Rebel invasion of Missouri and Kansas, and the campaign of the army of the border against General Sterling Price, in October and November, 1864.

Appendix: List of Union soldiers killed in Missouri and Kansas engagements.

A method for systematically pooling data in very early stage construction price forecasting

Client owners usually need an estimate or forecast of their likely building costs in advance of detailed design in order to confirm the financial feasibility of their projects. Because of their timing in the project life cycle, these early stage forecasts are characterized by the minimal amount of information available concerning the new (target) project to the point that often only its size and type are known. One approach is to use the mean contract sum of a sample, or base group, of previous projects of a similar type and size to the project for which the estimate is needed. Bernoulli’s law of large numbers implies that this base group should be as large as possible. However, increasing the size of the base group inevitably involves including projects that are less and less similar to the target project. Deciding on the optimal number of base group projects is known as the homogeneity or pooling problem. A method of solving the homogeneity problem is described involving the use of closed form equations to compare three different sampling arrangements of previous projects for their simulated forecasting ability by a cross-validation method, where a series of targets are extracted, with replacement, from the groups and compared with the mean value of the projects in the base groups. The procedure is then demonstrated with 450 Hong Kong projects (with different project types: Residential, Commercial centre, Car parking, Social community centre, School, Office, Hotel, Industrial, University and Hospital) clustered into base groups according to their type and size.

The effect of project information on the accuracy of building price forecasts

A fundamental proposition is that the accuracy of the designer's tender price forecasts is positively correlated with the amount of information available for that project. The paper describes an empirical study of the effects of the quantity of information available on practicing Quantity Surveyors' forecasting accuracy. The methodology involved the surveyors repeatedly revising tender price forecasts on receipt of chunks of project information. Each of twelve surveyors undertook two projects and selected information chunks from a total of sixteen information types. The analysis indicated marked differences in accuracy between different project types and experts/non-experts. The expert surveyors' forecasts were not found to be significantly improved by information other than that of basic building type and size, even after eliminating project type effects. The expert surveyors' forecasts based on the knowledge of building type and size alone were, however, found to be of similar accuracy to that of average practitioners pricing full bills of quantities.

Heuristics and building price forecasting

The construction industry contains two types of estimators the contractors' estimator and the designers' price forecaster. Each has two models of the building in which to systemize his procedures - the production model and the design model. The use of these models is discussed in the light of the industry's particular problems of complexity and uncertainty together with the pressures of the market. It is argued that estimators and forecasters, in order to function effectively in these conditions, are forced to exercise a high degree of subjective judgment. Means of eliciting good heuristics involved in judgment making are considered by reference to the artificial intelligence and construction literature and a methodology is proposed based on these findings. The results of two early trials of the method with students are given, indicating the usefulness of the approach.

Industrial land price and its impact on urban growth : a Chinese case study

China is experiencing rapid progress in industrialization, with its own rationale toward industrial land development based on a deliberate change from an extensive to intensive form of urban land use. One result has been concerted attempts by local government to attract foreign investment by a low industrial land price strategy, which has resulted in a disproportionally large amount of industrial land within the total urban land use structure at the expense of the urban sprawl of many cities. This paper first examines “Comparable Benchmark Price as Residential land use” (CBPR) as the theoretical basis of the low industrial land price phenomenon. Empirical findings are presented from a case study based on data from Jinyun County, China. These data are analyzed to reveal the rationale of industrial land price from 2000 to 2010 concerning the CBPR model. We then explore the causes of low industrial land prices in the form of a “Centipede Game Model”, involving two neighborhood regions as “major players” to make a set of moves (or strategies). When one of the players unilaterally reduces the land price to attract investment with the aim to maximize profits arising from the revenues generated from foreign investment and land premiums, a two-player price war begins in the form of a dynamic game, the effect of which is to produce a downward spiral of prices. In this context, the paradox of maximizing profits for each of the two players are not accomplished due to the inter-regional competition of attracted investment leading to a lose-lose situation for both sides’ in competing for land premium revenues. A short-term solution to the problem is offered involving the establishment of inter-regional cooperative partnerships. For the longer term, however, a comprehensive reform of the local financial system, more adroit regional planning and an improved means of evaluating government performance is needed to ensure the government's role in securing pubic goods is not abandoned in favor of one solely concerned with revenue generation.

Three generations of Therese Gottschalk nee Molling, her daughter Elizabeth Gottschalk and Grandmother Henny Molling; Hannover, Germany.

From left to right: Therese Gottschalk nee Molling, Elizabeth Gottschalk, Henny Molling

Henny Molling nee Meyerhof, Therese Gottschalk nee Molling, Kurt, Elizabeth and Hal Gottschalk on the beach; Norderney, Germany.

Sitting in the Strandkorb (beach chair) at Norderney are Henny Molling and Therese Gottschalk; sitting in the sand are Kurt, Elizabeth and Hal Gottschalk

Genetic studies of body mass index yield new insights for obesity biology

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10−8), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ~2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

Three generations of Therese Gottschalk nee Molling, her daughter Elizabeth Gottschalk and Grandmother Henny Molling; Hannover, Germany.

From left to right: Therese Gottschalk nee Molling, Elizabeth Gottschalk, Henny Molling