A non-antibacterial oxazolidinone derivative that inhibits epithelial cell sheet migration

We have developed a high-throughput assay for screening chemical libraries for compounds that affect cell sheet migration during wound closure in epithelial cell monolayers. By using this assay, we have discovered a new inhibitor of cell sheet migration. This compound (UIC-1005) is a 3,4-disubstituted oxazolidinone that bears an electrophilic alpha,beta-unsaturated N-acyl group required for activity. UIC-1005 also inhibits growth in an epithelial cell proliferation assay. The molecule does not display general toxicity at concentrations at which it potently inhibits cell sheet migration and growth. Unlike certain 3,5-disubstituted oxazolidinones, it exhibits no antibacterial activity. UIC-1005 therefore represents a new class of bioactive oxazolidinone derivative that may prove useful as a probe for signaling pathways leading to cell motility.     

A study on the effect of gas flow rate on the wave characteristics in two-phase gas–liquid annular flow

Interfacial waves play a very important role in the mass, momentum and energy transport phenomena in annular flow. In this paper, film thickness time–trace measurements for air–water annular flow were collected in a small vertical tube using a parallel wire probe. Using the data, a typical disturbance wave shape was obtained and wave properties (e.g., width, height, speed and roughness) were presented. The liquid mass flux ranged from 100 to 200 kg/m² s and the gas mass flux ranged from 18 to 47 kg/m² s. Disturbance wave characteristics were defined and the effects of changing the gas flow rate on the wave spacing, wave width, wave peak height and wave base height were studied. An average velocity model for the wave and base regions has been developed to determine the wave velocity. The investigation method could be further extended to annular-mist flow which frequently occurs in boiling water reactors.     

An A Posteriori Error Estimate for the Local Discontinuous Galerkin Method Applied to Linear and Nonlinear Diffusion Problems

In this paper we present a new residual-based reliable a posteriori error estimator for the local discontinuous Galerkin approximations of linear and nonlinear diffusion problems in polygonal regions of R ². Our analysis, which applies to convex and nonconvex domains, is based on Helmholtz decompositions of the error and a suitable auxiliary polynomial function interpolating the Dirichlet datum. Several examples confirming the reliability of the estimator and providing numerical evidences for its efficiency are given. Furthermore, the associated adaptive method, which considers meshes with and without hanging nodes, is shown to be much more efficient than a uniform refinement to compute the discrete solutions. In particular, the experiments illustrate the ability of the adaptive algorithm to localize the singularities of each problem.Mathematics Subject Classifications (1991). 65N30This revised version was published online in July 2005 with corrected volume and issue numbers.     

Economic Value of Building Faster

Owners, developers, and engineers are often challenged with determining the value of accelerating the construction of a project. There is a cost for accelerating the construction of a project to reduce the time required to transfer a facility into the operational phase. Determining the cost of acceleration is a difficult challenge with the limited information typically available early in the project development phase. Many unknowns exist (e.g., future revenue, costs, etc.) and the owner, developer, or engineer often make best guesses to justify if building faster is worthwhile. A simple methodology is needed to assess the value of building faster. This paper derives a set of equations that will allow owners, developers, and/or engineers to estimate the percent increase of the baseline project costs to reduce the time to completion of a construction project. The equations were derived such that variables that are easily known or can easily and reliably be determined are required. After the value of accelerating a project is determined (as a percentage of the original baseline budget), owner, developers, and/or engineers can use this information to determine if a project should be accelerated.     

Statistical Modeling to Forecast Odor Levels of Biosolids Applied to Reuse Sites

Proper use or disposal of wastewater solids is an important responsibility of wastewater treatment plants. At present, there are several options for wastewater solids, including agriculture, forestry, and mine reclamation reuse; production of marketable products such as compost and dried pellets; and disposal in landfills and incinerators. Land application of biosolids products is beneficial as part of recycling efforts on local farms, forests, tree farms, and mines and has gained greater acceptance of late. Coupled with these beneficial aspects are odors, which must be managed relative to the receiving populations. In this paper we present several statistical models that predict biosolids odor levels based on processing and management variables as well as ambient conditions. Such models are useful to managers at advanced wastewater treatment plants in helping them to better forecast the biosolids odors and minimize the “odor footprint,” thus making these biosolids products better received.     

Text classification without negative examples revisit

Traditionally, building a classifier requires two sets of examples: positive examples and negative examples. This paper studies the problem of building a text classifier using positive examples (P) and unlabeled examples (U). The unlabeled examples are mixed with both positive and negative examples. Since no negative example is given explicitly, the task of building a reliable text classifier becomes far more challenging. Simply treating all of the unlabeled examples as negative examples and building a classifier thereafter is undoubtedly a poor approach to tackling this problem. Generally speaking, most of the studies solved this problem by a two-step heuristic: first, extract negative examples (N) from U. Second, build a classifier based on P and N. Surprisingly, most studies did not try to extract positive examples from U. Intuitively, enlarging P by P' (positive examples extracted from U) and building a classifier thereafter should enhance the effectiveness of the classifier. Throughout our study, we find that extracting P' is very difficult. A document in U that possesses the features exhibited in P does not necessarily mean that it is a positive example, and vice versa. The very large size of and very high diversity in U also contribute to the difficulties of extracting P'. In this paper, we propose a labeling heuristic called PNLH to tackle this problem. PNLH aims at extracting high quality positive examples and negative examples from U and can be used on top of any existing classifiers. Extensive experiments based on several benchmarks are conducted. The results indicated that PNLH is highly feasible, especially in the situation where |P| is extremely small.     

Towards Reduced Basis Approaches in ab initio Electronic Structure Computations

Due to the high dimensionality of the spaces where the problems are set, adapted discretization basis are often advocated in complex physical problems (Navier–Stokes equations, solid mecanics, ab initio electronic structure computations) to express the solution in terms of solution of similar (but easier to solve) problems. However, very few mathematical studies have been undertaken to asses the numerical properties of these approximations. Within this context, we will present in this paper an overview of the tools required to develop more rigorous reduced basis approaches for quantum chemistry: a posteriori numerical analysis and fast exponential decay of the n-width of the solution set.     

HPCVIEW: A Tool for Top-down Analysis of Node Performance

It is increasingly difficult for complex scientific programs to attain a significant fraction of peak performance on systems that are based on microprocessors with substantial instruction-level parallelism and deep memory hierarchies. Despite this trend, performance analysis and tuning tools are still not used regularly by algorithm and application designers. To a large extent, existing performance tools fail to meet many user needs and are cumbersome to use. To address these issues, we developed HPCVIEW—a toolkit for combining multiple sets of program profile data, correlating the data with source code, and generating a database that can be analyzed anywhere with a commodity Web browser. We argue that HPCVIEW addresses many of the issues that have limited the usability and the utility of most existing tools. We originally built HPCVIEW to facilitate our own work on data layout and optimizing compilers. Now, in addition to daily use within our group, HPCVIEW is being used by several code development teams in DoD and DoE laboratories as well as at NCSA.