Modelling colloids with Baxter's adhesive hard sphere model

The structure of the Baxter adhesive hard sphere fluid is examined using computer simulation. The radial distribution function (which exhibits unusual discontinuities due to the particle adhesion) and static structure factor are calculated with high accuracy over a range of conditions and compared with the predictions of Percus--Yevick theory. We comment on rigidity in percolating clusters and discuss the role of the model in the context of experiments on colloidal systems with short-range attractive forces.Comment: 14 pages, 7 figures. (For proceedings of "Structural arrest in colloidal systems with short-range attractive forces", Messina, December 2003

SUPPRESSION OF CUTTING FORCES USING COMBINED INVERSE MODEL BASED DISTURBANCE OBSERVER AND DISTURBANCE FORCE OBSERVER

This paper focuses on damping strategies that addressed the effect that high frequency harmonics content of cutting force have on positioning accuracy of the x-axis of an XY positioning table via controller and observer design approaches. Cutting force generated from direct contact between the workpiece and cutting tool becomes input disturbance to the drive system of the positioning table. The force high frequency components if left undamped would generate vibration to the system thus affecting the system positioning accuracy, surface finish quality as well as tool life. For this purpose, a cascade P/PI position controller, an Inverse Model Based Disturbance Observer (IMBDO) and a Disturbance Force Observer (DFO) were designed and numerically analysed. The cascade P/PI controller was designed using traditional loop shaping frequency domain method. IMBDO estimates the input disturbance and any unmodelled system dynamics while DFO performs direct estimation of the cutting force using knowledge of harmonic frequencies corresponding to the input cutting force. A combined cascade P/PI controller with IMBDO and DFO reduced additional 3.83% and  1.90% tracking errors compared to separate application of IMBDO and DFO. This novel control approach produced between 34-80% greater reductions in peak amplitudes of the harmonics content of the cutting forces compared to cascade P/PI

A global assessment of the impact of climate change on water scarcity

This paper presents a global scale assessment of the impact of climate change on water scarcity. Patterns of climate change from 21 Global Climate Models (GCMs) under four SRES scenarios are applied to a global hydrological model to estimate water resources across 1339 watersheds. The Water Crowding Index (WCI) and the Water Stress Index (WSI) are used to calculate exposure to increases and decreases in global water scarcity due to climate change. 1.6 (WCI) and 2.4 (WSI) billion people are estimated to be currently living within watersheds exposed to water scarcity. Using the WCI, by 2050 under the A1B scenario, 0.5 to 3.1 billion people are exposed to an increase in water scarcity due to climate change (range across 21 GCMs). This represents a higher upper-estimate than previous assessments because scenarios are constructed from a wider range of GCMs. A substantial proportion of the uncertainty in the global-scale effect of climate change on water scarcity is due to uncertainty in the estimates for South Asia and East Asia. Sensitivity to the WCI and WSI thresholds that define water scarcity can be comparable to the sensitivity to climate change pattern. More of the world will see an increase in exposure to water scarcity than a decrease due to climate change but this is not consistent across all climate change patterns. Additionally, investigation of the effects of a set of prescribed global mean temperature change scenarios show rapid increases in water scarcity due to climate change across many regions of the globe, up to 2°C, followed by stabilisation to 4°C

Test of the Kolmogorov-Johnson-Mehl-Avrami picture of metastable decay in a model with microscopic dynamics

The Kolmogorov-Johnson-Mehl-Avrami (KJMA) theory for the time evolution of the order parameter in systems undergoing first-order phase transformations has been extended by Sekimoto to the level of two-point correlation functions. Here, this extended KJMA theory is applied to a kinetic Ising lattice-gas model, in which the elementary kinetic processes act on microscopic length and time scales. The theoretical framework is used to analyze data from extensive Monte Carlo simulations. The theory is inherently a mesoscopic continuum picture, and in principle it requires a large separation between the microscopic scales and the mesoscopic scales characteristic of the evolving two-phase structure. Nevertheless, we find excellent quantitative agreement with the simulations in a large parameter regime, extending remarkably far towards strong fields (large supersaturations) and correspondingly small nucleation barriers. The original KJMA theory permits direct measurement of the order parameter in the metastable phase, and using the extension to correlation functions one can also perform separate measurements of the nucleation rate and the average velocity of the convoluted interface between the metastable and stable phase regions. The values obtained for all three quantities are verified by other theoretical and computational methods. As these quantities are often difficult to measure directly during a process of phase transformation, data analysis using the extended KJMA theory may provide a useful experimental alternative.Comment: RevTex, 21 pages including 14 ps figures. Submitted to Phys. Rev. B. One misprint corrected in Eq.(C1

Development of a web-based insulin decision aid for the elderly: usability barriers and guidelines

In recent years, researchers have attempted to shift patient decision aids (PDAs) from paper-based to web-based to increase its accessibility. Insulin decision aids help diabetes patients, most of whom are elderly to make an informed decision to start insulin. However, the lack of usability guidelines applicable for such target group causes developers to struggle to answer the challenging question ‘How can such web service be made usable, and, ultimately, acceptable and accessible for elderly patients?’. Hence, the purpose of this study is to identify the common usability requirements that may facilitate good practices to empower elderly diabetes patients in utilizing a web-based insulin decision aid for their benefit. We set out an approach to use prototyping and retrospective think-aloud techniques to explore web usability barriers that elderly patients may encounter when using an insulin decision aid web site and use the feedback for improving the prototype. Usability requirements were captured iteratively through scoping, brainstorming, prototype, testing and evaluating. The study suggests that the insights from experts and users are equally important to assure the validity of the identified usability guidelines; they reflect the accessibility needs of the aging community while complementing the key requirements of an insulin decision aid. The study contributes to recommend web usability guidelines backed by a series of expert and user evaluations which could be a proactive resource to improve usability, acceptability and accessibility of online insulin decision aids for elderly with diabetes

Next-generation, personalised, model-based critical care medicine : a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to validation them

© 2018 The Author(s). Critical care, like many healthcare areas, is under a dual assault from significantly increasing demographic and economic pressures. Intensive care unit (ICU) patients are highly variable in response to treatment, and increasingly aging populations mean ICUs are under increasing demand and their cohorts are increasingly ill. Equally, patient expectations are growing, while the economic ability to deliver care to all is declining. Better, more productive care is thus the big challenge. One means to that end is personalised care designed to manage the significant inter- and intra-patient variability that makes the ICU patient difficult. Thus, moving from current "one size fits all" protocolised care to adaptive, model-based "one method fits all" personalised care could deliver the required step change in the quality, and simultaneously the productivity and cost, of care. Computer models of human physiology are a unique tool to personalise care, as they can couple clinical data with mathematical methods to create subject-specific models and virtual patients to design new, personalised and more optimal protocols, as well as to guide care in real-time. They rely on identifying time varying patient-specific parameters in the model that capture inter- and intra-patient variability, the difference between patients and the evolution of patient condition. Properly validated, virtual patients represent the real patients, and can be used in silico to test different protocols or interventions, or in real-time to guide care. Hence, the underlying models and methods create the foundation for next generation care, as well as a tool for safely and rapidly developing personalised treatment protocols over large virtual cohorts using virtual trials. This review examines the models and methods used to create virtual patients. Specifically, it presents the models types and structures used and the data required. It then covers how to validate the resulting virtual patients and trials, and how these virtual trials can help design and optimise clinical trial. Links between these models and higher order, more complex physiome models are also discussed. In each section, it explores the progress reported up to date, especially on core ICU therapies in glycemic, circulatory and mechanical ventilation management, where high cost and frequency of occurrence provide a significant opportunity for model-based methods to have measurable clinical and economic impact. The outcomes are readily generalised to other areas of medical care

Analysis of equations of state for polymers

AbstractIn the literature there are several studies comparing the accuracy of various models in describing the PvT behavior of polymers. However, most of these studies do not provide information about the quality of the estimated parameters or the sensitivity of the prediction of thermodynamic properties to the parameters of the equations. Furthermore, there are few studies exploring the prediction of thermal expansion and compression coefficients. Based on these observations, the objective of this study is to deepen the analysis of Tait, HH (Hartmann-Haque), MCM (modified cell model) and SHT (simplified hole theory) equations of state in predicting the PvT behavior of polymers, for both molten and solid states. The results showed that all equations of state provide an adequate description of the PvT behavior in the molten state, with low standard deviations in the estimation of parameters, adequate sensitivity of their parameters and plausible prediction of specific volume, thermal expansion and isothermal compression coefficients. In the solid state the Tait equation exhibited similar performance to the molten state, while HH showed satisfactory results for amorphous polymers and difficulty in adjusting the PvT curve for semicrystalline polymers.</p

Silicon uptake by a pasture grass experiencing simulated grazing is greatest under elevated precipitation

Background Grasses are hyper-accumulators of silicon (Si) and often up-regulate Si following herbivory. Positive correlations exist between Si and plant water content, yet the extent to which Si uptake responses can be mediated by changes in soil water availability has rarely been studied and never, to our knowledge, under field conditions. We used field-based rain-exclusion shelters to investigate how simulated grazing (shoot clipping) and altered rainfall patterns (drought and elevated precipitation, representing 50% and 150% of ambient precipitation levels, respectively) affected initial patterns of root- and shoot-Si uptake in a native Australian grass (Microlaena stipoides) in Si-supplemented and untreated soils. Results Si supplementation increased soil water retention under ambient and elevated precipitation but not under drought, although this had little effect on Si uptake and growth (tiller numbers or root biomass) of M. stipoides. Changes in rainfall patterns and clipping had strong individual effects on plant growth and Si uptake and storage, whereby clipping increased Si uptake by M. stipoides under all rainfall treatments but to the greatest extent under elevated precipitation. Moreover, above-ground–below-ground Si distribution only changed following elevated precipitation by decreasing the ratio of root:shoot Si concentrations. Conclusions Results highlight the importance of soil water availability for Si uptake and suggest a role for both active and passive Si transport mechanisms. Such manipulative field studies may provide a more realistic insight into how grasses initially respond to herbivory in terms of Si-based defence under different environmental conditions

Structure-property correlations in model composite materials

We investigate the effective properties (conductivity, diffusivity and elastic moduli) of model random composite media derived from Gaussian random fields and overlapping hollow spheres. The morphologies generated in the models exhibit low percolation thresholds and give a realistic representation of the complex microstructure observed in many classes of composites. The statistical correlation functions of the models are derived and used to evaluate rigorous bounds on each property. Simulation of the effective conductivity is used to demonstrate the applicability of the bounds. The key morphological features which effect composite properties are discussed