Testing the Underlying Chemical Principles of the Biotic Ligand Model (BLM) to Marine Copper Systems: Measuring Copper Speciation Using Fluorescence Quenching

Speciation of copper in marine systems strongly influences the ability of copper to cause toxicity. Natural organic matter (NOM) contains many binding sites which provides a protective effect on copper toxicity. The purpose of this study was to characterize copper binding with NOM using fluorescence quenching techniques. Fluorescence quenching of NOM with copper was performed on nine sea water samples. The resulting stability con- stants and binding capacities were consistent with literature values of marine NOM, show- ing strong binding with log K values from 7.64 to 10.2 and binding capacities ranging from 15 to 3110 nmole mg C −1 . Free copper concentrations estimated at total dissolved copper concentrations corresponding to previously published rotifer effect concentrations, in the same nine samples, were statistically the same as the range of free copper calculated for the effect concentration in NOM-free artificial seawater. These data confirms the applicability of fluorescence spectroscopy techniques for NOM and copper speciation characterization in sea water and demonstrates that such measured speciation is consistent with the chemical principles underlying the Biotic Ligand Model (BLM) approach for bioavailability-based metals risk assessment

Surface-slip equations for multicomponent nonequilibrium air flow

Equations are presented for the surface-slip (or jump) values of species concentration, pressure, velocity, and temperature in the low-Reynolds number, high-altitude flight regime of a space vehicle. The equations are obtained from closed form solutions of the mass, momentum, and energy flux equations using the Chapman-Enskog velocity distribution function. This function represents a solution of the Boltzmann equation in the Navier-Stokes approximation. The analysis, obtained for nonequilibrium multicomponent air flow, includes the finite-rate surface catalytic recombination and changes in the internal energy during reflection from the surface. Expressions for the various slip quantities were obtained in a form which can be employed in flowfield computations. A consistent set of equations is provided for multicomponent, binary, and single species mixtures. Expression is also provided for the finite-rate, species-concentration boundary condition for a multicomponent mixture in absence of slip

Survey of Human Mitochondrial Diseases Using New Genomic/Proteomic Tools

BACKGROUND. We have constructed Bayesian prior-based, amino-acid sequence profiles for the complete yeast mitochondrial proteome and used them to develop methods for identifying and characterizing the context of protein mutations that give rise to human mitochondrial diseases. (Bayesian priors are conditional probabilities that allow the estimation of the likelihood of an event - such as an amino-acid substitution - on the basis of prior occurrences of similar events.) Because these profiles can assemble sets of taxonomically very diverse homologs, they enable identification of the structurally and/or functionally most critical sites in the proteins on the basis of the degree of sequence conservation. These profiles can also find distant homologs with determined three-dimensional structures that aid in the interpretation of effects of missense mutations. RESULTS. This survey reports such an analysis for 15 missense mutations one insertion and three deletions involved in Leber's hereditary optic neuropathy, Leigh syndrome, mitochondrial neurogastrointestinal encephalomyopathy, Mohr-Tranebjaerg syndrome, iron-storage disorders related to Friedreich's ataxia, and hereditary spastic paraplegia. We present structural correlations for seven of the mutations. CONCLUSIONS. Of the 19 mutations analyzed, 14 involved changes in very highly conserved parts of the affected proteins. Five out of seven structural correlations provided reasonable explanations for the malfunctions. As additional genetic and structural data become available, this methodology can be extended. It has the potential for assisting in identifying new disease-related genes. Furthermore, profiles with structural homologs can generate mechanistic hypotheses concerning the underlying biochemical processes - and why they break down as a result of the mutations.United States Department of Energy (DE-FG02-98ER62558); National Science Foundation (DBI-9807993

Semiparametric Estimation and Inference in Multinomial Choice Models

The purpose of this paper is to incorporate semiparametric alternatives to maximum likelihood estimation and inference in the context of unordered multinomial response data when in practice there is often insufficient information to specify the parametric form of the function linking the observables to the unknown probabilities. We specify the function linking the observables to the unknown probabilities using a very general flexible class of functions belonging to the Pearson system of cumulative distribution equations. In this setting we consider the observations as arising from a multinomial distribution characterized by one of the CDFs in the Pearson system. Given this situation, it is possible to utilize the concept of unbiased estimating functions (EFs), combined with the concept of empirical likelihood (EL) to define an (empirical) likelihood function for the parameter vector based on a nonparametric representation of the sample's PDF. This leads to the concept of maximum empirical likelihood (MEL) estimation and inference, which is analogous to parametric maximum likelihood methods in many respects.Demand and Price Analysis,

A STRUCTURAL-EQUATION GME ESTIMATOR

A generalized maximum entropy estimator is developed for the linear simultaneous equations systems model. We provide results on large and small sample properties of the estimator. Empirical results illustrate efficiency advantages of the generalized maximum entropy estimator proposed in this study over traditional estimators (e.g., 2SLS and 3SLS).Research Methods/ Statistical Methods,

Dissipative solitons which cannot be trapped

In this paper we study the behavior of dissipative solitons in systems with high order nonlinear dissipation and show how they cannot survive under the effect of trapping potentials both of rigid wall type or asymptotically increasing ones. This provides an striking example of a soliton which cannot be trapped and only survives to the action of a weak potential

A microrod-resonator Brillouin laser with 240 Hz absolute linewidth

We demonstrate an ultralow-noise microrod-resonator based laser that oscillates on the gain supplied by the stimulated Brillouin scattering optical nonlinearity. Microresonator Brillouin lasers are known to offer an outstanding frequency noise floor, which is limited by fundamental thermal fluctuations. Here, we show experimental evidence that thermal effects also dominate the close-to-carrier frequency fluctuations. The 6-mm diameter microrod resonator used in our experiments has a large optical mode area of ~100 {\mu}m$^2$, and hence its 10 ms thermal time constant filters the close-to-carrier optical frequency noise. The result is an absolute laser linewidth of 240 Hz with a corresponding white-frequency noise floor of 0.1 Hz$^2$/Hz. We explain the steady-state performance of this laser by measurements of its operation state and of its mode detuning and lineshape. Our results highlight a mechanism for noise that is common to many microresonator devices due to the inherent coupling between intracavity power and mode frequency. We demonstrate the ability to reduce this noise through a feedback loop that stabilizes the intracavity power.Comment: 11 pages, 5 figure

Long delay times in reaction rates increase intrinsic fluctuations

In spatially distributed cellular systems, it is often convenient to represent complicated auxiliary pathways and spatial transport by time-delayed reaction rates. Furthermore, many of the reactants appear in low numbers necessitating a probabilistic description. The coupling of delayed rates with stochastic dynamics leads to a probability conservation equation characterizing a non-Markovian process. A systematic approximation is derived that incorporates the effect of delayed rates on the characterization of molecular noise, valid in the limit of long delay time. By way of a simple example, we show that delayed reaction dynamics can only increase intrinsic fluctuations about the steady-state. The method is general enough to accommodate nonlinear transition rates, allowing characterization of fluctuations around a delay-induced limit cycle.Comment: 8 pages, 3 figures, to be published in Physical Review