Effect of surface-perturbed intermolecular interaction on adsorption of simple gases on a graphitized carbon surface

In this paper, we investigate the effect of the solid surface on the fluid-fluid intermolecular potential energy. This modified fluid-fluid interaction energy due to the inducement of a solid surface is used in the grand canonical Monte Carlo (GCMC) simulation of various noble gases, nitrogen, and methane on graphitized thermal carbon black. This effect is such that the effective interaction potential energy between two particles close to surface is less than the potential energy if the solid substrate is not present. With this modification the GCMC simulation results agree extremely well with the experimental data over a wide range of pressures while the simulation results with the unmodified potential energy give rise to a shoulder near the neighborhood of monolayer coverage and the significant overprediction of the second and higher layer coverages. In particular the unmodified GCMC results exhibit very sharp change in those higher layers while the experimental data have a much gradual change in the uptake. We will illustrate this theory with adsorption data of argon, xenon, neon, nitrogen, and methane on graphitized thermal carbon black.

Comparative adsorption of spherical argon and flexible n-butane in carbon slit pores - a GCMC computer simulation study

In this paper we investigate the difference between the adsorption of spherical molecule argon (at 87.3 K) and the flexible normal butane (at an equivalent temperature of 150 K) in carbon slit pores. These temperatures are equivalent in the sense that they have the same relative distances between their respective triple points and critical points. Higher equivalent temperatures are also studied (122.67 K for argon and 303 K for n-butane) to investigate the effects of temperature on the 2D-transition in adsorbed density. The Grand Canonical Monte Carlo simulation is used to study the adsorption of these two model adsorbates. Beside the longer computation times involved in the computation of n-butane adsorption, n-butane exhibits many interesting behaviors such as: (i) the onset of adsorption occurs sooner (in terms of relative pressure), (ii) the hysteresis for 2D- and 3D-transitions is larger, (iii) liquid-solid transition is not possible, (iv) 2D-transition occurs for n-butane at 150 K while it does not happen for argon except for pores that accommodate two layers of molecules, (v) the maximum pore density is about four times less than that of argon and (vi) the sieving pore width is slightly larger than that for argon. Finally another feature obtained from the Grand Canonical Monte Carlo (GCMC) simulation is the configurational arrangement of molecules in pores. For spherical argon, the arrangement is rather well structured, while for n-butane the arrangement depends very much on the pore size. (C) 2004 Elsevier B.V. All rights reserved.

Molecular weight dependence of phase Behavior of PEO/P(EO-b-DMS) blends: Application of Sanchez-Lacombe lattice fluid theory

Molecular weight dependence of phase separation behavior of the Poly (ethylene oxide) (PEO)/Poly(ethylene oxide-block-dimethylsiloxane) (P(EO-b-DMS)) blends was investigated by both experimental and theoretical methods. The cloud point curves of PEO/P(EO-b-DMS) blends were obtained by turbidity method. Based on Sanchez-Lacombe lattice fluid theory (SLLFT), the adjustable parameter, epsilon*(12)/k (quantifying the interaction energy between different components), was evaluated by fitting the experimental data in phase diagrams. To calculate the spinodals, binodals, and the volume changes of mixing for these blends, three modified combining rules of the scaling parameters for the block copolymer were introduced.

Thermodynamics of phase behavior in PEO/P(EO-b-DMS) homopolymer and block co-oligomer mixtures under pressure

The cloud-point temperatures (T-cl's) of poly(ethylene oxide) (PEO) and poly(ethylene oxide)-block-polydimethylsiloxane (P(EO-b-DMS)) homopolymer and block-oligomer mixtures were determined by turbidity measurements over a range of temperatures (105 to 130degrees), pressures (1 to 800 bar), and compositions (10-40 wt.-% PEO). The system phase separates upon cooling and T-cl was found to decrease with an increase in pressure for a constant composition. In the absence of special effects, this finding indicates negative excess volumes. Special attention was paid to the demixing temperatures as a function of the pressure for the different polymer mixtures and the plots in the T-phi plane (where phi signifies volume fractions). The cloud-point curves of the polymer mixture under pressures were observed for different compositions. The Sanchez-Lacombe (SL) lattice fluid theory was used to calculate the spinodals, the binodals, the Flory-Huggins (FH) interaction parameter, the enthalphy of mixing, and the volume changes of mixing. The calculated results show that modified P(EO-b-DMS) scaling parameters with the new combining rules can describe the thermodynamics of the PEO/P(EO-b-DMS) system well with the SL theory.

Thermodynamics of PMMA/SAN blends: Application of the Sanchez-Lacombe lattice fluid theory

Polymer blends of poly(methyl methacrylate) (PMMA) and poly(styrene-co-acrylonitrile) (SAN) with an acrylonitrile content of about 30 wt % were prepared by means of solution-casting and characterized by virtue of pressure-volume-temperature (PVT) dilatometry. The Sanchez-Lacombe (SL) lattice fluid theory was used to calculate the spinodals, the binodals, the Flory-Huggins (FH) interaction parameter, the enthalpy of the mixing, the volume change of the mixing, and the combinatorial and vacancy entropies of the mixing for the PMMA/SAN system. A new volume-combining rule was used to evaluate the close-packed volume per mer, upsilon*, of the PMMA/SAN blends. The calculated results showed that the new and the original volume-combining rules had a slight influence on the FH interaction parameter, the enthalpy of the mixing, and the combinatorial entropy of the mixing. Moreover, the spinodals and the binodals calculated with the SL theory by means of the new volume-combining rule could coincide with the measured data for the PMMA/SAN system with a lower critical solution temperature, whereas those obtained by means of the original one could not.

Study of water and dimethylformamide interaction by computer simulation

Monte Carlo simulations of water-dimethylformamide (DMF) mixtures were performed in the isothermal and isobaric ensemble at 298.15 K and 1 atm. The intermolecular interaction energy was calculated using the classical 6-12 Lennard-Jones pairwise potential plus a Coulomb term. The TIP4P model was used for simulating water molecules, and a six-site model previously optimised by us was used to represent DMF. The potential energy for the water-DMF interaction was obtained via standard geometric combining rules using the original potential parameters for the pure liquids. The radial distribution functions calculated for water-DMF mixtures show well characterised hydrogen bonds between the oxygen site of DMF and hydrogen of water. A structureless correlation curve was observed for the interaction between the hydrogen site of the carbonyl group and the oxygen site of water. Hydration effects on the stabilisation of the DMF molecule in aqueous solution have been investigated using statistical perturbation theory. The results show that energetic changes involved in the hydration process are not strong enough to stabilise another configuration of DMF than the planar one.

Monte Carlo simulation of water-tetrahydrofuran mixtures

Monte Carlo simulations of water-tetrahydrofuran (THF) mixtures were performed in the isothermal-isobaric ensemble (NPT) at T = 298 K and p = 1 atm. The interaction energy was calculated using the TIP4P model for water and a five-site united atom representation for the THF molecule. The potential energy surfaces for water-THF interactions were obtained by using combining rules and the original potential functions used for pure liquids. Theoretical values obtained for the average interaction energy as a function of concentration are in good agreement with available experimental data. Results from the partitioning of the total interaction energy into water-water, water-THF and THF-THF contributions are presented. These results are useful to distinguish between the quantitative contributions of these molecular interactions to the energetic behavior of the water-THF mixing process. The radial distribution functions for HW-OTHF and OW-OTHF site-site interactions show the salient features of hydrogen-bonded liquids. Comparison of the average number of water-water complexes interacting through hydrogen bonding in water-THF and water-methanol mixtures shows an enhancement of the water-water coordination number in a THF rich environment. © 1995.

First lessons in Latin, upon a new plan : combining abstract rules, with a progressive series of practical exercises /

Mode of access: Internet.

Effective hybrid recommendation combining users-searches correlations using tensors

Most recommendation methods employ item-item similarity measures or use ratings data to generate recommendations. These methods use traditional two dimensional models to find inter relationships between alike users and products. This paper proposes a novel recommendation method using the multi-dimensional model, tensor, to group similar users based on common search behaviour, and then finding associations within such groups for making effective inter group recommendations. Web log data is multi-dimensional data. Unlike vector based methods, tensors have the ability to highly correlate and find latent relationships between such similar instances, consisting of users and searches. Non redundant rules from such associations of user-searches are then used for making recommendations to the users.

Essays on macroeconomic effects of fiscal policy rules

Economic and Monetary Union can be characterised as a complicated set of legislation and institutions governing monetary and fiscal responsibilities. The measures of fiscal responsibility are to be guided by the Stability and Growth Pact, which sets rules for fiscal policy and makes a discretionary fiscal policy virtually impossible. To analyse the effects of the fiscal and monetary policy mix, we modified the New Keynesian framework to allow for supply effects of fiscal policy. We show that defining a supply-side channel for fiscal policy using an endogenous output gap changes the stabilising properties of monetary policy rules. The stability conditions are affected by fiscal policy, so that the dichotomy between active (passive) monetary policy and passive (active) fiscal policy as stabilising regimes does not hold, and it is possible to have an active monetary - active fiscal policy regime consistent with dynamical stability of the economy. We show that, if we take supply-side effects into ac-count, we get more persistent inflation and output reactions. We also show that the dichotomy does not hold for a variety of different fiscal policy rules based on government debt and budget deficit, using the tax smoothing hypothesis and formulating the tax rules as difference equations. The debt rule with active monetary policy results in indeterminacy, while the deficit rule produces a determinate solution with active monetary policy, even with active fiscal policy. The combination of fiscal requirements in a rule results in cyclical responses to shocks. The amplitude of the cycle is larger with more weight on debt than on deficit. Combining optimised monetary policy with fiscal policy rules means that, under a discretionary monetary policy, the fiscal policy regime affects the size of the inflation bias. We also show that commitment to an optimal monetary policy not only corrects the inflation bias but also increases the persistence of output reactions. With fiscal policy rules based on the deficit we can retain the tax smoothing hypothesis also in a sticky price model.

Combining Associational and Causal Reasoning to Solve Interpretation and Planning Problems

This report describes a paradigm for combining associational and causal reasoning to achieve efficient and robust problem-solving behavior. The Generate, Test and Debug (GTD) paradigm generates initial hypotheses using associational (heuristic) rules. The tester verifies hypotheses, supplying the debugger with causal explanations for bugs found if the test fails. The debugger uses domain-independent causal reasoning techniques to repair hypotheses, analyzing domain models and the causal explanations produced by the tester to determine how to replace faulty assumptions made by the generator. We analyze the strengths and weaknesses of associational and causal reasoning techniques, and present a theory of debugging plans and interpretations. The GTD paradigm has been implemented and tested in the domains of geologic interpretation, the blocks world, and Tower of Hanoi problems.

The blended approach to real estate allocations: performance implications of combining an exposure to German Spezialfonds with Global Listed Real Estate Securities

This paper seeks to increase the understanding of the performance implications for investors who choose to combine an unlisted real estate portfolio (in this case German Spezialfonds) with a (global) listed real estate element. We call this a “blended” approach to real estate allocations. For the avoidance of doubt, in this paper we are dealing purely with real estate equity (listed and unlisted) allocations, and do not incorporate real estate debt (listed or unlisted) or direct property into the process. A previous paper (Moss and Farrelly 2014) showed the benefits of the blended approach as it applied to UK Defined Contribution Pension Schemes. The catalyst for this paper has been the recent attention focused on German pension fund allocations, which have a relatively low (real estate) equity content, and a high bond content. We have used the MSCI Spezialfonds Index as a proxy for domestic German institutional real estate allocations, and the EPRA Global Developed Index as a proxy for a global listed real estate allocation. We also examine whether a rules based trading strategy, in this case Trend Following, can improve the risk adjusted returns above those of a simple buy and hold strategy for our sample period 2004-2015. Our findings are that by blending a 30% global listed portfolio with a 70% allocation (as opposed to a typical 100% weighting) to Spezialfonds, the real estate allocation returns increase from 2.88% p.a. to 5.42% pa. Volatility increases, but only to 6.53%., but there is a noticeable impact on maximum drawdown which increases to 19.4%. By using a Trend Following strategy raw returns are improved from 2.88% to 6.94% p.a. , The Sharpe Ratio increases from 1.05 to 1.49 and the Maximum Drawdown ratio is now only 1.83% compared to 19.4% using a buy and hold strategy . Finally, adding this (9%) real estate allocation to a mixed asset portfolio allocation typical for German pension funds there is an improvement in both the raw return (from 7.66% to 8.28%) and the Sharpe Ratio (from 0.91 to 0.98).

Joint dynamic probabilistic constraints with projected linear decision rules

We consider multistage stochastic linear optimization problems combining joint dynamic probabilistic constraints with hard constraints. We develop a method for projecting decision rules onto hard constraints of wait-and-see type. We establish the relation between the original (in nite dimensional) problem and approximating problems working with projections from di erent subclasses of decision policies. Considering the subclass of linear decision rules and a generalized linear model for the underlying stochastic process with noises that are Gaussian or truncated Gaussian, we show that the value and gradient of the objective and constraint functions of the approximating problems can be computed analytically.

A Markov random field model for combining optimum-path forest classifiers using decision graphs and game strategy approach

The research on multiple classifiers systems includes the creation of an ensemble of classifiers and the proper combination of the decisions. In order to combine the decisions given by classifiers, methods related to fixed rules and decision templates are often used. Therefore, the influence and relationship between classifier decisions are often not considered in the combination schemes. In this paper we propose a framework to combine classifiers using a decision graph under a random field model and a game strategy approach to obtain the final decision. The results of combining Optimum-Path Forest (OPF) classifiers using the proposed model are reported, obtaining good performance in experiments using simulated and real data sets. The results encourage the combination of OPF ensembles and the framework to design multiple classifier systems. © 2011 Springer-Verlag.

Post-processing association rules with clustering and objective measures

The post-processing of association rules is a difficult task, since a large number of patterns can be obtained. Many approaches have been developed to overcome this problem, as objective measures and clustering, which are respectively used to: (i) highlight the potentially interesting knowledge in domain; (ii) structure the domain, organizing the rules in groups that contain, somehow, similar knowledge. However, objective measures don't reduce nor organize the collection of rules, making the understanding of the domain difficult. On the other hand, clustering doesn't reduce the exploration space nor direct the user to find interesting knowledge, making the search for relevant knowledge not so easy. This work proposes the PAR-COM (Post-processing Association Rules with Clustering and Objective Measures) methodology that, combining clustering and objective measures, reduces the association rule exploration space directing the user to what is potentially interesting. Thereby, PAR-COM minimizes the user's effort during the post-processing process.