Simulation Methods

A gradient free optimization-simulation method for processes modelled with the simulator Aspen HYSYS is developed. The tool is based on a Tabu Search (TS) and the Nelder-Mead Downhill Simplex (NMDS) method. The local optima that result from the TS are fine-tuned with NMDS to reduce the required number of simulations. The tool has been applied to find the total refrigerant flow rate, composition and the refrigerant suction and condenser pressures that minimize the energy requirements of a Prico process. The main strength of this method is that it has a high probability of obtaining a better solution with significantly fewer simulation runs than other metaheuristic methods. Also, by changing the TS step size it is possible to influence the initial search pattern, thereby taking advantage of already gained process knowledge to decrease the optimization time. The method is general and can be applied to other processes modelled in Aspen HYSYS.

We employ atomic-scale simulation methods to investigate bulk and surface properties of an analytic Tersoff-Abell type potential for describing interatomic interactions in GaAs. The potential is a modified form of that proposed by Albe and colleagues [Phys. Rev. B 66, 035205 (2002)] in which the cut-off parameters for the As-As interaction have been shortened. With this modification, many bulk properties predicted by the potential for solid GaAs are the same as those in the original potential, but properties of the GaAs(001) surface better match results from first-principles calculations with density-functional theory (DFT). We tested the ability of the potential to reproduce the phonon dispersion and heat capacity of bulk solid GaAs by comparing it to experiment and the overall agreement is good. In the modified potential, the GaAs(001) β2(2 × 4) reconstruction is favored under As-rich growth conditions in agreement with DFT calculations. Additionally, the binding energies and diffusion barriers for a Ga adatom on the β2(2 × 4) reconstruction generally match results from DFT calculations. These studies indicate that the potential is suitable for investigating aspects of GaAs(001) homoepitaxy.

Distributed discrete event simulation techniques aim at an acceleration of the execution of a self-contained simulation model by the spatial decomposition of that model and the concurrent simulation of the submodels by so called logical processes (LPs), each executing on a dedicated node of a (closed) multiprocessor system. The dedication of parallel simulators to specific platforms and their adaptation to the respective hardware and software intrinsics has widely preventend an industrial and/or commercial success of such high performance simulation methods. In this work we propose the building of logical prdcess simulators that use the World Wide Web as an execution platform. We have developed and implemented a Java-based simulation engine along the conservative Chandy/Misra/Bryant (CMB) synchronization protocol, allowing for a platform independent, scalable, and performance efficient distributed simulation model execution. Our simulation engine is open and general purpose in the sense that it can be reused in various simulation domains by simply "plugging in" different simulation models, and simulation codes that, once written, can be executed anywhere (on the Internet). The potential performance improvement of Web-based distributed simulation is investigated in a sensitivity analysis conducted on a hypothetical simulation model executed in a Javaenabled workstation LAN. Even for very small simulation models, a speedup of about 3.5 could be attained on a 4 processor (heterogeneous) host LAN.

Recent research has revealed the usefulness of Monte Carlo simulation for valuing complex American options which depend on non-conventional stochastic processes. This paper analyzes the possibilities to improve flexibility of traditional real options models by the use of simulation. The authors combine simulation and dynamic programming for valuing American real options contingent on the value of a state variable which evolves according to a mixed Brownian-Poisson process. The paper estimates the optimal exercise strategy using two alternative models, which are based on algorithms developed for financial derivatives. The authors evaluate both valuation proposals using a simple numerical example. The results highlight the need to achieve a trade-off between the accuracy of the estimations and the computational effort needed for this type of proposal. They also reveal the existence of non-monotonous and occasionally counterintuitive relations between the value of the growth option and the volatility and frequency of discontinuous jumps, which should be explained by the characteristics of the stochastic process under consideration.

This paper presents the first development of a space-borne power amplifier using the recently developed high breakdown, high Power HBT HB20S process of UMS. The inverse F class Hybrid Power Amplifier has been designed using intensive simulation methods developed at Alcatel Space for MMICs, allowing to reach very high performances without manual tuning. The results 10 W / PAE > 65% obtained with a single chip at 1.5 GHz demonstrate the capability of the process to handle with very high power densities and efficiencies.

This paper presents the first development of a space-borne power amplifier using the recently developed high breakdown, high Power HBT HB20S process of UMS. The inverse F class Hybrid Power Amplifier has been designed using intensive simulation methods developed at Alcatel Space for MMICs, allowing to reach very high performances without manual tuning. The results 10 W / PAE > 65% obtained with a single chip at 1.5 GHz demonstrate the capability of the process to handle with very high power densities and efficiencies.

Project scheduling models with resource constraints and multi-mode activities aims to create a schedule for carrying out activities considering precedence constraints and available resources in order to minimize the project duration. In the real world, we face uncertainty related to projects, where there are no historical data, hence, we should rely on the experts' judgements to estimate activity durations. For this purpose, in this paper, the 99-simulation method is used to deal with uncertainty. The exact mathematical programming model is presented in this paper and the hybrid algorithm based on Genetic Algorithm is used to solve this type of project scheduling problem which finds the near-optimal solution in a short computational time. Finally, the effectiveness of the proposed model is examined with a numerical example.

Gamificació, simulació, aula inversa... noves metodologies per a la formació en Direcció i Gestió d'Empreses l ' escola d'auditoria) INTRODUCCIÓ Barcelona té una llarga tradició i prestigi en universitats i centres privats de formació orientats als ensenyaments de Direcció i Gestió d'Empreses. Escoles de negocis com, per exemple,

Indeed, utilizing a base isolation system in RC structures can remarkably minimize the possibility of failure, particularly in seismic-prone countries. Despite that, the design of these structures is a long procedure that consists of choosing the appropriate isolator to optimize the nonlinear behavior of the superstructure. Moreover, the numerical simulations require huge computational effort when high accuracy is required. In recent decades, scientists and engineers have applied numerous estimation approaches such as multiple linear regression and artificial neural networks to decrease the required cost and time for daily design problems. Thus, this study's main objective is to solve the difficulty of rapid response prediction by using soft-computing techniques. Additionally, it aims to study the capability of multiple linear regression and artificial neural networks in estimating the seismic performance of base-isolated RC structures under earthquakes. A nonlinear response history analysis of four different lead rubber-bearing isolated RC structures will be performed in order to determine the responses of these structures. Subsequently, the prediction models will be developed using the responses of the structures as inputs for multiple linear regression and artificial neural networks. Lastly, the reliability of both estimation approaches in terms of the response of base-isolated structures will be investigated by comparing the prediction models' capability. In general, the results of the study show that artificial neural networks provide considerably better accuracy in estimating base-isolated structures compared to multiple linear regression, and their performance results in reliable prediction.

The attention towards seismic mitigation using passive control systems has increased significantly over the last few decades to reduce earthquake demands and achieve the required performance objectives. Nowadays, friction pendulum bearings have proven efficient in mitigating regular RC structures subjected to a wide range of earthquakes. Nonetheless, limited studies were dedicated to investigating the performance and efficiency of this type of isolation system utilized in RC structures with various types of vertical irregularities. Besides, comprehensive parametric assessments that investigate the behavior of structures supported on friction pendulum bearings subjected to pulse-like and non-pulse-like earthquakes are scarce. Thus, this study aims to assess the behavior of RC frames equipped with friction pendulum isolators under different types of earthquakes. In the context of the paper, three types of vertical irregularities, known as soft-story, heavy-story, and stepped structures, will be modeled and investigated. Moreover, the outcomes of these buildings will be benchmarked to a regular model to illustrate the efficiency of the selected isolation systems. Furthermore, the performance of the baseisolated buildings with friction pendulum isolators subjected to pulse-like and non-pulse-like earthquakes will be reported. In general, the study results have shown that pulse-like earthquakes exhibited higher values than non-pulse-like earthquakes for the different responses of the structures at the periods of 2.5 and 3 and the damping ratios of 15%, 20%, and 25%.

We develop a new method for the statistical estimation of the tail of the distribution of earthquake sizes recorded in the Harvard catalog of seismic moments converted to m Wmagnitudes (1977-2004 and 1977-2006). For this, we suggest a new parametric model for the distribution of main shock magnitudes, which is composed of two branches, the pure Gutenberg-Richter distribution up to an upper magnitude threshold m 1 , followed by another branch with a maximum upper magnitude bound M max , which we refer to as the two-branch model. We find that the number of main events in the catalog (N = 3975 for 1977-2004 and N=4193 for 1977-2006) is insufficient for a direct estimation of the parameters of this model, due to the inherent instability of the estimation problem. This problem is likely to be the same for any other twobranch model. This inherent limitation can be explained by the fact that only a small fraction of the empirical data populates the second branch. We then show that using the set of maximum magnitudes (the set of T-maxima) in windows of duration T days provides a significant improvement, in particular (i) by minimizing the negative impact of time-clustering of foreshock / main shock / aftershock sequences in the estimation of the tail of magnitude distribution, and (ii) by providing via a simulation method reliable estimates of the biases in the Moment estimation procedure (which turns out to be more efficient than the Maximum Likelihood estimation). We propose a method for the determination of the optimal choice of the T-value minimizing the Mean Square Error of the estimation of the form parameter of the GEV distribution approximating the sample distribution of T-maxima, which yields T optimal =500 days. We have estimated the following quantiles of the distribution of T-maxima for the whole period 1977-2006: Q 16% (M max )= 9.3, Q 50% (M max )= 9.7 and Q 84% (M max ) = 10.3. Finally, we suggest two more stable statistical characteristics of the tail of the distribution of earthquake magnitudes: the quantile Q T (q) of a high probability level q for the T-maxima, and the probability of exceedence of a high threshold magnitude ρ T (m*) = P{ m k ≥ m*}. We obtained the following sample estimates for the global Harvard catalog T Q ˆ(q=0.98) = 8.6 ± 0.2 and T ! ˆ(8) = 0.13-0.20. The comparison between our estimates for the two periods 1977-2004 and 1977-2006, where the later period included the great Sumatra earthquake 24.12.2004, m W =9.0 confirms the instability of the estimation of the parameter M max and the stability of Q T (q) and ρ T (m*) = P{ m k ≥ m*}.

The purpose of this research effort was to develop a straightforward method of aggregating output data from the SABSEL model for use in the TACWAR model. The objective was to develop a software application that would provide consistent results while not requiring a tremendous amount of effort on the part of the analyst. The majority of the effort focused on the construction of a functional approximation of the data and evaluation of this approximation against a look-up table methodology. For the SABSEL data set, a look-up table proved superior. An application was built using the look-up features of MS Access that is simple and straightforward. This work could not have been completed without the help and encouragement of others. First, I am most indebted to my Lord and Savior, Jesus Christ without whose sacrifice none these efforts would have the slightest eternal meaning. I would also like to thank my advisor, Ltc Jack Jackson, for his patient encouragement and pointed comments that helped maintain focus on the big picture. I'm also grateful to Dr. Steve Rogers, who helped keep this effort on track with his insight and direction throughout my efforts with neural networks. Major Don Hinton also provided great help with his insights into the vagaries of MS Access and saved me many hours of trial and error. Finally, I would like to give special thanks to my wife, Michelle, whose consistent love, patience and support were invaluable.

Multiple-point geostatistical simulation (MPS) has recently become popular in stochastic hydrogeology, primarily because of its capability to derive multivariate distributions from a training image (TI). However, its application in three-dimensional (3-D) simulations has been constrained by the difficulty of constructing a 3-D TI. The object-based unconditional simulation program TiGenerator may be a useful tool in this regard; yet the applicability of such parametric training images has not been documented in detail. Another issue in MPS is the integration of multiple geophysical data. The proper way to retrieve and incorporate information from high-resolution geophysical data is still under discussion. In this study, MPS simulation was applied to different scenarios regarding the TI and soft conditioning. By comparing their output from simulations of groundwater flow and probabilistic capture zone, TI from both sources (directly converted from high-resolution geophysical data and generated by TiGenerator) yields comparable results, even for the probabilistic capture zones, which are highly sensitive to the geological architecture. This study also suggests that soft conditioning in MPS is a convenient and efficient way of integrating secondary data such as 3-D airborne electromagnetic data (SkyTEM), but over-conditioning has to be avoided.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

ABSTRACT: 3D geometric modelling is a powerful tool to better understand geology. It allows to check and validate the consistency of the separate 1D or 2D data interpretations. Building a 3D model is also a way to share and communicate a geological view. ...

There is a long tradition of research using computational intelligence, i.e. methods from artificial intelligence (AI) and machine learning (ML), to automatically discover, implement, and fine-tune strategies for autonomous adaptive automated trading in financial markets, with a sequence of research papers on this topic published at major AI conferences such as IJCAI and in prestigious journals such as Artificial Intelligence: we show evidence here that this strand of research has taken a number of methodological missteps and that actually some of the reportedly bestperforming public-domain AI/ML trading strategies can routinely be out-performed by extremely simple trading strategies that involve no AI or ML at all. The results that we highlight here could easily have been revealed at the time that the relevant key papers were published, more than a decade ago, but the accepted methodology at the time of those publications involved a somewhat minimal approach to experimental evaluation of trader-agents, making claims on the basis of a few thousand test-sessions of the trader-agent in a small number of market scenarios. In this paper we present results from exhaustive testing over wide ranges of parameter values, using parallel cloud-computing facilities, where we conduct millions of tests and thereby create much richer data from which firmer conclusions can be drawn. We show that the best public-domain AI/ML traders in the published literature can be routinely outperformed by a "sub-zerointelligence" trading strategy that at face value appears to be so simple as to be financially ruinous, but which interacts with the market in such a way that in practice it is more profitable than the well-known AI/ML strategies from the research literature. That such a simple strategy can outperform established AI/ML-based strategies is a sign that perhaps the AI/ML trading strategies were good answers to the wrong question.

We describe a new public-domain open-source simulator of an electronic financial exchange, and of the traders that interact with the exchange, which is a truly distributed and cloud-native system that been designed to run on widely available commercial cloud-computing services, and in which various components can be placed in specified geographic regions around the world, thereby enabling the study of planetary-scale latencies in contemporary automated trading systems. The speed at which a trader can react to changes in the market is a key concern in current financial markets but is difficult to study latency issues using conventional market simulators, and is extremely difficult to study "in the wild" because of the financial and regulatory barriers to entry in conducting experimental work on real financial exchanges. Our simulator allows an exchange server to be launched in the cloud, specifying a particular geographic zone for the cloud hosting service; automated-trading clients which attach to the exchange can then also be launched in the cloud, in the same geographic zone and/or in different zones anywhere else on the planet, and those clients are then subject to the real-world latencies introduced by planetary-scale cloud communication interconnections. In this paper we describe the design and implementation of our simulator, called DBSE, which is based on a previous public-domain simulator, extended in ways that are partly inspired by the architecture of the real-world Jane Street Exchange. DBSE relies fundamentally on UDP and TCP network communications protocols and implements a subset of the FIX de facto standard protocol for financial information exchange. We show results from an example in which the exchange server is remotely launched on a cloud facility located in London (UK), with trader clients running in Ohio (USA) and Sydney (Australia). We close with discussion of how our simulator could be further used to study planetaryscale latency arbitrage in financial markets.

For more than a decade Vytelingum's Adaptive-Aggressive (AA) algorithm has been recognized as the best-performing automated auction-market trading-agent strategy currently known in the AI/Agents literature; in this paper, we demonstrate that it is in fact routinely outperformed by another algorithm when exhaustively tested across a sufficiently wide range of market scenarios. The novel step taken here is to use large-scale compute facilities to brute-force exhaustively evaluate AA in a variety of market environments based on those used for testing it in the original publications. Our results show that even in these simple environments AA is consistently outperformed by IBM's GDX algorithm, first published in 2002. We summarize here results from more than one million market simulation experiments, orders of magnitude more testing than was reported in the original publications that first introduced AA. A 2019 ICAART paper by Cliff claimed that AA's failings were revealed by testing it in more realistic experiments, with conditions closer to those found in real financial markets, but here we demonstrate that even in the simple experiment conditions that were used in the original AA papers, exhaustive testing shows AA to be outperformed by GDX. We close this paper with a discussion of the methodological implications of our work: any results from previous papers where any one trading algorithm is claimed to be superior to others on the basis of only a few thousand trials are probably best treated with some suspicion now. The rise of cloud computing means that the compute-power necessary to subject trading algorithms to millions of trials over a wide range of conditions is readily available at reasonable cost: we should make use of this; exhaustive testing such as is shown here should be the norm in future evaluations and comparisons of new trading algorithms.

I introduce parameterised response zero intelligence (PRZI), a new form of zero intelligence (ZI) trader intended for use in simulation studies of the dynamics of continuous double auction markets. Like Gode and Sunder's classic ZIC trader, PRZI generates quote prices from a random distribution over some specified domain of discretely valued allowable quote prices. Unlike ZIC, which uses a uniform distribution to generate prices, the probability distribution in a PRZI trader is parameterised in such a way that its probability mass function (PMF) is determined by a real-valued control variable s in the range [-1.0, +1.0] that determines the strategy for that trader. When s = 0 , a PRZI trader behaves identically to the ZIC strategy, with a uniform PMF; but when s ≈ ±1 the PRZI trader's PMF becomes maximally skewed to one extreme or the other of the price range, thereby making it more or less "urgent" in the prices that it generates, biasing the quote price distribution towards or away from the trader's limit price. To explore the co-evolutionary dynamics of populations of PRZI traders that dynamically adapt their strategies, I show initial results from long-term market experiments in which each trader uses a simple stochastic hill-climber algorithm to repeatedly evaluate alternative s-values and choose the most profitable at any given time. In these experiments the profitability of any particular s-value may be non-stationary because the profitability of one trader's strategy at any one time can depend on the mix of strategies being played by the other traders at that time, which are each themselves continuously adapting. Results from these market experiments demonstrate that the population of traders' strategies can exhibit rich dynamics, with periods of stability lasting over hundreds of thousands of trader interactions interspersed by occasional periods of change. Python source code for PRZI traders, and for the stochastic hill-climber, have been made publicly available on GitHub.

The objective of this research is to develop a novel asymmetric carbon hollow fiber membrane and to characterize it's gas separation performance and morphology. Polyacrylonitrile (PAN) was chosen as the precursor for carbon membranes. The hollow fiber membranes were produced using the dry/wet spinning process. PAN hollow fiber membranes were converted to carbon hollow fiber membranes with inert gas pyrolysis process. Carbon hollow fiber membranes were characterized by pure gas permeation measurement, Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR) and Thermogravimetry Analysis (TGA). The influence of the pyrolysis conditions on carbon membrane performance was investigated. Pyrolysis parameters including pyrolysis temperature, heating duration (soak time) and purge gas flow rate were studied. The results showed that pyrolysis temperatures of 700°C to 800°C increased O 2 /N 2 selectivity from 1.1 to 1.85 and the maximum O 2 permeability was achieved at 600°C with 480 GPU. Although the selectivity of 3.1 was achieved at 250°C, the membrane was not a pure carbon membrane. Longer duration of heating improved the selectivity from 1.1 to 1.8 with an increased in permeability at the initial stage. A decreased in permeability occurred at 180 min heating duration. Carbonized membrane with 10 min heating duration exhibited high selectivity of 3.7 with poorer permeability compared to PAN membranes. However, high purge gas flowrate gave an increase for O 2 and N 2 permeability from the original 50 -130 GPU to 150 -730 GPU without influencing it's selectivity. Therefore, pyrolysis condition has pronounced influence on asymmetric carbon hollow fiber membranes for gas separation.

A large volcanic eruption can generate large amounts of ash which affect the socio-economic activities of surrounding areas, affecting airline transportation, socio-economics activities, and human health. Accumulated ashfall has devastating impacts on areas surrounding the volcano and in other regions, and eruption scale and weather conditions may escalate ashfall hazards to wider areas. It is crucial to discover places with a high probability of exposure to ashfall deposition. Here, as a reference for ashfall disaster countermeasures, we present a dataset containing the estimated distributions of the ashfall deposit and airborne ash concentration, obtained from a simulation of ash dispersal following a large-scale explosive volcanic eruption. We selected the Taisho (1914) eruption of the Sakurajima volcano, as our case study. This was the strongest eruption in Japan in the last century, and our study provides a baseline for a worst-case scenario. We employed one eruption scenario (OES) approach by replicating the actual event under various extended weather conditions to show how it would affect contemporary Japan. We generated an ash dispersal dataset by simulating the ash transport of the Taisho eruption scenario using a volcanic ash dispersal model and meteorological reanalysis data for 64 years . We explain the dataset production and provide the dataset in multiple formats for broader audiences. We examine the validity of the dataset, its limitations, and its uncertainties. Countermeasure strategies can be derived from this dataset to reduce ashfall risk.

Coherent radar imaging (CRI), which is fundamentally a beamforming process, has been used to create images of microscale, reflectivity structures within the resolution volume of atmospheric Doppler radars. This powerful technique has the potential to unlock many new discoveries in atmospheric studies. The Turbulent Eddy Profiler (TEP) is a unique 915 MHz boundary layer radar consisting of a maximum of 91 independent receivers. The TEP configuration allows sophisticated CRI algorithms to be implemented providing significant improvement in angular resolution. The present work includes a thorough simulation study of some of the capabilities of the TEP system. The pulse pair processor, used for radial velocity and spectral width estimation with meteorological radars, is combined with beamforming technique, in an efficient manner, to the imaging radar case. By numerical simulation the new technique is shown to provide robust and computationally efficient estimates of the spectral moments. For this study, a recently developed atmospheric radar simulation method is employed that uses the ten thousand scattering points necessary for the high resolution imaging simulation. Previous methods were limited in the number of scatterers due to complexity issues. Radial velocity images from the beamforming radar are used to estimate the three-dimensional wind field map within the resolution volume. It is shown that a large root mean square (RMS) error in imputed three-dimensional wind fields can occur using standard Fourier imaging. This RMS error does not improve even as SNR is increased. The cause of the error is reflectivity variations within the resolution volume. The finite beamwidth of the beamformer skews the radial velocity estimate, and this results in poor wind field estimates. Adaptive Capon beamforming consistently outperforms the Fourier method in the quantitative study and has been demonstrated to enhance the performance compared to the Fourier method.

Coherent radar imaging (CRI), which is fundamentally a beamforming process, has been used to create images of microscale, reflectivity structures within the resolution volume of atmospheric Doppler radars. This powerful technique has the potential to unlock many new discoveries in atmospheric studies. The Turbulent Eddy Profiler (TEP) is a unique 915 MHz boundary layer radar consisting of a maximum of 91 independent receivers. The TEP configuration allows sophisticated CRI algorithms to be implemented providing significant improvement in angular resolution. The present work includes a thorough simulation study of some of the capabilities of the TEP system. The pulse pair processor, used for radial velocity and spectral width estimation with meteorological radars, is combined with beamforming technique, in an efficient manner, to the imaging radar case. By numerical simulation the new technique is shown to provide robust and computationally efficient estimates of the spectral moments...

This paper proposes a test for Lorenz dominance. Given independent samples of income or other welfare related variable, we propose a test of the null hypothesis that the Lorenz curve for one population is dominated by the Lorenz curve for a second population. The test statistic is based on the standardized largest difference between the empirical Lorenz curves for the two samples. The test is completely nonparametric in the sense that no distributional assumptions are made and the test is also consistent because it compares the Lorenz curves at all quantiles. We derive the asymptotic distribution of the test statistic under the null hypothesis. Since the limiting distribution of the test statistic is nonstandard, being dependent on the underlying Lorenz curves, we propose the use of two computer based procedures for conducting inference. The first is a simulation method that simulates p-values from an approximation to the underlying limiting distribution of the statistic while the second is based on the nonparametric bootstrap. In addition to providing a theoretical justification for the proposed methods, we examine the performance of the methods in a Monte Carlo study and with a comparison of the income based Lorenz curves for the US and Canada over time.

In this paper we investigate the effects of oil price uncertainty and its asymmetry on real economic activity in the United States, in the context of a bivariate vector autoregression with GARCH-in-mean errors. The model allows for the possibilities of spillovers and asymmetries in the variance–covariance structure for real output growth and the change in the real price of oil. Our measure of oil price uncertainty is the conditional variance of the oil price–change forecast error. We isolate the effects of volatility in the change in the price of oil and its asymmetry on output growth and employ simulation methods to calculate generalized impulse response functions and volatility impulse response functions to trace the effects of independent shocks on the conditional means and the conditional variances, respectively, of the variables. We find that oil price uncertainty has a negative effect on output, and that shocks to the price of oil and its uncertainty have asymmetric effects on...

We extend the basic model of spatial competition in two directions. First, political parties and voters do not have complete information but behave adaptively. Political parties use polls to search for policy platforms that maximize the probability of winning an election and the voting decision of voters is influenced by social interaction. Second, we allow for the emergence of interest groups. These interest groups transmit information about voter preferences to the political parties, and they coordinate voting behavior. We use simulation methods to investigate the convergence properties of this model. We find that the introduction of social dynamics and interest groups increases the separation between parties platforms, prohibits convergence to the center of the distribution of voter preferences, and increases the size of the winning set.

The FOLD v1 Specification defines a functional, category-inspired language for structural computation, physical modeling, and coherence-driven systems. Built on the principles of recursive generation, morphic depth, and coherence, FOLD unifies declarative expressiveness with constraint-based operational semantics. All computation is formulated as convergence toward structural fixpoints under explicit frames, with a minimal, extensible operator set and dual canonical/sugar syntax. The language features a structural type system, rational and real numeric domains, solver integration, and a standard library supporting advanced operations such as partition, entanglement, and optimization. All constructs are compositional, referentially transparent, and grounded in the formal requirements of Fold Theory. Reserved features include surreal number support and superposition-based modeling for future versions. This specification serves as the authoritative reference for language implementers, theorists, and advanced users seeking principled modeling of emergent and constraint-driven systems.

Aerosols on Mars have an important impact on the radiative transfer properties of its atmosphere. Today their spectral properties and therefore their interaction with UV radiation are only poorly known. Improving the radiative transfer modeling requires a better knowledge of their characteristics, in particular of their phase function, single scattering albedo and opacity. We have developed a new retrieval algorithm

This report was prepared with the support of the U.S. Department of Energy (DOE), under Award No. DE-FC26-04NT42768. However, any opinions, findings, conclusions, or recommendations expressed herein are those of the author and do not necessarily reflect the views of the DOE.

For the first time to our knowledge, we demonstrate fast magnetic reconnection near a magnetic null point in a fluid model of collisionless pair plasma without resorting to the contrivance of anomalous resistivity. In particular, we demonstrate that fast reconnection occurs in an anisotropic adiabatic two-fluid model of collisionless pair plasma with relaxation toward isotropy for a broad range of isotropization rates. For very rapid isotropization we see fast reconnection, but instabilities eventually arise that cause numerical error and cast doubt on the simulated behavior.

For the first time to our knowledge, we demonstrate fast magnetic reconnection near a magnetic null point in a fluid model of collisionless pair plasma without resorting to the contrivance of anomalous resistivity. In particular, we demonstrate that fast reconnection occurs in an anisotropic adiabatic two-fluid model of collisionless pair plasma with relaxation toward isotropy for a broad range of isotropization rates. For very rapid isotropization we see fast reconnection, but instabilities eventually arise that cause numerical error and cast doubt on the simulated behavior.

Many different experimental methods are used to evaluate driving performance as well as to evaluate the effectiveness of various vehicle safety systems but the results often do not match between different experimental approaches. This study aimed to determine the extent to which results can be matched between a driving simulator and a test track when carefully designed studies are used to replicate findings. This study collected simulator data on the National Advanced Driving Simulator (NADS) at the University of Iowa to replicate findings concerning Forward-Crash-Warning interface effectiveness at the Vehicle Research and Test Center (VRTC), East Liberty Ohio. The simulator used a virtual replica of the test track as well as a road course. Event choreography and scanning behavior were compared. Results indicate that results from the simulator were similar to those obtained on the test track. This indicates simulators can replicate findings for the test track and are a valuable tool. Careful experimental design is required to match the event choreography to insure an appropriate comparison. An exact match of the driving environment was not needed for this interface evaluation to obtain comparable results. The extent to which matching motion cues was not evaluated and may prove challenging in simulators without motion systems.

Self-organization in macromolecular systems refers to the transition from a random assembly of interacting oligomers to a system of stable heteropolymers. The concept of adaptive value describes the correlation between environmen- tal variability and the variability in replication and mutation rates of the interacting oligomers. This paper describes a mod- el of self-organization in macromolecular systems based on the concept of adaptive value. The equilibrium states of a set of interacting polymers are described by states that maximize the adaptive value. The analytic basis for this notion of equilibrium, which is called the adaptive value principle, is given and this principle is invoked to explain two examples of macromo- lecular self-assembly.

Self-organization in macromolecular systems refers to the transition from a random assembly of interacting oligomers to a system of stable heteropolymers. The concept of adaptive value describes the correlation between environmental variability and the variability in replication and mutation rates of the interacting oligomers. This paper describes a model of self-organization in macromolecular systems based on the concept of adaptive value. The equilibrium states of a set of interacting polymers are described by states that maximize the adaptive value. The analytic basis for this notion of equilibrium, which is called the adaptive value principle, is given and this principle is invoked to explain two examples of macromolecular self-assembly.

Human vascular systems have considerable anatomic variations. In diseased situation, significant pathological changes will be developed with the systems. However, vascular catheterization devices commercially available are essentially designed on normal or average anatomy. Their inadequacies in representing major deviations in human vascular anatomy may present problems during diagnostic or therapeutic interventions. A virtual reality (VR) based simulation method is described in this paper for prototyping of customized patient-specific catheterization devices. Techniques are developed to model patient-specific vascular network, to design catheterization devices, and to simulate physical-based interactions between blood vessels and the devices. Emphasis is made on the integration of normal and variant vascular models, the integration of modeling, visualization and interaction, and the integration of real-time simulation and virtual prototyping.

Pour ne plus faire peser le financement de la sécurité sociale uniquement sur le facteur travail, l’instauration d’une cotisation sociale généralisée (CSG) est souvent proposée. Une alternative, suggérée par la note du gouvernement fédéral sur les fins de carrière, est de rendre la pension plus sensible au nombre d’années travaillées, en introduisant un malus fonction du nombre d’années de préretraite. Cette mesure est sensée réduire le coût lié aux prépensions et ainsi rendre le financement du système plus aisé. Nous avons simulé ces deux options politiques dans un modèle d’équilibre général calculable afin d’en comparer les conséquences non seulement pour la sécurité sociale mais aussi pour la croissance et le bien-être des différentes générations. La CSG revient à introduire un impôt supplémentaire sur tous les revenus (comme des centimes additionnels), c’est-à-dire sur le travail mais également le capital, les allocations familiales, les pensions et les allocations de chômage. L...

This paper presents the heavy ordered weighted moving average (HOWMA) operator. It is an aggregation operator that uses the main characteristics of two well-known techniques: the heavy OWA and the moving averages. Therefore, this operator provides a parameterized family of aggregation operators from the minimum to the total operator and includes the OWA operator as a special case. It uses a heavy weighting vector in the moving average formulation and it represents the information available and the knowledge of the decision maker about the future scenarios of the phenomenon, according to his attitudinal character. Some of the main properties of this operator are studied, including a wide range of families of HOWMA operators such as the heavy moving average and heavy weighted moving average operators. The HOWMA operator is also extended using generalized and quasi-arithmetic means. An example concerning the foreign exchange rate between US dollars (USD) and Mexican pesos (MXN) is also presented.

The Inverse First Passage time problem seeks to determine the boundary corresponding to a given stochastic process and a fixed first passage time distribution. Here, we determine the numerical solution of this problem in the case of a two dimensional Gauss-Markov diffusion process. We investigate the boundary shape corresponding to Inverse Gaussian or Gamma first passage time distributions for different choices of the parameters, including heavy and light tails instances. Applications in neuroscience framework are illustrated.

The Inverse First Passage time problem seeks to determine the boundary corresponding to a given stochastic process and a fixed first passage time distribution. Here, we determine the numerical solution of this problem in the case of a two dimensional Gauss-Markov diffusion process. We investigate the boundary shape corresponding to Inverse Gaussian or Gamma first passage time distributions for different choices of the parameters, including heavy and light tails instances. Applications in neuroscience framework are illustrated.

A new method is proposed for calculation of the chemical potential of macromolecules by computer simulation. Simulations are performed in an expanded ensemble whose states are defined by the length of a tagged molecule of variable size. A configurational-bias sampling and a preweighting scheme are introduced to facilitate transitions between such states. The usefulness of the method is illustrated by calculations of the chemical potential of hard chain molecules over a wide range of densities. The method proposed here is shown to offer significant advantages over other available methods for calculation of chemical potentials, particularly for long chain molecules at high densities.

▪   This review provides a discussion of recent techniques for simulation of phase equilibria of complex fluids. Monte Carlo methods are emphasized over molecular dynamics methods. We describe recent developments, such as the use of expanded-ensemble, tempering, or histogram reweighting techniques. Our discussion of such developments is aimed at a general audience and is intended to provide an overview of the main advantages and limitations of each particular technique. References are provided to allow interested readers to identify and trace back most recent applications of a particular simulation technique. We conclude with general guidelines regarding selection of suitable simulation methods for particular problems and systems of interest.

The Reproducing Kernel Particle Method (RKPM) is a discretization technique for partial differential equations that uses the method of weighted residuals, classical reproducing kernel theory and modified kernels to produce either "mesh-bee" or '~mesh-full" methods. A1though RKPM has many appealing attributes, the method is new, and its numerical performance is just beginning to be quantified. In order to address the numerical performance of RKPM, von Neumann analysis is performed for semi-discretizations of three model one-dimensional PDEs. The von Neumann analyses results are used to examine the global and asymptotic behavior of the semi-discretizations. The model PDEs considered for this analysis include the parabolic and hyperbolic (first and-second-order wave) equations. Numerical diffusivity for the former and phase speed for the later are presented over the range of discrete wavenumbers and in an asymptotic sense as the particle spacing tends to zero. Group speed is also presented for the hyperbolic problems. Excellent diffusive and dispersive characteristics are observed when a consistent mass matrix formulation is used with the proper choice of refinement parameter. In contrast, the row-sum lumped mass matrix formulation severely degraded performance. The asymptotic analysis indicates that very good rates of convergence are possible when the consistent mass matrix formulation is used with an appropriate choice of refinement parameter.

We describe state-reduction algorithms for the analysis of first-passage processes in discrete-and continuoustime finite Markov chains. We present a formulation of the graph transformation algorithm that allows for the evaluation of exact mean first-passage times, stationary probabilities, and committor probabilities for all nonabsorbing nodes of a Markov chain in a single computation. Calculation of the committor probabilities within the state-reduction formalism is readily generalizable to the first hitting problem for any number of alternative target states. We then show that a state-reduction algorithm can be formulated to compute the expected number of times that each node is visited along a first-passage path. Hence, all properties required to analyze the first-passage path ensemble (FPPE) at both a microscopic and macroscopic level of detail, including the mean and variance of the first-passage time distribution, can be computed using state-reduction methods. In particular, we derive expressions for the probability that a node is visited along a direct transition path, which proceeds without returning to the initial state, considering both the nonequilibrium and equilibrium (steady-state) FPPEs. The reactive visitation probability provides a rigorous metric to quantify the dynamical importance of a node for the productive transition between two endpoint states and thus allows the local states that facilitate the dominant transition mechanisms to be readily identified. The state-reduction procedures remain numerically stable even for Markov chains exhibiting metastability, which can be severely ill-conditioned. The rare event regime is frequently encountered in realistic models of dynamical processes, and our methodology therefore provides valuable tools for the analysis of Markov chains in practical applications. We illustrate our approach with numerical results for a kinetic network representing a structural transition in an atomic cluster.

Ongoing research at Sandia National Laboratories has been in the area of developing models and simulation methods that can be used to uncover and illuminate the material defects created during He bubble growth in aging bulk metal tritides. Previous efforts have used molecular dynamics calculations to examine the physical mechanisms by which growing He bubbles in a Pd metal lattice create material defects. However, these efforts focused only on the growth of He bubbles in pure Pd and not on bubble growth in the material of interest, palladium tritide (PdT), or its non-radioactive isotope palladium hydride (PdH). The reason for this is that existing inter-atomic potentials do not adequately describe the thermodynamics of the Pd-H system, which includes a miscibility gap that leads to phase separation of the dilute (alpha) and concentrated (beta) alloys of H in Pd at room temperature. This document will report the results of research to either find or develop inter-atomic potentials for the Pd-H and Pd-T systems, including our efforts to use experimental data and density functional theory calculations to create an inter-atomic potential for this unique metal alloy system. This research was funded by the Physics and Engineering Models sub-program of the Advanced Simulation and Computing program conducted at Sandia National Laboratories.

The design and study of new materials with specific properties is interesting in several scientific and technological fields. In the last years, nanostructured carbons (NC) have rapidly attracted the attention of some researchers due to their physicochemical properties useful for many applications among them in adsorption and catalysis. In this work, the synthesis of a NC was carried out by a nanocasting method, using as a template a very ordered mesoporous material (SBA-15) and sucrose as carbon source. The final material consists of an ordered arrangement of parallel carbon nanorods bonded with some carbon nanowires (CMK-3 type), formed in the mesopores and micropores of the inorganic matrix. The inorganic matrix and the NC were structurally characterized by X-ray diffraction, texturally by N 2 sorption at 77 K, and morphologically by scanning electron microscopy. The Nitrogen experimental isotherms were simulated using Grand Canonical Monte Carlo (GCMC) method based on two kernels using slit and cylindrical pore models. From these models were obtained the pore size distributions (PSD) which were compared with those obtained by Quenched Solid Density Functional Theory (QSDFT) model. The GCMC simulation showed a good agreement with experimental adsorption isotherms and some differences with the corresponding pore size distribution obtained by Density Functional Theories Methods. These correlations validate the presented GCMC method as an alternative to study in detail the porosity of these materials.

We developed and validated a specific laparoscopic fundoplication simulator for use with the objective endoscopic surgical skills evaluation system. The aim of this study was to verify the quality of skills of surgeons. We developed a 1-year-old infant body model based on computed tomography data and reproduced pneumoperitoneum model based on the clinical situation. The examinees were divided into three groups: fifteen pediatric surgery experts (PSE), twenty-four pediatric surgery trainees (PSN), and ten general surgeons (GS). They each had to perform three sutures ligatures for construction of Nissen wrap. Evaluate points are time for task, the symmetry of the placement of the sutures, and the uniformity of the interval of suture ligatures in making wrap. And the total path length and velocity of forceps were measured to assess bi-hand coordination. PSE were significantly superior to PSN regarding total time spent (p < 0.01) and total path length (p < 0.01). GS used both forc...