Monte Carlo Simulation

In this study, the problem of discriminating between interictal epileptic and non-epileptic pathological EEG cases, which present episodic loss of consciousness, investigated. We verify the accuracy of the feature extraction method of autocross-correlated coefficients which extracted and studied in previous study. For this purpose we used in one hand a suitable constructed artificial supervised LVQ1 neural network and in other a cross-correlation technique. To enforce the above verification we used a statistical procedure which based on a chi-square control. The classification and the statistical results showed that the proposed feature extraction is a significant accurate method for diagnostic discrimination cases between interictal and non-interictal EEG events and specifically the classification procedure showed that the LVQ neural method is superior than the cross-correlation one.

We describe a Monte Carlo procedure for the simulation of dynamically triangulate random surfaces with a boundary (topology of a disk). The algorithm keeps the total number of triangles fixed, while the length of the boundary is allowed to fluctuate. The algorithm works in the presence of matter fields. We here present results for the pure gravity case. The algorithm reproduces the theoretical expectations.

Municipal solid waste generation is a rapidly increasing challenge that is leading to severe pollution and environmental degradation in many urban areas of developing countries. Globally, the solid waste sector accounts for 18% of methane emissions and 3e4% of greenhouse gas emissions overall. Waste handling and disposal systems in most large cities have largely been designed with minimal accounting of environmental issues. This study presents the Waste to Energy Recovery Assessment (WERA) framework, a new quantitative decision support model for initial evaluation and alternative comparisons of different thermochemical treatments of municipal wastes. The framework not only accounts for benefits through electricity generation but also accounts for emissions from facilities and the associated social cost of carbon in a cost-benefit assessment. The assessments are conducted with Monte Carlo simulations that explicitly account for uncertain factors such as future composition and generation of solid waste, technical efficiency of treatment processes, capital and operating costs, as well as future policies. The framework is used to study waste-to-energy (WtE) systems for Abu Dhabi, Riyadh, Tokyo and New York. The results show that WtE systems can fulfill only 1.4e3.6% of 2014 electricity demand in the analyzed cases. Furthermore, the net present value for different technologies can be positive if collection fees and electricity rates (potentially set through feed-in-tariff policies) are sufficiently high. The analysis for Abu Dhabi and Riyadh also reveals that in a limited set of conditions (of technology efficiencies, and waste collection rates etc.) the WtE facilities can be self-sustaining investments.

The increasing wind power generation requires the updating of the computational tools that support decision making in the operation and planning of electric power systems. This work describes a methodology to model the spatial correlations among wind speeds probability distributions in probabilistic power flow. The proposed methodology is based on Nataf transformation and Monte Carlo Simulation. The proposed methodology is illustrated in case studies with the IEEE 24 bus test system, highlighting the importance of adequately considering such correlations.

Spatial variability is one of the most significant characteristics of soil properties, even within homogeneous layers. The physical description of this spatial variation is unclear, due to the highly expensive sampling, uncontrollable measurement errors, and modeling uncertainty. While the deterministic approach failed to present a reasonable quantification for the spatial variability of soil properties, the probabilistic approach has been utilized to assess and quantify the effects of soil spatial variability on the behavior of some typical soil-structure systems.
This study investigates the effect of spatial variability of soil properties (mass density γs, coefficient of friction tanδ, angle of internal friction (φ), and wall mass density γc, on the factors of safety against sliding (Fs), and overturning (Fo), as well as the maximum bending moment (M) of cantilever retaining walls.
For risk assessment, soil properties are described using appropriate probabilistic models. Deterministic analysis combined with Monte Carlo Simulation (MCS) is employed to analyze both spatially fully correlated and spatially uncorrelated soil profiles.
A FORTRAN program is developed to: (1) generate random variables with both Gauassian and non-Gauassian probability density functions (PDF); (2) simulate possible probability distributions for distinct soil properties; (3) perform repetitive analysis for each set of variable PDFs to generate the population of Fs, Fo, and M; and (4) calculate the statistical parameters of Fs, Fo, and M. The program is then applied to conduct an extensive parametric study.
This parametric study is performed to quantify and assess the effects of model uncertainty and the effect of spatial heterogeneity of soil properties, utilizing two different soil profiles: (1) spatially fully correlated soil profile; and (2) spatially uncorrelated soil profile. 
The numerical results show that the effects of spatial variability and uncertainty of input variables on wall safety vary from one variable to the other. Consequently, considerable care should be directed to those variables that have the greatest effects. For typical degrees of uncertainty, it is found that the structural risk is highest when the PDF of tanδ and φ is normal (Gauassian), or has an upper triangular shape (non-Gauassian). In addition, it is found that accounting for soil spatial variability in design of retaining walls leads to more economic designs, as it produces smaller probabilities of failure. In other word, negligence of the spatial variability in the design of retaining wall is conservative.

O Serviço Municipal de Saúde do Rio de Janeiro tem exigido um projeto para avaliar a capacidade de atendimento do serviço de emergência, tendo em vista os desastres urbanos e naturais que estão acontecendo em muitos lugares, além dos dois grandes eventos que estão prestes a acontecer na cidade do Rio de Janeiro em 2014 e 2016. O objetivo deste trabalho é propor um Sistema de Informações e Coordenação que envolva três órgãos públicos: o Centro de Operações do GSE/SAMU, o Centro de Operações da Prefeitura do Rio de Janeiro e o Núcleo Interno de Regulação (NIR) dos hospitais municipais. O modelo baseia-se no fluxo de informações, centrando-se nos pacientes de alta complexidade. A simulação de eventos discretos é utilizada para identificar como o sistema responde à demanda aumentada. Afirma-se que o “uso da informação” é a chave para melhorar o desempenho global do sistema.

The construction project management is about quality, timely, and costly managing construction inputs and outputs. However, its achievement continues to present a major challenge to most large construction projects all over the world due to the high degrees of complexity and variability. For instance, delivery of construction projects has been adversely influenced by several drastic risks. A major and critical concern in the time scheduling process is the accurate determination of activities durations. This calls for a continuous improvement in the conventional techniques of estimating activity duration and in utilizing the deterministic scheduling.
This thesis presents a comprehensive analysis of activities duration of construction projects in the Middle East countries. The analysis was carried out on twenty construction projects including more than 125,000 activities with a total budget of about fifteen billions Egyptian Pounds (EGP) and comprising all engineering, procurement and construction (EPC) activities. The thesis seeks to bridge the gap between theory and application and to utilize      a probabilistic scheduling approach that yields reliable estimations of activity duration. The focus is to evaluate the actual behaviour of activities exposed to different types of risk and uncertainty and to derive regression models predicting activities’ durations categorized according to country, type of work, and to the Construction Specifications Institute (CSI) divisions.
First, previous research on the causes of delay and the probabilistic analysis of activities in developing and developed countries has been compiled and critically reviewed. This review indicated that there is no generally accepted Probability Density Function (PDF) to represent the activity duration through the simulation process. However, Beta and Triangular distributions were the mostly used PDF’s.
Then, activity and project durations of different projects such as hospitals, hotels, stadiums, highways, malls, and high rise buildings in Egypt, Kuwait, Saudi Arabia, UAE, Qatar and Oman were analysed. The analysis considered the estimated durations, the actual durations, and the budgets of the EPC activities. It also included the quantitative analysis of causes of delay on the performance of seven repetitive construction activities in a housing project that is composed of 1271 similar houses in Kuwait. Besides, statistical analysis and curve fitting of the estimated versus the actual durations of activities were conducted. In addition, the study developed predictive regression models to estimate the statistics of activities durations. Finally, a special program that uses the concluded PDF and regression models to predict the project’s overall durations at different levels of confidence was developed.
It is found that the three most influencing risks on the time performance of construction activities in Kuwait are: (1) inadequate planning and time scheduling; (2) slow financial and payment procedures; and (3) fluctuation of productivity levels. In addition, it is found that the best PDF to represent activities in construction projects is the lognormal distribution, while the second best PDF is the gamma distribution. Besides, it is shown that the normal distribution has the lowest level of confidence. Furthermore, it is found that as the estimated duration decreases, the relative duration slippage increases. The ratio of the highest, actual activity duration to the corresponding mean duration is always more than 4 for projects in the Middle East, which differs from that suggested in previous studies (1.25). As a general rule, the forecasted project’s overall duration- based on the proposed regression models and utilizing lognormal distribution- tends to be greater than that calculated using conventionally estimated activities. Nevertheless, validation tests showed that the forecasted projects’ durations are good estimates of the real ones. Consequently, these forecasted projects’ durations could oblige contractors to implement different methodologies and alternative plans to reduce the project’s duration.

Today's consumers are often overloaded with information. This article argues that traditional approaches to measuring the amount of information in a choice set fail to account for important structural dimensions of information and may therefore incorrectly predict information overload. Two experiments show that a structural approach to measuring information, such as information theory, is better able to predict information overload and that information structure also has important implications for information acquisition. A Monte-Carlo simulation, in which decision rules are applied to multiple information environments, shows that the amount of information processing mediates the relationship between information structure and information overload.

This work proposes a parametric probabilistic approach to model damage accumulation using the double linear damage rule (DLDR) considering the existence of limited experimental fatigue data. A probabilistic version of DLDR is developed in which the joint distribution of the knee-point coordinates is obtained as a function of the joint distribution of the DLDR model input parameters. Considering information extracted from experiments containing a limited number of data points, an uncertainty quantification framework based on the Maximum Entropy Principle and Monte Carlo simulations is proposed to determine the distribution of fatigue life. The proposed approach is validated using fatigue life experiments available in the literature.

In biological suspensions, the forward light scattering is done mainly by the contribution of the suspended cells. The multiple scattering is almost always unavoidable, its contribution being described by Monte Carlo simulations or by approximate analytical formula. The Monte Carlo approach we propose moves one photon at a time and checks all scattering centers to find, at each simulation step, which one will scatter the photon. The validation of the simulation results is performed by comparing the obtained angular distribution with the predictions of the effective phase function theory reported recently in the literature and with the angle resolved experimental measurements performed on human red blood cells (RBCs) in suspensions at different hematocrits. The results show a good agreement in the small concentration range.

Coulomb interaction limits the beam current for a required resolution but it can be influenced by the layout of the optical system. Therefore it is necessary to obtain design information for future charged particle lithography tools. Monte Carlo simulations are an important tool in this design. Two of these programs, COUTRAC and BOERSCH, are compared with experimental data of an Ion Projection Lithography (IPL) set-up. The results of COUTRAC are in agreement with the measurements to within 19% in case of a uniform cross-over. With an aberrated cross-over the difference increases to 126 % near the axis since the experiment showed no increase of Coulomb interaction over the inner quarter of the exposure field while both Monte Carlo models show a monotone increase to the axis.

A complete analysis of low-noise 0.1 m gate AlInAs/GaInAs HEMT's has been performed by using a semiclassical Monte Carlo simulation. The validity of the model has been checked through the comparison of the simulated results with static, dynamic and noise experimental measurements of real HEMTs. In order to reproduce the experimental results, we have included in the model some important real effects such as degeneracy, surface charges, T-shape of the gate, presence of dielectrics and contact resistances. Moreover, the extrinsic parameters of the devices have been added to the usual intrinsic small-signal equivalent circuit, thus allowing the calculation of the real noise of the HEMTs (characterized using the extrinsic minimum noise . In this way, we make possible not only the comparison with the experimental noise results, but also the analysis of the influence of the parasitic elements, the device width or the number of gate fingers on the noise of the HEMTs. The reliability of the simulator allows us to realize "computer experiments" which will make faster and cheaper the optimization process of the device design. for his work on the modeling and the characterization of MES-FETs and HEMTs. In 1977, he joined the Centre Hyperfrequences et Semiconducteurs, University of Lille, France. He is now Professor of electronics at the University of Lille. His main research interests are concerned with the modeling, the realization and the characterization of low noise devices for application in the centimeter and millimeter wave ranges.

Using scintillation crystal sheets instead of discrete crystal arrays in high-resolution PET has the immediate advantage of reduced complexity as well as a potential for increased sensitivity. In order to evaluate the positioning capability of a position sensitive avalanche photodioide (PSAPD) using a sheet Lutetium Oxyorthosilicate (LSO) crystal scintillator, we studied the dependence of detected event position versus the known source position. In particular, we studied positioning in a continuous 8 mm 8 mm LSO sheet coupled to a PSAPD with an 8 mm 8 mm active area experimentally, studied optical transport in the sheet crystal with Monte Carlo simulation, and used two positioning methods to evaluate PSAPD pincushioning effects. Both collimated 57 Co 122 keV and coincidence-triggered 22 Na 511 keV sources were used in the experiments performed. We analyze the energy resolution, sensitivity, photopeak position and spatial resolution as a function of source position. An average point spread function (PSF) resolution of 2.86 and 1.12 mm FWHM for 57 Co and 22 Na respectively was observed. Within 1.2 mm from the edge of the LSO sheet, the average photopeak position change was 5%. Simulations using annihilation photon interactions from GATE and scintillation photon transport from DETECT2000, as well as utilizing a pincushion-reduction posioning algorithm, have confirmed that the positioning and energy response observed experimently at the edge of the crystal is due to optical transport near those edges.

Soft error tolerant design becomes more crucial due to exponential increase in the vulnerability of computer systems to soft errors. Accurate estimation of soft error rate (SER), the probability of system failure due to soft errors, is a key factor in design of cost-effective soft error resilient systems. We present a very fast and accurate approach based on enhanced static timing analysis and signal probabilities to estimate the probability of latching an incorrect value in the system bistables (timing derating). Experimental results and comparison with fault injections using timing accurate Monte-Carlo simulations show that the accuracy of our approach is within 1% while orders of magnitude faster.

Salmonella enteritidis (SE) is a common foodborne pathogen, the transmission of which is primarily associated with the consumption of contaminated Grade A shell eggs. In order to estimate the level of SE present in raw shell eggs, it is necessary to consider the protective effects of the egg albumin, which effectively inhibits SE growth in a time-and temperature-dependent manner. In this study, a SE growth model was produced by combining two mathematical equations that described both the extended lag phase of SE growth (food component) and a SE growth model (pathogen component). This biphasic growth model was then applied to various egg handling scenarios based on the farm-to-table continuum, including in-line and off-line processing facilities with consideration of key events in production, processing, transportation, and storage. Seasonal effects were also studied. Monte Carlo simulation was used to characterize variability in temperature and time parameter values influencing the level of SE to which individuals are exposed. The total level of SE consumed was estimated under best, most likely, and time -temperature abusive handling scenarios. The model estimated that, in most cases, there was no SE growth in contaminated eggs handled under most likely practices, because 10 -70% of the yolk membrane remained intact. Under abusive handling scenarios, complete loss of yolk membrane integrity frequently occurred by the time eggs reach the distribution phase, followed by subsequent SE growth, which was often quite rapid. In general, the effect of season and processing method (in-line vs. off-line) was minimal. Further sensitivity analysis demonstrated that the initial SE contamination level significantly influenced the final exposure levels only under no-abuse or mildly abusive conditions. The results of our study suggest that, for maximum reduction of SE exposure level, cooling strategies should not only focus on the on-farm or processing phases, but should emphasize the importance of cooling strategies at the distribution and consumer phases of the farm-to-fork continuum. D

Lead-210 assay and dating are subject to several sources of error, including natural variation, the statistical nature of measuring radioactivity, and estimation of the supported fraction. These measurable errors are considered in calculating confidence intervals for 210Pb dates. Several sources of error, including the effect of blunders or misapplication of the mathematical model, are not included in the quantitative analysis.

We investigate the survival probability ⌽(n,c) of particles performing a random walk on a two-dimensional lattice that contains static traps, which are randomly distributed with a concentration c, as a function of the number of steps n. ⌽(n,c) is analyzed in terms of a scaling ansatz, which allows us to locate quantitatively the crossover between the Rosenstock approximation ͑valid only at early times͒ and the asymptotic Donsker-Varadhan behavior ͑valid only at long times͒. While the existence of the crossover has been postulated before, its exact location has not been known. Our scaling hypothesis is based on the mean value of the quantity S n , the number of sites visited in an n-step walk. We make use of the idea of self-interacting random walks, and a ''slithering'' snake algorithm, available in the literature, and we are thus able to obtain accurate survival probability data indirectly by Monte Carlo simulation techniques. The crossover can now be determined by our method, and it is found to depend on a combination of c and n. It occurs at small ⌽(n,c) values, which is typically the case for large values of n.

Two pairs of confidence intervals for a proportion, similar to that of Larson, are compared. It can be shown through computer simulation experiments that, for certain values of p, the confidence interval obtained by the approximation is superior.

Comparison of the spatial and temporal information retrieved from near-infrared phase and average intensity (DC) data reveals that these data types can play a complementary role in the study of the temporal and spatial features of the optical response associated with brain activation during a finger-tapping test. The optical data have been collected with a frequency-domain tissue imager at two wavelengths (690 and 830 nm) and have been analyzed using standard filtering and folding-average procedures. DC and phase data show different temporal and spatial features. A plausible explanation of the different behavior of DC and phase data has been attempted by using Monte Carlo simulations.

The elliptical flow of fragments is studied for different systems at incident energies between 50 and 1000 MeV/nucleon using Isospin-dependent Quantum Molecular Dynamics (IQMD) Model. Our findings reveal that elliptical flow shows a transition from positive (in-plane) to negative (out-of-plane) value in the mid-rapidity region at certain incident energy, known as transition energy. This transition energy is found to depend on the model ingredients, size of the fragments, composite mass of the reacting system as well as on the impact parameter of the reaction. A reasonable agreement is observed for the excitation function of elliptical flow between the data and our calculations. Interestingly, the transition energy is found to exhibit a power law mass dependence.

L'apport des connaissances dans la science est soumis à l’expérience. Dans la vision de Pascal les anciens les ont trouvées seulement ébauchées, et nous les laisserons à ceux qui viendront après nous en un état plus accompli que nous ne les avons reçues se voyant ainsi infinies en l’étendue de leurs recherches. Cet écrit propose d’explorer la tension philosophique autour de l’expérience de simulation et de l’expérience de pensée qui créent et explorent tous deux des mondes hypothétiques.

This article presents a framework for the representation of uncertainty in the early design of complex adaptive products such as automobiles. The core of the framework is an object-oriented approach in which design objects and their interrelationships may be modeled, and in which both the design attributes and the product structure may be uncertain. Relationship objects allow product variants and design alternatives to be represented. In addition to the design model, derivation methods for design attributes may be modeled, and methods may be incorporated to allow the deterministic or probabilistic computation of attributes. The modeling framework is the basis of a risk modeling tool, RiTo, in which Monte Carlo simulation is used to compute estimates for costs and other design attributes together with their probability of achievement in the final design. Uncertainties may be aggregated and levels of uncertainty in different parts of the model may be continually analysed and assessed. The framework also provides a mechanism for accumulating product knowledge, in particular knowledge concerning relationships between elements of part and assembly models, product volumes and manufacturing considerations.

The fortune and the risk of a business venture depends on the future course of the economy. There is a strong demand for economic forecasts and scenarios that can be applied to planning and modeling. While there is an ongoing debate on modeling economic scenarios, the bootstrapping (or resampling) approach presented here has several advantages. As a non-parametric method, it directly relies on past market behaviors rather than debatable assumptions on models and parameters. Simultaneous dependencies between economic variables are automatically captured. Some aspects of the bootstrapping method require additional modeling: choice and transformation of the economic variables, arbitrage-free consistency, heavy tails of distributions, serial dependence, trends and mean reversion. Results of a complete economic scenario generator are presented, tested and discussed.

Using Monte Carlo simulations we examine the diffusive properties of the greedy algorithm in the d-dimensional traveling salesman problem. Our results show that for d = 3 and 4 the average squared distance from the origin r 2 is proportional to the number of steps t. In the d = 2 case such a scaling is modified with some logarithmic corrections, which might suggest that d = 2 is the critical dimension of the problem. The distribution of lengths also shows marked differences between d = 2 and d > 2 versions. A simple strategy adopted by the salesman might resemble strategies chosen by some foraging and hunting animals, for which anomalous diffusive behavior has recently been reported and interpreted in terms of Lévy flights. Our results suggest that broad and Lévy-like distributions in such systems might appear due to dimension-dependent properties of a search space.

Climate is one of the single most important factors affecting watershed ecosystems and water resources. The effect of climate variability and change has been studied extensively in some places; in many places, however, assessments are hampered by limited availability of long-term continuous climate data. Weather generators provide a means of synthesizing long-term climate data that can then be used in natural resource assessments. Given their potential, there is the need to evaluate the performance of the generators; in this study, three commonly used weather generators—CLImate GENerator (CLIGEN), Long Ashton Research Station Weather Generator (LARS-WG), and Weather Generators (WeaGETS) were compared with regard to their ability to capture the essential statistical characteristics of observed data (distribution, occurrence of wet and dry spells, number of snow days, growing season temperatures, and growing degree days). The study was based on observed 1966–2015 weather station data from the Western Lake Erie Basin (WLEB), from which 50 different realizations were generated, each spanning 50 years. Both CLIGEN and LARS-WG performed fairly well with respect to representing the statistical characteristics of observed precipitation and minimum and maximum temperatures, although CLIGEN tended to overestimate values at the extremes. This generator also overestimated dry sequences by 18%–30% and snow-day counts by 12%–19% when considered over the entire WLEB. It (CLIGEN) was, however, well able to simulate parameters specific to crop growth such as growing degree days and had an added advantage over the other generators in that it simulates a larger number of weather variables. LARS-WG overestimated wet sequence counts across the basin by 15%–38%. In addition, the optimal growth period simulated by LARS-WG also exceeded that obtained from observed data by 16%–29% basin-wide. Preliminary results with WeaGETS indicated that additional evaluation is needed to better define its parameters. Results provided insights into the suitability of both CLIGEN and LARS-WG for use with water resource applications.

Different international plant protection organisations advocate different schemes for conducting pest risk assessments. Most of these schemes use structured questionnaire in which experts are asked to score several items using an ordinal scale. The scores are then combined using a range of procedures, such as simple arithmetic mean, weighted averages, multiplication of scores, and cumulative sums. The most useful schemes will correctly identify harmful pests and identify ones that are not. As the quality of a pest risk assessment can depend on the characteristics of the scoring system used by the risk assessors (i.e., on the number of points of the scale and on the method used for combining the component scores), it is important to assess and compare the performance of different scoring systems. In this article, we proposed a new method for assessing scoring systems. Its principle is to simulate virtual data using a stochastic model and, then, to estimate sensitivity and specificity values from these data for different scoring systems. The interest of our approach was illustrated in a case study where several scoring systems were compared. Data for this analysis were generated using a probabilistic model describing the pest introduction process. The generated data were then used to simulate the outcome of scoring systems and to assess the accuracy of the decisions about positive and negative introduction. The results showed that ordinal scales with at most 5 or 6 points were sufficient and that the multiplication-based scoring systems performed better than their sum-based counterparts. The proposed method could be used in the future to assess a great diversity of scoring systems.

Purpose -The aim of the research was to evaluate the concept that utilizes structured planar substrates based on low temperature co-fired ceramics (LTCC) as a precision platform for the passive alignment of a multimode fiber and wide-stripe diode laser. Design/methodology/approach -Presents the manufacturing process for realisation of 3D precision structures, heat dissipation structures and a cooling channel into the LTCC substrate. The developed methodology for 3D modelling and simulation of the system was used to optimize structures, materials and components in order to achieve optimal performance for the final product and still maintain reasonably low fabrication costs. The simulated optical coupling efficiency and alignment tolerances were verified by prototype realization and characterization. Findings -The achieved passive alignment accuracy allows high coupling efficiency realisations of multimode fiber pigtailed laser modules and is suitable for mass production. Research limitations/implications -Provides guidance in the design of LTCC precision platforms for passive alignment and presents a hybrid simulation method for photonics module concept analysis. Practical implications -The three-dimensional shape of the laminated and fired ceramic substrate provides the necessary alignment structures including holes, grooves and cavities for the laser to fiber coupling. Thick-film printing and via punching can be incorporated in order to integrate electronic assemblies directly into the opto-mechanical platform. Originality/value -Introduces the LTCC 3D precision structures for photonics modules enabling passive alignment of multimode fiber pigtailed laser with high efficiency optical coupling. Demonstrates the hybrid simulation methodology for concept analysis.

The White-tailed Tropicbird Phaethon lepturus breeding population of Aride Island, Seychelles, has experienced a strong decline in the recent past. To predict the future trends of the White-tailed Tropicbird population on Aride Island and understand the urgency of applying management procedures, we developed a population matrix model. We estimated White-tailed Tropicbird adult survival rate over a 12-year period and investigated whether oceanographic conditions (El Niño Southern Oscillation, ENSO, and inter-annual climate variability in the Indian Ocean, Indian Ocean Dipole, IOD) or local factors (Pisonia grandis fruiting events) potentially affect adult survival. Annual adult survival could not be linked to inter-annual variability in oceanographic conditions, but may be more influenced by Pisonia fruiting events, which, overall, accounts for 23.2% of the adult mortality. The growth rate of the population, primarily influenced by annual adult survival, was estimated to be 0.946, which indicates an annual population decline of 5.4%. At the current rate, the probability of extinction of this population would be 99% in 170 years. Management scenarios studied through Monte Carlo simulations, assuming small increments in adult survival and/or breeding success, dramatically reduce the risk of extinction of White-tailed Tropicbirds. Habitat management, in order to maintain an open canopy and little understorey vegetation, appears to be crucial for the conservation of White-tailed Tropicbirds on Aride Island, as has already been shown for other groundnesting tropical seabirds nesting on forested islands.

The increasing use of Carbon nuclei in cancer therapy centres is motivated by their potential advantages as a very precise high LET radiation. The knowledge of the fragmentation of Carbon nuclei when they interact with the human body is important to evaluate the spatial profile of their energy deposition in the tissues, hence the damage to the tissues neighbouring the tumour. We report here a study of the fragmentation with the nuclear emulsion experimental technique. We have designed, built and exposed to a Carbon nuclei beam a chamber made of Lexan plates alternated with nuclear emulsion films. Lexan plates acted as passive material simulating human body tissues while nuclear emulsion films were used as both tracking devices with micrometric accuracy and ionisation detectors. Such a detector allowed the detection of Carbon interactions produced along their path, the identification of the fragments produced and the measurement of their scattering angle. We have measured the Carbon ion survival probability and studied their interactions. We report on the secondary particle multiplicity and the electrical charge distribution. We give results of the scattering angle of final state fragments as well as the range for H and He. Finally we give the total and partial charge-changing cross-sections for z = 1, 2, 3, 4 which are compared with previous results when available. The present work aims at providing data required as input to Monte Carlo simulations of Carbon ion interactions in the human body and ultimately of their therapeutic effectiveness.

Environmental modelling languages provide the possibility to construct models in two or three spatial dimensions. These models can be static models, without a time component, or dynamic models. Dynamic models are simulations run forward in time, where the state of the model at time t is defined as a function of its state in a period or time step preceding t. Since inputs and parameters of environmental models are associated with errors, environmental modelling languages need to provide techniques to calculate how these errors propagate to the output(s) of the model. Since these techniques are not yet available, the paper describes concepts for extending an environmental-modelling language with functionality for error-propagation modelling. The approach models errors in inputs and parameters as stochastic variables, while the error in the model outputs is approximated with a Monte Carlo simulation. A modelling language is proposed which combines standard functions in a structured script (program) for building environmental models, and calculation of error propagation in these models. A prototype implementation of the language is used in three example models to illustrate the concepts.

We propose an efficient algorithm to sample the volume in Monte Carlo simulations in the isobaric-isothermal ensemble. The method is designed to be applied in the simulation of hardcore models at high density. The algorithm is based in the generation of clusters of particles. At the volume change step, the distances between pairs of particles belonging to the same cluster do not change. This is done by rescaling the positions of the center of mass of each cluster instead of the position of each individual particle. We have tested the performance of the algorithm by simulating fluid and solid phases of hard spheres, finding that in both cases the algorithm is much more efficient than the standard procedure. Moreover, the efficiency of the method measured in terms of correlation "time" does not depend on the system size in contrast with the standard method, in which the sampling becomes rapidly inefficient as the system size increases. We have used the procedure to compute with high precision the equation of state of the face-centered cubic phase of the hard sphere system for different system sizes. Using these results we have estimated the equation of state at the thermodynamic limit. The results are compared with different equations of state proposed in the literature.

The homogeneous precipitation kinetics of the ordered phases Al 3 Zr and Al 3 Sc in Al solid solutions has been simulated at the mesoscopic scale by the cluster dynamics method. The polyatomic clusters, embedded in the solid solution, have an L1 2 structure and exchange solute atoms via absorption and emission reactions controlled by interfacial and long range diffusion. The time evolution of the cluster distribution is determined numerically, solving a set of master differential equations coupled through monomer exchanges. Results are presented for different temperatures and solute supersaturations and are discussed in terms of the classical schemes of precipitation and of recent atomistic Monte-Carlo simulations.

Differential cross sections (DCS) suitable for Monte Carlo simulation of the energy loss of fast electrons and positrons in matter are proposed. These DCSs are based on high-energy approximations, complemented with semiempirical ingredients which make them accurate for a wide energy range. The DCS for collision losses, including Fermi's density effect correction, is obtained from the Born approximation and a simple generalized oscillator strength model. Collision stopping powers, and also mean free paths and energy straggling parameters, can be evaluated in a purely analytical way. The DCS for bremsstrahlung emission is given in the form of the Bethe-Heitler DCS with exponential screening including a Coulomb correction. The described DCSs have moderately simple analytical expressions which allow random sampling of the energy loss in detailed Monte Carlo simulations by using purely analytical methods. Suitable sampling algorithms are also described.

Recently, Monte Carlo (MC) calculation method has reported as the most accurate method of predicting dose distributions in radiotherapy. In this present work investigation on the accuracy of MC (EGSnrc) in calculating electron beam central axis dose was conducted. Calculation of central axis depth dose distributions for 9 MeV electron beams from medical linear accelerator (Siemens Primus) was performed with BEAMnrc and DOSXYZnrc source code on personal desktop. Both source codes were included in EGSnrc package. Results were compared with an ion chamber measurement. On central axis dose MC data shows a good agreement with ion chamber measurement which is less than 2% percentage different. In this context the model is accurate and potentially to achieve the dose delivery as recommended by ICRU report.

Abstract-Low voltage CMOS circuits, operating in current mode, that exhibit piecewise transfer characteristics are presented. These circuits can be used for the synthesis of arbitrary piecewise transfer functions. Several circuits were developed. Nonlinear functions were synthesized with several approaches and results were compared using the Monte Carlo simulation of PSPICE software. The best results were obtained with double break point circuits. These circuits can be supplied with less than 1V.

The formation of two-component multilayer films on homogeneous solid surfaces is discussed using the mean-field theory and Monte Carlo' simulation. Adsorption systems exhibiting complete and incomplete mixing of components are discussed. It is shown that the structure of adsorbed films depends strongly on the relative strength of the adsorbate-adsorbate and the adsorbate-substrate interactions for both components. In particular, it is demonstrated that the enhanced adsorption of one component due to adsorption of another gas, which is observed in monolayer films, occurs also in multilayer films. It is shown that in the systems considered in this work the displacement of preadsorbed film due to adsorption of the second component may occur via the desorption or via the transfer of molecules to the higher layers. The mechanism of the displacement is shown to depend strongly on the details of gas-gas and gas-solid interactions of both components.

A simple membrane, supporting charge densities 1 and 2 ϭϪ 1 on its inner and outer surfaces, is considered. In addition to the electrostatic potential, the membrane interacts with the surrounding fluid by a short range van der Waals-like potential. The fluid beyond the outer surface is a three-component restricted primitive electrolyte consisting of two cations and one anion. The membrane is impermeable to one of the cations so that the fluid in the membrane and beyond the inner surface is a two-component restricted primitive electrolyte. We use Monte Carlo simulations and density functional theory to study the density profiles of the electrolyte and the charge-electrostatic potential relationship for the membrane surfaces. Even though 2 ϭϪ 1 , the potentials on the membrane surfaces are not equal and opposite. We also study a membrane consisting of a single charged plane. For both models, the density functional results are in good agreement with the simulations.

Results. For signals near the detection threshold, our low-latency algorithms often localized simulated GW burst signals to tens of square degrees, while neutron star/neutron star inspirals and neutron star/black hole inspirals were localized to a few hundred square degrees. Localization precision improves for moderately stronger signals. The correct sky location of signals well above threshold and originating from nearby galaxies may be observed with ~50% or better probability with a few pointings of wide-field telescopes.

A study on the applicability of dierent kinds of neural networks for the probabilistic analysis of structures, when the sources of randomness can be modeled as random variables, is summarized. The networks are employed as numerical devices for substituting the ®nite element code needed by Monte Carlo simulation. The comparison comprehends two network types (multi-layer perceptrons and radial basis functions classi®ers), cost functions (sum of square errors and cross-entropy), optimization algorithms (back-propagation, Gauss±Newton, Newton±Raphson), sampling methods for generating the training population (using uniform and actual distributions of the variables) and purposes of neural network use (as functional approximators and data classi®ers). The comparative study is performed over four examples, corresponding to dierent types of the limit state function and structural behaviors. The analysis indicates some recommended ways of employing neural networks in this ®eld. Ó

Angular Domain Imaging (ADI) is a high resolution, ballistic imaging method that utilizes the angular spectrum of photons to filter multiply-scattered photons which have a wide distribution of angles from ballistic and quasi-ballistic photons which exit a scattering medium with a small distribution of angles around their original trajectory. Such spatial gating has been previously accomplished using a scanning array of collimating holes micromachined into a silicon wafer section. We now extend that work to include using a wide-beam, full-field, converging lens and pinhole aperture system to capture images in a single exposure. We have developed an analysis of resolution and sensitivity trade-offs of such a system using Fourier optics theory to show that the system resolution is primarily governed by collimation ability at larger aperture sizes and by spatiofrequency (Fourier space-gated) filtering at smaller aperture sizes. It is found that maximum sensitivity is achieved when spatiofrequency resolution and collimation resolution are equal. Planar, high contrast, phantom test objects are observed in 5 cm thick media with effective scattered to ballistic photon ratios >1.25×10 7 :1 using a wide-beam, full-field lens and aperture system. Comparisons are made between ballistic imaging with the lens and aperture system and with the scanning silicon micromachined collimating array. Monte-Carlo simulations with angular tracking validate the experimental results.

Background: Polymer gel dosimetry showed the ability to measure three dimensional dose distribution of radiation treatment. The challenge in gel dosimetry is to extract dose information from the irradiated gel dosimeter through medical imaging techniques such as MRI (Magnetic Resonance Image), Ultrasound, Optical CT, Raman Spectroscopy and CT (Computed Tomography) Imaging. Objective: The aim of this work is to evaluate the three dimension dose distribution measured using CT based MAGAT (methacrylic acid, gelatine and THP) gel dosimetry in radiation treatment and compare it with Monte Carlo simulation. Results: The qualitative comparison of dose distribution for the three fields technique measured using gel dosimetry agreed very well with that calculated using Monte Carlo simulation, with maximum disagreement of 4 mm. Conclusion: The Monte Carlo simulation verified that the CT based normoxic gel dosimeter showed to be a great promising method for verifying 3D dose distribution.

Suppose we are interested in forecasting a time series and, in addition to the time series data, we have data from many time series related to the one we want to forecast. Since building a dynamic multivariate model for the set of time series can be a complex task, it is important to measure in advance the increase in precision to be attained by using multivariate forecasts with respect to univariate ones. This article presents a simple procedure designed to obtain a consistent estimate of this measure. Its performance is illustrated with Monte Carlo simulations and examples.

From time to time, economies undergo far-reaching structural changes. In this paper we investigate the consequences of structural breaks in the factor loadings for the specification and estimation of factor models based on principal components and suggest test procedures for structural breaks. It is shown that structural breaks severely inflate the number of factors identified by the usual information criteria. Based on the strict factor model the hypothesis of a structural break is tested by using Likelihood-Ratio, Lagrange-Multiplier and Wald statistics. The LM test which is shown to perform best in our Monte Carlo simulations, is generalized to factor models where the common factors and idiosyncratic components are serially correlated. We also apply the suggested test procedure to a US dataset used in Stock and Watson (2005) and a euro-area dataset described in Altissimo et al. (2007). We find evidence that the beginning of the so-called Great Moderation in the US as well as the Maastricht treaty and the handover of monetary policy from the European national central banks to the ECB coincide with structural breaks in the factor loadings. Ignoring these breaks may yield misleading results if the empirical analysis focuses on the interpretation of common factors or on the transmission of common shocks to the variables of interest.

A preliminary study on the possible use of the GEANT4 (GEometry ANd Tracking) toolkit and Grid technology, for the Monte Carlo simulation of a clinical beam line for proton therapy, has been investigated. We realized a GEANT4 application giving the possibility to simulate a typical proton therapy beam line (including all its elements and two dosimetric systems: an ionisation chamber and a radiochromic film). The application realized was tested simulating the proton therapy beam line operating at the Laboratori Nazionali del Sud of the Instituto Nazionale di Fisica Nucleare in Catania, Italy. Actually the main disanvatage of a Monte Carlo simulation are the long computation times. In order to overcome this problem and to obtain resonable computation times we decided to exploit the power of the Grid. We based our work on the local Grid installed at the Physics Department of the Catania University consisting of 20 machine, each one with two INTEL-Xeon at 2.8 GHz processors. The Grid approach, consisting in the distribution of a single big job in many CPUs, permitted us to decrease, in the actual configuration, of a factor 20 the time necessary for a complete simulation. Obtained results permit us to adfirm that GEANT4 toolkit, coupled with the Grid, can represent an answer for the routinary use of the Monte Carlo method for designing and simulating a clinical proton beam line. Moreover this can represent a first step for the use of Monte Carlo in proton treatment planning software development.