Graph theory based representation of building information models for access control applications

Building information models are increasingly being utilised for facility management of large facilities such as critical infrastructures. In such environments, it is valuable to utilise the vast amount of data contained within the building information models to improve access control administration. The use of building information models in access control scenarios can provide 3D visualisation of buildings as well as many other advantages such as automation of essential tasks including path finding, consistency detection, and accessibility verification. However, there is no mathematical model for building information models that can be used to describe and compute these functions. In this paper, we show how graph theory can be utilised as a representation language of building information models and the proposed security related functions. This graph-theoretic representation allows for mathematically representing building information models and performing computations using these functions.

Intramacrophage survival of uropathogenic Escherichia coli : differences between diverse clinical isolates and between mouse and human macrophages

Uropathogenic E. coli (UPEC) are the primary cause of urinary tract infections. Recent studies have demonstrated that UPEC can invade and replicate within epithelial cells, suggesting that this bacterial pathogen may occupy an intracellular niche within the host. Given that many intracellular pathogens target macrophages, we assessed the interactions between UPEC and macrophages. Colonization of the mouse bladder by UPEC strain CFT073 resulted in increased expression of myeloid-restricted genes, consistent with the recruitment of inflammatory macrophages to the site of infection. In in vitro assays, CFT073 was able to survive within primary mouse bone marrow-derived macrophages (BMM) up to 24 h post-infection. Three additional well-characterized clinical UPEC isolates associated with distinct UTI symptomatologies displayed variable long-term survival within BMM. UPEC strains UTI89 and VR50, originally isolated from patients with cystitis and asymptomatic bacteriuria respectively, showed elevated bacterial loads in BMM at 24 h post-infection as compared to CFT073 and the asymptomatic bacteriuria strain 83972. These differences did not correlate with differential effects on macrophage survival or initial uptake of bacteria. E. coli UTI89 localized to a Lamp1+ vesicular compartment within BMM. In contrast to survival within mouse BMM, intracellular bacterial loads of VR50 were low in both human monocyte-derived macrophages (HMDM) and in human T24 bladder epithelial cells. Collectively, these data suggest that some UPEC isolates may subvert macrophage anti-microbial pathways, and that host species differences may impact on intracellular UPEC survival.

Meta-analysis of microarray data identifies GAS6 expression as an independent predictor of poor survival in ovarian cancer

Seeking new biomarkers for epithelial ovarian cancer, the fifth most common cause of death from all cancers in women and the leading cause of death from gynaecological malignancies, we performed a meta-analysis of three independent studies and compared the results in regard to clinicopathological parameters. This analysis revealed that GAS6 was highly expressed in ovarian cancer and therefore was selected as our candidate of choice. GAS6 encodes a secreted protein involved in physiological processes including cell proliferation, chemotaxis, and cell survival. We performed immunohistochemistry on various ovarian cancer tissues and found that GAS6 expression was elevated in tumour tissue samples compared to healthy control samples (P < 0.0001). In addition, GAS6 expression was also higher in tumours from patients with residual disease compared to those without. Our data propose GAS6 as an independent predictor of poor survival, suggesting GAS6, both on the mRNA and on the protein level, as a potential biomarker for ovarian cancer. In clinical practice, the staining of a tumour biopsy for GAS6 may be useful to assess cancer prognosis and/or to monitor disease progression.

A pseudo-marginal sequential Monte Carlo algorithm for random effects models in Bayesian sequential design

A computationally efficient sequential Monte Carlo algorithm is proposed for the sequential design of experiments for the collection of block data described by mixed effects models. The difficulty in applying a sequential Monte Carlo algorithm in such settings is the need to evaluate the observed data likelihood, which is typically intractable for all but linear Gaussian models. To overcome this difficulty, we propose to unbiasedly estimate the likelihood, and perform inference and make decisions based on an exact-approximate algorithm. Two estimates are proposed: using Quasi Monte Carlo methods and using the Laplace approximation with importance sampling. Both of these approaches can be computationally expensive, so we propose exploiting parallel computational architectures to ensure designs can be derived in a timely manner. We also extend our approach to allow for model uncertainty. This research is motivated by important pharmacological studies related to the treatment of critically ill patients.

Incorporating human-factors in car-following models : a review of recent developments and research needs

Over the past decades there has been a considerable development in the modeling of car-following (CF) behavior as a result of research undertaken by both traffic engineers and traffic psychologists. While traffic engineers seek to understand the behavior of a traffic stream, traffic psychologists seek to describe the human abilities and errors involved in the driving process. This paper provides a comprehensive review of these two research streams. It is necessary to consider human-factors in {CF} modeling for a more realistic representation of {CF} behavior in complex driving situations (for example, in traffic breakdowns, crash-prone situations, and adverse weather conditions) to improve traffic safety and to better understand widely-reported puzzling traffic flow phenomena, such as capacity drop, stop-and-go oscillations, and traffic hysteresis. While there are some excellent reviews of {CF} models available in the literature, none of these specifically focuses on the human factors in these models. This paper addresses this gap by reviewing the available literature with a specific focus on the latest advances in car-following models from both the engineering and human behavior points of view. In so doing, it analyses the benefits and limitations of various models and highlights future research needs in the area.

Theorizing the use of multiple conceptual models in combination

Conceptual modelling continues to be an important means for graphically capturing the requirements of an information system. Observations of modelling practice suggest that modellers often use multiple conceptual models in combination, because they articulate different aspects of real-world domains. Yet, the available empirical as well as theoretical research in this area has largely studied the use of single models, or single modelling grammars. We develop a Theory of Combined Ontological Coverage by extending an existing theory of ontological expressiveness of conceptual modelling grammars. Our new theory posits that multiple conceptual models are used to increase the maximum coverage of the real-world domain being modelled, whilst trying to minimize the ontological overlap between the models. We illustrate how the theory can be applied to analyse sets of conceptual models. We develop three propositions of the theory about evaluations of model combinations in terms of users’ selection, understandability and usefulness of conceptual models.

Amazing tale of teen's survival in torrent gives hope to families of the missing

Flailing in a maelstrom of muddy water, a teenager being swept along Toowoomba's shopping strip has become a reason for hope for the loved ones of the 12 people still missing in the devastating Queensland floods...