Master crossover behavior of parachor correlations for one-component fluids

The master asymptotic behavior of the usual parachor correlations, expressing surface tension $\sigma$ as a power law of the density difference $\rho_{L}-\rho_{V}$ between coexisting liquid and vapor, is analyzed for a series of pure compounds close to their liquid-vapor critical point, using only four critical parameters $(\beta_{c})^{-1}$, $\alpha_{c}$, $Z_{c}$ and $Y_{c}$, for each fluid. ... The main consequences of these theoretical estimations are discussed in the light of engineering applications and process simulations where parachor correlations constitute one of the most practical method for estimating surface tension from density and capillary rise measurements

Master singular behavior for the Sugden factor of the one-component fluids near their gas-liquid critical point

We present the master (i.e. unique) behavior of the squared capillary length - so called the Sudgen factor-, as a function of the temperature-like field along the critical isochore, asymptotically close to the gas-liquid critical point of twenty (one component) fluids. This master behavior is obtained using the scale dilatation of the relevant physical fields of the one-component fluids. The scale dilatation introduces the fluid-dependent scale factors in a manner analog with the linear relations between physical fields and scaling fields needed by the renormalization theory applied to the Ising-like universality class. The master behavior for the Sudgen factor satisfies hyperscaling and can be asymptotically fitted by the leading terms of the theoretical crossover functions for the correlation length and the susceptibility in the homogeneous domain recently obtained from massive renormalization in field theory. In the absence of corresponding estimation of the theoretical crossover functions for the interfacial tension, we define the range of the temperature-like field where the master leading power law can be practically used to predict the singular behavior of the Sudgen factor in conformity with the theoretical description provided by the massive renormalization scheme within the extended asymptotic domain of the one-component fluid "subclass"

The functional landscape of mouse gene expression

BACKGROUND: Large-scale quantitative analysis of transcriptional co-expression has been used to dissect regulatory networks and to predict the functions of new genes discovered by genome sequencing in model organisms such as yeast. Although the idea that tissue-specific expression is indicative of gene function in mammals is widely accepted, it has not been objectively tested nor compared with the related but distinct strategy of correlating gene co-expression as a means to predict gene function. RESULTS: We generated microarray expression data for nearly 40,000 known and predicted mRNAs in 55 mouse tissues, using custom-built oligonucleotide arrays. We show that quantitative transcriptional co-expression is a powerful predictor of gene function. Hundreds of functional categories, as defined by Gene Ontology 'Biological Processes', are associated with characteristic expression patterns across all tissues, including categories that bear no overt relationship to the tissue of origin. In contrast, simple tissue-specific restriction of expression is a poor predictor of which genes are in which functional categories. As an example, the highly conserved mouse gene PWP1 is widely expressed across different tissues but is co-expressed with many RNA-processing genes; we show that the uncharacterized yeast homolog of PWP1 is required for rRNA biogenesis. CONCLUSIONS: We conclude that 'functional genomics' strategies based on quantitative transcriptional co-expression will be as fruitful in mammals as they have been in simpler organisms, and that transcriptional control of mammalian physiology is more modular than is generally appreciated. Our data and analyses provide a public resource for mammalian functional genomics