likely due to the fact that it is much more computationally intensive to perform optimal experimental design for nonlinear mixed effects models than it is to perform inference in the Bayesian framework. In this paper, the design problem is to determine the optimal number of subjects and samples per subject, as well as the (near) optimal urine sampling times for a population pharmacokinetic study in horses, so that the population pharmacokinetic parameters can be precisely estimated, subject to cost constraints. The optimal sampling strategies, in terms of the number of subjects and the number of samples per subject, were found to be substantially different between the examples considered in this work, which highlights the fact that the designs are rather problem-dependent and require optimisation using the methods presented in this paper.

Methodology for developing real-time motorway traffic risk identification models using individual-vehicle data

Most of existing motorway traffic safety studies using disaggregate traffic flow data aim at developing models for identifying real-time traffic risks by comparing pre-crash and non-crash conditions. One of serious shortcomings in those studies is that non-crash conditions are arbitrarily selected and hence, not representative, i.e. selected non-crash data might not be the right data comparable with pre-crash data; the non-crash/pre-crash ratio is arbitrarily decided and neglects the abundance of non-crash over pre-crash conditions; etc. Here, we present a methodology for developing a real-time MotorwaY Traffic Risk Identification Model (MyTRIM) using individual vehicle data, meteorological data, and crash data. Non-crash data are clustered into groups called traffic regimes. Thereafter, pre-crash data are classified into regimes to match with relevant non-crash data. Among totally eight traffic regimes obtained, four highly risky regimes were identified; three regime-based Risk Identification Models (RIM) with sufficient pre-crash data were developed. MyTRIM memorizes the latest risk evolution identified by RIM to predict near future risks. Traffic practitioners can decide MyTRIM’s memory size based on the trade-off between detection and false alarm rates. Decreasing the memory size from 5 to 1 precipitates the increase of detection rate from 65.0% to 100.0% and of false alarm rate from 0.21% to 3.68%. Moreover, critical factors in differentiating pre-crash and non-crash conditions are recognized and usable for developing preventive measures. MyTRIM can be used by practitioners in real-time as an independent tool to make online decision or integrated with existing traffic management systems.

Beyond tasks and gateways: discovering BPMN models with subprocesses, boundary events and activity markers

Existing techniques for automated discovery of process models from event logs largely focus on extracting flat process models. In other words, they fail to exploit the notion of subprocess, as well as structured error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of BPMN models containing subprocesses, interrupting and non-interrupting boundary events, and loop and multi-instance markers. The technique analyzes dependencies between data attributes associated with events, in order to identify subprocesses and to extract their associated logs. Parent process and subprocess models are then discovered separately using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. A validation with one synthetic and two real-life logs shows that process models derived using the proposed technique are more accurate and less complex than those derived with flat process model discovery techniques.

STI-GMaS : an open-source environment for simulation of sexually-transmitted infections

Background Sexually-transmitted pathogens often have severe reproductive health implications if treatment is delayed or absent, especially in females. The complex processes of disease progression, namely replication and ascension of the infection through the genital tract, span both extracellular and intracellular physiological scales, and in females can vary over the distinct phases of the menstrual cycle. The complexity of these processes, coupled with the common impossibility of obtaining comprehensive and sequential clinical data from individual human patients, makes mathematical and computational modelling valuable tools in developing our understanding of the infection, with a view to identifying new interventions. While many within-host models of sexually-transmitted infections (STIs) are available in existing literature, these models are difficult to deploy in clinical/experimental settings since simulations often require complex computational approaches. Results We present STI-GMaS (Sexually-Transmitted Infections – Graphical Modelling and Simulation), an environment for simulation of STI models, with a view to stimulating the uptake of these models within the laboratory or clinic. The software currently focuses upon the representative case-study of Chlamydia trachomatis, the most common sexually-transmitted bacterial pathogen of humans. Here, we demonstrate the use of a hybrid PDE–cellular automata model for simulation of a hypothetical Chlamydia vaccination, demonstrating the effect of a vaccine-induced antibody in preventing the infection from ascending to above the cervix. This example illustrates the ease with which existing models can be adapted to describe new studies, and its careful parameterisation within STI-GMaS facilitates future tuning to experimental data as they arise. Conclusions STI-GMaS represents the first software designed explicitly for in-silico simulation of STI models by non-theoreticians, thus presenting a novel route to bridging the gap between computational and clinical/experimental disciplines. With the propensity for model reuse and extension, there is much scope within STI-GMaS to allow clinical and experimental studies to inform model inputs and drive future model development. Many of the modelling paradigms and software design principles deployed to date transfer readily to other STIs, both bacterial and viral; forthcoming releases of STI-GMaS will extend the software to incorporate a more diverse range of infections.

A comparison of three models for mine water management

Water management is vital for mine sites both for production and sustainability related issues. Effective water management is a complex task since the role of water on mine sites is multifaceted. Computers models are tools that represent mine site water interaction and can be used by mine sites to inform or evaluate their water management strategies. There exist several types of models that can be used to represent mine site water interactions. This paper presents three such models: an operational model, an aggregated systems model and a generic systems model. For each model the paper provides a description and example followed by an analysis of its advantages and disadvantages. The paper hypotheses that since no model is optimal for all situations, each model should be applied in situations where it is most appropriate based upon the scale of water interactions being investigated, either unit (operation), inter-site (aggregated systems) or intra-site (generic systems).

Vertical alignment of process models – how can we get there?

There is a wide variety of drivers for business process modelling initiatives, reaching from business evolution and process optimisation over compliance checking and process certification to process enactment. That, in turn, results in models that differ in content due to serving different purposes. In particular, processes are modelled on different abstraction levels and assume different perspectives. Vertical alignment of process models aims at handling these deviations. While the advantages of such an alignment for inter-model analysis and change propagation are out of question, a number of challenges has still to be addressed. In this paper, we discuss three main challenges for vertical alignment in detail. Against this background, the potential application of techniques from the field of process integration is critically assessed. Based thereon, we identify specific research questions that guide the design of a framework for model alignment.

Integrated access control for smart buildings using building information models

This thesis investigates the use of building information models for access control and security applications in critical infrastructures and complex building environments. It examines current problems in security management for physical and logical access control and proposes novel solutions that exploit the detailed information available in building information models. The project was carried out as part of the Airports of the Future Project and the research was modelled based on real-world problems identified in collaboration with our industry partners in the project.