Effective control of ion fluxes over large areas by magnetic fields : from narrow beams to highly uniform fluxes

An effective control of the ion current distribution over large-area (up to 103 cm2) substrates with the magnetic fields of a complex structure by using two additional magnetic coils installed under the substrate exposed to vacuum arc plasmas is demonstrated. When the magnetic field generated by the additional coils is aligned with the direction of the magnetic field generated by the guiding and focusing coils of the vacuum arc source, a narrow ion density distribution with the maximum current density 117 A m-2 is achieved. When one of the additional coils is set to generate the magnetic field of the opposite direction, an area almost uniform over the substrate of 103 cm2 ion current distribution with the mean value of 45 A m-2 is achieved. Our findings suggest that the system with the vacuum arc source and two additional magnetic coils can be effectively used for the effective, high throughput, and highly controllable plasma processing.

A model of a large-area planar plasma producer based on surface wave propagation in a plasma-metal structure with a dielectric sheath

A theoretical model of a large-area planar plasma producer based on surface wave (SW) propagation in a plasma-metal structure with a dielectric sheath is presented. The SW which produces and sustains the microwave gas discharge in the planar structure propagates along an external magnetic field and possesses an eigenfrequency within the range between electron cyclotron and electron plasma frequencies. The spatial distributions of the produced plasma density, electromagnetic fields, energy flow density, phase velocity and reverse skin depth of the SW are obtained analytically and numerically.

Parameters and equilibrium profiles for large-area surface-wave sustained plasmas

The equilibrium profiles of the plasma parameters of large-area if discharges in a finite-length metal-shielded dielectric cylinder are computed using a two-dimensional fluid code. The rf power is coupled to the plasma through edge-localized surface waves traveling in the azimuthal direction along the plasma edge. It is shown that self-consistent accounting for axial plasma diffusion and radial nonuniformity of the electron temperature can explain the frequently reported deviations of experimentally measured radial density profiles from that of the conventional linear diffusion models. The simulation results are in a good agreement with existing experimental data obtained from surface-wave sustained large-diameter plasmas. © 2002 The American Physical Society.

Low-temperature growth of large area, vertically aligned carbon nanotubes for field emission applications

Large area, highly uniform vertically aligned carbon nanotips (VACNTP) and other nanostructures have been grown on silicon (100) substrates with Ni catalyst in the low-temperature, low-frequency, high-density inductively coupled plasmas (ICP) of methane-hydrogen-argon gas mixtures. The control strategies for the morphology, crystalline structure and chemical states of the resulting nanostructures by varying the growth conditions are proposed. XRD and Roman analyses confirm that the nanotips are well graphitized, which is favorable for the field emission applications.

Benefits and risks of large hydrostatic recesses in hydroelectric turbine thrust bearings

Operators of hydroelectric power stations sometimes call upon engineers to modify existing hydroelectric turbines, usually several decades old, for improved maintainability and reliability. One common modification is the hybridisation of plain thrust pads to allow hydrostatic operation to reduce the risk of bearing wipe at low speed (virtually all new installations benefit from this feature). A modification such as this is not a difficult undertaking; however, there are numerous factors that need to be considered in order to maximize bearing performance. One factor that stands out above the others is whether the thrust bearing should be designed to lift the turbine immediately from the standing condition, which presents an interesting challenge: the recess has to have a sufficiently large area in order for the supply pressure to be able to overcome the dead weight of the turbine. If the combination of groove area and pressure is insufficient, then lifting is neither immediate nor guaranteed. This need not be a significant problem, as the bearings have exhibited adequate performance even in the absence of a hydrostatic lubricant supply. A case study is presented whereby relatively large hydrostatic recesses are added to the pads of thrust bearing. It is demonstrated with the aid of simple numerical modelling that the impact of the recess relative to the original pad is small under normal operating conditions. Most surprising, however, is that significant reductions in average oil film temperature and power dissipation are predicted.

Unbalance identification in large steam turbo-generator unit using a model-based method

Fault identification in industrial machine is a topic of major importance under engineering point of view. In fact, the possibility to identify not only the type, but also the severity and the position of a fault occurred along a shaft-line allows quick maintenance and shorten the downtime. This is really important in the power generation industry where the units are often of several tenths of meters long and where the rotors are enclosed by heavy and pressure-sealed casings. In this paper, an industrial experimental case is presented related to the identification of the unbalance on a large size steam turbine of about 1.3 GW, belonging to a nuclear power plant. The case history is analyzed by considering the vibrations measured by the condition monitoring system of the unit. A model-based method in the frequency domain, developed by the authors, is introduced in detail and it is then used to identify the position of the fault and its severity along the shaft-line. The complete model of the unit (rotor – modeled by means of finite elements, bearings – modeled by linearized damping and stiffness coefficients and foundation – modeled by means of pedestals) is analyzed and discussed before being used for the fault identification. The assessment of the actual fault was done by inspection during a scheduled maintenance and excellent correspondence was found with the identified one by means of authors’ proposed method. Finally a complete discussion is presented about the effectiveness of the method, even in presence of a not fine tuned machine model and considering only few measuring planes for the machine vibration.

Large scale read classification for next generation sequencing

Next Generation Sequencing (NGS) has revolutionised molecular biology, resulting in an explosion of data sets and an increasing role in clinical practice. Such applications necessarily require rapid identification of the organism as a prelude to annotation and further analysis. NGS data consist of a substantial number of short sequence reads, given context through downstream assembly and annotation, a process requiring reads consistent with the assumed species or species group. Highly accurate results have been obtained for restricted sets using SVM classifiers, but such methods are difficult to parallelise and success depends on careful attention to feature selection. This work examines the problem at very large scale, using a mix of synthetic and real data with a view to determining the overall structure of the problem and the effectiveness of parallel ensembles of simpler classifiers (principally random forests) in addressing the challenges of large scale genomics.

Particle number emissions from a large fleet of diesel and CNG buses

Exhaust emissions were monitored in real-time at the kerb of a busy busway used by a mix of diesel and CNG-powered transport buses. Particle number concentration in the size range 3 nm to 3 µm was measured with a TSI condensation particle counter (CPC 3025). Particle mass (PM2.5) was measured with a TSI Dustrak 8520. The CO2 emissions were measured with a fast response CO2 analyser (Sable CA-10A). All emission concentrations were recorded in real time at 1 sec resolution, together with the precise passage times of buses. The instantaneous ratio of particle number (or mass) to CO2 concentration, denoted Z, was used as a measure of the particle number (or mass) emission factor of each passing bus.

Large arrays and networks of carbon nanotubes : morphology control by process parameters

Large arrays and networks of carbon nanotubes, both single- and multi-walled, feature many superior properties which offer excellent opportunities for various modern applications ranging from nanoelectronics, supercapacitors, photovoltaic cells, energy storage and conversation devices, to gas- and biosensors, nanomechanical and biomedical devices etc. At present, arrays and networks of carbon nanotubes are mainly fabricated from the pre-fabricated separated nanotubes by solution-based techniques. However, the intrinsic structure of the nanotubes (mainly, the level of the structural defects) which are required for the best performance in the nanotube-based applications, are often damaged during the array/network fabrication by surfactants, chemicals, and sonication involved in the process. As a result, the performance of the functional devices may be significantly degraded. In contrast, directly synthesized nanotube arrays/networks can preclude the adverse effects of the solution-based process and largely preserve the excellent properties of the pristine nanotubes. Owing to its advantages of scale-up production and precise positioning of the grown nanotubes, catalytic and catalyst-free chemical vapor depositions (CVD), as well as plasma-enhanced chemical vapor deposition (PECVD) are the methods most promising for the direct synthesis of the nanotubes.

An application of the Driver Behaviour Questionnaire in a large Australian organisational fleeting setting : can it predict crashes and demerit point loss?

This study reports on the utilisation of the Manchester Driver Behaviour Questionnaire (DBQ) to examine the self-reported driving behaviours of a large sample of Australian fleet drivers (N = 3414). Surveys were completed by employees before they commenced a one day safety workshop intervention. Factor analysis techniques identified a three factor solution similar to previous research, which was comprised of: (a) errors, (b) highway-code violations and (c) aggressive driving violations. Two items traditionally related with highway-code violations were found to be associated with aggressive driving behaviours among the current sample. Multivariate analyses revealed that exposure to the road, errors and self-reported offences predicted crashes at work in the last 12 months, while gender, highway violations and crashes predicted offences incurred while at work. Importantly, those who received more fines at work were at an increased risk of crashing the work vehicle. However, overall, the DBQ demonstrated limited efficacy at predicting these two outcomes. This paper outlines the major findings of the study in regards to identifying and predicting aberrant driving behaviours and also highlights implications regarding the future utilisation of the DBQ within fleet settings.

Understanding and analyzing a large collection of archived swimming videos

In elite sports, nearly all performances are captured on video. Despite the massive amounts of video that has been captured in this domain over the last 10-15 years, most of it remains in an 'unstructured' or 'raw' form, meaning it can only be viewed or manually annotated/tagged with higher-level event labels which is time consuming and subjective. As such, depending on the detail or depth of annotation, the value of the collected repositories of archived data is minimal as it does not lend itself to large-scale analysis and retrieval. One such example is swimming, where each race of a swimmer is captured on a camcorder and in-addition to the split-times (i.e., the time it takes for each lap), stroke rate and stroke-lengths are manually annotated. In this paper, we propose a vision-based system which effectively 'digitizes' a large collection of archived swimming races by estimating the location of the swimmer in each frame, as well as detecting the stroke rate. As the videos are captured from moving hand-held cameras which are located at different positions and angles, we show our hierarchical-based approach to tracking the swimmer and their different parts is robust to these issues and allows us to accurately estimate the swimmer location and stroke rates.

Melanopsin expressing intrinsically photosensitive Retinal Ganglion cells in retinal disease

Melanopsin containing intrinsically photosensitive Retinal Ganglion Cells (ipRGCs) are a class of photoreceptors with established roles in non-image forming processes. Their contributions to image forming vision may include the estimation of brightness. Animal models have been central for understanding the physiological mechanisms of ipRGC function and there is evidence of conservation of function across species. ipRGCs can be divided into 5 ganglion cell subtypes that show morphological and functional diversity. Research in humans has established that ipRGCs signal environmental irradiance to entrain the central body clock to the solar day for regulating circadian processes and sleep. In addition, ipRGCs mediate the pupil light reflex (PLR), making the PLR a readily accessible behavioural marker of ipRGC activity. Less is known about ipRGC function in retinal and optic nerve disease, with emerging research providing insight into their function in diabetes, retinitis pigmentosa, glaucoma and hereditary optic neuropathy. We briefly review the anatomical distributions, projections and basic physiological mechanisms of ipRGCs, their proposed and known functions in animals and humans with and without eye disease. We introduce a paradigm for differentiating inner and outer retinal inputs to the pupillary control pathway in retinal disease and apply this paradigm to patients with age-related macular degeneration (AMD). In these cases of patients with AMD, we provide the initial evidence that ipRGC function is altered, and that the dysfunction is more pronounced in advanced disease. Our perspective is that with refined pupillometry paradigms, the pupil light reflex can be extended to AMD assessment as a tool for the measurement of inner and outer retinal dysfunction.

A large proportion of asymptomatic Plasmodium infections with low and sub-microscopic parasite densities in the low transmission setting of Temotu Province, Solomon Islands : challenges for malaria diagnostics in an elimination setting

Background Many countries are scaling up malaria interventions towards elimination. This transition changes demands on malaria diagnostics from diagnosing ill patients to detecting parasites in all carriers including asymptomatic infections and infections with low parasite densities. Detection methods suitable to local malaria epidemiology must be selected prior to transitioning a malaria control programme to elimination. A baseline malaria survey conducted in Temotu Province, Solomon Islands in late 2008, as the first step in a provincial malaria elimination programme, provided malaria epidemiology data and an opportunity to assess how well different diagnostic methods performed in this setting. Methods During the survey, 9,491 blood samples were collected and examined by microscopy for Plasmodium species and density, with a subset also examined by polymerase chain reaction (PCR) and rapid diagnostic tests (RDTs). The performances of these diagnostic methods were compared. Results A total of 256 samples were positive by microscopy, giving a point prevalence of 2.7%. The species distribution was 17.5% Plasmodium falciparum and 82.4% Plasmodium vivax. In this low transmission setting, only 17.8% of the P. falciparum and 2.9% of P. vivax infected subjects were febrile (≥38°C) at the time of the survey. A significant proportion of infections detected by microscopy, 40% and 65.6% for P. falciparum and P. vivax respectively, had parasite density below 100/μL. There was an age correlation for the proportion of parasite density below 100/μL for P. vivax infections, but not for P. falciparum infections. PCR detected substantially more infections than microscopy (point prevalence of 8.71%), indicating a large number of subjects had sub-microscopic parasitemia. The concordance between PCR and microscopy in detecting single species was greater for P. vivax (135/162) compared to P. falciparum (36/118). The malaria RDT detected the 12 microscopy and PCR positive P. falciparum, but failed to detect 12/13 microscopy and PCR positive P. vivax infections. Conclusion Asymptomatic malaria infections and infections with low and sub-microscopic parasite densities are highly prevalent in Temotu province where malaria transmission is low. This presents a challenge for elimination since the large proportion of the parasite reservoir will not be detected by standard active and passive case detection. Therefore effective mass screening and treatment campaigns will most likely need more sensitive assays such as a field deployable molecular based assay.

Exploring Retinal Markers of Diabetic Neuropathy

Purpose : To investigate the application of retinal nerve fibre layer (RNFL) thickness as a marker for severity of diabetic peripheral neuropathy (DPN) in people with Type 2 diabetes. Methods : This was a cross-sectional study whereby 61 participants (mean age 61 [41-75 years], mean duration of diabetes 14 [1-40 years], 70% male) with Type 2 diabetes and DPN underwent optical coherence tomography (OCT) scans. Global and 4 quadrant (TSNI) RNFL thicknesses were measured at 3.45mm around the optic nerve head of one eye. Neuropathy disability score (NDS) was used to assess the severity of DPN on a 0 to 10 scale. Participants were divided into three age-matched groups representing mild (NDS=3-5), moderate (NDS=6-8) and severe (NDS=9-10) neuropathy. Two regression models were fitted for statistical analysis: 1) NDS scores as co-variate for global and quadrant RNFL thicknesses, 2) NDS groups as a factor for global RNFL thickness only. Results : Mean (SD) RNFL thickness (µm) was 103(9) for mild neuropathy (n=34), 101(10) for moderate neuropathy (n=16) and 95(13) in the group with severe neuropathy (n=11). Global RNFL thickness and NDS scores were statistically significantly related (b=-1.20, p=0.048). When neuropathy was assessed across groups, a trend of thinner mean RNFL thickness was observed with increasing severity of neuropathy; however, this result was not statistically significant (F=2.86, p=0.065). TSNI quadrant analysis showed that mean RNFL thickness reduction in the inferior quadrant was 2.55 µm per 1 unit increase in NDS score (p=0.005). However, the regression coefficients were not statistically significant for RNFL thickness in the superior (b=-1.0, p=0.271), temporal (b=-0.90, p=0.238) and nasal (b=-0.99, p=0.205) quadrants. Conclusions : RNFL thickness was reduced with increasing severity of DPN and the effect was most evident in the inferior quadrant. Measuring RNFL thickness using OCT may prove to be a useful, non-invasive technique for identifying severity of DPN and may also provide additional insight into common mechanisms for peripheral neuropathy and RNFL damage.

Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images

Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.