Fibroblasts can condense a hydrated collagen lattice to a tissue-like structure 1/28th the area of the starting gel in 24 hr. The rate of the process can be regulated by varying the protein content of the lattice, the cell number, or the con- centration of an inhibitor such as Colcemid. Fibroblasts of high population doubling level propagated in vitro, which have left the cell cycle, can carry out the contraction at least as efficiently as cycling cells. The potential uses of the system as an immu- nologically tolerated "tissue" for wound hea ing and as a model for studying fibroblast function are discussed.

Production of a tissue-like structure by contraction of collagen lattices by human fibroblasts of different proliferative

Introduction.- Data management and software.- Advice for teachers.- Exploration.- Linear regression.- Generalised linear modelling.- Additive and generalised additive modelling.- Introduction to mixed modelling.- Univariate tree models.- Measures of association.- Ordination--first encounter.- Principal component analysis and redundancy analysis.- Correspondence analysis and canonical correspondence analysis.- Introduction to discriminant analysis.- Principal coordinate analysis and non-metric multidimensional scaling.- Time series analysis--Introduction.- Common trends and sudden changes.- Analysis and modelling lattice data.- Spatially continuous data analysis and modelling.- Univariate methods to analyse abundance of decapod larvae.- Analysing presence and absence data for flatfish distribution in the Tagus estuary, Portugual.- Crop pollination by honeybees in an Argentinean pampas system using additive mixed modelling.- Investigating the effects of rice farming on aquatic birds with mixed modelling.- Classification trees and radar detection of birds for North Sea wind farms.- Fish stock identification through neural network analysis of parasite fauna.- Monitoring for change: using generalised least squares, nonmetric multidimensional scaling, and the Mantel test on western Montana grasslands.- Univariate and multivariate analysis applied on a Dutch sandy beach community.- Multivariate analyses of South-American zoobenthic species--spoilt for choice.- Principal component analysis applied to harbour porpoise fatty acid data.- Multivariate analysis of morphometric turtle data--size and shape.- Redundancy analysis and additive modelling applied on savanna tree data.- Canonical correspondence analysis of lowland pasture vegetation in the humid tropics of Mexico.- Estimating common trends in Portuguese fisheries landings.- Common trends in demersal communities on the Newfoundland-Labrador Shelf.- Sea level change and salt marshes in the Wadden Sea: a time series analysis.- Time series analysis of Hawaiian waterbirds.- Spatial modelling of forest community features in the Volzhsko-Kamsky reserve.

Analysing Ecological Data

This study aimed to review the literature describing and quantifying time lags in the health research translation process. Papers were included in the review if they quantified time lags in the development of health interventions. The study identified 23 papers. Few were comparable as different studies use different measures, of different things, at different time points. We concluded that the current state of knowledge of time lags is of limited use to those responsible for R&D and knowledge transfer who face difficulties in knowing what they should or can do to reduce time lags. This effectively ‘blindfolds’ investment decisions and risks wasting effort. The study concludes that understanding lags first requires agreeing models, definitions and measures, which can be applied in practice. A second task would be to develop a process by which to gather these data.

The Answer Is 17 Years, What Is the Question

In this paper we describe a cellular automaton (CA) simulation model developed to predict urban growth as part of a project for estimating the regional and broader impact of urbanization on the San Francisco Bay area's climate. The rules of the model are more complex than those of a typical CA and involve the use of multiple data sources, including topography, road networks, and existing settlement distributions, and their modification over time. In addition, the control parameters of the model are allowed to self-modify: that is, the CA adapts itself to the circumstances it generates, in particular, during periods of rapid growth or stagnation. In addition, the model was written to allow the accumulation of probabilistic estimates based on Monte Carlo methods. Calibration of the model has been accomplished by the use of historical maps to compare model predictions of urbanization, based solely upon the distribution in year 1900, with observed data for years 1940, 1954, 1962, 1974, and 1990. The complexity of this model has made calibration a particularly demanding step. Lessons learned about the methods, measures, and strategies developed to calibrate the model may be of use in other environmental modeling contexts. With the calibration complete, the model is being used to generate a set of future scenarios for the San Francisco Bay area along with their probabilities based on the Monte Carlo version of the model. Animated dynamic mapping of the simulations will be used to allow visualization of the impact of future urban growth.

/pdf/a-self-modifying-cellular-automaton-model-of-historical-4znon8yqbj.pdf

A Self-Modifying Cellular Automaton Model of Historical Urbanization in the San Francisco Bay Area

Poor housing conditions are associated with a wide range of health conditions, including respiratory infections, asthma, lead poisoning, injuries, and mental health. Addressing housing issues offers public health practitioners an opportunity to address an important social determinant of health. Public health has long been involved in housing issues. In the 19th century, health officials targeted poor sanitation, crowding, and inadequate ventilation to reduce infectious diseases as well as fire hazards to decrease injuries. Today, public health departments can employ multiple strategies to improve housing, such as developing and enforcing housing guidelines and codes, implementing “Healthy Homes” programs to improve indoor environmental quality, assessing housing conditions, and advocating for healthy, affordable housing. Now is the time for public health to create healthier homes by confronting substandard housing.

Housing and Health: Time Again for Public Health Action

(1998). Creating a Web-based Electronic Reserve Library for Teaching World Regional Geography. Journal of Geography in Higher Education: Vol. 22, No. 2, pp. 257-262.

Creating a Web-Based Electronic Reserve Library for Teaching World Regional Geography.

Geographic areas of different sizes and shapes of polygons that represent counts or rate data are often encountered in social, economic, health, and other information Often political or census boundaries are used to define these areas because the information is available only for those geographies Therefore, these types of boundaries are frequently used to define neighborhoods in spatial analyses using geographic information systems and related approaches such as multilevel models When point data can be geocoded, it is possible to examine the impact of polygon shape on spatial statistical properties, such as clustering We utilized point data (alcohol outlets) to examine the issue of polygon shape and size on visualization and statistical properties The point data were allocated to regular lattices (hexagons and squares) and census areas for zip-code tabulation areas and tracts The number of units in the lattices was set to be similar to the number of tract and zip-code areas A spatial clustering statistic and visualization were used to assess the impact of polygon shape for zip- and tract-sized units Results showed substantial similarities and notable differences across shape and size The specific circumstances of a spatial analysis that aggregates points to polygons will determine the size and shape of the areal units to be used The irregular polygons of census units may reflect underlying characteristics that could be missed by large regular lattices Future research to examine the potential for using a combination of irregular polygons and regular lattices would be useful WIREs Comp Stat 2012, 4:67–74 doi: 101002/wics196



For further resources related to this article, please visit the WIREs website

Clusters in irregular areas and lattices.

In mapping population characteristics, data are usually portrayed as accurate without error. However, many population datasets provide estimates derived from surveys or samples, and a certain level of uncertainty is associated with each estimate. Ignoring estimated uncertainty information in mapping may produce misleading maps and generate spurious spatial patterns. In this paper, we introduce a measure of separability to indicate the likelihood that units assigned to different classes are truly different statistically. A series of map symbolization techniques is proposed to communicate class separability to the cartographer or map reader, and presented in four series of maps of American Community Survey data on median household income for Iowa counties. These map series illustrate several different techniques: a legend designed to communicate separability between classes, graduated line symbols to communicate separability between individual map units, and a color scheme in which perceptual color differen...

Cartographic techniques for communicating class separability: enhanced choropleth maps of median household income, Iowa

Spatial aggregation as a means to improve attribute reliability

Spatial autocorrelation (SA) is regarded as an important dimension of spatial pattern. SA measures usually consist of two components: measuring the similarity of attribute values and defining the spatial relationships among observations. The latter component is often represented by a spatial weights matrix that predefines spatial relationship between observations in most measures. Therefore, SA measures, in essence, are measures of attribute similarity, conditioned by spatial relationship. Another dimension of spatial pattern can be explored by controlling observations to be compared based upon the degree of attribute similarity. The resulting measures are spatial proximity measures of observations, meeting predefined attribute similarity criteria. Proposed measures reflect degrees of clustering or dispersion for observations meeting certain levels of attribute similarity. An existing spatial autocorrelation framework is expanded to a general framework to evaluate spatial patterns and can accommodate the proposed approach measuring proximity. Analogous to the concept of variogram, clustergram is proposed to show the levels of spatial clustering over a range of attribute similarity, or attribute lags. Specific measures based on the proposed approach are formulated and applied to a hypothetical landscape and an empirical example, showing that these new measures capture spatial pattern information not reflected by traditional spatial autocorrelation measures.

David Wong

Papers

Creating a Web-Based Electronic Reserve Library for Teaching World Regional Geography.

Clusters in irregular areas and lattices.

Cartographic techniques for communicating class separability: enhanced choropleth maps of median household income, Iowa

Spatial aggregation as a means to improve attribute reliability

Exploring Spatial Patterns Using an Expanded Spatial Autocorrelation Framework