Series Of Monte-Carlo Simulations Research Articles

Comment on ``Determination of the bulk melting temperature of nickel using Monte Carlo simulations: Inaccuracy of extrapolation from cluster melting temperatures''

In a series of Monte Carlo simulations, Los and Pellenq [Phys. Rev. B 81, 064112 (2010)] determined the melting temperature of pure Ni using the thermodynamic integration method with a tight binding description of its internal energy. These authors found a melting temperature of pure Ni around 1996 \ifmmode\pm\else\textpm\fi{} 40 K, which is 268 K higher than the experimental value. It is believed that the selection of the interatomic potential used to describe the energetic behavior of Ni and the simulation procedure of Los and Pellenq are not optimal and that a higher accuracy can be obtained. The disputed points of their study are discussed in this comment.

Extending the actor–partner interdependence model for binary outcomes: A multilevel logistic approach

Relationship researchers face many challenges when samples consist of dyads. The actor–partner interdependence model provides a framework for the analysis of dyadic data (D. A. Kashy & D. A. Kenny, 2000). Binary variables like discrete health diagnoses present additional challenges that are not easily handled using existing models. The analysis was demonstrated using SAS PROC GLIMMIX and HLM6. An example is presented where couple's personality traits are used to predict discrete health outcomes. A series of Monte Carlo simulations were performed to compare PROC GLIMMIX to HLM. GLIMMIX performed acceptably compared to HLM for small dyad‐level sample sizes (100 or fewer), but HLM clearly outperformed in larger samples. Both had problems estimating the variance of the random intercept and its standard error.

Investigations of shield effect and type of soil on landmine detection

This paper investigates the possibility of optimizing the performance of the neutron backscattering method in landmine detection by designing a suitable shield around a 252Cf neutron source to reduce the background due to soil and the neutrons emitted from the source that hit the detector directly. A series of Monte Carlo simulations were performed to improve the source shield thickness and to study the elastically backscattered (EBS) 252Cf neutrons from the buried explosive material TNT in the soil; the optimal configuration was examined against different soil types and source heights. The results obtained in terms of performance of the relative (EBS) neutrons confirmed that the proposed source shield has significantly improved the signal to background ratio. Higher signal-to-background ratio was observed using 252Cf neutron source as compared to Pu–Be source.

Optimisation of temporal averaging processes in PIV

A hybrid of correlation and vector averaging is introduced to capitalise on the advantages of each process. An extensive series of Monte Carlo simulations have been conducted to investigate hybrid averaging and evaluate it against both vector and correlation averaging. The simulations show that hybrid averaging improves the measurement accuracy over both correlation and vector averaging over a wide range of imaging conditions. The simulations are validated by applying hybrid averaging to experimental micro- and macro-flows. In pulsatile conditions, correlation averaging yields an averaged correlation function that is multi-modal, which can result in unpredictable measurements. A Monte Carlo simulation shows the benefits of hybrid averaging over correlation averaging in such conditions. This has been experimentally validated on the unsteady wake behind a shedding circular cylinder at Re = 98.

Vancomycin: We Can't Get There From Here

We sought to characterize the pharmacodynamic profile of the more intensive vancomycin dosing regimens currently used in response to the recent vancomycin guidelines. A series of Monte Carlo simulations was performed for vancomycin regimens ranging from .5 g intravenous (IV) Q12H to 2 g IV Q12H. The probability of achieving an AUC/MIC ratio ≥ 400 for each dosing regimen was calculated for minimum inhibitory concentrations (MICs) from .5 to 2 mg/L. The risk of nephrotoxicity for each regimen was derived from a previously published vancomycin trough-nephrotoxicity logistic regression function. Restricted analyses were performed that only included subjects with troughs between 15 and 20 mg/L. At a MIC of 2 mg/L, even the most aggressive dosing regimen considered (2 g every 12 h) only yielded a probability of target attainment (PTA) of 57% while generating a nephrotoxicity probability upward of 35%(.) At a MIC of 1 mg/L, ≥3 g per day provided PTA in excess of 80% but were associated with unacceptable risks of nephrotoxicity. In the restricted analyses of subjects with troughs between 15 and 20 mg/L, all regimens produced a PTA of 100% at MICs ≤1 mg/L. The PTA was variable among the regimens at a MIC of 2 mg/L and was highly dependent on the total daily dose administered. This study indicates that vancomycin may not be useful for treating serious methicillin-resistant Staphylococcus aureus (MRSA) infections with MIC values > 1 mg/L where PTA is questionable. Since an AUC/MIC ratio ≥ 400 is target associated with efficacy, one should consider incorporating computation of AUC when monitoring vancomycin.

Epistatic Association Mapping in Homozygous Crop Cultivars

The genetic dissection of complex traits plays a crucial role in crop breeding. However, genetic analysis and crop breeding have heretofore been performed separately. In this study, we designed a new approach that integrates epistatic association analysis in crop cultivars with breeding by design. First, we proposed an epistatic association mapping (EAM) approach in homozygous crop cultivars. The phenotypic values of complex traits, along with molecular marker information, were used to perform EAM. In our EAM, all the main-effect quantitative trait loci (QTLs), environmental effects, QTL-by-environment interactions and QTL-by-QTL interactions were included in a full model and estimated by empirical Bayes approach. A series of Monte Carlo simulations was performed to confirm the reliability of the new method. Next, the information from all detected QTLs was used to mine novel alleles for each locus and to design elite cross combination. Finally, the new approach was adopted to dissect the genetic basis of seed length in 215 soybean cultivars obtained, by stratified random sampling, from 6 geographic ecotypes in China. As a result, 19 main-effect QTLs and 3 epistatic QTLs were identified, more than 10 novel alleles were mined and 3 elite parental combinations, such as Daqingdou and Zhengzhou790034, were predicted.

Optimal caliper widths for propensity‐score matching when estimating differences in means and differences in proportions in observational studies

In a study comparing the effects of two treatments, the propensity score is the probability of assignment to one treatment conditional on a subject's measured baseline covariates. Propensity-score matching is increasingly being used to estimate the effects of exposures using observational data. In the most common implementation of propensity-score matching, pairs of treated and untreated subjects are formed whose propensity scores differ by at most a pre-specified amount (the caliper width). There has been a little research into the optimal caliper width. We conducted an extensive series of Monte Carlo simulations to determine the optimal caliper width for estimating differences in means (for continuous outcomes) and risk differences (for binary outcomes). When estimating differences in means or risk differences, we recommend that researchers match on the logit of the propensity score using calipers of width equal to 0.2 of the standard deviation of the logit of the propensity score. When at least some of the covariates were continuous, then either this value, or one close to it, minimized the mean square error of the resultant estimated treatment effect. It also eliminated at least 98% of the bias in the crude estimator, and it resulted in confidence intervals with approximately the correct coverage rates. Furthermore, the empirical type I error rate was approximately correct. When all of the covariates were binary, then the choice of caliper width had a much smaller impact on the performance of estimation of risk differences and differences in means. Copyright © 2010 John Wiley & Sons, Ltd.

TOTAL UTILITY DEMAND PREDICTION CONSIDERING VARIATION OF OCCUPANTS' BEHAVIOR SCHEDULES APPLIED TO MULTI DWELLINGS

Following the authors' previous work, this paper describes a new methodology in calculating accurately the time series utility loads (energy, power, city water, hot water, etc.) for multi-dwelling system such as a whole residential building, residential block area, even a city by means of the so-called bottom-up approach. This calculation takes into account the behavioral variations of the dwelling inhabitants. The proposed method contains a procedure for cooling load calculations based on a series of Monte Carlo simulations where the HVAC on/off state and the indoor heat generation schedules are varied, time-step by time-step. A data set of time-varying inhabitant behavior schedules, with a 15 minute resolution, was integrated into the model. The established model, which is called the Total Utility Demand Prediction System (TUD-PS) was integrated to estimate multi dwellings system, where we can accurately argue various peak demands and seasonal or annual demands. By applying to a typical residential building, we highlight several advantages of TUD-PS.

Reconsidering the Analysis of Longitudinal Happiness Data - With an Application to the Effect of Unemployment

The paper reconsiders existing estimators for the panel data fixed effects ordered logit model, including one that has not been used in econometric studies before, and studies the small sample properties of these estimators in a series of Monte Carlo simulations. There are two main findings. First, we show that some of the estimators used in the literature are inconsistent. Second, the new estimator seems to be more immune to small sample bias than other consistent estimators and is easy to implement. The empirical relevance is illustrated in an application to the effect of unemployment on happiness. Choosing the right estimator avoids a bias of up to 30 percent in key parameters.

Consistent Estimation of the Fixed Effects Ordered Logit Model

The paper re-examines existing estimators for the panel data fixed effects ordered logit model, proposes a new one, and studies the sampling properties of these estimators in a series of Monte Carlo simulations. There are two main findings. First, we show that some of the estimators used in the literature are inconsistent, and provide reasons for the inconsistency. Second, the new estimator is never outperformed by the others, seems to be substantially more immune to small sample bias than other consistent estimators, and is easy to implement. The empirical relevance is illustrated in an application to the effect of unemployment on life satisfaction.

Multiple Trials May Yield Exaggerated Effect Size Estimates

ABSTRACT Published psychological research attempting to support the existence of small and medium effect sizes may not have enough participants to do so accurately, and thus, repeated trials or the use of multiple items may be used in an attempt to obtain significance. Through a series of Monte-Carlo simulations, this article describes the results of multiple trials or items on effect size estimates when the averages and aggregates of a dependent measure are analyzed. The simulations revealed a large increase in observed effect size estimates when the numbers of trials or items in an experiment were increased. Overestimation effects are mitigated by correlations between trials or items, but remain substantial in some cases. Some concepts, such as a P300 wave or a test score, are best defined as a composite of measures. Troubles may arise in more exploratory research where the interrelations among trials or items may not be well described.

Corruption, Voting and Employment Status: Evidence from Russian Parliamentary Elections

This paper examines to what extent the distribution of votes and voting behavior of people with different employment status are affected by regional differences in corruption. Using data from the Russian Parliamentary (State Duma) Elections 1999 and 2003, I develop and estimate a SUR system of equations which takes into account specific features of the Russian electoral system. The paper distinguishes between hard and perceived measures of corruption and analyzes the effects of corruption on the voting shares of particular parties and on voters’ participation in elections. Additionally, a series of Monte Carlo simulations are performed to analyze the effects of corruption on the distribution of votes.

Photogrammetric and spatial analysis of a bioeroded Early Miocene rocky shore, western Portugal

A method for systematically acquiring and analyzing images of Miocene bivalve borings (Gastrochaenolites lapidicus and Gastrochaenolitestorpedo) is applied for analysis of spatial patterns in Foz da Fonte (Sesimbra, Portugal). Space point pattern analysis is used to describe patterns of locations of fossils and to test whether there is a significant occurrence of clustering in the study area. Emphasis is placed in close-range photogrammetry methods for data acquisition and spatial statistics for data analysis. Thresholds for the occurrence of clustering at various scales of observation were computed based on a series of Monte Carlo simulations of random spatial point patterns. Goals of the analysis are focused on the statistical description of the borers population, the investigation of some spatial relationship among G. lapidicus of different dimensions and, finally, the investigation of a preferential orientation of the G. torpedo in order to draw paleogeographic and paleoenvironmental conclusions. Both G. lapidicus and G.torpedo were significantly clustered during life of the borers. The preferential cluster location of different diameter classes of G. lapidicus indicates the relative location and orientation of the paleoshore. G. torpedo populations show preferential orientations interpreted as being perpendicular to the predominant swell moving direction during a Middle Burdigalian transgression, around 18 My ago.

Scaling Usability in Terms of Requirements: A Method for Evaluating User Interfaces

Software usability should be scaled in terms of the probability that a user interface will meet established usability requirements. This paper describes a scaling procedure that first estimates the distribution of common usability metrics and then calculates the probability that a user interface will meet a specific requirement. A series of Monte Carlo simulations showed that even with a small sample of usability test participants, the scaling procedure remained unbiased and could accurately differentiate usable from unusable user interfaces.

Compton Scattering in Clinical PET/CT With High Resolution Half Ring PET Insert Device

The integration of a high resolution PET insert into a conventional PET system can significantly improve the resolution and the contrast of its images within a reduced imaging field of view. For the rest of the scanner imaging field of view, the insert is a highly attenuating and scattering media. In order to use all available coincidence events (including coincidences between 2 detectors in the original scanner, namely the scanner-scanner coincidences), appropriate scatter and attenuation corrections have to be implemented. In this work, we conducted a series of Monte Carlo simulations to estimate the composition of the scattering background and the importance of the scatter correction. We implemented and tested the Single Scatter Simulation (SSS) algorithm for a hypothetical system and show good agreement between the estimated scatter using SSS and Monte Carlo simulated scatter contribution. We further applied the SSS to estimate scatter contribution from an existing prototype PET insert for a clinical PET/CT scanner. The results demonstrated the applicability of SSS to estimate the scatter contribution within a clinical PET/CT system even when there is a high resolution half ring PET insert device in its imaging field of view.

Total utility demand prediction system for dwellings based on stochastic processes of actual inhabitants

This article describes a new methodology to calculate the likely utility load profiles (energy such as power, natural gas, space heating and cooling, and other thermal requirements, as well as city water) in a dwelling. This calculation takes into account the behavioural variations of the dwelling inhabitants. The proposed method contains a procedure for cooling load calculations based on a series of Monte Carlo simulations where the heating, ventilating and air conditioning (HVAC) on/off state and the indoor heat generation schedules are varied, time-step by time-step. A data set of time-varying inhabitant behaviour schedules, with a 15-min resolution, generated by the authors in previous studies and validated by a comparison analysis to several field measurement data sets, was integrated into the model. The established model, which is called the total utility demand prediction system, can be applied to, for example, likely estimation of an integrated space maximum requirement, such as the total load of a building or an urban area. In a series of numerical experiments, huge discrepancies were found between the conventional results and those considering the time-varying inhabitant behaviour schedules. In particular, deriving the dynamic state change, of having the HVAC on/off from the inhabitants' schedules, was found to be a significant factor in the maximum cooling and heating loads.

Determining the Absolute Abundances of Natural Radioactive Elements on the Lunar Surface by the Kaguya Gamma-ray Spectrometer

The Kaguya gamma-ray spectrometer (KGRS) has great potential to precisely determine the absolute abundances of natural radioactive elements K, Th and U on the lunar surface because of its excellent spectroscopic performance. In order to achieve the best performance of the KGRS, it is important to know the spatial response function (SRF) that describes the directional sensitivity of the KGRS. The SRF is derived by a series of Monte Carlo simulations of gamma-ray transport in the sensor of the KGRS using the full-fledged simulation model of the KGRS, and is studied in detail. In this paper, the method for deriving absolute abundance of natural radioactive elements based on the SRF is described for the analysis of KGRS data, which is also applicable to any gamma-ray remote sensings. In the preliminary analysis of KGRS data, we determined the absolute abundances of K and Th on the lunar surface without using any previous knowledge of chemical information gained from Apollo samples, lunar meteorites and/or previous lunar remote sensings. The results are compared with the previous measurements and the difference and the correspondence are discussed. Future detailed analysis of KGRS data will provide new and more precise maps of K, Th and U on the lunar surface.

The cost-effectiveness of directly observed highly-active antiretroviral therapy in the third trimester in HIV-infected pregnant women.

BackgroundIn HIV-infected pregnant women, viral suppression prevents mother-to-child HIV transmission. Directly observed highly-active antiretroviral therapy (HAART) enhances virological suppression, and could prevent transmission. Our objective was to project the effectiveness and cost-effectiveness of directly observed administration of antiretroviral drugs in pregnancy.Methods and FindingsA mathematical model was created to simulate cohorts of one million asymptomatic HIV-infected pregnant women on HAART, with women randomly assigned self-administered or directly observed antiretroviral therapy (DOT), or no HAART, in a series of Monte Carlo simulations. Our primary outcome was the quality-adjusted life expectancy in years (QALY) of infants born to HIV-infected women, with the rates of Caesarean section and HIV-transmission after DOT use as intermediate outcomes. Both self-administered HAART and DOT were associated with decreased costs and increased life-expectancy relative to no HAART. The use of DOT was associated with a relative risk of HIV transmission of 0.39 relative to conventional HAART; was highly cost-effective in the cohort as a whole (cost-utility ratio $14,233 per QALY); and was cost-saving in women whose viral loads on self-administered HAART would have exceeded 1000 copies/ml. Results were stable in wide-ranging sensitivity analyses, with directly observed therapy cost-saving or highly cost-effective in almost all cases.ConclusionsBased on the best available data, programs that optimize adherence to HAART through direct observation in pregnancy have the potential to diminish mother-to-child HIV transmission in a highly cost-effective manner. Targeted use of DOT in pregnant women with high viral loads, who could otherwise receive self-administered HAART would be a cost-saving intervention. These projections should be tested with randomized clinical trials.

Firm and industry level profit efficiency analysis using absolute and uniform shadow prices

We discuss the nonparametric approach to profit efficiency analysis at the firm and industry levels in the absence of complete price information. Two new insights are developed. First, we measure profit inefficiency in monetary terms using absolute shadow prices. Second, we evaluate all firms using the same input-output prices. This allows us to aggregate firm-level profit inefficiencies to the overall industry inefficiency. Besides the measurement of profit losses, the presented approach enables one to recover absolute price information from quantity data. We conduct a series of Monte Carlo simulations to study the performance of the proposed approach in controlled production environments.

Investigating the Impact of Selection Bias in Dose-Response Analyses of Preventive Interventions

This paper focuses on the impact of selection bias in the context of extended, community-based prevention trials that attempt to "unpack" intervention effects and analyze mechanisms of change. Relying on dose-response analyses as the most general form of such efforts, this study provides two examples of how selection bias can affect the estimation of treatment effects. In Example 1, we describe an actual intervention in which selection bias was believed to influence the dose-response relation of an adaptive component in a preventive intervention for young children with severe behavior problems. In Example 2, we conduct a series of Monte Carlo simulations to illustrate just how severely selection bias can affect estimates in a dose-response analysis when the factors that affect dose are not recorded. We also assess the extent to which selection bias is ameliorated by the use of pretreatment covariates. We examine the implications of these examples and review trial design, data collection, and data analysis factors that can reduce selection bias in efforts to understand how preventive interventions have the effects they do.