Pulsed i-PVD of dielectric nanodot arrays using a nanoporous template

The results of multi-scale numerical simulations of pulsed i-PVD template-assisted nanofabrication of ZnO nanodot arrays on a silicon substrate are presented. The ratios and spatial distributions of the ion fluxes deposited on the lateral and bottom surfaces of the nanopores are computed as a function of the external bias and plasma parameters. The results show that the pulsed bias plays a significant role in the ion current distribution inside the nanopores. The results of numerical experiments of this work suggest that by finely adjusting the pulse voltage, the pulse duration and the duty cycle of the external pulsed bias, the nanopore clogging can be successfully avoided during the deposition and the shapes of the deposited ZnO nanodots can be effectively controlled. A figure is presented.

Plasma-deposited Ge nanoisland films on Si : is Stranski–Krastanow fragmentation unavoidable?

The formation of Ge quantum dot arrays by deposition from a low-temperature plasma environment is investigated by kinetic Monte Carlo numerical simulation. It is demonstrated that balancing of the Ge influx from the plasma against surface diffusion provides an effective control of the surface processes and can result in the formation of very small densely packed quantum dots. In the supply-controlled mode, a continuous layer is formed which is then followed by the usual Stranski-Krastanow fragmentation with a nanocluster size of 10 nm. In the diffusion-controlled mode, with the oversupply relative to the surface diffusion rate, nanoclusters with a characteristic size of 3 nm are formed. Higher temperatures change the mode to supply controlled and thus encourage formation of the continuous layer that then fragments into an array of large size. The use of a high rate of deposition, easily accessible using plasma techniques, changes the mode to diffusion controlled and thus encourages formation of a dense array of small nanoislands.

Growth of carbon nanocone arrays on a metal catalyst: The effect of carbon flux ionization

The growth of carbon nanocone arrays on metal catalyst particles by deposition from a low-temperature plasma is studied by multiscale Monte Carlo/surface diffusion numerical simulation. It is demonstrated that the variation in the degree of ionization of the carbon flux provides an effective control of the growth kinetics of the carbon nanocones, and leads to the formation of more uniform arrays of nanostructures. In the case of zero degree of ionization (neutral gas process), a width of the distribution of nanocone heights reaches 360 nm with the nanocone mean height of 150 nm. When the carbon flux of 75% ionization is used, the width of the distribution of nanocone heights decreases to 100 nm, i.e., by a factor of 3.6. A higher degree of ionization leads to a better uniformity of the metal catalyst saturation and the nanocone growth, thus contributing to the formation of more height-uniform arrays of carbon nanostructures.

A review of modern computational algorithms for Bayesian optimal design

Bayesian experimental design is a fast growing area of research with many real-world applications. As computational power has increased over the years, so has the development of simulation-based design methods, which involve a number of algorithms, such as Markov chain Monte Carlo, sequential Monte Carlo and approximate Bayes methods, facilitating more complex design problems to be solved. The Bayesian framework provides a unified approach for incorporating prior information and/or uncertainties regarding the statistical model with a utility function which describes the experimental aims. In this paper, we provide a general overview on the concepts involved in Bayesian experimental design, and focus on describing some of the more commonly used Bayesian utility functions and methods for their estimation, as well as a number of algorithms that are used to search over the design space to find the Bayesian optimal design. We also discuss other computational strategies for further research in Bayesian optimal design.

Bayesian hierarchical models for analysing spatial point-based data at a grid level: A comparison of approaches

Spatial data are now prevalent in a wide range of fields including environmental and health science. This has led to the development of a range of approaches for analysing patterns in these data. In this paper, we compare several Bayesian hierarchical models for analysing point-based data based on the discretization of the study region, resulting in grid-based spatial data. The approaches considered include two parametric models and a semiparametric model. We highlight the methodology and computation for each approach. Two simulation studies are undertaken to compare the performance of these models for various structures of simulated point-based data which resemble environmental data. A case study of a real dataset is also conducted to demonstrate a practical application of the modelling approaches. Goodness-of-fit statistics are computed to compare estimates of the intensity functions. The deviance information criterion is also considered as an alternative model evaluation criterion. The results suggest that the adaptive Gaussian Markov random field model performs well for highly sparse point-based data where there are large variations or clustering across the space; whereas the discretized log Gaussian Cox process produces good fit in dense and clustered point-based data. One should generally consider the nature and structure of the point-based data in order to choose the appropriate method in modelling a discretized spatial point-based data.

An experimental approach to air gap optimisation for a correction-less small field diode

Aim A recent Monte Carlo based study has shown that it is possible to design a diode that measures small field output factors equivalent to that in water. This is accomplished by placing an appropriate sized air gap above the silicon chip (1) with experimental results subsequently confirming that a particular Monte Carlo design was accurate (2). The aim of this work was to test if a new correction-less diode could be designed using an entirely experimental methodology. Method: All measurements were performed on a Varian iX at a depth of 5 cm, SSD of 95 cm and field sizes of 5, 6, 8, 10, 20 and 30 mm. Firstly, the experimental transfer of kq,clin,kq,msr from a commonly used diode detector (IBA, stereotactic field diode (SFD)) to another diode detector (Sun Nuclear, unshielded diode, (EDGEe)) was tested. These results were compared to Monte Carlo calculated values of the EDGEe. Secondly, the air gap above the EDGEe silicon chip was optimised empirically. Nine different air gap “tops” were placed above the EDGEe (air depth = 0.3, 0.6, 0.9 mm; air width = 3.06, 4.59, 6.13 mm). The sensitivity of the EDGEe was plotted as a function of air gap thickness for the field sizes measured. Results: The transfer of kq,clin,kq,msr from the SFD to the EDGEe was correct to within the simulation and measurement uncertainties. The EDGEe detector can be made “correction-less” for field sizes of 5 and 6 mm, but was ∼2% from being “correction-less” at field sizes of 8 and 10 mm. Conclusion Different materials will perturb small fields in different ways. A detector is only “correction-less” if all these perturbations happen to cancel out. Designing a “correction-less” diode is a complicated process, thus it is reasonable to expect that Monte Carlo simulations should play an important role.

Approximate Bayesian Computation for astronomical model analysis : a case study in galaxy demographics and morphological transformation at high redshift

Approximate Bayesian Computation’ (ABC) represents a powerful methodology for the analysis of complex stochastic systems for which the likelihood of the observed data under an arbitrary set of input parameters may be entirely intractable – the latter condition rendering useless the standard machinery of tractable likelihood-based, Bayesian statistical inference [e.g. conventional Markov chain Monte Carlo (MCMC) simulation]. In this paper, we demonstrate the potential of ABC for astronomical model analysis by application to a case study in the morphological transformation of high-redshift galaxies. To this end, we develop, first, a stochastic model for the competing processes of merging and secular evolution in the early Universe, and secondly, through an ABC-based comparison against the observed demographics of massive (Mgal > 1011 M⊙) galaxies (at 1.5 < z < 3) in the Cosmic Assembly Near-IR Deep Extragalatic Legacy Survey (CANDELS)/Extended Groth Strip (EGS) data set we derive posterior probability densities for the key parameters of this model. The ‘Sequential Monte Carlo’ implementation of ABC exhibited herein, featuring both a self-generating target sequence and self-refining MCMC kernel, is amongst the most efficient of contemporary approaches to this important statistical algorithm. We highlight as well through our chosen case study the value of careful summary statistic selection, and demonstrate two modern strategies for assessment and optimization in this regard. Ultimately, our ABC analysis of the high-redshift morphological mix returns tight constraints on the evolving merger rate in the early Universe and favours major merging (with disc survival or rapid reformation) over secular evolution as the mechanism most responsible for building up the first generation of bulges in early-type discs.

Estimating the burden of disease attributable to excess body weight in South Africa in 2000

Objective. To estimate the burden of disease attributable to excess body weight using the body mass index (BMI), by age and sex, in South Africa in 2000. Design. World Health Organization comparative risk assessment (CRA) methodology was followed. Re-analysis of the 1998 South Africa Demographic and Health Survey data provided mean BMI estimates by age and sex. Populationattributable fractions were calculated and applied to revised burden of disease estimates. Monte Carlo simulation-modelling techniques were used for the uncertainty analysis. Setting. South Africa. Subjects. Adults 30 years of age. Outcome measures. Deaths and disability-adjusted life years (DALYs) from ischaemic heart disease, ischaemic stroke, hypertensive disease, osteoarthritis, type 2 diabetes mellitus, and selected cancers. Results. Overall, 87% of type 2 diabetes, 68% of hypertensive disease, 61% of endometrial cancer, 45% of ischaemic stroke, 38% of ischaemic heart disease, 31% of kidney cancer, 24% of osteoarthritis, 17% of colon cancer, and 13% of postmenopausal breast cancer were attributable to a BMI 21 kg/m2. Excess body weight is estimated to have caused 36 504 deaths (95% uncertainty interval 31 018 - 38 637) or 7% (95% uncertainty interval 6.0 - 7.4%) of all deaths in 2000, and 462 338 DALYs (95% uncertainty interval 396 512 - 478 847) or 2.9% of all DALYs (95% uncertainty interval 2.4 - 3.0%). The burden in females was approximately double that in males. Conclusions. This study shows the importance of recognising excess body weight as a major risk to health, particularly among females, highlighting the need to develop, implement and evaluate comprehensive interventions to achieve lasting change in the determinants and impact of excess body weight.

Estimating the burden of disease attributable to physical inactivity in South Africa in 2000

Objectives. To quantify the burden of disease attributable to physical inactivity in persons 15 years or older, by age group and sex, in South Africa for 2000. Design. The global comparative risk assessment (CRA) methodology of the World Health Organization was followed to estimate the disease burden attributable to physical inactivity. Levels of physical activity for South Africa were obtained from the World Health Survey 2003. A theoretical minimum risk exposure of zero, associated outcomes, relative risks, and revised burden of disease estimates were used to calculate population-attributable fractions and the burden attributed to physical inactivity. Monte Carlo simulation-modelling techniques were used for the uncertainty analysis. Setting. South Africa. Subjects. Adults ≥ 15 years. Outcome measures. Deaths and disability-adjusted life years (DALYs) from ischaemic heart disease, ischaemic stroke, breast cancer, colon cancer, and type 2 diabetes mellitus. Results. Overall in adults ≥ 15 years in 2000, 30% of ischaemic heart disease, 27% of colon cancer, 22% of ischaemic stroke, 20% of type 2 diabetes, and 17% of breast cancer were attributable to physical inactivity. Physical inactivity was estimated to have caused 17 037 (95% uncertainty interval 11 394 - 20 407), or 3.3% (95% uncertainty interval 2.2 - 3.9%) of all deaths in 2000, and 176 252 (95% uncertainty interval 133 733 - 203 628) DALYs, or 1.1% (95% uncertainty interval 0.8 - 1.3%) of all DALYs in 2000. Conclusions. Compared with other regions and the global average, South African adults have a particularly high prevalence of physical inactivity. In terms of attributable deaths, physical inactivity ranked 9th compared with other risk factors, and 12th in terms of DALYs. There is a clear need to assess why South Africans are particularly inactive, and to ensure that physical activity/inactivity is addressed as a national health priority.

Estimating the burden of disease attributable to four selected environmental risk factors in South Africa

INTRODUCTION: The first South African National Burden of Disease study quantified the underlying causes of premature mortality and morbidity experienced in South Africa in the year 2000. This was followed by a Comparative Risk Assessment to estimate the contributions of 17 selected risk factors to burden of disease in South Africa. This paper describes the health impact of exposure to four selected environmental risk factors: unsafe water, sanitation and hygiene; indoor air pollution from household use of solid fuels; urban outdoor air pollution and lead exposure. METHODS: The study followed World Health Organization comparative risk assessment methodology. Population-attributable fractions were calculated and applied to revised burden of disease estimates (deaths and disability adjusted life years, [DALYs]) from the South African Burden of Disease study to obtain the attributable burden for each selected risk factor. The burden attributable to the joint effect of the four environmental risk factors was also estimated taking into account competing risks and common pathways. Monte Carlo simulation-modeling techniques were used to quantify sampling, uncertainty. RESULTS: Almost 24 000 deaths were attributable to the joint effect of these four environmental risk factors, accounting for 4.6% (95% uncertainty interval 3.8-5.3%) of all deaths in South Africa in 2000. Overall the burden due to these environmental risks was equivalent to 3.7% (95% uncertainty interval 3.4-4.0%) of the total disease burden for South Africa, with unsafe water sanitation and hygiene the main contributor to joint burden. The joint attributable burden was especially high in children under 5 years of age, accounting for 10.8% of total deaths in this age group and 9.7% of burden of disease. CONCLUSION: This study highlights the public health impact of exposure to environmental risks and the significant burden of preventable disease attributable to exposure to these four major environmental risk factors in South Africa. Evidence-based policies and programs must be developed and implemented to address these risk factors at individual, household, and community levels.

Estimating the burden of disease attributable to high cholesterol in South Africa in 2000

Objectives To estimate the burden of disease attributable to high cholesterol in adults aged 30 years and older in South Africa in 2000. Design World Health Organization comparative risk assessment (CRA) methodology was followed. Small community studies were used to derive the prevalence by population group. Population-attributable fractions were calculated and applied to revised burden of disease estimates for the relevant disease categories for each population group. The total attributable burden for South Africa in 2000 was obtained by adding the burden attributed to high cholesterol for the four population groups. Monte Carlo simulation-modelling techniques were used for uncertainty analysis. Setting South Africa. Subjects Black African, coloured, white and Indian adults aged 30 years and older. Outcome measures Mortality and disability-adjusted life years (DALYs) from ischaemic heart disease (IHD) and ischaemic stroke. Results Overall, about 59% of IHD and 29% of ischaemic stroke burden in adult males and females (30+ years) were attributable to high cholesterol (≥ 3.8 mmol/l), with marked variation by population group. High cholesterol was estimated to have caused 24 144 deaths (95% uncertainty interval 22 404 - 25 286) or 4.6% (95% uncertainty interval 4.3 - 4.9%) of all deaths in South Africa in 2000. Since most cholesterol-related cardiovascular disease events occurred in middle or old age, the loss of life years comprised a smaller proportion of the total: 222 923 DALYs (95% uncertainty interval 206 712 - 233 460) or 1.4% of all DALYs (95% uncertainty interval 1.3 - 1.4%) in South Africa in 2000. Conclusions High cholesterol is an important cardiovascular risk factor in all population groups in South Africa.

Estimating the burden of disease attributable to high blood pressure in South Africa in 2000

Objectives To estimate the burden of disease attributable to high blood pressure (BP) in adults aged 30 years and older in South Africa in 2000. Design World Health Organization comparative risk assessment (CRA) methodology was followed. Mean systolic BP (SBP) estimates by age and sex were obtained from the 1998 South African Demographic and Health Survey adult data. Population-attributable fractions were calculated and applied to revised burden of disease estimates for the relevant disease categories for South Africa in 2000. Monte Carlo simulation modelling techniques were used for uncertainty analysis. Setting South Africa Subjects Adults aged 30 years and older. Outcome measures Mortality and disability-adjusted life years (DALYs) from ischaemic heart disease (IHD), stroke, hypertensive disease and other cardiovascular disease (CVD). Results High BP was estimated to have caused 46 888 deaths (95% uncertainty interval 44 878 - 48 566) or 9% (95% uncertainty interval 8.6 - 9.3%) of all deaths in South Africa in 2000, and 390 860 DALYs (95% uncertainty interval 377 955 - 402 256) or 2.4% of all DALYs (95% uncertainty interval 2.3 - 2.5%) in South Africa in 2000. Overall, 50% of stroke, 42% of IHD, 72% of hypertensive disease and 22% of other CVD burden in adult males and females (30+ years) were attributable to high BP (systolic BP ≥ 115 mmHg). Conclusions High BP contributes to a considerable burden of CVD in South Africa and results indicate that there is considerable potential for health gain from implementing BP-lowering interventions that are known to be highly costeffective.

Estimating the burden of disease attributable to lead exposure in South Africa in 2000

Objectives To estimate the burden of disease attributable to lead exposure in South Africa in 2000. Design World Health Organization comparative risk assessment (CRA) methodology was followed. Recent community studies were used to derive mean blood lead concentrations in adults and children in urban and rural areas. Population-attributable fractions were calculated and applied to revised burden of disease estimates for the relevant disease categories for South Africa in the year 2000. Monte Carlo simulation-modelling techniques were used for the uncertainty analysis. Setting South Africa. Subjects Children under 5 and adults 30 years and older. Outcome measures Cardiovascular mortality and disability-adjusted life years (DALYs) in adults 30 years and older and mild mental disability DALYs in children under 5 years. Results Lead exposure was estimated to cause 1 428 deaths (95% uncertainty interval 1 086-1 772) or 0.27% (95% uncertainty interval: 0.21 - 0.34%) of all deaths in South Africa in 2000. Burden of disease attributed to lead exposure was dominated by mild mental disability in young children, accounting for 75% of the total 58 939 (95% uncertainty interval 55 413 - 62 500) attributable DALYs. Cardiovascular disease in adults accounted for the remainder of the burden. Conclusions Even with the phasing out of leaded petrol, exposure to lead from its ongoing addition to paint, paraoccupational exposure and its use in backyard 'cottage industries' will continue to be an important public health hazard in South Africa for decades. Young children, especially those from disadvantaged communities, remain particularly vulnerable to lead exposure and poisoning.

Clinical use of diodes and micro-chambers to obtain accurate small field output factor measurements

There have been substantial advances in small field dosimetry techniques and technologies, over the last decade, which have dramatically improved the achievable accuracy of small field dose measurements. This educational note aims to help radiation oncology medical physicists to apply some of these advances in clinical practice. The evaluation of a set of small field output factors (total scatter factors) is used to exemplify a detailed measurement and simulation procedure and as a basis for discussing the possible effects of simplifying that procedure. Field output factors were measured with an unshielded diode and a micro-ionisation chamber, at the centre of a set of square fields defined by a micro-multileaf collimator. Nominal field sizes investigated ranged from 6×6 to 98×98 mm2. Diode measurements in fields smaller than 30 mm across were corrected using response factors calculated using Monte Carlo simulations of the full diode geometry and daisy-chained to match micro-chamber measurements at intermediate field sizes. Diode measurements in fields smaller than 15 mm across were repeated twelve times over three separate measurement sessions, to evaluate the to evaluate the reproducibility of the radiation field size and its correspondence with the nominal field size. The five readings that contributed to each measurement on each day varied by up to 0.26%, for the “very small” fields smaller than 15 mm, and 0.18% for the fields larger than 15 mm. The diode response factors calculated for the unshielded diode agreed with previously published results, within 1.6%. The measured dimensions of the very small fields differed by up to 0.3 mm, across the different measurement sessions, contributing an uncertainty of up to 1.2% to the very small field output factors. The overall uncertainties in the field output factors were 1.8% for the very small fields and 1.1% for the fields larger than 15 mm across. Recommended steps for acquiring small field output factor measurements for use in radiotherapy treatment planning system beam configuration data are provided.

An efficient DSE using conditional multivariate complex Gaussian distribution

This paper presents an efficient noniterative method for distribution state estimation using conditional multivariate complex Gaussian distribution (CMCGD). In the proposed method, the mean and standard deviation (SD) of the state variables is obtained in one step considering load uncertainties, measurement errors, and load correlations. In this method, first the bus voltages, branch currents, and injection currents are represented by MCGD using direct load flow and a linear transformation. Then, the mean and SD of bus voltages, or other states, are calculated using CMCGD and estimation of variance method. The mean and SD of pseudo measurements, as well as spatial correlations between pseudo measurements, are modeled based on the historical data for different levels of load duration curve. The proposed method can handle load uncertainties without using time-consuming approaches such as Monte Carlo. Simulation results of two case studies, six-bus, and a realistic 747-bus distribution network show the effectiveness of the proposed method in terms of speed, accuracy, and quality against the conventional approach.