Surface texture produced by peripheral milling with helical end mills

An investigation of the surface texture produced by peripheral milling with end mills has been made. Theoretical relationships are presented to predict the theoretical cusp height and approximate the arithmetical average surface roughness based on the geometrical considerations of a circular tooth path. Experimentation was conducted to correlate the theoretical approximations and to determine the significance of process variables using multiple regression analysis. The theory, based entirely on the geometrical aspects of a circular tooth path, indicated that the theoretical cusp height may be determined knowing the cutter diameter and the incremental feed per tooth. The location of the mean line, about which the surface roughness was evaluated, is determined. Approximations of the arithmetical average surface roughness are presented which indicate that the roughness may be approximated knowing only the cutter diameter and the incremental feed per tooth. A compensation for tooth height variation is also considered. Multiple regression analyses of data obtained experimentally for this project and data obtained from a similar study involving end mill deflection indicate that feed per tooth and cutter helix angle are the primary process parameters contributing to surface finish. A relationship between cutter helix angle, radial rake angle and oblique radial rake angle indicates that the oblique radial rake angle and not the helix angle may be the most significant variable not included in the geometry based theory

Regression of binary network data with exchangeable latent errors

Undirected, binary network data consist of indicators of symmetric relations between pairs of actors. Regression models of such data allow for the estimation of effects of exogenous covariates on the network and for prediction of unobserved data. Ideally, estimators of the regression parameters should account for the inherent dependencies among relations in the network that involve the same actor. To account for such dependencies, researchers have developed a host of latent variable network models, however, estimation of many latent variable network models is computationally onerous and which model is best to base inference upon may not be clear. We propose the Probit Exchangeable (PX) Model for undirected binary network data that is based on an assumption of exchangeability, which is common to many of the latent variable network models in the literature. The PX model can represent the second moments of any exchangeable network model, yet specifies no particular parametric model. We present an algorithm for obtaining the maximum likelihood estimator of the PX model, as well as a modified version of the algorithm that is extremely computationally efficient and provides an approximate estimator. Using simulation studies, we demonstrate the improvement in estimation of regression coefficients of the proposed model over existing latent variable network models. In an analysis of purchases of politically-aligned books, we demonstrate political polarization in purchase behavior and show that the proposed estimator significantly reduces runtime relative to estimators of latent variable network models while maintaining predictive performance

Latent influence networks in global environmental politics

International environmental treaties are the key means by which states overcome collective action problems and make specific commitments to address environmental issues. However, systematically assessing states’ influence in promoting global environmental protection has proven difficult. Analyzing newly compiled data with a purpose-built statistical model, we provide a novel measurement of state influence within the scope of environmental politics and find strong influences among states and treaties. Specifically, we report evidence that states are less likely to ratify when states within their region ratify, and results suggesting that countries positively influence other countries at similar levels of economic development. By examining several prominent treaties, we illustrate the complex nature of influence: a single act of ratification can dramatically reshape global environmental politics. More generally, our findings and approach provide an innovative means to understand the evolution and complexity of international environmental protection

The Northwestern Greenland Ice Sheet During The Early Pleistocene Was Similar To Today

The multi-million year history of the Greenland Ice Sheet remains poorly known. Ice-proximal glacial marine diamict provides a direct but discontinuous record of ice sheet behavior; it is underutilized as a climate archive. Here, we present a novel multiproxy analysis of an Early Pleistocene marine diamict from northwestern Greenland. Low cosmogenic nuclide concentrations indicate minimal near-surface exposure, similar to modern terrestrial sediment. Detrital apatite (U-Th-Sm)/He (AHe) ages all predate glaciation by \u3e150 million years, suggesting the northwestern Greenland Ice Sheet had, by 1.9 Ma, not yet incised fjords of sufficient depth to excavate grains with young AHe ages. The diamict contains terrestrial plant leaf wax, likely from land surfaces surrounding the ice sheet. These data indicate that a persistent, dynamic ice sheet existed in northwestern Greenland by 1.9 Ma and that diamict is a useful archive of ice sheet history and process

Construction and Random Generation of Hypergraphs with Prescribed Degree and Dimension Sequences

We propose algorithms for construction and random generation of hypergraphs without loops and with prescribed degree and dimension sequences. The objective is to provide a starting point for as well as an alternative to Markov chain Monte Carlo approaches. Our algorithms leverage the transposition of properties and algorithms devised for matrices constituted of zeros and ones with prescribed row- and column-sums to hypergraphs. The construction algorithm extends the applicability of Markov chain Monte Carlo approaches when the initial hypergraph is not provided. The random generation algorithm allows the development of a self-normalised importance sampling estimator for hypergraph properties such as the average clustering coefficient.We prove the correctness of the proposed algorithms. We also prove that the random generation algorithm generates any hypergraph following the prescribed degree and dimension sequences with a non-zero probability. We empirically and comparatively evaluate the effectiveness and efficiency of the random generation algorithm. Experiments show that the random generation algorithm provides stable and accurate estimates of average clustering coefficient, and also demonstrates a better effective sample size in comparison with the Markov chain Monte Carlo approaches.Comment: 21 pages, 3 figure

On general measures of deformation

Each particle of a continuum is assigned a second order tensor which is taken as a measure of the deformation of some neighborhood of the particle, and which is determined by a functional depending on the configurations of that neighborhood. Two invariance restrictions are imposed on the functional whose values are spatial strain tensors, that is, associated with the deformed configuration. The first requirement is that a time shift and rigid transformation of the deformed configuration leave the spatial deformation tensor unaltered relative to it. The second requires that if particles of distinct continua undergo the same deformation, the corresponding deformation tensors should be the same. For the special case in which the functional depends on the deformation in the smallest neighborhood of a particle, the restrictions imply that the deformation tensors associated with the deformed and reference configurations are isotropic functions of the left and right Cauchy-Green tensors, respectively. Jedem Teilchen eines Kontinuums wird ein Tensor zweiter Stufe als Maß für die Deformation einer gewissen Nachbarschaft dieses Teilchen zugeordnet, der durch ein Funktional bestimmt wird, das von der Konfiguration dieser Nachbarschaft abhängt. Zwei Invarianzbedingungen werden diesem Funktional, dessen Werte räumliche Verzerrungstensoren darstellen, auferlegt, und zwar im Hindblick auf die deformierte Konfiguration. Die erste Forderung besagt, daß eine Zeitverschiebung und eine starre Transformation der deformierten Konfiguration den räumlichen Verzerrungstensor im Hinblick auf diese ungeändert lassen. Die zweite Einschränkung besagt, daß entsprechende Deformationstensoren von Partikeln verschiedener Kontinua, die dieselbe Verformung erlitten haben, gleich sein sollen. Im Spezialfall, daß die Funktionale nur von der Deformation in der nächsten Umgebung des Partikels abhängen, beinhalten die Einschränkungen die Aussage, daß die mit dem deformierten und dem undeformierten Zustand verknüpften Deformationstensoren nur isotrope Funktionen des linken und des rechten Cauchy-Green Tensors sein können.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41717/1/707_2005_Article_BF01172146.pd