SwarmPS: Rapid, semi-automated single particle selection software

Single particle analysis (SPA) coupled with high-resolution electron cryo-microscopy is emerging as a powerful technique for the structure determination of membrane protein complexes and soluble macromolecular assemblies. Current estimates suggest that ∼104–105 particle projections are required to attain a 3 Å resolution 3D reconstruction (symmetry dependent). Selecting this number of molecular projections differing in size, shape and symmetry is a rate-limiting step for the automation of 3D image reconstruction. Here, we present SwarmPS, a feature rich GUI based software package to manage large scale, semi-automated particle picking projects. The software provides cross-correlation and edge-detection algorithms. Algorithm-specific parameters are transparently and automatically determined through user interaction with the image, rather than by trial and error. Other features include multiple image handling (∼102), local and global particle selection options, interactive image freezing, automatic particle centering, and full manual override to correct false positives and negatives. SwarmPS is user friendly, flexible, extensible, fast, and capable of exporting boxed out projection images, or particle coordinates, compatible with downstream image processing suites.

Automatic particle picking of biological molecules imaged by electron microscopy

One of the next great challenges of cell biology is the determination of the enormous number of protein structures encoded in genomes. In recent years, advances in electron cryo-microscopy and high-resolution single particle analysis have developed to the point where they now provide a methodology for high resolution structure determination. Using this approach, images of randomly oriented single particles are aligned computationally to reconstruct 3-D structures of proteins and even whole viruses. One of the limiting factors in obtaining high-resolution reconstructions is obtaining a large enough representative dataset ($>100,000$ particles). Traditionally particles have been manually picked which is an extremely labour intensive process. The problem is made especially difficult by the low signal-to-noise ratio of the images. This paper describes the development of automatic particle picking software, which has been tested with both negatively stained and cryo-electron micrographs. This algorithm has been shown to be capable of selecting most of the particles, with few false positives. Further work will involve extending the software to detect differently shaped and oriented particles.

Simulation of Au particle interaction on graphene sheets

The interaction of Au particles with few layer graphene is of interest for the formation of the next generation of sensing devices(1). In this paper we investigate the coupling of single gold nanoparticles to a graphene sheet, and multiple gold nanoparticles with a graphene sheet using COMSOL Multiphysics. By using these simulations we are able to determine the electric field strength and associated hot-spots for various gold nanoparticle-graphene systems. The Au nanoparticles were modelled as 8 nm diameter spheres on 1.5 nm thick (5 layers) graphene, with properties of graphene obtained from the refractive index data of Weber(2) and the Au refractive index data from Palik(3). The field was incident along the plane of the sheet with polarisation tested for both s and p. The study showed strong localised interaction between the Au and graphene with limited spread; however the double particle case where the graphene sheet separated two Au nanoparticles showed distinct interaction between the particles and graphene. An offset was introduced (up to 4 nm) resulting in much reduced coupling between the opposed particles as the distance apart increased. Findings currently suggest that the graphene layer has limited interaction with incident fields with a single particle present whilst reducing the coupling region to a very fine area when opposing particles are involved. It is hoped that the results of this research will provide insight into graphene-plasmon interactions and spur the development of the next generation of sensing devices.

Inferring diffusion in single live cells at the single-molecule level

The movement of molecules inside living cells is a fundamental feature of biological processes. The ability to both observe and analyse the details of molecular diffusion in vivo at the single-molecule and single-cell level can add significant insight into understanding molecular architectures of diffus- ing molecules and the nanoscale environment in which the molecules diffuse. The tool of choice for monitoring dynamic molecular localization in live cells is fluorescence microscopy, especially so combining total internal reflection fluorescence with the use of fluorescent protein (FP) reporters in offering exceptional imaging contrast for dynamic processes in the cell mem- brane under relatively physiological conditions compared with competing single-molecule techniques. There exist several different complex modes of diffusion, and discriminating these from each other is challenging at the mol- ecular level owing to underlying stochastic behaviour. Analysis is traditionally performed using mean square displacements of tracked particles; however, this generally requires more data points than is typical for single FP tracks owing to photophysical instability. Presented here is a novel approach allowing robust Bayesian ranking of diffusion processes to dis-criminate multiple complex modes probabilistically. It is a computational approach that biologists can use to understand single-molecule features in live cells.

Mathematical modelling of the drying of sol gel microspheres

This thesis presents a mathematical model of the evaporation of colloidal sol droplets suspended within an atmosphere consisting of water vapour and air. The main purpose of this work is to investigate the causes of the morphologies arising within the powder collected from a spray dryer into which the precursor sol for Synroc™ is sprayed. The morphology is of significant importance for the application to storage of High Level Liquid Nuclear Waste. We begin by developing a model describing the evaporation of pure liquid droplets in order to establish a framework. This model is developed through the use of continuum mechanics and thermodynamic theory, and we focus on the specific case of pure water droplets. We establish a model considering a pure water vapour atmosphere, and then expand this model to account for the presence of an atmospheric gas such as air. We model colloidal particle-particle interactions and interactions between colloid and electrolyte using DLVO Theory and reaction kinetics, then incorporate these interactions into an expression for net interaction energy of a single particle with all other particles within the droplet. We account for the flow of material due to diffusion, advection, and interaction between species, and expand the pure liquid droplet models to account for the presence of these species. In addition, the process of colloidal agglomeration is modelled. To obtain solutions for our models, we develop a numerical algorithm based on the Control Volume method. To promote numerical stability, we formulate a new method of convergence acceleration. The results of a MATLAB™ code developed from this algorithm are compared with experimental data collected for the purposes of validation, and further analysis is done on the sensitivity of the solution to various controlling parameters.

VESUVIO : a novel instrument for performing spectroscopic studies in condensed matter with eV neutrons at the ISIS facility

The VESUVIO project aims to provide unique prototype instrumentation at the ISIS-pulsed neutron source and to establish a routine experimental and theoretical program in neutron scattering spectroscopy at eV energies. This instrumentation will be specifically designed for high momentum, , and energy transfer inelastic neutron scattering studies of microscopic dynamical processes in materials and will represent a unique facility for EU researchers. It will allow to derive single-particle kinetic energies and single-particle momentum distributions, n(p), providing additional and/or complementary information to other neutron inelastic spectroscopic techniques.

Improved rural health through a collaborative model of care – qualitative findings

INTRODUCTION Health disparity between urban and rural regions in Australia is well-documented. In the Wheatbelt catchments of Western Australia there is higher incidence and rate of avoidable hospitalisation for chronic diseases. Structured care approach to chronic illnesses is not new but the focus has been on single disease state. A recent ARC Discovery Project on general practice nurse-led chronic disease management of diabetes, hypertension and stable ischaemic heart disease reported improved communication and better medical administration.[1] In our study we investigated the sustainability of such a multi-morbidities general practice –led collaborative model of care in rural Australia. METHODS A QUAN(qual) design was utilised. Eight pairs of rural general practices were matched. Inclusion criteria used were >18 years and capable of giving informed consent, at least one identified risk factor or diagnosed with chronic conditions. Patients were excluded if deemed medically unsuitable. A comprehensive care plan was formulated by the respective general practice nurse in consultation with the treating General Practitioner (GP) and patient based on the individual’s readiness to change, and was informed by available local resource. A case management approach was utilised. Shediaz-Rizkallah and Lee’s conceptual framework on sustainability informed our evaluation.[2] Our primary outcome on measures of sustainability was reduction in avoidable hospitalisation. Secondary outcomes were patients and practitioners acceptance and satisfaction, and changes to pre-determined interim clinical and process outcomes. RESULTS The qualitative interviews highlighted the community preference for a ‘sustainable’ local hospital in addition to general practice. Costs, ease of access, low prioritisation of self chronic care, workforce turnover and perception of losing another local resource if underutilised influenced the respondents’ decision to present at local hospital for avoidable chronic diseases regardless. CONCLUSIONS Despite the pragmatic nature of rural general practice in Australia, the sustainability of chronic multi-morbidities management in general practice require efficient integration of primary-secondary health care and consideration of other social determinants of health. What this study adds: What is already known on this subject: Structured approach to chronic disease management is not new and has been shown to be effective for reducing hospitalisation. However, the focus has been on single disease state. What does this study add: Sustainability of collaborative model of multi-morbidities care require better primary-secondary integration and consideration of social determinants of health.

High-resolution GNSS-tracked drifter for studying surface dispersion in shallow water

The use of GNSS tracked Lagrangian drifters allows more realistic quantification of fluid motion and dispersion coefficients than Eulerian techniques because such drifters are analogues of particles that are relevant to flow field characterisation and pollutant dispersion. Using the fast growing Real Time Kinematic (RTK) positioning technique derived from Global Satellite Navigation Systems (GNSS), drifters are developed for high frequency (10 Hz) sampling with position estimates to centimetre accuracy. The drifters are designed with small size and less direct wind drag to follow the sub-surface flow which characterizes dispersion in shallow waters. An analysis of position error from stationary observation indicates that the drifter can efficiently resolve motion up to 1 Hz. The result of the field deployments of the drifter in conjunction with acoustic Eulerian devices shows higher estimate of the drifter streamwise velocities. Single particle statistical analysis of field deployments in a shallow estuarine zone yielded dispersion coefficients estimate comparable to those of dye tracer studies. The drifters capture the tidal elevation during field studies in a tidal estuary.

Estimate of Lagrangian integral scales in shallow tidal water using high resolution GPS-tracked drifters

In estuaries and natural water channels, the estimate of velocity and dispersion coefficients is critical to the knowledge of scalar transport and mixing. This estimate is rarely available experimentally at sub-tidal time scale in shallow water channels where high frequency is required to capture its spatio-temporal variation. This study estimates Lagrangian integral scales and autocorrelation curves, which are key parameters for obtaining velocity fluctuations and dispersion coefficients, and their spatio-temporal variability from deployments of Lagrangian drifters sampled at 10 Hz for a 4-hour period. The power spectral densities of the velocities between 0.0001 and 0.8 Hz were well fitted with a slope of 5/3 predicted by Kolmogorov’s similarity hypothesis within the inertial subrange, and were similar to the Eulerian power spectral previously observed within the estuary. The result showed that large velocity fluctuations determine the magnitude of the integral time scale, TL. Overlapping of short segments improved the stability of the estimate of TL by taking advantage of the redundant data included in the autocorrelation function. The integral time scales were about 20 s and varied by up to a factor of 8. These results are essential inputs for spatial binning of velocities, Lagrangian stochastic modelling and single particle analysis of the tidal estuary.

Deformation properties of single red blood cell in a stenosed microchannel

Red Blood Cells (RBCs) exhibit different types of motions and different deformed shapes, when they move through capillaries. RBCs can travel through capillaries having smaller diameters than RBCs’ diameter, due to the capacity of high deformability of the viscoelastic RBC membrane. The motion and the steady state shape of the RBCs depend on many factors, such as the geometrical parameters of the microvessel through which blood flows, the RBC membrane bending stiffness and the flow velocity. In this study, the effect of the RBC’s membrane stiffness on the deformation of a single RBC in a stenosed capillary is comprehensively examined. Smoothed Particle Hydrodynamics (SPH) in combination with the two-dimensional spring network membrane model is used to investigate the motion and the deformation property of the RBC. The simulation results demonstrate that the membrane bending stiffness of the RBC has a significant impact on the RBCs’ deformability.

Distribution state estimation based on particle swarm and doubly loop mutant optimization (DLM-PSO)

This paper presents a novel algorithm based on particle swarm optimization (PSO) to estimate the states of electric distribution networks. In order to improve the performance, accuracy, convergence speed, and eliminate the stagnation effect of original PSO, a secondary PSO loop and mutation algorithm as well as stretching function is proposed. For accounting uncertainties of loads in distribution networks, pseudo-measurements is modeled as loads with the realistic errors. Simulation results on 6-bus radial and 34-bus IEEE test distribution networks show that the distribution state estimation based on proposed DLM-PSO presents lower estimation error and standard deviation in comparison with algorithms such as WLS, GA, HBMO, and original PSO.

Numerical investigation of motion and deformation of a single red blood cell in a stenosed capillary

It is generally assumed that influence of the red blood cells (RBCs) is predominant in blood rheology. The healthy RBCs are highly deformable and can thus easily squeeze through the smallest capillaries having internal diameter less than their characteristic size. On the other hand, RBCs infected by malaria or other diseases are stiffer and so less deformable. Thus it is harder for them to flow through the smallest capillaries. Therefore, it is very important to critically and realistically investigate the mechanical behavior of both healthy and infected RBCs which is a current gap in knowledge. The motion and the steady state deformed shape of the RBCs depend on many factors, such as the geometrical parameters of the capillary through which blood flows, the membrane bending stiffness and the mean velocity of the blood flow. In this study, motion and deformation of a single two-dimensional RBC in a stenosed capillary is explored by using smoothed particle hydrodynamics (SPH) method. An elastic spring network is used to model the RBC membrane, while the RBC's inside fluid and outside fluid are treated as SPH particles. The effect of RBC's membrane stiffness (kb), inlet pressure (P) and geometrical parameters of the capillary on the motion and deformation of the RBC is studied. The deformation index, RBC's mean velocity and the cell membrane energy are analyzed when the cell passes through the stenosed capillary. The simulation results demonstrate that the kb, P and the geometrical parameters of the capillary have a significant impact on the RBCs' motion and deformation in the stenosed section.

Particle and gaseous emissions from compressed natural gas and ultralow sulphur diesel-fuelled buses at four steady engine loads

Exhaust emissions from thirteen compressed natural gas (CNG) and nine ultralow sulphur diesel in-service transport buses were monitored on a chassis dynamometer. Measurements were carried out at idle and at three steady engine loads of 25%, 50% and 100% of maximum power at a fixed speed of 60 kmph. Emission factors were estimated for particle mass and number, carbon dioxide and oxides of nitrogen for two types of CNG buses (Scania and MAN, compatible with Euro 2 and 3 emission standards, respectively) and two types of diesel buses (Volvo Pre-Euro/Euro1 and Mercedez OC500 Euro3). All emission factors increased with load. The median particle mass emission factor for the CNG buses was less than 1% of that from the diesel buses at all loads. However, the particle number emission factors did not show a statistically significant difference between buses operating on the two types of fuel. In this paper, for the very first time, particle number emission factors are presented at four steady state engine loads for CNG buses. Median values ranged from the order of 1012 particles min-1 at idle to 1015 particles km-1 at full power. Most of the particles observed in the CNG emissions were in the nanoparticle size range and likely to be composed of volatile organic compounds The CO2 emission factors were about 20% to 30% greater for the diesel buses over the CNG buses, while the oxides of nitrogen emission factors did not show any difference due to the large variation between buses.

Increase in particle number emissions from motor vehicles due to interruption of steady traffic flow

We assess the increase in particle number emissions from motor vehicles driving at steady speed when forced to stop and accelerate from rest. Considering the example of a signalized pedestrian crossing on a two-way single-lane urban road, we use a complex line source method to calculate the total emissions produced by a specific number and mix of light petrol cars and diesel passenger buses and show that the total emissions during a red light is significantly higher than during the time when the light remains green. Replacing two cars with one bus increased the emissions by over an order of magnitude. Considering these large differences, we conclude that the importance attached to particle number emissions in traffic management policies be reassessed in the future.

Freeway traffic estimation in Beijing based on particle filter

Short-term traffic flow data is characterized by rapid and dramatic fluctuations. It reflects the nature of the frequent congestion in the lane, which shows a strong nonlinear feature. Traffic state estimation based on the data gained by electronic sensors is critical for much intelligent traffic management and the traffic control. In this paper, a solution to freeway traffic estimation in Beijing is proposed using a particle filter, based on macroscopic traffic flow model, which estimates both traffic density and speed.Particle filter is a nonlinear prediction method, which has obvious advantages for traffic flows prediction. However, with the increase of sampling period, the volatility of the traffic state curve will be much dramatic. Therefore, the prediction accuracy will be affected and difficulty of forecasting is raised. In this paper, particle filter model is applied to estimate the short-term traffic flow. Numerical study is conducted based on the Beijing freeway data with the sampling period of 2 min. The relatively high accuracy of the results indicates the superiority of the proposed model.