Made-to-order nanocarbons through deterministic plasma nanotechnology

Through a combinatorial approach involving experimental measurement and plasma modelling, it is shown that a high degree of control over diamond-like nanocarbon film sp3/sp2 ratio (and hence film properties) may be exercised, starting at the level of electrons (through modification of the plasma electron energy distribution function). Hydrogenated amorphous carbon nanoparticle films with high percentages of diamond-like bonds are grown using a middle-frequency (2 MHz) inductively coupled Ar + CH4 plasma. The sp3 fractions measured by X-ray photoelectron spectroscopy (XPS) and Raman spectroscopy in the thin films are explained qualitatively using sp3/sp2 ratios 1) derived from calculated sp3 and sp2 hybridized precursor species densities in a global plasma discharge model and 2) measured experimentally. It is shown that at high discharge power and lower CH4 concentrations, the sp3/sp2 fraction is higher. Our results suggest that a combination of predictive modeling and experimental studies is instrumental to achieve deterministically grown made-to-order diamond-like nanocarbons suitable for a variety of applications spanning from nano-magnetic resonance imaging to spin-flip quantum information devices. This deterministic approach can be extended to graphene, carbon nanotips, nanodiamond and other nanocarbon materials for a variety of applications

Silicon on silicon : self-organized nanotip arrays formed in reactive Ar+H2 plasmas

The formation of arrays of vertically aligned nanotips on a moderately heated (up to 500 degrees C) Si surface exposed to reactive low-temperature radio frequency (RF) Ar+H(2) plasmas is studied. It is demonstrated that the nanotip surface density, aspect ratio and height dispersion strongly depend on the substrate temperature, discharge power, and gas composition. It is shown that nanotips with aspect ratios from 2.0 to 4.0 can only be produced at a higher RF power density (41.7 mW cm(-3)) and a hydrogen content of about 60%, and that larger aspect ratios can be achieved at substrate temperatures of about 300 degrees C. The use of higher (up to 500 degrees C) temperatures leads to a decrease of the aspect ratio but promotes the formation of more uniform arrays with the height dispersion decreasing to 1.5. At lower (approximately 20 mW cm(-3)) RF power density, only semispherical nanodots can be produced. Based on these experimental results, a nanotip formation scenario is proposed suggesting that sputtering, etching, hydrogen termination, and atom/radical re-deposition are the main concurrent mechanisms for the nanostructure formation. Numerical calculations of the ion flux distribution and hydrogen termination profiles can be used to predict the nanotip shapes and are in a good agreement with the experimental results. This approach can be applied to describe the kinetics of low-temperature formation of other nanoscale materials by plasma treatment.

Catalytic probes with nanostructured surface for gas/discharge diagnostics : a study of a probe signal behaviour

Catalytic probes are used for plasma diagnostics in order to quantify the density of neutral atoms. The probe response primarily depends on the probe material and its surface morphology. Here we report on the design, operation and modelling of the response of niobium pentoxide sensors with a flat and nanowire (NW) surfaces. These sensors were used to detect neutral oxygen atoms in the afterglow region of an inductively coupled rf discharge in oxygen. A very different response of the flat-surface and NW probes to the varying densities of oxygen atoms was explained by modelling heat conduction and taking into account the associated temperature gradients. It was found that the nanostructure probe can measure in a broader range than the flat oxide probe due to an increase in the surface to volume ratio, and the presence of nanostructures which act as a thermal barrier against sensor overheating. These results can be used for the development of the new generation of catalytic probes for gas/discharge diagnostics in a range of industrial and environmental applications.

Evaluation of resonant damping techniques for Z-source current-type inverter

For the renewable energy sources whose outputs vary continuously, a Z-source current-type inverter has been proposed as a possible buck-boost alternative for grid-interfacing. With a unique X-shaped LC network connected between its dc power source and inverter topology, Z-source current-type inverter is however expected to suffer from compounded resonant complications in addition to those associated with its second-order output filter. To improve its damping performance, this paper proposes the careful integration of Posicast or three-step compensators before the inverter pulse-width modulator for damping triggered resonant oscillations. In total, two compensators are needed for wave-shaping the inverter boost factor and modulation ratio, and they can conveniently be implemented using first-in first-out stacks and embedded timers of modern digital signal processors widely used in motion control applications. Both techniques are found to damp resonance of ac filter well, but for cases of transiting from current-buck to boost state, three-step technique is less effective due to the sudden intermediate discharging interval introduced by its non-monotonic stepping (unlike the monotonic stepping of Posicast damping). These findings have been confirmed both in simulations and experiments using an implemented laboratory prototype.

Biodiesel production from non-edible beauty leaf (Calophyllum Inophyllum) oil : process optimization using response surface methodology (RSM)

In recent years, the beauty leaf plant (Calophyllum Inophyllum) is being considered as a potential 2nd generation biodiesel source due to high seed oil content, high fruit production rate, simple cultivation and ability to grow in a wide range of climate conditions. However, however, due to the high free fatty acid (FFA) content in this oil, the potential of this biodiesel feedstock is still unrealized, and little research has been undertaken on it. In this study, transesterification of beauty leaf oil to produce biodiesel has been investigated. A two-step biodiesel conversion method consisting of acid catalysed pre-esterification and alkali catalysed transesterification has been utilized. The three main factors that drive the biodiesel (fatty acid methyl ester (FAME)) conversion from vegetable oil (triglycerides) were studied using response surface methodology (RSM) based on a Box-Behnken experimental design. The factors considered in this study were catalyst concentration, methanol to oil molar ratio and reaction temperature. Linear and full quadratic regression models were developed to predict FFA and FAME concentration and to optimize the reaction conditions. The significance of these factors and their interaction in both stages was determined using analysis of variance (ANOVA). The reaction conditions for the largest reduction in FFA concentration for acid catalysed pre-esterification was 30:1 methanol to oil molar ratio, 10% (w/w) sulfuric acid catalyst loading and 75 °C reaction temperature. In the alkali catalysed transesterification process 7.5:1 methanol to oil molar ratio, 1% (w/w) sodium methoxide catalyst loading and 55 °C reaction temperature were found to result in the highest FAME conversion. The good agreement between model outputs and experimental results demonstrated that this methodology may be useful for industrial process optimization for biodiesel production from beauty leaf oil and possibly other industrial processes as well.

Longitudinal Assessment of Neuropathy in Diabetes using novel ophthalmic MARKers (LANDMark): Baseline findings

Purpose:Over the past decade, corneal nerve morphology and corneal sensation threshold have been explored as potential surrogate markers for the evaluation of diabetic neuropathy. We present the baseline findings of a Longitudinal Assessment of Neuropathy in Diabetes using novel ophthalmic Markers (LANDMark). Methods:The LANDMark Study is a 5-year, two-site, natural history (observational) study of individuals with Type 1 diabetes stratified into those with (T1W) and without (T1WO) neuropathy according to the Toronto criteria, and control subjects. All study participants undergo detailed annual assessment of neuropathy including corneal nerve parameters measured using corneal confocal microscopy and corneal sensitivity measured using non-contact corneal esthesiometry. Results:396 eligible individuals (208 in Brisbane and 188 in Manchester) were assessed: 76 T1W, 166 T1WO and 154 controls. Corneal sensation threshold (mbars) was significantly higher in T1W (1.0 ± 1.1) than T1WO (0.7 ± 0.7) and controls (0.6 ± 0.4) (P=0.002); post-hoc analysis (PHA) revealed no difference between T1WO and controls (Tukey HSD, P=0.502). Corneal nerve fiber length (mm/mm2) (CNFL) was lower in T1W (13.8 ± 6.4) than T1WO (19.1 ± 5.8) and controls (23.2 ± 6.3) (P<0.001); PHA revealed CNFL to be lower in T1W than T1WO, and lower in both of these groups than controls (P<0.001). Corneal nerve branch density (branches/mm2) (CNBD) was significantly lower in T1W (40 ± 32) than T1WO (62 ± 37) and controls (83 ± 46) (P<0.001); PHA showed CNBD was lower in T1W than T1WO, and lower in both groups than controls (P<0.001). Alcohol and cigarette consumption did not differ between groups, although age, BMI, BP, waist circumference, HbA1c, albumin-creatinine ratio, and cholesterol were slightly greater in T1W than T1WO (p<0.05). Some site differences were observed. Conclusions:The LANDMark baseline findings confirm that corneal sensitivity and corneal nerve morphometry can detect differences in neuropathy status in individuals with Type 1 diabetes and healthy controls. Corneal nerve morphology is significantly abnormal even in diabetic patients ‘without neuropathy’ compared to control participants. Results of the longitudinal trial will assess the capability of these tests for monitoring change in these parameters over time as potential surrogate markers for neuropathy.

Warm

Warm was series of collaborative fashion designs workshops delivered as part of the International Kids Carnival hosted by the Venice Biennale Feb 11th - Feb 21st 2012. The workshops were based in the broad research domain of Design for Sustainability and involved an up-cycling process whereby school -aged children how to transform t-shirts into scarves and hats. Workshop participants learnt about the social and ethical imperative to re-cycle, the ways in which garments can be transformed and consequently re-valued, and how form, colour and proportion play a role in the design process. The workshops involved the development of highly visual models, images and translations.

DS-VBF : dual sink vector-based routing protocol for underwater wireless sensor network

Underwater wireless sensor networks (UWSNs) have become the seat of researchers' attention recently due to their proficiency to explore underwater areas and design different applications for marine discovery and oceanic surveillance. One of the main objectives of each deployed underwater network is discovering the optimized path over sensor nodes to transmit the monitored data to onshore station. The process of transmitting data consumes energy of each node, while energy is limited in UWSNs. So energy efficiency is a challenge in underwater wireless sensor network. Dual sinks vector based forwarding (DS-VBF) takes both residual energy and location information into consideration as priority factors to discover an optimized routing path to save energy in underwater networks. The modified routing protocol employs dual sinks on the water surface which improves network lifetime. According to deployment of dual sinks, packet delivery ratio and the average end to end delay are enhanced. Based on our simulation results in comparison with VBF, average end to end delay reduced more than 80%, remaining energy increased 10%, and the increment of packet reception ratio was about 70%.

Inter-cycle variability of ignition delay in an ethanol fumigated common rail diesel engine

An experimental study has been performed to investigate the ignition delay of a modern heavy-duty common-rail diesel engine run with fumigated ethanol substitutions up to 40% on an energy basis. The ignition delay was determined through the use of statistical modelling in a Bayesian framework this framework allows for the accurate determination of the start of combustion from single consecutive cycles and does not require any differentiation of the in-cylinder pressure signal. At full load the ignition delay has been shown to decrease with increasing ethanol substitutions and evidence of combustion with high ethanol substitutions prior to diesel injection have also been shown experimentally and by modelling. Whereas, at half load increasing ethanol substitutions have increased the ignition delay. A threshold absolute air to fuel ratio (mole basis) of above ~110 for consistent operation has been determined from the inter-cycle variability of the ignition delay, a result that agrees well with previous research of other in-cylinder parameters and further highlights the correlation between the air to fuel ratio and inter-cycle variability. Numerical modelling to investigate the sensitivity of ethanol combustion has also been performed. It has been shown that ethanol combustion is sensitive to the initial air temperature around the feasible operating conditions of the engine. Moreover, a negative temperature coefficient region of approximately 900{1050 K (the approximate temperature at fuel injection) has been shown with for n-heptane and n-heptane/ethanol blends in the numerical modelling. A consequence of this is that the dominate effect influencing the ignition delay under increasing ethanol substitutions may rather be from an increase in chemical reactions and not from in-cylinder temperature. Further investigation revealed that the chemical reactions at low ethanol substitutions are different compared to the high (> 20%) ethanol substitutions.

Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group

The pattern of structural brain alterations associated with major depressive disorder (MDD) remains unresolved. This is in part due to small sample sizes of neuroimaging studies resulting in limited statistical power, disease heterogeneity and the complex interactions between clinical characteristics and brain morphology. To address this, we meta-analyzed three-dimensional brain magnetic resonance imaging data from 1728 MDD patients and 7199 controls from 15 research samples worldwide, to identify subcortical brain volumes that robustly discriminate MDD patients from healthy controls. Relative to controls, patients had significantly lower hippocampal volumes (Cohen’s d=−0.14, % difference=−1.24). This effect was driven by patients with recurrent MDD (Cohen’s d=−0.17, % difference=−1.44), and we detected no differences between first episode patients and controls. Age of onset ⩽21 was associated with a smaller hippocampus (Cohen’s d=−0.20, % difference=−1.85) and a trend toward smaller amygdala (Cohen’s d=−0.11, % difference=−1.23) and larger lateral ventricles (Cohen’s d=0.12, % difference=5.11). Symptom severity at study inclusion was not associated with any regional brain volumes. Sample characteristics such as mean age, proportion of antidepressant users and proportion of remitted patients, and methodological characteristics did not significantly moderate alterations in brain volumes in MDD. Samples with a higher proportion of antipsychotic medication users showed larger caudate volumes in MDD patients compared with controls. This currently largest worldwide effort to identify subcortical brain alterations showed robust smaller hippocampal volumes in MDD patients, moderated by age of onset and first episode versus recurrent episode status.

A robust optimization approach for index tracking problem

Index tracking is an investment approach where the primary objective is to keep portfolio return as close as possible to a target index without purchasing all index components. The main purpose is to minimize the tracking error between the returns of the selected portfolio and a benchmark. In this paper, quadratic as well as linear models are presented for minimizing the tracking error. The uncertainty is considered in the input data using a tractable robust framework that controls the level of conservatism while maintaining linearity. The linearity of the proposed robust optimization models allows a simple implementation of an ordinary optimization software package to find the optimal robust solution. The proposed model of this paper employs Morgan Stanley Capital International Index as the target index and the results are reported for six national indices including Japan, the USA, the UK, Germany, Switzerland and France. The performance of the proposed models is evaluated using several financial criteria e.g. information ratio, market ratio, Sharpe ratio and Treynor ratio. The preliminary results demonstrate that the proposed model lowers the amount of tracking error while raising values of portfolio performance measures.

Text segmentation in unconstrained hand-drawings in whiteboard photos

In this paper we present a robust method to detect handwritten text from unconstrained drawings on normal whiteboards. Unlike printed text on documents, free form handwritten text has no pattern in terms of size, orientation and font and it is often mixed with other drawings such as lines and shapes. Unlike handwritings on paper, handwritings on a normal whiteboard cannot be scanned so the detection has to be based on photos. Our work traces straight edges on photos of the whiteboard and builds graph representation of connected components. We use geometric properties such as edge density, graph density, aspect ratio and neighborhood similarity to differentiate handwritten text from other drawings. The experiment results show that our method achieves satisfactory precision and recall. Furthermore, the method is robust and efficient enough to be deployed in a mobile device. This is an important enabler of business applications that support whiteboard-centric visual meetings in enterprise scenarios. © 2012 IEEE.

Computer analysis of impact behavior of concrete filled steel tube columns

This paper presents a numerical study of the response of axially loaded concrete filled steel tube (CFST) columns under lateral impact loading using explicit non-linear finite element techniques. The aims of this paper are to evaluate the vulnerability of existing columns to credible impact events as well as to contribute new information towards the safe design of such vulnerable columns. The model incorporates concrete confinement, strain rate effects of steel and concrete, contact between the steel tube and concrete and dynamic relaxation for pre-loading, which is a relatively recent method for applying a pre-loading in the explicit solver. The finite element model was first verified by comparing results with existing experimental results and then employed to conduct a parametric sensitivity analysis. The effects of various structural and load parameters on the impact response of the CFST column were evaluated to identify the key controlling factors. Overall, the major parameters which influence the impact response of the column are the steel tube thickness to diameter ratio, the slenderness ratio and the impact velocity. The findings of this study will enhance the current state of knowledge in this area and can serve as a benchmark reference for future analysis and design of CFST columns under lateral impact.

Development of a new design expression for the in-plane shear capacity of the partially grouted concrete masonry walls

Partially grouted masonry walls subjected to in-plane shear exhibit a complex behaviour because of the influence of the aspect ratio, the pre-compression, the grouting pattern, the ratios of the horizontal and the vertical reinforcements, the boundary conditions and the characteristics of the constituent materials. The existing in-plane shear expressions for the partially grouted masonry are formulated as sum of strength of three parameters, namely, the masonry, the reinforcement and the axial force. The parameter ‘masonry’ includes the wall aspect ratio and the masonry compressive strength; the aspect ratio of the unreinforced panel inscribed into the grouted cores and bond beams are not considered, although failure is often dominated by these unreinforced masonry panels. This paper describes the dominance of these panels, particularly those that are squat, to the shear capacity of whole of shear walls. Further, the current design formulae are shown highly un-conservative by many researchers; this paper provides a potential reason for this un-conservativeness. It is shown that by including an additional term of the unreinforced panel aspect ratio a rational design formula could be established. This new expression is validated with independent test results reported in the literature – both Australian and overseas; the predictions are shown to be conservative.

Predictive models for water sources with high susceptibility for bromine-containing disinfection by-product formation: Implications for water treatment

This study examines a matrix of synthetic water samples designed to include conditions that favour brominated disinfection by-product (Br-DBP) formation, in order to provide predictive models suitable for high Br-DBP forming waters such as salinity-impacted waters. Br-DBPs are known to be more toxic than their chlorinated analogues, in general, and their formation may be favoured by routine water treatment practices such as coagulation/flocculation under specific conditions; therefore, circumstances surrounding their formation must be understood. The chosen factors were bromide concentration, mineral alkalinity, bromide to dissolved organic carbon (Br/DOC) ratio and Suwannee River natural organic matter concentration. The relationships between these parameters and DBP formation were evaluated by response surface modelling of data generated using a face-centred central composite experimental design. Predictive models for ten brominated and/or chlorinated DBPs are presented, as well as models for total trihalomethanes (tTHMs) and total dihaloacetonitriles (tDHANs), and bromide substitution factors for the THMs and DHANs classes. The relationships described revealed that increasing alkalinity and increasing Br/DOC ratio were associated with increasing bromination of THMs and DHANs, suggesting that DOC lowering treatment methods that do not also remove bromide such as enhanced coagulation may create optimal conditions for Br-DBP formation in waters in which bromide is present.