Project report. A subtropical urban community: Investigating medium to high density residential typologies by Design Charrette

The Centre for Subtropical Design at QUT, in partnership with the Queensland Government and Brisbane City Council, conducts research focused on 'best practice' outcomes for higher density urban living environments in the subtropics through the study of typical urban residential typologies, and urban design. The aim of the research is to inform and illustrate best practice subtropical design principles to policy makers and development industry professionals to stimulate climate-responsive outcomes. The Centre for Subtropical Design recently sought project-specific funding from the Queensland Department of Infrastructure and Planning (DIP) to investigate residential typologies for sustainable subtropical urban communities, based on transit orientated development principles and outcomes for areas around public transport nodes. A development site within the Fitzgibbon Urban Development Area, and close to a rail and bsu transport corridor, provided a case study location for this project. Four design-led multi-disciplinary creative teams participated in a Design Charrette and have produced concept drawings and propositions on a range of options, or prototypes. Analysis of selected prototypes has been undertaken to determine their environmental, economic and social performance. This Project Report discusses the scope of the project funded by DIP in terms of activities undertaken to date, and deliverables achieved. A subsequent Research Report will discuss the detailed findings of the analysis.

Research report. A subtropical urban community. Investigating medium to high density residential typologies. Findings and recommendations from the Design Charrette

In June 2009 the Centre for Subtropical Design at the Queensland University of Technology conducted a design charrette to research design concepts for liveable subtropical neighbourhoods characterised by higher-density, mixed-use, family orientated housing. Subsequent analysis of the proposed designs evaluated how well these typologies support economic, environmental and social sustainability. The study was led by Ms Rosemary Kennedy, Director of the Centre for Subtropical Design and QUT School of Design Adjunct Professor Peter Richards, Chair of the Centre for Subtropical Design Board and director of Deicke Richards Architects and Urban Designers.

A subtropical urban community. Investigating medium to high density residential typologies. Recommendations from the design charrette

In June 2009 the Centre for Subtropical Design at the Queensland University of Technology conducted a design charrette to research design concepts for liveable subtropical neighbourhoods characterised by higher-density, mixed-use, family orientated housing. Subsequent analysis of the proposed designs evaluated how well these typologies support economic, environmental and social sustainability. The study was led by Ms Rosemary Kennedy, Director of the Centre for Subtropical Design and QUT School of Design Adjunct Professor Peter Richards, Chair of the Centre for Subtropical Design Board and director of Deicke Richards Architects and Urban Designers.

Case study 1 : a subtropical urban community : investigating medium to high density residential typologies by design charrette

The public transport corridor bordering the study site runs NW to SE and is perceived as a source of noise and pollution. The key urban planning strategies adopted by this team were: • Acoustic separation from transport corridor noise source, • A regular grid pattern of urban blocks, and • A clear hierarchy of accessible open space throughout the development.

Report : Case study 2 : a subtropical urban community : investigating medium to high density residential typologies by design charrette

The case study site is physically disconnected from its surrounding community by the rail corridor and future bus lanes and is unlikely to be able to sustain its own commercial retail centre. As a result, it may also be socially disconnected from surrounding suburbs. However, it does offer proximity and access to an extensive „natural‟ area, and this is seen as key opportunity for the proposed development to develop a strong relationship with surrounding suburbs...

Decentralised Data Fusion with Parzen Density Estimates

Decentralised sensor networks typically consist of multiple processing nodes supporting one or more sensors. These nodes are interconnected via wireless communication. Practical applications of Decentralised Data Fusion have generally been restricted to using Gaussian based approaches such as the Kalman or Information Filter This paper proposes the use of Parzen window estimates as an alternate representation to perform Decentralised Data Fusion. It is required that the common information between two nodes be removed from any received estimates before local data fusion may occur Otherwise, estimates may become overconfident due to data incest. A closed form approximation to the division of two estimates is described to enable conservative assimilation of incoming information to a node in a decentralised data fusion network. A simple example of tracking a moving particle with Parzen density estimates is shown to demonstrate how this algorithm allows conservative assimilation of network information.

A subtropical urban community : medium to high density residential typologies - case study 4

On the case study site, using these strategies, the site density achieved was approximately 180 dwellings per hectare. According to ASK consulting engineers‟ acoustic report (in Ecolateral‟s report) the design gives solid consideration to the environmental noise issues associated with the site. The subject structure not only provides significant shielding of transport corridor noise to the suburb, it also minimises the potential for adverse impact on residential amenity within the building itself...

Porphyromonas gingivalis lipopolysaccharide alters atherosclerotic-related gene expression in oxidized low-density-lipoprotein-induced macrophages and foam cells

The molecular mechanism between atherosclerosis formation and periodontal pathogens is not clear although positive correlation between periodontal infections and cardiovascular diseases has been reported. Objective: To determine if atherosclerosis related genes were affected in foam cells during and after its formation by P. gingivalis lipopolysaccharide (LPS) stimulation. Methods: Macrophages from human THP-1 monocytes were treated with oxidized low density lipoprotein (oxLDL) to induce the formation of foam cells. P. gingivalis LPS was added to cultures of either oxLDL-induced macrophages or foam cells. The expression of atherosclerosis related genes was assayed by quantitative real time PCR and the protein production of granulocyte-macrophage colony-stimulating factor（GM-CSF）, monocyte chemotactic protein-1 (MCP-1), IL-1β, IL-10 and IL-12 was determined by ELISA. Nuclear translocation of NF-κB P65 was detected by immunocytochemistry and western blot was used to evaluate IKB-α degradation to confirm the NF-κB pathway activation. Results: P. gingivalis LPS stimulated atherosclerosis related gene expression in foam cells and increased oxLDL induced expression of chemokines, adhesion molecules, growth factors, apoptotic genes, and nuclear receptors in macrophages. Transcription of the pro-inflammatory cytokines IL-1β and IL-12 was elevated in response to LPS in both macrophages and foam cells, whereas the anti-inflammatory cytokine IL-10 was not affected. Increased NF-κB pathway activation was also observed in LPS and oxLDL co-stimulated macrophages. Conclusion: P. gingivalis LPS appears to be an important factor in the development of atherosclerosis by stimulation of atherosclerosis related gene expression in both macrophages and foam cells via activation of the NF-κB pathway.

Cell density alters matrix accumulation in two distinct fractions and the mechanical integrity of alginate-chondrocyte constructs

Chondrocyte density in articular cartilage is known to change with the development and growth of the tissue and may play an important role in the formation of a functional extracellular matrix (ECM). The objective of this study was to determine how initial chondrocyte density in an alginate hydrogel affects the matrix composition, its distribution between the cell-associated (CM) and further removed matrix (FRM) fractions, and the tensile mechanical properties of the developing engineered cartilage. Alginate constructs containing primary bovine chondrocytes at densities of 0, 4, 16, and 64 million cells/ml were fabricated and cultured for 1 or 2 weeks, at which time structural, biochemical, and mechanical properties were analyzed. Both matrix content and distribution varied with the initial cell density. Increasing cell density resulted in an increasing content of collagen and sulfated-glycosaminoglycan (GAG) and an increasing proportion of these molecules localized in the CM. While the equilibrium tensile modulus of cell-free alginate did not change with time in culture, the constructs with highest cell density were 116% stiffer than cell-free controls after 2 weeks of culture. The equilibrium tensile modulus was positively correlated with total collagen (r2 = 0.47, p < 0.001) and GAG content (r2 = 0.68, p < 0.001), and these relationships were enhanced when analyzing only those matrix molecules in the CM fraction (r2 = 0.60 and 0.72 for collagen and GAG, respectively, each p < 0.001). Overall, the results of this study indicate that initial cell density has a considerable effect on the developing composition, structure, and function of alginate–chondrocyte constructs.

High-density lipoprotein and the risk of recurrent venous thromboembolism

BACKGROUND - High-density lipoprotein (HDL) protects against arterial atherothrombosis, but it is unknown whether it protects against recurrent venous thromboembolism. METHODS AND RESULTS - We studied 772 patients after a first spontaneous venous thromboembolism (average follow-up 48 months) and recorded the end point of symptomatic recurrent venous thromboembolism, which developed in 100 of the 772 patients. The relationship between plasma lipoprotein parameters and recurrence was evaluated. Plasma apolipoproteins AI and B were measured by immunoassays for all subjects. Compared with those without recurrence, patients with recurrence had lower mean (±SD) levels of apolipoprotein AI (1.12±0.22 versus 1.23±0.27 mg/mL, P<0.001) but similar apolipoprotein B levels. The relative risk of recurrence was 0.87 (95% CI, 0.80 to 0.94) for each increase of 0.1 mg/mL in plasma apolipoprotein AI. Compared with patients with apolipoprotein AI levels in the lowest tertile (<1.07 mg/mL), the relative risk of recurrence was 0.46 (95% CI, 0.27 to 0.77) for the highest-tertile patients (apolipoprotein AI >1.30 mg/mL) and 0.78 (95% CI, 0.50 to 1.22) for midtertile patients (apolipoprotein AI of 1.07 to 1.30 mg/mL). Using nuclear magnetic resonance, we determined the levels of 10 major lipoprotein subclasses and HDL cholesterol for 71 patients with recurrence and 142 matched patients without recurrence. We found a strong trend for association between recurrence and low levels of HDL particles and HDL cholesterol. CONCLUSIONS - Patients with high levels of apolipoprotein AI and HDL have a decreased risk of recurrent venous thromboembolism. © 2007 American Heart Association, Inc.

High-density lipoprotein deficiency and dyslipoproteinemia associated with venous thrombosis in men

Background-Although dyslipoproteinemia is associated with arterial atherothrombosis, little is known about plasma lipoproteins in venous thrombosis patients. Methods and Results-We determined plasma lipoprotein subclass concentrations using nuclear magnetic resonance spectroscopy and antigenic levels of apolipoproteins AI and B in blood samples from 49 male venous thrombosis patients and matched controls aged <55 years. Venous thrombosis patients had significantly lower levels of HDL particles, large HDL particles, HDL cholesterol, and apolipoprotein AI and significantly higher levels of LDL particles and small LDL particles. The quartile-based odds ratios for decreased HDL particle and apolipoprotein AI levels in patients compared with controls were 6.5 and 6.0 (95% CI, 2.3 to 19 and 2.1 to 17), respectively. Odds ratios for apolipoprotein B/apolipoprotein AI ratio and LDL cholesterol/HDL cholesterol ratio were 6.3 and 2.7 (95% CI, 1.9 to 21 and 1.1 to 6.5), respectively. When polymorphisms in genes for hepatic lipase, endothelial lipase, and cholesteryl ester transfer protein were analyzed, patients differed significantly from controls in the allelic frequency for the TaqI B1/B2 polymorphism in cholesteryl ester transfer protein, consistent with the observed pattern of lower HDL and higher LDL. Conclusions-Venous thrombosis in men aged <55 years old is associated with dyslipoproteinemia involving lower levels of HDL particles, elevated levels of small LDL particles, and an elevated ratio of apolipoprotein B/apolipoprotein AI. This dyslipoproteinemia seems associated with a related cholesteryl ester transfer protein genotype difference. © 2005 American Heart Association, Inc.

Learning the kernel matrix with semidefinite programming

Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive semidefinite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space - classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semidefinite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -using the labeled part of the data one can learn an embedding also for the unlabeled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method for learning the 2-norm soft margin parameter in support vector machines, solving an important open problem.