STI-GMaS : an open-source environment for simulation of sexually-transmitted infections

Background Sexually-transmitted pathogens often have severe reproductive health implications if treatment is delayed or absent, especially in females. The complex processes of disease progression, namely replication and ascension of the infection through the genital tract, span both extracellular and intracellular physiological scales, and in females can vary over the distinct phases of the menstrual cycle. The complexity of these processes, coupled with the common impossibility of obtaining comprehensive and sequential clinical data from individual human patients, makes mathematical and computational modelling valuable tools in developing our understanding of the infection, with a view to identifying new interventions. While many within-host models of sexually-transmitted infections (STIs) are available in existing literature, these models are difficult to deploy in clinical/experimental settings since simulations often require complex computational approaches. Results We present STI-GMaS (Sexually-Transmitted Infections – Graphical Modelling and Simulation), an environment for simulation of STI models, with a view to stimulating the uptake of these models within the laboratory or clinic. The software currently focuses upon the representative case-study of Chlamydia trachomatis, the most common sexually-transmitted bacterial pathogen of humans. Here, we demonstrate the use of a hybrid PDE–cellular automata model for simulation of a hypothetical Chlamydia vaccination, demonstrating the effect of a vaccine-induced antibody in preventing the infection from ascending to above the cervix. This example illustrates the ease with which existing models can be adapted to describe new studies, and its careful parameterisation within STI-GMaS facilitates future tuning to experimental data as they arise. Conclusions STI-GMaS represents the first software designed explicitly for in-silico simulation of STI models by non-theoreticians, thus presenting a novel route to bridging the gap between computational and clinical/experimental disciplines. With the propensity for model reuse and extension, there is much scope within STI-GMaS to allow clinical and experimental studies to inform model inputs and drive future model development. Many of the modelling paradigms and software design principles deployed to date transfer readily to other STIs, both bacterial and viral; forthcoming releases of STI-GMaS will extend the software to incorporate a more diverse range of infections.

Automatic inference of driving task demand from visual cues of emotion and attention

Sensing the mental, physical and emotional demand of a driving task is of primary importance in road safety research and for effectively designing in-vehicle information systems (IVIS). Particularly, the need of cars capable of sensing and reacting to the emotional state of the driver has been repeatedly advocated in the literature. Algorithms and sensors to identify patterns of human behavior, such as gestures, speech, eye gaze and facial expression, are becoming available by using low cost hardware: This paper presents a new system which uses surrogate measures such as facial expression (emotion) and head pose and movements (intention) to infer task difficulty in a driving situation. 11 drivers were recruited and observed in a simulated driving task that involved several pre-programmed events aimed at eliciting emotive reactions, such as being stuck behind slower vehicles, intersections and roundabouts, and potentially dangerous situations. The resulting system, combining face expressions and head pose classification, is capable of recognizing dangerous events (such as crashes and near misses) and stressful situations (e.g. intersections and way giving) that occur during the simulated drive.

Intercalation of dodecylamine into kaolinite and its layering structure investigated by molecular dynamics simulation

Dodecylamine was successfully intercalated into the layer space of kaolinite by utilizing the methanol treated kaolinite–dimethyl sulfoxide (DMSO) intercalation complex as an intermediate. The basal spacing of kaolinite, measured by X-ray diffraction (XRD), increased from 0.72 nm to 4.29 nm after the intercalation of dodecylamine. Also, the significant variation observed in the Fourier Transform Infrared Spectroscopy (FTIR) spectra of kaolinite when intercalated with dodecylamine verified the feasibility of intercalation of dodecylamine into kaolinite. Isothermal-isobaric (NPT) molecular dynamics simulation with the use of Dreiding force field was performed to probe into the layering behavior and structure of nanoconfined dodecylamine in the kaolinite gallery. The concentration profiles of the nitrogen atom, methyl group and methylene group of intercalated dodecylamine molecules in the direction perpendicular to the kaolinite basal surface indicated that the alkyl chains within the interlayer space of kaolinite exhibited an obvious layering structure. However, the unified bilayer, pseudo-trilayer, or paraffin-type arrangements of alkyl chains deduced based on their chain length combined with the measured basal spacing of organoclays were not found in this study. The alkyl chains aggregated to a mixture of ordered paraffin-type-like structure and disordered gauche conformation in the middle interlayer space of kaolinite, and some alkyl chains arranged in two bilayer structures, in which one was close to the silica tetrahedron surface, and the other was close to the alumina octahedron surface with their alkyl chains parallel to the kaolinite basal surface.

Two dynamic discrete choice estimation problems and simulation method solutions

This paper considers two problems that frequently arise in dynamic discrete choice problems but have not received much attention with regard to simulation methods. The first problem is how to simulate unbiased simulators of probabilities conditional on past history. The second is simulating a discrete transition probability model when the underlying dependent variable is really continuous. Both methods work well relative to reasonable alternatives in the application discussed. However, in both cases, for this application, simpler methods also provide reasonably good results.

Simulation-based estimation

In this paper, I present a number of leading examples in the empirical literature that use simulation-based estimation methods. For each example, I describe the model, why simulation is needed, and how to simulate the relevant object. There is a section on simulation methods and another on simulations-based estimation methods. The paper concludes by considering the significance of each of the examples discussed a commenting on potential future areas of interest.

Idealised simulation of downburst winds

Convectively driven downburst winds pose a threat to structures and communities in many regions of Australia not subject to tropical cyclones. Extreme value analysis shows that for return periods of interest to engineering design these events produce higher gust wind speeds than synoptic scale windstorms. Despite this, comparatively little is known of the near ground wind structure of these potentially hazardous windstorms. With this in mind, a series of idealised three-dimensional numerical simulations were undertaken to investigate convective storm wind fields. A dry, non-hydrostatic, sub-cloud model with parameterisation of the microphysics was used. Simulations were run with a uniform 20 m horizontal grid resolution and a variable vertical resolution increasing from 1 m. A systematic grid resolution study showed further refinement did not alter the morphological structure of the outflow. Simulations were performed for stationary downbursts in a quiescent air field, stationary downbursts embedded within environmental boundary layer winds, and also translating downbursts embedded within environmental boundary layer winds.

CFD and experimental modelling of an impinging jet for thunderstorm downburst simulation

A thunderstorm downburst in its simplest form can be modelled as a steady flow impinging air jet. Although this simplification neglects some important atmospheric and physical parameters it has proven to be a useful tool for understanding the kinematics of these events. Assuming this simple impinging jet model also allows numerical models to be developed which can be directly compared with experimental results to validate the use of CFD. Confidence gained from these simulations will allow the use of more complex atmospheric impinging jet models that cannot be directly validated. Thunderstorm downbursts are important for wind engineers because in many parts of the world they produce the design wind speeds used in design standards, but are not structurally represented in these documents.

Self-organization in arrays of surface-grown nanoparticles : characterization, control, driving forces

Some important issues related to the self-organization in the arrays of nanoparticles on solid surfaces exposed to the low-temperature plasma are analysed and discussed. The available tools for the characterization of the size and position uniformity in nanoarrays are examined. The technique capable of revealing the realistic adsorbed atom and adsorbed radical capture zone pattern based on the surface physics is indicated as the most promising characterization tool. The processes responsible for the self-organization are analysed, the main driving forces of the self-organization are discussed, and possible ways to control the self-organization by controlling the plasma parameters are introduced. A view on the possible ways to further improve the methods of nanoarray characterization and self-organization is presented as well.

Simulation of carbon arc discharge for the synthesis of nanotubes

Arc discharge ablation with a catalyst-filled carbon anode in a helium background was used for the synthesis of graphene and carbon nanotubes. In this paper, we present the results of the numerical simulation of the distribution of various plasma parameters in discharge, as well as the distribution of carbon flux on the nanotube surface, for the typical discharge with an arc current of 60 A and a background gas pressure of 68 kPa.

Simulation and visualization of self-assembled nanodevice networks synthesized via plasma–surface interaction

Using advanced visualization techniques, a comprehensive visualization of all the stages of the self-organized growth of internetworked nanostructures on plasma-exposed surface has been made. Atomistic kinetic Monte Carlo simulation for the initial stage of deposition, with 3-D visualization of the whole system and half-tone visualization of the density field of the adsorbed atoms, makes it possible to implement a multiscale predictive modeling of the development of the nanoscale system.

Diagnostics and two-dimensional simulation of low-frequency inductively coupled plasmas with neutral gas heating and electron heat fluxes

This article presents the results on the diagnostics and numerical modeling of low-frequency (∼460 KHz) inductively coupled plasmas generated in a cylindrical metal chamber by an external flat spiral coil. Experimental data on the electron number densities and temperatures, electron energy distribution functions, and optical emission intensities of the abundant plasma species in low/intermediate pressure argon discharges are included. The spatial profiles of the plasma density, electron temperature, and excited argon species are computed, for different rf powers and working gas pressures, using the two-dimensional fluid approach. The model allows one to achieve a reasonable agreement between the computed and experimental data. The effect of the neutral gas temperature on the plasma parameters is also investigated. It is shown that neutral gas heating (at rf powers≥0.55kW) is one of the key factors that control the electron number density and temperature. The dependence of the average rf power loss, per electron-ion pair created, on the working gas pressure shows that the electron heat flux to the walls appears to be a critical factor in the total power loss in the discharge.

Tailoring the composition of self-assembled Si1−xCx quantum dots : simulation of plasma/ion-related controls

Precise control of composition and internal structure is essential for a variety of novel technological applications which require highly tailored binary quantum dots (QDs) with predictable optoelectronic and mechanical properties. The delicate balancing act between incoming flux and substrate temperature required for the growth of compositionally graded (Si1-xC x; x varies throughout the internal structure), core-multishell (discrete shells of Si and C or combinations thereof) and selected composition (x set) QDs on low-temperature plasma/ion-flux-exposed Si(100) surfaces is investigated via a hybrid numerical simulation. Incident Si and C ions lead to localized substrate heating and a reduction in surface diffusion activation energy. It is shown that by incorporating ions in the influx, a steady-state composition is reached more quickly (for selected composition QDs) and the composition gradient of a Si1-xCx QD may be fine tuned; additionally (with other deposition conditions remaining the same), larger QDs are obtained on average. It is suggested that ionizing a portion of the influx is another way to control the average size of the QDs, and ultimately, their internal structure. Advantages that can be gained by utilizing plasma/ion-related controls to facilitate the growth of highly tailored, compositionally controlled quantum dots are discussed as well.

Nanosphere monolayer-templated, ion-assisted nanofeature etching in dielectric materials : a numerical simulation of nanoscale ion flux topography

The results of numerical simulations of nanometer precision distributions of microscopic ion fluxes in ion-assisted etching of nanoscale features on the surfaces of dielectric materials using a self-assembled monolayer of spherical nanoparticles as a mask are presented. It is shown that the ion fluxes to the substrate and nanosphere surfaces can be effectively controlled by the plasma parameters and the external bias applied to the substrate. By proper adjustment of these parameters, the ion flux can be focused onto the areas uncovered by the nanospheres. Under certain conditions, the ion flux distributions feature sophisticated hexagonal patterns, which may lead to very different nanofeature etching profiles. The results presented are generic and suggest viable ways to overcome some of the limitations of the existing plasma-assisted nanolithography.