Identifying Trends in Masterplanning: A Typological Classification System

This document is the Accepted Manuscript version of the following article: Robert Adam, and Claire Jamieson, ‘Identifying trends in masterplanning: A typological classification system’, URBAN DESIGN International, Vol. 19 (4): 274-290, December 2014. The final publication is available at Springer via https://doi.org/10.1057/udi.2013.24.This article reports research carried out to develop a new typological method for the analysis of masterplans. This quantitative method of analysis can be used to produce comparative data that will help in the comparison of urban design typologies and their development over time. This article sets out the research to date, describing how the initial aims have developed from simple analysis to the creation of an analytical tool with wide applications. Comprising a detailed taxonomy of urban design features gathered from a wide database of recent and emerging masterplans, the system provides opportunities for further study such as trends, qualitative comparison against quantitative measurement, and comparison of aims and outcomes. This article will describe the methodology and process of research, while elaborating on the potential of the tool.Peer reviewedFinal Accepted Versio

Towards analytical typologies of plot systems: quantitative profile of five European cities

The importance of the plot (also referred to as ‘property’) as one of the fundamental elements of urban form is well recognized within the field of urban morphology. Despite the fact that it is often described as the basic element in the pattern of land divisions, which are essential as organizational frameworks for urban form, studies offering comprehensive descriptions and classifications of plot systems are quite scant. The aim of the paper is to introduce a classification of plot systems into typologies based on five European cities, in order to distinguish particular spatial differences and similarities in terms of their plot structure. The proposed typologies are developed using unsupervised k-means cluster analysis based on numeric attributes derived from central theories in urban morphology. The introduced typologies are essentially configurational, allowing collective systematic properties of plot systems to be captured. Numeric attributes include plot differentiation (or plot size), plot frontage and compactness ratio, corresponding to essential qualities of plot systems such as the capacity to carry differences in space, the ability to operate as interface between street and building and providing a framework for evolution of built form over time. All three attributes are translated into configurational measures in order to capture the context of the plot system, rather than the parameters of individual plots. The combination of these deductively defined variables with algorithmically defined classification methods results in seven plot types that can be used to scale up traditional urban morphological analysis to whole city regions and conduct substantial comparison of patterns within, but also between these regions. Further, it also makes it possible to describe commonly recognized plot patterns and discover new ones

2-Aminophenoxazine-3-one and 2-amino-4,4α-dihydro-4α,7-dimethyl-3H-phenoxazine-3-one cause cellular apoptosis by reducing higher intracellular pH in cancer cells

We examined intracellular pH (pHi) of ten cancer cell lines derived from different organs and two normal cell lines including human embryonic lung fibroblast cells (HEL) and human umbilical vein endothelial cells (HUVEC) in vitro, and found that pHi of most of these cancer cells was evidently higher (pH 7.5 to 7.7) than that of normal cells (7.32 and 7.44 for HEL and HUVEC, respectively) and that of primary leukemic cells and erythrocytes hitherto reported (≤7.2). Higher pHi in these cancer cells could be related to the Warburg effect in cancer cells with enhanced glycolytic metabolism. Since reversal of the Warburg effect may perturb intracellular homeostasis in cancer cells, we looked for compounds that cause extensive reduction of pHi, a major regulator of the glycolytic pathway and its associated metabolic pathway. We found that phenoxazine compounds, 2-aminophenoxazine-3-one (Phx-3) and 2-amino-4,4α-dihydro-4α,7-dimethyl-3H-phenoxazine-3-one (Phx-1) caused a rapid and drastic dose-dependent decrease of pHi in ten different cancer cells within 30 min, though the extent of the decrease of pHi was significantly larger for Phx-3 (ΔpHi = 0.6 pH units or more for 100 µM Phx-3) than for Phx-1 (ΔpHi = 0.1 pH units or more for 100 µM Phx-1). This rapid and drastic decrease of pHi in a variety of cancer cells caused by Phx-3 and Phx-1 possibly perturbed their intracellular homeostasis, and extensively affected the subsequent cell death, because these phenoxazines exerted dose-dependent proapoptotic and cytotoxic effects on these cells during 72 h incubation, confirming a causal relationship between ΔpHi and cytotoxic effects due to Phx-3 and Phx-1. Phx-3 and Phx-1 also reduced pHi of normal cells including HEL and HUVEC, although they exerted less proapoptotic and cytotoxic effects on these cells than on cancer cells. Drugs such as Phx-3 and Phx-1 that reduce pHi and thereby induce cellular apoptosis might serve as benevolent anticancer drugs

The recent intellectual structure of geography

An active learning project in an introductory graduate course used multidimensional scaling of the name index in Geography in America at the Dawn of the 21st Century, by Gary Gaile and Cort Willmott, to reveal some features of the discipline\u27s recent intellectual structure relevant to the relationship between human and physical geography. Previous analyses, dating to the 1980s, used citation indices or Association of American Geographers spe- cialty-group rosters to conclude that either the regional or the methods and environmental subdisciplines bridge human and physical geography. The name index has advantages over those databases, and its analysis reveals that the minimal connectivity that occurs between human and physical geography has recently operated more through environmental than through either methods or regional subdisciplines

Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set

Using quantitative radiomics, we demonstrate that computer-extracted magnetic resonance (MR) image-based tumor phenotypes can be predictive of the molecular classification of invasive breast cancers. Radiomics analysis was performed on 91 MRIs of biopsy-proven invasive breast cancers from National Cancer Institute’s multi-institutional TCGA/TCIA. Immunohistochemistry molecular classification was performed including estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and for 84 cases, the molecular subtype (normal-like, luminal A, luminal B, HER2-enriched, and basal-like). Computerized quantitative image analysis included: three-dimensional lesion segmentation, phenotype extraction, and leave-one-case-out cross validation involving stepwise feature selection and linear discriminant analysis. The performance of the classifier model for molecular subtyping was evaluated using receiver operating characteristic analysis. The computer-extracted tumor phenotypes were able to distinguish between molecular prognostic indicators; area under the ROC curve values of 0.89, 0.69, 0.65, and 0.67 in the tasks of distinguishing between ER+ versus ER−, PR+ versus PR−, HER2+ versus HER2−, and triple-negative versus others, respectively. Statistically significant associations between tumor phenotypes and receptor status were observed. More aggressive cancers are likely to be larger in size with more heterogeneity in their contrast enhancement. Even after controlling for tumor size, a statistically significant trend was observed within each size group (P = 0.04 for lesions ≤ 2 cm; P = 0.02 for lesions >2 to≤ 5 cm) as with the entire data set (P-value = 0.006) for the relationship between enhancement texture (entropy) and molecular subtypes (normal-like, luminal A, luminal B, HER2-enriched, basal-like). In conclusion, computer-extracted image phenotypes show promise for high-throughput discrimination of breast cancer subtypes and may yield a quantitative predictive signature for advancing precision medicine

On the origin of spaces: morphometric foundations of urban form evolution

The modern discipline of urban morphology gives us a ground for the comparative analysis of cities, which increasingly includes specific quantitative elements. In this paper, we make a further step forward towards the definition of a general method for the classification of urban form. We draw from morphometrics and taxonomy in life sciences to propose such method, which we name ‘urban morphometrics’. We then test it on a unit of the urban landscape named ‘Sanctuary Area’ (SA), explored in 45 cities whose origins span four historic time periods: Historic (medieval), Industrial (19th century), New Towns (post-WWII, high-rise) and Sprawl (post-WWII, low-rise). We describe each SA through 207 physical dimensions and then use these to discover features that discriminate them among the four temporal groups. Nine dimensions emerge as sufficient to correctly classify 90% of the urban settings by their historic origins. These nine attributes largely identify an area's ‘visible identity’ as reflected by three characteristics: (1) block perimeterness, or the way buildings define the street-edge; (2) building coverage, or the way buildings cover the land and (3) regular plot coverage, or the extent to which blocks are made of plots that have main access from a street. Hierarchical cluster analysis utilising only the nine key variables nearly perfectly clusters each SA according to its historic origin; moreover, the resulting dendrogram shows, just after WWII, the first ‘bifurcation’ of urban history, with the emergence of the modern city as a new ‘species’ of urban form. With ‘urban morphometrics’ we hope to extend urban morphological research and contribute to understanding the way cities evolve