Gravitationally Collapsing Shells in (2+1) Dimensions

We study gravitationally collapsing models of pressureless dust, fluids with pressure, and the generalized Chaplygin gas (GCG) shell in (2+1)-dimensional spacetimes. Various collapse scenarios are investigated under a variety of the background configurations such as anti-de Sitter(AdS) black hole, de Sitter (dS) space, flat and AdS space with a conical deficit. As with the case of a disk of dust, we find that the collapse of a dust shell coincides with the Oppenheimer-Snyder type collapse to a black hole provided the initial density is sufficiently large. We also find -- for all types of shell -- that collapse to a naked singularity is possible under a broad variety of initial conditions. For shells with pressure this singularity can occur for a finite radius of the shell. We also find that GCG shells exhibit diverse collapse scenarios, which can be easily demonstrated by an effective potential analysis.Comment: 27 pages, Latex, 11 figures, typos corrected, references added, minor amendments in introduction and conclusion introd

Ab initio equilibrium constants for H2O–H2O and H2O–CO2

Ab initio 6‐31G** electronic structure calculations have been used to determine the minimum energy geometries and vibrational frequencies of molecular clusters of water and carbon dioxide. Application of statistical thermodynamics leads to theoretical equilibrium constants for gas phase dimerization of water and the formation of an adduct of carbon dioxide with water.The low energy vibrations of the clusters lead to much larger contributions to the vibrational partitioning of the energy than do the fundamental vibrations of the monomeric species. A new ‘‘Harmonic‐Morse’’ formula is derived to estimate anharmonicity from optimized harmonic frequencies and two additional values on the potential surface for each vibration. These ab initiocalculations of equilibrium constants are very close to recent measurements and fall within the range of values obtained by other methods. This no‐parameter treatment gives excellent agreement for the equilibrium of H2O–CO2 near the supercritical fluid range of CO2 and suggests that a ‘‘Theory of Significant Clusters’’ may be extended to a model of supercritical fluids which includes the effects of anharmonicity

Observing biogeochemical cycles at global scales with profiling floats and gliders: prospects for a global array

Chemical and biological sensor technologies have advanced rapidly in the past five years. Sensors that require low power and operate for multiple years are now available for oxygen, nitrate, and a variety of bio-optical properties that serve as proxies for important components of the carbon cycle (e.g., particulate organic carbon). These sensors have all been deployed successfully for long periods, in some cases more than three years, on platforms such as profiling floats or gliders. Technologies for pH, pCO2, and particulate inorganic carbon are maturing rapidly as well. These sensors could serve as the enabling technology for a global biogeochemical observing system that might operate on a scale comparable to the current Argo array. Here, we review the scientific motivation and the prospects for a global observing system for ocean biogeochemistry

Randomly Broken Nuclei and Disordered Systems

Similarities between models of fragmenting nuclei and disordered systems in condensed matter suggest corresponding methods. Several theoretical models of fragmentation investigated in this fashion show marked differences, indicating possible new methods for distinguishing models using yield data. Applying nuclear methods to disordered systems also yields interesting results.Comment: 10 pages, 4 figure

Optical properties of the vibrations in charged C60_{60} molecules

The transition strengths for the four infrared-active vibrations of charged C$_{60}$ molecules are evaluated in self-consistent density functional theory using the local density approximation. The oscillator strengths for the second and fourth modes are strongly enhanced relative to the neutral C$_{60}$ molecule, in good agreement with the experimental observation of ``giant resonances'' for those two modes. Previous theory, based on a ``charged phonon'' model, predicted a quadratic dependence of the oscillator strength on doping, but this is not borne out in our calculations.Comment: 10 pages, RevTeX3.

Integral-based filtering of continuous glucose sensor measurements for glycaemic control in critical care

Hyperglycaemia is prevalent in critical illness and increases the risk of further complications and mortality, while tight control can reduce mortality up to 43%. Adaptive control methods are capable of highly accurate, targeted blood glucose regulation using limited numbers of manual measurements due to patient discomfort and labour intensity. Therefore, the option to obtain greater data density using emerging continuous glucose sensing devices is attractive. However, the few such systems currently available can have errors in excess of 20-30%. In contrast, typical bedside testing kits have errors of approximately 7-10%. Despite greater measurement frequency larger errors significantly impact the resulting glucose and patient specific parameter estimates, and thus the control actions determined creating an important safety and performance issue. This paper models the impact of the Continuous Glucose Monitoring System (CGMS, Medtronic, Northridge, CA) on model-based parameter identification and glucose prediction. An integral-based fitting and filtering method is developed to reduce the effect of these errors. A noise model is developed based on CGMS data reported in the literature, and is slightly conservative with a mean Clarke Error Grid (CEG) correlation of R=0.81 (range: 0.68-0.88) as compared to a reported value of R=0.82 in a critical care study. Using 17 virtual patient profiles developed from retrospective clinical data, this noise model was used to test the methods developed. Monte-Carlo simulation for each patient resulted in an average absolute one-hour glucose prediction error of 6.20% (range: 4.97-8.06%) with an average standard deviation per patient of 5.22% (range: 3.26-8.55%). Note that all the methods and results are generalisable to similar applications outside of critical care, such as less acute wards and eventually ambulatory individuals. Clinically, the results show one possible computational method for managing the larger errors encountered in emerging continuous blood glucose sensors, thus enabling their more effective use in clinical glucose regulation studies

Predicting the public health benefit of vaccinating cattle against Escherichia coli O157

Identifying the major sources of risk in disease transmission is key to designing effective controls. However, understanding of transmission dynamics across species boundaries is typically poor, making the design and evaluation of controls particularly challenging for zoonotic pathogens. One such global pathogen is Escherichia coli O157, which causes a serious and sometimes fatal gastrointestinal illness. Cattle are the main reservoir for E. coli O157, and vaccines for cattle now exist. However, adoption of vaccines is being delayed by conflicting responsibilities of veterinary and public health agencies, economic drivers, and because clinical trials cannot easily test interventions across species boundaries, lack of information on the public health benefits. Here, we examine transmission risk across the cattle–human species boundary and show three key results. First, supershedding of the pathogen by cattle is associated with the genetic marker stx2. Second, by quantifying the link between shedding density in cattle and human risk, we show that only the relatively rare supershedding events contribute significantly to human risk. Third, we show that this finding has profound consequences for the public health benefits of the cattle vaccine. A naïve evaluation based on efficacy in cattle would suggest a 50% reduction in risk; however, because the vaccine targets the major source of human risk, we predict a reduction in human cases of nearly 85%. By accounting for nonlinearities in transmission across the human–animal interface, we show that adoption of these vaccines by the livestock industry could prevent substantial numbers of human E. coli O157 cases

A biophysical model of prokaryotic diversity in geothermal hot springs

Recent field investigations of photosynthetic bacteria living in geothermal hot spring environments have revealed surprisingly complex ecosystems, with an unexpected level of genetic diversity. One case of particular interest involves the distribution along hot spring thermal gradients of genetically distinct bacterial strains that differ in their preferred temperatures for reproduction and photosynthesis. In such systems, a single variable, temperature, defines the relevant environmental variation. In spite of this, each region along the thermal gradient exhibits multiple strains of photosynthetic bacteria adapted to several distinct thermal optima, rather than the expected single thermal strain adapted to the local environmental temperature. Here we analyze microbiology data from several ecological studies to show that the thermal distribution field data exhibit several universal features independent of location and specific bacterial strain. These include the distribution of optimal temperatures of different thermal strains and the functional dependence of the net population density on temperature. Further, we present a simple population dynamics model of these systems that is highly constrained by biophysical data and by physical features of the environment. This model can explain in detail the observed diversity of different strains of the photosynthetic bacteria. It also reproduces the observed thermal population distributions, as well as certain features of population dynamics observed in laboratory studies of the same organisms