What Development Regulatory Variables Say—or Don’t Say—About A Municipality

Little is known about how regulatory development variables reflect and define a community. This paper explores the correlation of development regulatory variables with broader community measures in 68 municipalities in the Twin Cities area of Minnesota. Coefficients of determination, correlation coefficients, principal component analysis, and factor analysis were used to compare development regulatory data with broader municipal measures. The hypothesis tested is overarching: that a municipality’s development regulations and processes correlate to general measures of community composition. The strongest and only significant correlations found were in the municipal use of tax increment financing and commercial/ industrial property values, non-residential construction activity, population, and multi-family building permit activity.

Theorems of Sylow Theory

Call number: LD2668 .R4 1965 M98

A Unique Population of Cave Bears (Carnivora: Ursidae) from the Middle Pleistocene of Kents Cavern, England, Based on Dental Morphometrics

The ‘breccia’ stratum from Kents (we follow local tradition in using the form ‘Kents’, without an apostrophe) Cavern, England, has been well known for its rich yield of cave-bear material since excavations began in the mid-19th century. Recent work has established that the bears are of latest MIS 12 or earliest MIS 11 age. A life table based on a collection of 67 molariform teeth is consistent with the use of the cave as a hibernaculum. Univariate and morphological assessment of the teeth shows an unusual range of primitive and more derived characters. Multivariate morphometric analysis of cave-bear teeth from the site demonstrates that these animals, while currently assignable to Ursus deningeri sensu lato, are nevertheless morphologically distinct and not simply late deningeri on a hypothetical chronospecific continuum

Discrete tomography and joint inversion for loosely connected or unconnected physical properties: application to crosshole seismic and georadar data sets

Tomographic inversions of geophysical data generally include an underdetermined component. To compensate for this shortcoming, assumptions or a priori knowledge need to be incorporated in the inversion process. A possible option for a broad class of problems is to restrict the range of values within which the unknown model parameters must lie. Typical examples of such problems include cavity detection or the delineation of isolated ore bodies in the subsurface. In cavity detection, the physical properties of the cavity can be narrowed down to those of air and/or water, and the physical properties of the host rock either are known to within a narrow band of values or can be established from simple experiments. Discrete tomography techniques allow such information to be included as constraints on the inversions. We have developed a discrete tomography method that is based on mixed-integer linear programming. An important feature of our method is the ability to invert jointly different types of data, for which the key physical properties are only loosely connected or unconnected. Joint inversions reduce the ambiguity in tomographic studies. The performance of our new algorithm is demonstrated on several synthetic data sets. In particular, we show how the complementary nature of seismic and georadar data can be exploited to locate air- or water-filled cavitie

Two-Functional Direct Current Sputtered Silver-Containing Titanium Dioxide Thin Films

The article reports on structure, mechanical, optical, photocatalytic and biocidal properties of Ti–Ag–O films. The Ti–Ag–O films were reactively sputter-deposited from a composed Ti/Ag target at different partial pressures of oxygen on unheated glass substrate held on floating potentialUfl. It was found that addition of ~2 at.% of Ag into TiO2film has no negative influence on UV-induced hydrophilicity of TiO2film. Thick (~1,500 nm) TiO2/Ag films containing (200) anatase phase exhibit the best hydrophilicity with water droplet contact angle (WDCA) lower than 10° after UV irradiation for 20 min. Thick (~1,500 nm) TiO2/Ag films exhibited a better UV-induced hydrophilicity compared to that of thinner (~700 nm) TiO2/Ag films. Further it was found that hydrophilic TiO2/Ag films exhibit a strong biocidal effect under both the visible light and the UV irradiation with 100% killing efficiency ofEscherichia coliATCC 10536 after UV irradiation for 20 min. Reported results show that single layer of TiO2with Ag distributed in its whole volume exhibits, after UV irradiation, simultaneously two functions: (1) excellent hydrophilicity with WDCA < 10° and (2) strong power to killE. colieven under visible light due to direct toxicity of Ag

Assembly of a polymer lab-on-chip device for impedimetric measurements of D-dimers in whole blood

This paper reports the development and characterisation of an assembly technology for a polymer lab-on-chip. The system consists of a 150 m deep hot embossed microfluidic channel in polycarbonate and Au electrodes fabricated separately by photolithography on polyethylenenaphthalate. The system is designed for impedimetric immunoassay detection in whole blood. Electrode layer and microfluidic substrate are joined by means of a 50 m thick double-sided medical grade adhesive tape, adjusted with an optical alignment system. The bond proved to be liquid tight at room temperature. An alignment accuracy of 34 m (+/- 19 m) evaluated over a set of 23 samples, was achieved. The effect of alignment accuracy of the intermediate adhesive film on whole blood flow properties in the device is studied. Already an alignment error of 70 m increases the flushing out time of whole blood by approximately 20 %

Atomic-scale representation and statistical learning of tensorial properties

This chapter discusses the importance of incorporating three-dimensional symmetries in the context of statistical learning models geared towards the interpolation of the tensorial properties of atomic-scale structures. We focus on Gaussian process regression, and in particular on the construction of structural representations, and the associated kernel functions, that are endowed with the geometric covariance properties compatible with those of the learning targets. We summarize the general formulation of such a symmetry-adapted Gaussian process regression model, and how it can be implemented based on a scheme that generalizes the popular smooth overlap of atomic positions representation. We give examples of the performance of this framework when learning the polarizability and the ground-state electron density of a molecule