Monte carlo simulation for molecular gas dynamics

The dynamics of low-density flows is governed by the Boltzmann equation of the kinetic theory of gases. This is a nonlinear integro-differential equation and, in general, numerical methods must be used to obtain its solution. The present paper, after a brief review of Direct Simulation Monte Carlo (DSMC) methods due to Bird, and Belotserkovskii and Yanitskii, studies the details of theDSMC method of Deshpande for mono as well as multicomponent gases. The present method is a statistical particle-in-cell method and is based upon the Kac-Prigogine master equation which reduces to the Boltzmann equation under the hypothesis of molecular chaos. The proposed Markoff model simulating the collisions uses a Poisson distribution for the number of collisions allowed in cells into which the physical space is divided. The model is then extended to a binary mixture of gases and it is shown that it is necessary to perform the collisions in a certain sequence to obtain unbiased simulation.

Theory of the effects of destruction of localization by inelastic scattering in the resistivity of pure thin potassium wires

Measurements of the electrical resistivity of thin potassium wires at temperatures near 1 K have revealed a minimum in the resistivity as a function of temperature. By proposing that the electrons in these wires have undergone localization, albeit with large localization length, and that inelastic-scattering events destroy the coherence of that state, we can explain both the magnitude and shape of the temperature-dependent resistivity data. Localization of electrons in these wires is to be expected because, due to the high purity of the potassium, the elastic mean free path is comparable to the diameters of the thinnest samples, making the Thouless length lT (or inelastic diffusion length) much larger than the diameter, so that the wire is effectively one dimensional. The inelastic events effectively break the wire into a series of localized segments, whose resistances can be added to obtain the total resistance of the wire. The ensemble-averaged resistance for all possible segmented wires, weighted with a Poisson distribution of inelastic-scattering lengths along the wire, yields a length dependence for the resistance that is proportional to [L3/lin(T)], provided that lin(T)?L, where L is the sample length and lin(T) is some effective temperature-dependent one-dimensional inelastic-scattering length. A more sophisticated approach using a Poisson distribution in inelastic-scattering times, which takes into account the diffusive motion of the electrons along the wire through the Thouless length, yields a length- and temperature-dependent resistivity proportional to (L/lT)4 under appropriate conditions. Inelastic-scattering lifetimes are inferred from the temperature-dependent bulk resistivities (i.e., those of thicker, effectively three-dimensional samples), assuming that a minimum amount of energy must be exchanged for a collision to be effective in destroying the phase coherence of the localized state. If the dominant inelastic mechanism is electron-electron scattering, then our result, given the appropriate choice of the channel number parameter, is consistent with the data. If electron-phason scattering were of comparable importance, then our results would remain consistent. However, the inelastic-scattering lifetime inferred from bulk resistivity data is too short. This is because the electron-phason mechanism dominates in the inelastic-scattering rate, although the two mechanisms may be of comparable importance for the bulk resistivity. Possible reasons why the electron-phason mechanism might be less effective in thin wires than in bulk are discussed.

Time-dependent transitions with time-space noncommutativity and its implications in quantum optics

We study the time-dependent transitions of a quantum-forced harmonic oscillator in noncommutative R(1,1) perturbatively to linear order in the noncommutativity theta. We show that the Poisson distribution gets modified, and that the vacuum state evolves into a `squeezed' state rather than a coherent state. The time evolutions of uncertainties in position and momentum in vacuum are also studied and imply interesting consequences for modeling nonlinear phenomena in quantum optics.

Kinetic measurements of cell surface E-selectin/carbohydrate ligand interactions

Selectin/ligand interactions initiate the multistep adhesion and signaling cascades in the recruitment of leukocytes from circulation to inflamed tissues and may also play a role in tumor metastasis. Kinetic properties of these interactions are essential determinants governing blood-borne cells' tethering to and rolling on the vessel wall. Extending our recently developed micropipette method, we have measured the kinetic rates of E-selectin/ligand interactions. Red cells coated with an E-selectin construct were allowed to bind HL-60 or Colo-205 cells bearing carbohydrate ligands. Specific adhesions were observed to occur at isolated points, the frequency of which followed a Poisson distribution. These point attachments were formed at the same rate with both the HL-60 and Colo-205 cells (0.14 +/- 0.04 and 0.13 +/- 0.03 mum(2) s(-1) per unit density of E-selectin, respectively) but dissociated from the former at a rate twice as fast as did from the latter (0.92 +/- 0.23 and 0.44 +/- 0.10 s(-1), respectively). The reverse rates agree well with those measured by the flow chamber. The forward rates are orders of magnitude higher than those of Fc gamma receptors interacting with IgG measured under similar conditions, consistent with the rapid kinetics requirement for the function of E-selectin/ligand binding, which is to capture leukocytes on endothelial surfaces from flow.

Surface-enhanced resonance Raman scattering spectroscopy of single R6G molecules

Surface-enhanced resonance Raman scattering (SERRS) of Rhodamine 6G (R6G) adsorbed on colloidal silver clusters has been studied. Based on the great enhancement of the Raman signal and the quench of the fluorescence, the SERRS spectra of R6G were recorded for the samples of dye colloidal solution with different concentrations. Spectral inhomogeneity behaviours from single molecules in the dried sample films were observed with complementary evidences, such as spectral polarization, spectral diffusion, intensity fluctuation of vibrational lines and even "breathing" of the molecules. Sequential spectra observed from a liquid sample with an average of 0.3 dye molecules in the probed volume exhibited the expected Poisson distribution for actually measuring 0, 1 or 2 molecules. Difference between the SERRS spectra of R6G excited by linearly and circularly polarized light were experimentally measured.

Single molecule dynamics and statistical fluctuations of gene regulatory networks: A repressilator

The authors developed a time dependent method to study the single molecule dynamics of a simple gene regulatory network: a repressilator with three genes mutually repressing each other. They quantitatively characterize the time evolution dynamics of the repressilator. Furthermore, they study purely dynamical issues such as statistical fluctuations and noise evolution. They illustrated some important features of the biological network such as monostability, spirals, and limit cycle oscillation. Explicit time dependent Fano factors which describe noise evolution and show statistical fluctuations out of equilibrium can be significant and far from the Poisson distribution. They explore the phase space and the interrelationships among fluctuations, order, amplitude, and period of oscillations of the repressilators. The authors found that repressilators follow ordered limit cycle orbits and are more likely to appear in the lower fluctuating regions. The amplitude of the repressilators increases as the suppressing of the genes decreases and production of proteins increases. The oscillation period of the repressilators decreases as the suppressing of the genes decreases and production of proteins increases.

Photosynthesis-irradiance response at physiological level: A mechanistic model

A mechanistic model is developed to present the photosynthetic response of phytoplankton to irradiance at the physiological level. The model is operated on photosynthetic units (PSU), and each PSU is assumed to have two states: reactive and activated. Light absorption that drives a reactive PSU into the activated state results from the effective absorption of the PSU. Transitions between the two states are asymmetrical in rate. A PSU in the reactive state becomes activated much faster than it recovers from the activated state to the reactive one. The turnover time for an activated PSU to transit into the reactive one is defined by the turnover time of the electron transport chain. The present model yields a photosynthesis-irradiance curve (PE-curve) in a hyperbola, which is described by three physiological parameters: effective cross-section (sigma (PSII)), turnover time of electron transport chain (tau) and number of PSUs (N). The PE-curve has an initial slope of sigma (PSII) x N, a half-saturated irradiance of 1/(sigma (PSII)), and a maximal photosynthetic rate of Nlc at the saturated irradiance. The PE-curve from the present model is comparable to the empirical function based on the target theory described by the Poisson distribution. (C) 2001 Academic Press.

Variation in Inpatient Rehabilitation Utilization After Hospitalization for Burn Injury in the United States.

Approximately 45,000 individuals are hospitalized annually for burn treatment. Rehabilitation after hospitalization can offer a significant improvement in functional outcomes. Very little is known nationally about rehabilitation for burns, and practices may vary substantially depending on the region based on observed Medicare post-hospitalization spending amounts. This study was designed to measure variation in rehabilitation utilization by state of hospitalization for patients hospitalized with burn injury. This retrospective cohort study used nationally collected data over a 10-year period (2001 to 2010), from the Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SIDs). Patients hospitalized for burn injury (n = 57,968) were identified by ICD-9-CM codes and were examined to see specifically if they were discharged immediately to inpatient rehabilitation after hospitalization (primary endpoint). Both unadjusted and adjusted likelihoods were calculated for each state taking into account the effects of age, insurance status, hospitalization at a burn center, and extent of burn injury by TBSA. The relative risk of discharge to inpatient rehabilitation varied by as much as 6-fold among different states. Higher TBSA, having health insurance, higher age, and burn center hospitalization all increased the likelihood of discharge to inpatient rehabilitation following acute care hospitalization. There was significant variation between states in inpatient rehabilitation utilization after adjusting for variables known to affect each outcome. Future efforts should be focused on identifying the cause of this state-to-state variation, its relationship to patient outcome, and standardizing treatment across the United States.

Variation in pediatric traumatic brain injury outcomes in the United States.

OBJECTIVE: To ascertain the degree of variation, by state of hospitalization, in outcomes associated with traumatic brain injury (TBI) in a pediatric population. DESIGN: A retrospective cohort study of pediatric patients admitted to a hospital with a TBI. SETTING: Hospitals from states in the United States that voluntarily participate in the Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project. PARTICIPANTS: Pediatric (age ≤ 19 y) patients hospitalized for TBI (N=71,476) in the United States during 2001, 2004, 2007, and 2010. INTERVENTIONS: None. MAIN OUTCOME MEASURES: Primary outcome was proportion of patients discharged to rehabilitation after an acute care hospitalization among alive discharges. The secondary outcome was inpatient mortality. RESULTS: The relative risk of discharge to inpatient rehabilitation varied by as much as 3-fold among the states, and the relative risk of inpatient mortality varied by as much as nearly 2-fold. In the United States, approximately 1981 patients could be discharged to inpatient rehabilitation care if the observed variation in outcomes was eliminated. CONCLUSIONS: There was significant variation between states in both rehabilitation discharge and inpatient mortality after adjusting for variables known to affect each outcome. Future efforts should be focused on identifying the cause of this state-to-state variation, its relationship to patient outcome, and standardizing treatment across the United States.

Maximum likelihood estimation of higher-order integer-valued autoregressive processes

In this article, we extend the earlier work of Freeland and McCabe [Journal of time Series Analysis (2004) Vol. 25, pp. 701–722] and develop a general framework for maximum likelihood (ML) analysis of higher-order integer-valued autoregressive processes. Our exposition includes the case where the innovation sequence has a Poisson distribution and the thinning is binomial. A recursive representation of the transition probability of the model is proposed. Based on this transition probability, we derive expressions for the score function and the Fisher information matrix, which form the basis for ML estimation and inference. Similar to the results in Freeland and McCabe (2004), we show that the score function and the Fisher information matrix can be neatly represented as conditional expectations. Using the INAR(2) speci?cation with binomial thinning and Poisson innovations, we examine both the asymptotic e?ciency and ?nite sample properties of the ML estimator in relation to the widely used conditional least
squares (CLS) and Yule–Walker (YW) estimators. We conclude that, if the Poisson assumption can be justi?ed, there are substantial gains to be had from using ML especially when the thinning parameters are large.

Long-term genomic instability in human lymphocytes induced by single-particle irradiation

Recent evidence suggests that genomic instability, which is an important step in carcinogenesis, may be important in the effectiveness of radiation as a carcinogen, particularly for high-LET radiations. Understanding the biological effects underpinning the risks associated with low doses of densely ionizing radiations is complicated in experimental systems by the Poisson distribution of particles that ran be delivered, In this study, we report an approach to determine the effect of the lowest possible cellular radiation dose of densely ionizing at particles, that of a single particle traversal. Using microbeam technology and an approach for immobilizing human T-lymphocytes, we have measured the effects of single alpha -particle traversals on the surviving progeny of cells. A significant increase in the proportion of aberrant cells is observed 12-13 population doublings after exposure, with a high level of chromatid-type aberrations, indicative of an instability phenotype, These data suggest that instability may be important in situations where even a single particle traverses human cells. (C) 2001 by Radiation Research Society.

The measurement of the optical absorption cross section of photosystem 1 and photosystem 2 from whole live cells of porphyridium cruentum, in light state 1 and light state 2

The optical cross section of PS I in whole cells of Porphyridium cruentum (UTEX 161), held in either state 1 or state 2, was determined by measuring the change in absorbance at 820nm, an indication of P700+; the X-section of PS2 was determined by measuring the variable fluorescence, (Fv-Fo)/Fo, from PS2. Both cross-sections were 7 determined by fitting Poisson distribution equations to the light saturation curves obtained with single turnover laser flashes which varied in intensity from zero to a level where maximum yield occurred. Flash wavelengths of 574nm, 626nm, and 668nm were used, energy absorbed by PBS, by PBS and chla, and by chla respectively. There were two populations of both PSi and PS2. A fraction of PSi is associated with PBS, and a fraction of PS2 is free from PBS. On the transition S1->S2, only with PBS-absorbed energy (574nm) did the average X-section of PSi increase (27%), and that of PS2 decrease (40%). The fraction of PSi associated with PBS decreased, from 0.65 to 0.35, and the Xsection of this associated PS 1 increased, from 135±65 A2 to 400±300A2. The cross section of PS2 associated with PBS decreased from 150±50 A2 to 85±45 A2, but the fraction of PS2 associated with PBS, approximately 0.75, did not change significantly. The increase in PSi cross section could not be completely accounted for by postulating that several PSi are associated with a single PBS and that in the transition to state2, fewer PSi share the same number of PBS, resulting in a larger X-section. It is postulated that small changes occur in the attachment of PS2 to PBS causing energy to be diverted to the attached PSi. These experiments support neither the mobile-PBS model of state transitions nor that of spillover. From cross section changes there was no evidence of energy transfer from PS2 to PSi with 668nm light. The decrease in PS2 fluorescence which occurred at this wavelength cannot be explained by energy transfer; another explanation must be sought. No explanation was found for an observed decrease in PSi yield at high flash intensities.

Modélisation bayésienne des changements aux niches écologiques causés par le réchauffement climatique

Cette thèse présente des méthodes de traitement de données de comptage en particulier et des données discrètes en général. Il s'inscrit dans le cadre d'un projet stratégique du CRNSG, nommé CC-Bio, dont l'objectif est d'évaluer l'impact des changements climatiques sur la répartition des espèces animales et végétales. Après une brève introduction aux notions de biogéographie et aux modèles linéaires mixtes généralisés aux chapitres 1 et 2 respectivement, ma thèse s'articulera autour de trois idées majeures. Premièrement, nous introduisons au chapitre 3 une nouvelle forme de distribution dont les composantes ont pour distributions marginales des lois de Poisson ou des lois de Skellam. Cette nouvelle spécification permet d'incorporer de l'information pertinente sur la nature des corrélations entre toutes les composantes. De plus, nous présentons certaines propriétés de ladite distribution. Contrairement à la distribution multidimensionnelle de Poisson qu'elle généralise, celle-ci permet de traiter les variables avec des corrélations positives et/ou négatives. Une simulation permet d'illustrer les méthodes d'estimation dans le cas bidimensionnel. Les résultats obtenus par les méthodes bayésiennes par les chaînes de Markov par Monte Carlo (CMMC) indiquent un biais relatif assez faible de moins de 5% pour les coefficients de régression des moyennes contrairement à ceux du terme de covariance qui semblent un peu plus volatils. Deuxièmement, le chapitre 4 présente une extension de la régression multidimensionnelle de Poisson avec des effets aléatoires ayant une densité gamma. En effet, conscients du fait que les données d'abondance des espèces présentent une forte dispersion, ce qui rendrait fallacieux les estimateurs et écarts types obtenus, nous privilégions une approche basée sur l'intégration par Monte Carlo grâce à l'échantillonnage préférentiel. L'approche demeure la même qu'au chapitre précédent, c'est-à-dire que l'idée est de simuler des variables latentes indépendantes et de se retrouver dans le cadre d'un modèle linéaire mixte généralisé (GLMM) conventionnel avec des effets aléatoires de densité gamma. Même si l'hypothèse d'une connaissance a priori des paramètres de dispersion semble trop forte, une analyse de sensibilité basée sur la qualité de l'ajustement permet de démontrer la robustesse de notre méthode. Troisièmement, dans le dernier chapitre, nous nous intéressons à la définition et à la construction d'une mesure de concordance donc de corrélation pour les données augmentées en zéro par la modélisation de copules gaussiennes. Contrairement au tau de Kendall dont les valeurs se situent dans un intervalle dont les bornes varient selon la fréquence d'observations d'égalité entre les paires, cette mesure a pour avantage de prendre ses valeurs sur (-1;1). Initialement introduite pour modéliser les corrélations entre des variables continues, son extension au cas discret implique certaines restrictions. En effet, la nouvelle mesure pourrait être interprétée comme la corrélation entre les variables aléatoires continues dont la discrétisation constitue nos observations discrètes non négatives. Deux méthodes d'estimation des modèles augmentés en zéro seront présentées dans les contextes fréquentiste et bayésien basées respectivement sur le maximum de vraisemblance et l'intégration de Gauss-Hermite. Enfin, une étude de simulation permet de montrer la robustesse et les limites de notre approche.

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