Vapor phase oxidation of ethanol over thorium molybdate catalyst

Ethanol oxidation in the vapor phase was studied in an isothermal flow reactor using thorium molybdate catalyst in the temperature range 220–280 °C. Under these conditions the catalyst was highly selective to acetaldehyde formation. The rate data were well represented by a steady state two-stage redox model given by the equation: View the MathML source The parameters of the above model were estimated by linear and nonlinear least squares methods. In the case of nonlinear estimation the sum of the squares of residuals decreased. The activation energies and preexponential factors for the reduction and oxidation steps of the model, estimated by nonlinear least squares technique are: 9.47 kcal/mole, 9.31 g mole/ (sec) (g cat) (atm) and 9.85 kcal/mole, 0.17 g mole/(sec) (g cat) (atm)0.5, respectively. Oxidations of ethanol and methanol over thorium molybdate catalyst were compared under similar conditions.

A model for doped-oxide-source diffusion with a chemical reaction at the silicon-silicon dioxide interface

A mathematical model for doped-oxide-source diffusion is proposed. In this model the concept of segregation of impurity at the silicon-silicon dioxide is used and also a constant of “rate limitation” is introduced through a chemical reaction at the interface.

Dispersal and related life history traits in the Glanville fritillary butterfly

Most studies of life history evolution are based on the assumption that species exist at equilibrium and spatially distinct separated populations. In reality, this is rarely the case, as populations are often spatially structured with ephemeral local populations. Therefore, the characteristics of metapopulations should be considered while studying factors affecting life history evolution. Theoretical studies have examined spatial processes shaping the evolution of life history traits to some extent, but there is little empirical data and evidence to investigate model predictions. In my thesis I have tried to bridge the gap between theoretical and empirical studies by using the well-known Glanville fritillary (Melitaea cinxia) metapopulation as a model system. The long-term persistence of classic metapopulations requires sufficient dispersal to establish new local populations to compensate for local extinctions. Previous studies on the Glanville fritillary have shown that females establishing new populations are not a random sample from the metapopulation, but they are in fact more dispersive than females in old populations. Many other life-history traits, such as body size, fecundity and lifespan, may be related to dispersal rate. Therefore, I examined a range of correlated traits for their evolutionary and ecological consequences. I was particularly interested in how the traits vary under natural environmental conditions, hence all studies were conducted in a large (32 x 26 m) outdoor population cage built upon a natural habitat patch. Individuals for the experiments were sampled from newly-established and old populations within a large metapopulation. Results show that females originating from newly-established populations had higher within-habitat patch mobility than females from old populations. I showed that dispersal rate is heritable and that flight activity is related to variation in a gene encoding the glycolytic enzyme phosphoglucose isomerase. Both among-individual and among-population variation in dispersal are correlated with the reproductive performance of females, though I found no evidence for a trade-off between dispersal and fecundity in terms of lifetime egg production or clutch size. Instead, the results suggest that highly dispersive females from newly-established populations have a shorter lifespan than females from old populations, and that dispersive females may pay a cost in terms of reduced lifetime reproductive success due to increased time spent outside habitat patches. In summary, the results of this thesis show that genotype-dependent dispersal rate correlates with other life history traits in the Glanville fritillary, and that the rapid turnover of local populations (extinctions and re-colonisations) is likely to be the mechanism that maintains phenotypic variation in many life history traits at the metapopulation level.

A curve shortening flow rule for closed embedded plane curves with a prescribed rate of change in enclosed area

Motivated by a problem from fluid mechanics, we consider a generalization of the standard curve shortening flow problem for a closed embedded plane curve such that the area enclosed by the curve is forced to decrease at a prescribed rate. Using formal asymptotic and numerical techniques, we derive possible extinction shapes as the curve contracts to a point, dependent on the rate of decreasing area; we find there is a wider class of extinction shapes than for standard curve shortening, for which initially simple closed curves are always asymptotically circular. We also provide numerical evidence that self-intersection is possible for non-convex initial conditions, distinguishing between pinch-off and coalescence of the curve interior.

trans gene regulation in adaptive evolution: A genetic algorithm model

This is a continuation of earlier studies on the evolution of infinite populations of haploid genotypes within a genetic algorithm framework. We had previously explored the evolutionary consequences of the existence of indeterminate—“plastic”—loci, where a plastic locus had a finite probability in each generation of functioning (being switched “on”) or not functioning (being switched “off”). The relative probabilities of the two outcomes were assigned on a stochastic basis. The present paper examines what happens when the transition probabilities are biased by the presence of regulatory genes. We find that under certain conditions regulatory genes can improve the adaptation of the population and speed up the rate of evolution (on occasion at the cost of lowering the degree of adaptation). Also, the existence of regulatory loci potentiates selection in favour of plasticity. There is a synergistic effect of regulatory genes on plastic alleles: the frequency of such alleles increases when regulatory loci are present. Thus, phenotypic selection alone can be a potentiating factor in a favour of better adaptation.

Behaviour of natural zeolites used for the treatment of simulated and actual coal seam gas water

Coal seam gas operations produce significant quantities of associated water which often require demineralization. Ion exchange with natural zeolites has been proposed as a possible approach. The interaction of natural zeolites with solutions of sodium chloride and sodium bicarbonate in addition to coal seam gas water is not clear. Hence, we investigated ion exchange kinetics, equilibrium, and column behaviour of an Australian natural zeolite. Kinetic tests suggested that the pseudo first order equation best simulated the data. Intraparticle diffusion was part of the rate limiting step and more than one diffusion process controlled the overall rate of sodium ion uptake. Using a constant mass of zeolite and variable concentration of either sodium chloride or sodium bicarbonate resulted in a convex isotherm which was fitted by a Langmuir model. However, using a variable mass of zeolite and constant concentration of sodium ions revealed that the exchange of sodium ions with the zeolite surface sites was in fact unfavourable. Sodium ion exchange from bicarbonate solutions (10.3 g Na/kg zeolite) was preferred relative to exchange from sodium chloride solutions (6.4 g Na/kg zeolite). The formation of calcium carbonate species was proposed to explain the observed behaviour. Column studies of coal seam gas water showed that natural zeolite had limited ability to reduce the concentration of sodium ions (loading 2.1 g Na/kg zeolite) with rapid breakthrough observed. It was concluded that natural zeolites may not be suitable for the removal of cations from coal seam gas water without improvement of their physical properties.

Low carbon fuels and commodity chemicals from waste gases – systematic approach to understand energy metabolism in a model acetogen

Gas fermentation using acetogenic bacteria offers a promising route for the sustainable production of low carbon fuels and commodity chemicals from abundant, inexpensive C1 feedstocks including industrial waste gases, syngas, reformed methane or methanol. Clostridium autoethanogenum is a model gas fermenting acetogen that produces fuel ethanol and 2,3-butanediol, a precursor for nylon and rubber. Acetogens have already been used in large scale industrial fermentations, they are ubiquitous and known to play a prominent role in the global carbon cycle. Still, they are considered to live on the thermodynamic edge of life and potential energy constraints when growing on C1 gases pose a major challange for the commercial production of fuels and chemicals. We have developed a systematic platform to investigate acetogenic energy metabolism, exemplified here by experiments contrasting heterotrophic and autotrophic metabolism. The platform is built from complete omics technologies, augmented with genetic tools and complemented by a manually curated genome-scale mathematical model. Together the tools enable the design and development of new, energy efficient pathways and strains for the production of chemicals and advanced fuels via C1 gas fermentation. As a proof-of-platform, we investigated heterotrophic growth on fructose versus autotrophic growth on gas that demonstrate the role of the Rnf complex and Nfn complex in maintaining growth using the Wood–Ljungdahl pathway. Pyruvate carboxykinase was found to control the rate-limiting step of gluconeogenesis and a new specialized glyceraldehyde-3-phosphate dehydrogenase was identified that potentially enhances anabolic capacity by reducing the amount of ATP consumed by gluconeogenesis. The results have been confirmed by the construction of mutant strains.

Mathematical model and rule extraction for tool wear monitoring problem using nature inspired techniques

In this paper, pattern classification problem in tool wear monitoring is solved using nature inspired techniques such as Genetic Programming(GP) and Ant-Miner (AM). The main advantage of GP and AM is their ability to learn the underlying data relationships and express them in the form of mathematical equation or simple rules. The extraction of knowledge from the training data set using GP and AM are in the form of Genetic Programming Classifier Expression (GPCE) and rules respectively. The GPCE and AM extracted rules are then applied to set of data in the testing/validation set to obtain the classification accuracy. A major attraction in GP evolved GPCE and AM based classification is the possibility of obtaining an expert system like rules that can be directly applied subsequently by the user in his/her application. The performance of the data classification using GP and AM is as good as the classification accuracy obtained in the earlier study.

CFD analysis of high frequency miniature pulse tube refrigerators for space applications with thermal non-equilibrium model

High frequency, miniature, pulse tube cryocoolers are extensively used in space applications because of their simplicity. Parametric studies of inertance type pulse tube cooler are performed with different length-to-diameter ratios of the pulse tube with the help of the FLUENT (R) package. The local thermal non-equilibrium of the gas and the matrix is taken into account for the modeling of porous zones, in addition to the wall thickness of the components. Dynamic characteristics and the actual mechanism of energy transfer in pulse are examined with the help of the pulse tube wall time constant. The heat interaction between pulse tube wall and the oscillating gas, leading to surface heat pumping, is quantified. The axial heat conduction is found to reduce the performance of the pulse tube refrigerator. The thermal non-equilibrium predicts a higher cold heat exchanger temperature compared to thermal equilibrium. The pressure drop through the porous medium has a strong non-linear effect due to the dominating influence of Forchheimer term over that of the linear Darcy term at high operating frequencies. The phase angle relationships among the pressure, temperature and the mass flow rate in the porous zones are also important in determining the performance of pulse tuberefrigerator.

Kinetic characterization of rat brain type IIA sodium channel alpha-subunit stably expressed in a somatic cell line

1. The rat brain type IIA Na+ channel alpha-subunit was stably expressed in Chinese hamster ovary (CHO) cells. Current through the expressed Na+ channels was studied using the whole-cell configuration of the patch clamp technique. The transient Na+ current was sensitive to TTX and showed a bell-shaped peak current vs. membrane potential relation. 2. Na+ current inactivation was better described by the sum of two exponentials in the potential range -30 to +40 mV, with. a dominating fast component and a small slower component. 3. The steady-state inactivation, h(infinity), was related to potential by a Boltzmann distribution, underlying thr ee states of the inactivation gate. 4. Recovery of the channels from inactivation at different potentials in the range -70 to -120 mV were characterized by al? initial delay which decreased with hyperpolarization. The time course was well fitted by the sum of two exponentials. In this case the slower exponential was the major component, and both time constants decreased with hyperpolarization. 5. For a working description of the Na+ channel inactivation in this preparation, with a minimal deviation from the Hodgkin-Huxley model, a three-state scheme of the form O reversible arrow I-1 reversible arrow I-2 was proposed, replacing the original two-state scheme of the Hodgkin-Huxley model, and the rate constants are reported. 6. The instantaneous current-voltage relationship showed marked deviation from linearity and was satisfactorily fitted by the constant-field equation. 7. The time course of activation was described by an m(x) model. However, the best-fitted value of x varied with the membrane potential and had a mean value of 2. 8. Effective gating charge was determined to be 4.7e from the slope of the activation plot, plotted on a logarithmic scale. 9. The rate constants of activation, alpha(m) and beta(m), were determined. Their functional dependence on the membrane potential was investigated.

The virial expansion of a classical interacting system

We consider N particles interacting pairwise by an inverse square potential in one dimension (Calogero-Sutherland-Moser model). For a system placed in a harmonic trap, its classical partition function for the repulsive regime is recognised in the literature. We start by presenting a concise re-derivation of this result. The equation of state is then calculated both for the trapped and the homogeneous gas. Finally, the classical limit of Wu's distribution function for fractional exclusion statistics is obtained and we re-derive the classical virial expansion of the homogeneous gas using this distribution function.

A model of the polarization position-angle swings in BL Lacertae objects

The polarization position-angle swings that have been measured in a number of BL Lacertae objects and highly variable quasars are interpreted in terms of shock waves which illuminate (by enhanced synchrotron radiation) successive transverse cross sections of a magnetized, relativistic jet. The jet is assumed to have a nonaxisymmetric magnetic field configuration of the type discussed in the companion paper on the equilibria of force-free jets. For a jet that is viewed at a small angle to the axis, the passage of a shock will give rise to an apparent rotation of the polarization position angle whose amplitude can be substantially larger than 180 deg. The effects of freely propagating shocks are compared with those of bow shocks which form in front of dense obstacles in the jet, and specific applications to 0727 - 115 and BL Lacertae are considered. In the case of 0727 - 115, it is pointed out that the nonuniformity of the swing rate and the apparent oscillations of the degree of polarization could be a consequence of relativistic aberration.

Effect of Bottom Bubbling Conditions on Surface Reaction Rate in Oxygen-Water System

In secondary steelmaking, the enhancement of the reaction rate in the low carbon period during the decarburization of steel is considered the most effective method to produce ultralow carbon steel. In a previous study, it was revealed that the surface reaction is dominant during the final stage of the actual refining process. In order to improve the surface reaction rate, it is necessary to enlarge the reaction region, which is usually achieved by increasing the plume eye area. In this study, water model experiments were carried out to estimate the influence of bottom stirring conditions on the gas-liquid reaction rate; for this purpose, the deoxidation rate during the bottom bubbling process was measured. Five types of nozzle configurations were used to study the effect of the plume eye area on the reaction rate at various gas flow rates. The results reveal that the surface reaction rate is influenced by the gas flow rate and the plume eye area. An empirical correlation was developed for the reaction rate and the plume eye area. This correlation was applied to estimate the gas-liquid reaction rate mat the bath surface.

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: A simulation study

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

A Model of Anomalous Chain Translocation Dynamics

A model of polymer translocation based on the stochastic dynamics of the number of monomers on one side of a pore-containing surface is formulated in terms of a one-dimensional generalized Langevin equation, in which the random force is assumed to be characterized by long-ranged temporal correlations. The model is introduced to rationalize anomalies in measured and simulated values of the average time of passage through the pore, which in general cannot be satisfactorily accounted for by simple Brownian diffusion mechanisms. Calculations are presented of the mean first passage time for barrier crossing and of the mean square displacement of a monomeric segment, in the limits of strong and weak diffusive bias. The calculations produce estimates of the exponents in various scaling relations that are in satisfactory agreement with available data.