Characterization of a DC-driven microplasma between a capillary tube and water surface

A microplasma generated between a stainless-steel capillary and water surface in ambient air with flowing argon as working gas appears as a bright spot at the tube orifice and expands to form a larger footprint on the water surface, and the dimensions of the bell-shaped microplasma are all below 1 mm. The electron density of the microplasma is estimated to be ranging from 5.32 × 109 cm−3 to 2.02 × 1014 cm−3 for the different operating conditions, which is desirable for generating abundant amounts of reactive species. A computational technique is adopted to fit the experimental emission from the N2 second positive system with simulation results. It is concluded that the vibrational temperature (more than 2000 K) is more than twice the gas temperature (more than 800 K), which indicates the non-equilibrium state of the microplasma. Both temperatures showed dependence on the discharge parameters (i.e., gas flow and discharge current). Such a plasma device could be arranged in arrays for applications utilizing plasmainduced liquid chemistry.

CFD convective flow simulation of the varying properties of CO2-H20 mixtures in geothermal systems

Numerical simulation of a geothermal reservoir, modelled as a bottom-heated square box, filled with water-CO2 mixture is presented in this work. Furthermore, results for two limiting cases of a reservoir filled with either pure water or CO2 are presented. Effects of different parameters including CO2 concentration as well as reservoir pressure and temperature on the overall performance of the system are investigated. It has been noted that, with a fixed reservoir pressure and temperature, any increase in CO2concentration leads to better performance, i.e. stronger convection and higher heat transfer rates. With a fixed CO2 concentration, however, the reservoir pressure and temperature can significantly affect the overall heat transfer and flow rate from the reservoir. Details of such variations are documented and discussed in the present paper.

CFD simulations of flow and heat transfer through the porous interface of a metal foam heat exchanger

This paper offers numerical modelling of a waste heat recovery system. A thin layer of metal foam is attached to a cold plate to absorb heat from hot gases leaving the system. The heat transferred from the exhaust gas is then transferred to a cold liquid flowing in a secondary loop. Two different foam PPI (Pores Per Inch) values are examined over a range of fluid velocities. Numerical results are then compared to both experimental data and theoretical results available in the literature. Challenges in getting the simulation results to match those of the experiments are addressed and discussed in detail. In particular, interface boundary conditions specified between a porous layer and a fluid layer are investigated. While physically one expects much lower fluid velocity in the pores compared to that of free flow, capturing this sharp gradient at the interface can add to the difficulties of numerical simulation. The existing models in the literature are modified by considering the pressure gradient inside and outside the foam. Comparisons against the numerical modelling are presented. Finally, based on experimentally-validated numerical results, thermo-hydraulic performance of foam heat exchangers as waste heat recovery units is discussed with the main goal of reducing the excess pressure drop and maximising the amount of heat that can be recovered from the hot gas stream.

Effect of ion current density on the properties of vacuum arc-deposited TiN coatings

The influence of ion current density on the thickness of coatings deposited in a vacuum arc setup has been investigated to optimize the coating porosity. A planar probe was used to measure the ion current density distribution across plasma flux. A current density from 20 to 50 A/m2 was obtained, depending on the probe position relative to the substrate center. TiN coatings were deposited onto the cutting inserts placed at different locations on the substrate, and SEM was used to characterize the surfaces of the coatings. It was found that lowdensity coatings were formed at the decreased ion current density. A quantitative dependence of the coating thickness on the ion current density in the range of 20-50 A/m2 were obtained for the films deposited at substrate bias of 200 V and nitrogen pressure 0.1 Pa, and the coating porosity was calculated. The coated cutting inserts were tested by lathe machining of the martensitic stainless steel AISI 431. The results may be useful for controlling ion flux distribution over large industrial-scale substrates.

Measuring patient flow variations : a cross-organisational process mining approach

Variations that exist in the treatment of patients (with similar symptoms) across different hospitals do substantially impact the quality and costs of healthcare. Consequently, it is important to understand the similarities and differences between the practices across different hospitals. This paper presents a case study on the application of process mining techniques to measure and quantify the differences in the treatment of patients presenting with chest pain symptoms across four South Australian hospitals. Our case study focuses on cross-organisational benchmarking of processes and their performance. Techniques such as clustering, process discovery, performance analysis, and scientific workflows were applied to facilitate such comparative analyses. Lessons learned in overcoming unique challenges in cross-organisational process mining, such as ensuring population comparability, data granularity comparability, and experimental repeatability are also presented.

Optimisation methods for coupled thermodynamic and 1D design of radial-inflow turbines

Optimisation is a fundamental step in the turbine design process, especially in the development of non-classical designs of radial-inflow turbines working with high-density fluids in low-temperature Organic Rankine Cycles (ORCs). The present work discusses the simultaneous optimisation of the thermodynamic cycle and the one-dimensional design of radial-inflow turbines. In particular, the work describes the integration between a 1D meanline preliminary design code adapted to real gases and the performance estimation approach for radial-inflow turbines in an established ORC cycle analysis procedure. The optimisation approach is split in two distinct loops; the inner operates on the 1D design based on the parameters received from the outer loop, which optimises the thermodynamic cycle. The method uses parameters including brine flow rate, temperature and working fluid, shifting assumptions such as head and flow coefficients into the optimisation routine. The discussed design and optimisation method is then validated against published benchmark cases. Finally, using the same conditions, the coupled optimisation procedure is extended to the preliminary design of a radial-inflow turbine with R143a as working fluid in realistic geothermal conditions and compared against results from commercially-available software RITAL from Concepts-NREC.

Charge transport and density of trap states in balanced high mobility ambipolar organic thin-film transistors

We report on charge transport and density of trap states (trap DOS) in ambipolar diketopyrrolopyrrole-benzothiadiazole copolymer thin-film transistors. This semiconductor possesses high electron and hole field-effect mobilities of up to 0.6 cm 2/V-s. Temperature and gate-bias dependent field-effect mobility measurements are employed to extract the activation energies and trap DOS to understand its unique high mobility balanced ambipolar charge transport properties. The symmetry between the electron and hole transport characteristics, parameters and activation energies is remarkable. We believe that our work is the first charge transport study of an ambipolar organic/polymer based field-effect transistor with room temperature mobility higher than 0.1 cm 2/V-s in both electrons and holes.

A fast track SAP R/3 implementation at Guilbert Niceday

This paper examines the approach of Guilbert, a European stationery company, which has chosen a fast track strategy towards implementation of enterprise resource planning.

Topological localization using optical flow descriptors

We propose a topological localization method based on optical flow information. We analyse the statistical characteristics of the optical flow signal and demonstrate that the flow vectors can be used to identify and describe key locations in the environment. The key locations (nodes) correspond to significant scene changes and depth discontinuities. Since optical flow vectors contain position, magnitude and angle information, for each node, we extract low and high order statistical moments of the vectors and use them as descriptors for that node. Once a database of nodes and their corresponding optical flow features is created, the robot can perform topological localization by using the Mahalanobis distance between the current frame and the database. This is supported by field trials, which illustrate the repeatability of the proposed method for detecting and describing key locations in indoor and outdoor environments in challenging and diverse lighting conditions.

A Study of feature extraction algorithms for optical flow tracking

Sparse optical flow algorithms, such as the Lucas-Kanade approach, provide more robustness to noise than dense optical flow algorithms and are the preferred approach in many scenarios. Sparse optical flow algorithms estimate the displacement for a selected number of pixels in the image. These pixels can be chosen randomly. However, pixels in regions with more variance between the neighbours will produce more reliable displacement estimates. The selected pixel locations should therefore be chosen wisely. In this study, the suitability of Harris corners, Shi-Tomasi's “Good features to track", SIFT and SURF interest point extractors, Canny edges, and random pixel selection for the purpose of frame-by-frame tracking using a pyramidical Lucas-Kanade algorithm is investigated. The evaluation considers the important factors of processing time, feature count, and feature trackability in indoor and outdoor scenarios using ground vehicles and unmanned aerial vehicles, and for the purpose of visual odometry estimation.

Interpreting scratch assays using pair density dynamics and approximate Bayesian computation

Quantifying the impact of biochemical compounds on collective cell spreading is an essential element of drug design, with various applications including developing treatments for chronic wounds and cancer. Scratch assays are a technically simple and inexpensive method used to study collective cell spreading; however, most previous interpretations of scratch assays are qualitative and do not provide estimates of the cell diffusivity, D, or the cell proliferation rate,l. Estimating D and l is important for investigating the efficacy of a potential treatment and provides insight into the mechanism through which the potential treatment acts. While a few methods for estimating D and l have been proposed, these previous methods lead to point estimates of D and l, and provide no insight into the uncertainty in these estimates. Here, we compare various types of information that can be extracted from images of a scratch assay, and quantify D and l using discrete computational simulations and approximate Bayesian computation. We show that it is possible to robustly recover estimates of D and l from synthetic data, as well as a new set of experimental data. For the first time, our approach also provides a method to estimate the uncertainty in our estimates of D and l. We anticipate that our approach can be generalized to deal with more realistic experimental scenarios in which we are interested in estimating D and l, as well as additional relevant parameters such as the strength of cell-to-cell adhesion or the strength of cell-to-substrate adhesion.

Development of a dragline in-bucket bulk density monitor

This paper details the implementation and trialling of a prototype in-bucket bulk density monitor on a production dragline. Bulk density information can provide feedback to mine planning and scheduling to improve blasting and consequently facilitating optimal bucket sizing. The bulk density measurement builds upon outcomes presented in the AMTC2009 paper titled ‘Automatic In-Bucket Volume Estimation for Dragline Operations’ and utilises payload information from a commercial dragline monitor. While the previous paper explains the algorithms and theoretical basis for the system design and scaled model testing this paper will focus on the full scale implementation and the challenges involved.

Mismatch negativity in recent-onset and chronic schizophrenia : a current source density analysis

Mismatch negativity (MMN) is a component of the event-related potential elicited by deviant auditory stimuli. It is presumed to index pre-attentive monitoring of changes in the auditory environment. MMN amplitude is smaller in groups of individuals with schizophrenia compared to healthy controls. We compared duration-deviant MMN in 16 recent-onset and 19 chronic schizophrenia patients versus age- and sex-matched controls. Reduced frontal MMN was found in both patient groups, involved reduced hemispheric asymmetry, and was correlated with Global Assessment of Functioning (GAF) and negative symptom ratings. A cortically-constrained LORETA analysis, incorporating anatomical data from each individual's MRI, was performed to generate a current source density model of the MMN response over time. This model suggested MMN generation within a temporal, parietal and frontal network, which was right hemisphere dominant only in controls. An exploratory analysis revealed reduced CSD in patients in superior and middle temporal cortex, inferior and superior parietal cortex, precuneus, anterior cingulate, and superior and middle frontal cortex. A region of interest (ROI) analysis was performed. For the early phase of the MMN, patients had reduced bilateral temporal and parietal response and no lateralisation in frontal ROIs. For late MMN, patients had reduced bilateral parietal response and no lateralisation in temporal ROIs. In patients, correlations revealed a link between GAF and the MMN response in parietal cortex. In controls, the frontal response onset was 17 ms later than the temporal and parietal response. In patients, onset latency of the MMN response was delayed in secondary, but not primary, auditory cortex. However amplitude reductions were observed in both primary and secondary auditory cortex. These latency delays may indicate relatively intact information processing upstream of the primary auditory cortex, but impaired primary auditory cortex or cortico-cortical or thalamo-cortical communication with higher auditory cortices as a core deficit in schizophrenia.

Lazy days of simply going with the flow

A travel article about a river cruise from Amsterdam to Basel. When Captain Plamen Veselinov invites me to join him on the bridge, I can at last put a question that’s been running through my mind for days. It’s about the locks. How does he manage to line up the vessel as it approaches? Is the ship guided in electronically? He returns my questions with a boyish smile that does a good deal to veil his many years on the river. Crunching his way through a heavy Bulgarian accent, he says, “No, it’s all in the eyes and the hands. It’s magic. Don’t tell David Copperfield. He would get very jealous...