Self-similarity of Mean Flow in Pipe Turbulence

Based on our previous modified log-wake law in turbulent pipe ‡flows, we invent two compound similarity numbers (Y;U), where Y is a combination of the inner variable y+ and outer variable , and U is the pure exect of the wall. The two similarity numbers can well collapse mean velocity profile data with different moderate and large Reynolds numbers into a single universal profile. We then propose an arctangent law for the buffer layer and a general log law for the outer region in terms of (Y;U). From Milikan’s maximum velocity law and the Princeton superpipe data, we derive the von Kármán constant = 0:43 and the additive constant B=6. Using an asymptotic matching method, we obtain a self-similarity law that describes the mean velocity profile from the wall to axis; and embeds the linear law in the viscous sublayer, the quartic law in the bursting sublayer, the classic log law in the overlap, the sine-square wake law in the wake layer, and the parabolic law near the pipe axis. The proposed arctangent law, the general log law and the self-similarity law have been compared with the high-quality data sets, with diffrent Reynolds numbers, including those from the Princeton superpipe, Loulou et al., Durst et al., Perry et al., and den Toonder and Nieuwstadt. Finally, as an application of the proposed laws, we improve the McKeon et al. method for Pitot probe displacement correction, which can be used to correct the widely used Zagarola and Smits data set

Permeability Characteristics of Various Intestinal Regions of Rabbit, Dog, and Monkey

The in vitro permeability of a series of both hydrophilic and lipophilic compounds, as defined by the octanol/water partition coefficient, was measured in four segments of rabbit, monkey, and dog intestine using a side-by-side diffusion cell. A linear relationship was established for tissue resistance to hydrophilic compound diffusion in jejunum and colon among rabbit, monkey, and dog. The results suggest that rabbit jejunum is twice as permeable as monkey and dog jejunum. The colonic tissues of monkey, rabbit, and dog demonstrate similar permeabilities. Measuring the permeabilities of different tissues with compounds of similar physicochemical properties allows comparison of tissue restriction to transport. Thus, in vitro permeability measurements may be used to investigate physiological differences of various intestinal tissue segments that influence tissue permeability. Investigating the permeability of different intestinal segments from various species could allow the identification of an appropriate in vitro intestinal permeability model that will lead to the prediction of intestinal absorption in humans, eliminating the need for extensive and often misleading in vivo animal testing.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41567/1/11095_2004_Article_305334.pd

Comparison of the Permeability Characteristics of a Human Colonic Epithelial (Caco-2) Cell Line to Colon of Rabbit, Monkey, and Dog Intestine and Human Drug Absorption

The in vitro permeabilities of Caco-2 monolayers and permeabilities in tissue sections from colon of monkey, rabbit, and dog were compared using a series of compounds. The selected compounds differed in their physicochemical properties, such as octanol/water partition coefficient, water solubility, and molecular weight. Their structure included steroids, carboxylic acids, xanthins, alcohols, and polyethylene glycols. A linear permeability relationship was established between Caco-2 and colon tissue from both rabbit and monkey. The results suggest that Caco-2 is twice as permeable as rabbit and five times as permeable as monkey colon. However, no clear relationship could be established between Caco-2 monolayers and dog colon permeability. A relationship between permeability in Caco-2 monolayers and human absorption was found. The results suggest that within certain limits, permeability of Caco-2 monolayers may be used as a predictive tool to estimate human drug absorption.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41425/1/11095_2004_Article_304739.pd

Effect of Rhodium Distribution on Thermal Stability of Nanoporous Palladium-Rhodium Powders

Nanoporous palladium−rhodium alloys with nonuniform Rh distribution show enhanced thermal stability of pores in Rh-rich regions when the surface is under vacuum in either oxidized or reduced form. However, when heated in the presence of hydrogen, accelerated rearrangement of surface atoms is observed, and pores are less stable

Mechanisms of gold biomineralization in the bacterium Cupriavidus metallidurans

While the role of microorganisms as main drivers of metal mobility and mineral formation under Earth surface conditions is now widely accepted, the formation of secondary gold (Au) is commonly attributed to abiotic processes. Here we report that the biomineralization of Au nanoparticles in the metallophillic bacterium Cupriavidus metallidurans CH34 is the result of Au-regulated gene expression leading to the energy-dependent reductive precipitation of toxic Au(III)-complexes. C. metallidurans, which forms biofilms on Au grains, rapidly accumulates Au(III)-complexes from solution. Bulk and microbeam synchrotron X-ray analyses revealed that cellular Au accumulation is coupled to the formation of Au(I)-S complexes. This process promotes Au toxicity and C. metallidurans reacts by inducing oxidative stress and metal resistances gene clusters (including a Au-specific operon) to promote cellular defense. As a result, Au detoxification is mediated by a combination of efflux, reduction, and possibly methylation of Au-complexes, leading to the formation of Au(I)-C-compounds and nanoparticulate Au(0). Similar particles were observed in bacterial biofilms on Au grains, suggesting that bacteria actively contribute to the formation of Au grains in surface environments. The recognition of specific genetic responses to Au opens the way for the development of bioexploration and bioprocessing tools.Frank Reith, Barbara Etschmann, Cornelia Grosse, Hugo Moors, Mohammed A. Benotmane, Pieter Monsieurs, Gregor Grass, Christian Doonan, Stefan Vogt, Barry Lai, Gema Martinez-Criado, Graham N. George, Dietrich H. Nies, Max Mergeay, Allan Pring, Gordon Southam and Joël Brugge

Open Source Bayesian Models. 1. Application to ADME/Tox and Drug Discovery Datasets

On the order of hundreds of absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) models have been described in the literature in the past decade which are more often than not inaccessible to anyone but their authors. Public accessibility is also an issue with computational models for bioactivity, and the ability to share such models still remains a major challenge limiting drug discovery. We describe the creation of a reference implementation of a Bayesian model-building software module, which we have released as an open source component that is now included in the Chemistry Development Kit (CDK) project, as well as implemented in the CDD Vault and in several mobile apps. We use this implementation to build an array of Bayesian models for ADME/Tox, <i>in vitro</i> and <i>in vivo</i> bioactivity, and other physico­chemical properties. We show that these models possess cross-validation receiver operator curve values comparable to those generated previously in prior publications using alternative tools. We have now described how the implementation of Bayesian models with FCFP6 descriptors generated in the CDD Vault enables the rapid production of robust machine learning models from public data or the user’s own datasets. The current study sets the stage for generating models in proprietary software (such as CDD) and exporting these models in a format that could be run in open source software using CDK components. This work also demonstrates that we can enable biocomputation across distributed private or public datasets to enhance drug discovery