Simple Simulation Approach Research Articles

On Influencing Population Means

Findings on the existence or the lack of temporal trends in sperm concentration at the population level have been used to discuss the role of environmental factors (including endocrine disruptors) on male fertility. An assumption sometimes made 1 is that temporal trends in biological parameters such as sperm concentration will parallel temporal trends in their risk factors. As we illustrate below, this assumption is a too simple view, outside the probably rare situation where one prevalent environmental factor has a major impact on the biological parameter considered. Let us consider the case of an environmental factor A to which no pregnant woman was exposed before year t0 and to which 40% of pregnant women were exposed at a later time t1; we assumed that in utero exposure to this factor causes an average decrease of 20% in sperm concentration in adulthood among male offspring. We also considered factors B and C, supposed to have a much stronger impact at the individual level (sperm concentration decrease by 85%) and whose prevalence in pregnant women rose by 10% (factor B) or 60% (factor C) between t0 and t1. We estimated the population mean of sperm concentration in adulthood among men born at period t1, assuming that either factor existed alone; we assumed lack of selection bias, measurement or random error, and of temporal trends in the prevalence of any other factor. Using a simple simulation approach (detailed in eAppendix), we also estimated the change in mean concentration assuming that several factors simultaneously impacted on sperm concentration independently. Compared to the unexposed cohort of men born at t0, the impact of factor A in men from t1 birth cohort corresponded to a decrease in sperm concentration by 8% (Table). Sperm concentration decrease was 9% for factor B, while it reached 51% in the case of the more prevalent factor C (Table). Finally, when exposure to 5 factors, each having the same individual impact as factor A (sperm concentration change by −20%) simultaneously increased, sperm concentration decreased by 34% at the population level; 8 such factors were required to cause a population decrease by 49% (Table). Table Sperm concentration in adulthood among men born at periods t0 and t1, assuming the existence of an environmental factor whose prevalence increased between t0 and t1. This study shows that a single factor with a moderate but realistic influence on sperm concentration at the individual level (−20%, comparable to the reported effect of in utero exposure to tobacco smoke 2), whose prevalence has increased significantly over time (+40%) would cause a relatively small decrease in sperm concentration at the population level (−8%). This is because the population impact of a single factor will remain lower than its individual impact, except if prevalence increases from 0 to 100%. Several independent factors with moderate effects in the same direction and with rather high increase in exposure prevalence might entail substantial changes in sperm concentration. Although some chemicals with a strong impact at the individual level have been identified in occupational settings,3 the prevalence of exposure in the general population probably remained low. Therefore, to our knowledge, a factor with such high impact and prevalence than those hypothesized here for factor C has to date not been identified. If one looks for causes of a strong reduction in sperm concentration at the population level, a combination of several factors, each having a limited impact at the individual level and whose prevalences simultaneously strongly increased appears like a more realistic explanation. We assumed that factors acted independently, but of course synergy between factors could also exist 4 (see eAppendix for an illustration). In another setting, a simulation study has quantified the impact of public health interventions on smoking prevalence.5 Data on temporal trends in outcome alone (without individual information on exposures), although very relevant in a public health perspective,6 correspond to a simple form of ecological studies and are, outside specific settings,7 generally very limited to draw strong conclusions regarding the influence of environmental factors. Indeed, several factors may have opposed impacts at the individual level or opposed temporal trends. For these reasons, conclusions on the impact of endocrine disruptors and other families of environmental factors on male fertility (or the lack thereof) should not be drawn from studies of temporal trends in male fertility parameters alone. In order to characterize the impact of exposures during the developmental window, mother-child cohorts with a biomarker-based assessment of exposure during pregnancy and long-term follow-up constitute a more relevant tool. Such studies are currently very rare.2, 8

A Simple and Accurate Simulation Approach to theHeston Model

Models with stochastic volatility often require Monte Carlo simulation. One of the most popular volatility processes is the mean-reverting square root diffusion, as proposed by Heston. The theoretical model as developed in continuous time has the virtue that it does not allow volatility to become negative. But when the model is adapted to discrete non-infinitesimal time steps in a simulation, negative variance values can be encountered. Several ways to deal with this problem have been proposed, but they can come with inconvenient side effects, such as slow or erratic convergence or the failure to preserve correlation properties with other stochastic variables in the model. Zhu shows how building the model in terms of volatility rather than variance can produce more-accurate and more-efficient simulations within a Heston-type model

Generating crop sequences in land-use models using maximum entropy and Markov chains

Farm management models often produce average crop shares over a number of years, whereas models from the natural sciences often require inputs of sequences of crops grown on a specific field over several years. In interdisciplinary modelling, this difference can be a relevant obstacle. To bridge this gap, an approach is presented that allows disaggregating results from farm management models to the level required by many natural science models. The approach presented includes two methodological innovations: first, minimum cross entropy is used to ensure a unique solution when modelling a linear programming model at the field level, even when objective and constraint coefficients are identical for different fields. Second, the use of a calibrated Markov chain approach allows the creation of land-use sequences that are closer to the linear programming model’s results than an unconditional stochastic simulation would be. The calibrated Markov chain makes use of a prior matrix of transition probabilities that can be empirically derived. Both simulations and analytical calculations with case study data show that the variances of the Markov chain approach are systematically lower than those yielded by a simple stochastic simulation approach. The approach introduced in this paper can improve the coupling of farm-level economic models with natural science models at the field level.

Is it possible to infer the number of colonisation events from genetic data alone?

The current state of populations is to a large determined by events in the past that we have no information about. Thus, we have to rely on indirect methods to infer likely scenarios of these events. In this paper we describe a simple simulation approach to infer the minimum number of introductions of an invasive species, the round goby in the Baltic Sea. The results show that several introductions are most likely to have occurred, possibly even a constant rate of immigration. This poses new threats to local fish populations that currently suffer from overfishing. The method is very general and can be applied to other similar situations.

Modelling daytime thermal infrared directional anisotropy over Toulouse city centre

Measurements of thermal infrared (TIR) directional anisotropy (difference between off-nadir and nadir brightness temperatures) performed over the city of Toulouse using a method based on the use of 2 airborne TIR cameras are presented. Results from 3 flights at different times during a summer day (July 15th 2004) and from 1 flight in winter (February 25th 2005) all confirm important anisotropy (up to 10 °C) and hot spot effects as previously reported in literature. A simple simulation approach is then proposed. It is based on the aggregation in any viewing direction of 6 directional temperatures (sunlit/shaded walls/streets/roofs) weighted by their corresponding surface ratios within the scene viewed. The city is described by 18 canyon streets oriented in all directions by 10° steps and the 6 temperatures are determined by integrating simulations of the energy balance model SOLENE repeated for the 18 canyon streets. The surface ratios are computed from images of the studied area generated with the POV-Ray software (Persistence of Vison Raytracer, http://www.povray.org/). This method is described in detail. The modelled anisotropy compares favourably with the measurements on all dates, despite a systematic underestimation ranging between 15 and 30%. The possible sources of discrepancy including sensitivity to the aspect ratio and to the surface parameters and possible impact of microscale structures are briefly discussed and several improvements of the modelling system are suggested.

ON THE CONDITIONAL LIKELIHOOD RATIO TEST FOR SEVERAL PARAMETERS IN IV REGRESSION

For the problem of testing the hypothesis that all m coefficients of the right-hand-side endogenous variables in an instrumental variables (IV) regression are zero, the likelihood ratio (LR) test can, if the reduced form covariance matrix is known, be rendered similar by a conditioning argument. To exploit this fact requires knowledge of the relevant conditional cumulative distribution function (c.d.f.) of the LR statistic, but the statistic is a function of the smallest characteristic root of an (m + 1)-square matrix and is therefore analytically difficult to deal with when m > 1. We show in this paper that an iterative conditioning argument used by Hillier (2009) and Andrews, Moreira, and Stock (2007 Journal of Econometrics 139, 116–132) to evaluate the c.d.f. in the case m = 1 can be generalized to the case of arbitrary m. This means that we can completely bypass the difficulty of dealing with the smallest characteristic root. Analytic results are obtained for the case m = 2, and a simple and efficient simulation approach to evaluating the c.d.f. is suggested for larger values of m.

Applications of MATLAB Symbolic and Optimization Toolboxes in Static Voltage Stability in Power Systems

Abstract This paper presents a simple simulation approach to study static voltage stability in power systems. Symbolic and Optimization toolboxes in MATLAB are used to simulate load flow, continuation power flow and optimization technique in static voltage stability study. Flexible AC Transmission System devices including SVC, TCSC, STATCOM, SSSC and UPFC are used to validate the proposed technique. Various voltage stability parameters including PV curves, loading margin and simulation times are investigated. Three-bus and IEEE fourteen-bus test systems are used to demonstrate the proposed technique. The proposed approach may be of interest to utilities and researchers who wish to study voltage stability of medium size power systems in a simple way.

The international VAMAS project on X-ray reflectivity measurements for evaluation of thin films and multilayers — Preliminary results from the second round-robin

X-ray reflectometry (XRR) is a unique technique for thin film analysis providing information on thickness, density, and roughness. The Versailles Project on Advanced Materials and Standards (VAMAS) project “X-ray reflectivity measurements for evaluation of thin films and multilayers” has the goal to assess the accuracy and precision of thickness, density and roughness as determined by XRR measurements and simulations. Here we present preliminary results from the second round-robin analysis on a TaN/Ta metallization on a silicon substrate. This work demonstrated a good inter-laboratory reproducibility for the tantalum film thickness with a standard deviation of 0.04 nm corresponding to about 0.3%. The use of the auto-correlation function (extracted from the derivative of density profiles obtained via a Fourier transform) was found to provide useful layer thickness measurements from important samples that are too complex for a simple direct simulation and fitting approach.

Patterns and Determinants of Historical Woodland Clearing in Central‐Western New South Wales, Australia

AbstractWe consider the history of woodland clearing in central western New South Wales, Australia, which has led to the present highly cleared and fragmented landscape. A combined approach is used examining available historical land‐use data and using regression analysis to relate the pattern of cleared and wooded areas in the recent landscape to environmental variables, taking into account the contagious nature of clearing. We also ask whether it would be possible to apply a simple simulation modelling approach to reconstruct a credible historical sequence of clearing in the study area. The historical data indicate that annual clearing rates have varied substantially in the study area and selective tree removal (ringbarking and thinning) has been common. These findings make it unlikely that a simple simulation approach would replicate the spatial and temporal sequence of woodland loss. Our regression results show that clearing patterns can be related to environmental variables, particularly annual rainfall and estimated pre‐European vegetation type, but that patterns are dominated by contagion.

Analytical approach of thermosyphon solar domestic hot water system performance

An efficient and simple simulation approach for thermosyphon solar water heaters has been developed and compared with experimental data. This approach, valid for solar-only systems, gives the ability to link the system main design and constructional parameters with the expected energy output through an analytical determination of the coefficients of the characteristic input–output equation of the system. The proposed methodology can be used not only for energy optimization of the system in the design phase but also for evaluation of test results of an existing system in order to improve it further.

Age, growth and mortality of Serranus cabrilla (Linnaeus, 1758) on the Cretan shelf

The population dynamics of comber, Serranus cabrilla on the Cretan shelf was studied to estimate age, growth, mortality and exploitation rate of the stock. Annuli on otoliths indicated the presence of five age classes. Marginal increment analysis performed for ages 1–3 showed that the annulus is formed from April to June. Growth was well described by both the standard and the seasonalised von Bertalanffy growth models. The computed growth parameters were: (a) L ∞=222.93, k=0.39 and t 0=−0.59 for the standard model, and (b) L ∞=223.89, k=0.38, t 0=−0.53, C=1 and WP=0.25 for the seasonalised one. Mortality parameters were estimated by means of catch curve analysis and an empirical formula. A simple simulation approach has been introduced to examine the sensitivity of mortality estimates to variations in the growth parameters. Our results suggest that the annual total mortality rate is probably between 1.1 and 1.5 and the exploitation rate is around 0.7.

Applying Simple Geostatistical Techniques to a Routine Production Geology Problem--A Case Study: ABSTRACT

A production geology reservoir description was shown to represent poorly the known dynamic reservoir behavior. The permeability field was originally generated from a general porosity-permeability law applied to a contoured porosity field. This resulted in unrealistically high permeability values in some layers and early water breakthrough in flow simulations. Furthermore, known well values of permeability were not honored. To improve the model, a geostatistical approach was used. The first step involved the use of a porosity-permeability law based on total layer porosity values. That is, with no cutoff applied, thereby allowing obtainment of values of k closer to the known reservoir values. This alone produces a permeability field, which although better represents the absolute permeability values is still too smooth-preferential pathways occurring as artifacts of contouring. A second step, therefore, involves the [open quotes]unsmoothing[close quotes] of the permeability field. At each point of the permeability field the permeability values are resampled from a distribution centered around the original value. This is a form of Monte-Carlo replacement, conditioned to well data and honoring the original trend to the data. In this case no correlation was included due to lack of information. This simple Gaussian simulation approach provides multiple realizations based onmore » deterministic information. The advantages are clear, more realistic images (no artificial pathways), improved match of water breakthrough, and the honoring of all deterministic data (wells and trend). A subsequent step was the incorporation of further [open quotes]soft[close quotes] information. Geological analysis suggested that there was a degradation of reservoir properties along the east-west axis. This new information was rapidly assimilated into the model to produce final images of the reservoir.« less

Effect of System Uncertainty on Control of Seismic‐Excited Buildings

A sensitivity study is conducted to investigate the effect of uncertainties in system identification on the performance of the active control system for seismic‐excited buildings. Four control algorithms feasible for applications to seismic‐excited buildings have been examined, including the linear quadratic optimal control algorithm and three instantaneous optimal control algorithms. A simple simulation approach is used for the sensitivity analysis. Both the active tendon control system and the active mass damper system have been considered. Numerical examples are worked out to illustrate the effect of uncertainties in identifying stiffnesses and dampings on the active control system. The effect of parametric uncertainties on the performance of active control systems for seismic‐excited buildings depends on the particular control algorithm used. It is demonstrated that, while dampings of structures are difficult to identify, the accuracy of damping estimation has a negligible effect on the performance of the control system. For some control algorithms, however, care should be taken to estimate the structural stiffness.

Combine speed strategies in cereal harvesting. Part 2: Adjustment for weather variability

Existing models of cereal harvesting have derived a common optimum combine speed for every harvesting day on a particular farm. This study is an assessment of the economic benefits of selecting a different speed for each day of the harvest, taking into account the history of previous weather. Both a simple simulation approach, and a dynamic-stochastic programming approach which incorporates a forecast of future work-days, have been developed. Overall, the results showed small benefits from a strategy based on a selected daily speed compared with single constant speed operation, when averaged out over a number of years. However, substantial benefits were shown in the occasional very wet harvests, when combining could take place on only a small number of days, and in some other exceptional situations.