The effect of termination alloying elements on the resistance of vacuum evaporated aluminum thin films

A study was conducted to investigate the reasons for changes in the effective series resistance of aluminized capacitors with time. The elements of quarternary alloy, zinc, tin, cadmium and iodium were chosen for the study

A Comparison of U.S. and European University-Industry Relations in the Life Sciences

We draw on diverse data sets to compare the institutional organization of upstream life science research across the United States and Europe. Understanding cross-national differences in the organization of innovative labor in the life sciences requires attention to the structure and evolution of biomedical networks involving public research organizations (universities, government laboratories, nonprofit research institutes, and research hospitals), science-based biotechnology firms, and multinational pharmaceutical corporations. We use network visualization methods and correspondence analyses to demonstrate that innovative research in biomedicine has its origins in regional clusters in the United States and in European nations. But the scientific and organizational composition of these regions varies in consequential ways. In the United States, public research organizations and small firms conduct R&D across multiple therapeutic areas and stages of the development process. Ties within and across these regions link small firms and diverse public institutions, contributing to the development of a robust national network. In contrast, the European story is one of regional specialization with a less diverse group of public research organizations working in a smaller number of therapeutic areas. European institutes develop local connections to small firms working on similar scientific problems, while cross-national linkages of European regional clusters typically involve large pharmaceutical corporations. We show that the roles of large and small firms differ in the United States and Europe, arguing that the greater heterogeneity of the U.S. system is based on much closer integration of basic science and clinical development.University-Industry Relations; National Innovation Systems; R&D Networks; Spatial Clustering; Network Visualization

Quality determination and the repair of poor quality spots in array experiments.

BACKGROUND: A common feature of microarray experiments is the occurrence of missing gene expression data. These missing values occur for a variety of reasons, in particular, because of the filtering of poor quality spots and the removal of undefined values when a logarithmic transformation is applied to negative background-corrected intensities. The efficiency and power of an analysis performed can be substantially reduced by having an incomplete matrix of gene intensities. Additionally, most statistical methods require a complete intensity matrix. Furthermore, biases may be introduced into analyses through missing information on some genes. Thus methods for appropriately replacing (imputing) missing data and/or weighting poor quality spots are required. RESULTS: We present a likelihood-based method for imputing missing data or weighting poor quality spots that requires a number of biological or technical replicates. This likelihood-based approach assumes that the data for a given spot arising from each channel of a two-dye (two-channel) cDNA microarray comparison experiment independently come from a three-component mixture distribution--the parameters of which are estimated through use of a constrained E-M algorithm. Posterior probabilities of belonging to each component of the mixture distributions are calculated and used to decide whether imputation is required. These posterior probabilities may also be used to construct quality weights that can down-weight poor quality spots in any analysis performed afterwards. The approach is illustrated using data obtained from an experiment to observe gene expression changes with 24 hr paclitaxel (Taxol) treatment on a human cervical cancer derived cell line (HeLa). CONCLUSION: As the quality of microarray experiments affect downstream processes, it is important to have a reliable and automatic method of identifying poor quality spots and arrays. We propose a method of identifying poor quality spots, and suggest a method of repairing the arrays by either imputation or assigning quality weights to the spots. This repaired data set would be less biased and can be analysed using any of the appropriate statistical methods found in the microarray literature.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Diversity and Dominant Species of Ground Beetle Assemblages (Coleoptera: Carabidae) in Crop Rotation and Chemical Input Systems for the Northern Great Plains

Dominant carabid species present in crops and crop rotation sequences commonly used in the northern Great Plains were assessed as an initial step toward the management of carabids as natural control agents. Ground beetle populations were determined by pitfall trapping in 4 crop rotation treatments maintained under high, managed, and low levels of chemical fertilizer and pesticide inputs. Diversity and species richness among crops, rotations, and input levels were compared using 3 indices—the Shannon-Weaver Index, relative diversity, and the Hierarchical Richness Index (HRI). Four carabid species, Cyclotrachelus altemans (Casey), Poecilvs lucublandus Say, Harpalns pensylvanicus (DeGeer), and Bembidion quadrimaculatum L., comprising ≈80% of the total collected, were considered dominant species. When carabid abundance data were grouped by crop, C. altemans was the dominant species in corn and alfalfa and P. lucublandus was dominant in wheat. In soybean plots, C. altemans and P. lucublandus were equally abundant. The relative abundance of H. pensylvanicus was highest in the low-input plots. High values of HRI for carabid diversity and species richness in the managed plots suggested that reduced chemical inputs encouraged greater abundance and diversity of beneficial carabids than were found in the high-input plots without the loss of yield seen in the low-input plots

Diversity and Dominant Species of Ground Beetle Assemblages (Coleoptera: Carabidae) in Crop Rotation and Chemical Input Systems for the Northern Great Plains

Dominant carabid species present in crops and crop rotation sequences commonly used in the northern Great Plains were assessed as an initial step toward the management of carabids as natural control agents. Ground beetle populations were determined by pitfall trapping in 4 crop rotation treatments maintained under high, managed, and low levels of chemical fertilizer and pesticide inputs. Diversity and species richness among crops, rotations, and input levels were compared using 3 indices—the Shannon-Weaver Index, relative diversity, and the Hierarchical Richness Index (HRI). Four carabid species, Cyclotrachelus altemans (Casey), Poecilvs lucublandus Say, Harpalns pensylvanicus (DeGeer), and Bembidion quadrimaculatum L., comprising ≈80% of the total collected, were considered dominant species. When carabid abundance data were grouped by crop, C. altemans was the dominant species in corn and alfalfa and P. lucublandus was dominant in wheat. In soybean plots, C. altemans and P. lucublandus were equally abundant. The relative abundance of H. pensylvanicus was highest in the low-input plots. High values of HRI for carabid diversity and species richness in the managed plots suggested that reduced chemical inputs encouraged greater abundance and diversity of beneficial carabids than were found in the high-input plots without the loss of yield seen in the low-input plots

Networks, Fields and Organizations: Micro-Dynamics, Scale and Cohesive Embeddings

Social action is situated in fields that are simultaneously composed of interpersonal ties and relations among organizations, which are both usefully characterized as social networks. We introduce a novel approach to distinguishing different network macro-structures in terms of cohesive subsets and their overlaps. We develop a vocabulary that relates different forms of network cohesion to field properties as opposed to organizational constraints on ties and structures. We illustrate differences in probabilistic attachment processes in network evolution that link on the one hand to organizational constraints versus field properties and to cohesive network topologies on the other. This allows us to identify a set of important new micro-macro linkages between local behavior in networks and global network properties. The analytic strategy thus puts in place a methodology for Predictive Social Cohesion theory to be developed and tested in the context of informal and formal organizations and organizational fields. We also show how organizations and fields combine at different scales of cohesive depth and cohesive breadth. Operational measures and results are illustrated for three organizational examples, and analysis of these cases suggests that different structures of cohesive subsets and overlaps may be predictive in organizational contexts and similarly for the larger fields in which they are embedded. Useful predictions may also be based on feedback from level of cohesion in the larger field back to organizations, conditioned on the level of multiconnectivity to the field.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44715/1/10588_2005_Article_5273175.pd

A Comparison of U. S. and European University-Industry Relations in the Life Sciences

We draw on diverse data sets to compare the institutional organization of upstream life science research across the United States and Europe. Understanding cross-national differences in the organization of innovative labor in the life sciences requires attention to the structure and evolution of biomedical networks involving public research organizations (universities, government laboratories, nonprofit research institutes, and research hospitals), science-based biotechnology firms, and multinational pharmaceutical corporations. We use network visualization methods and correspondence analyses to demonstrate that innovative research in biomedicine has its origins in regional clusters in the United States and in European nations. But the scientific and organizational composition of these regions varies in consequential ways. In the United States, public research organizations and small firms conduct R&D across multiple therapeutic areas and stages of the development process. Ties within and across these regions link small firms and diverse public institutions, contributing to the development of a robust national network. In contrast, the European story is one of regional specialization with a less diverse group of public research organizations working in a smaller number of therapeutic areas. European institutes develop local connections to small firms working on similar scientific problems, while cross-national linkages of European regional clusters typically involve large pharmaceutical corporations. We show that the roles of large and small firms differ in the United States and Europe, arguing that the greater heterogeneity of the U. S. system is based on much closer integration of basic science and clinical development

The Two Variables in The Triple System HR 6469=V819 Her: One Eclipsing, One Spotted

A complete BV light curve, from 14 nights of good data obtained with the Vanderbilt University-Tennessee State University (VU-TSU) automatic telescope, are presented and solved with the Wilson-Devinney program. Third light is evaluated, with the companion star brighter by 0.58m in V and 0.11m in B. The eclipses are partial. Inferred color indices yield F2 V and F8 V for the eclipsing pair and G8 IV-III for the distant companion star. After removing the variability due to eclipses, we study the residual variability of the G8 IV-III star over the ten years 1982 to 1992. Each yearly light curve is fit with a two-spot model. Three relatively long-lived spots are identified, with rotation periods of 85.9d, 85.9d, and 86.1d. The weak and intermittent variability is understood because the G8 IV-III star has a Rossby number at the threshold for the onset of heavy spottedness