Improving the hydrogen gas sensing performance of Pt/MoO3 nanoplatelets using a nano thick layer of La2O3

In this paper, we present how a thin RF sputtered layer of lanthanum oxide (La2O3) can alter electrical and improve hydrogen gas sensing characteristics of Pt/molybdenum oxide (MoO3) nanostructures Schottky diodes. We derived the barrier height, ideality factor and dielectric constant from the measured I–V characteristics at operating temperatures in the range of 25–300 ◦C. The dynamic response, response and recovery times were obtained upon exposure to hydrogen gas at different concentrations. Analysis of the results indicated a substantial improvement to the voltage shift sensitivity of the sensors incorporating the La2O3 layer. We associate this enhancement to the formation of numerous trap states due to the presence of the La2O3 thin film on the MoO3 nanoplatelets. These trap states increase the intensity of the dipolar charges at the metal–semiconductor interface, which induce greater bending of the energy bands. However, results also indicate that the presence of La2O3 trap states also increases response and recover times as electrons trapping and de-trapping processes occur before they can pass through this thin dielectric layer.

Heteroscedastic probabilistic linear discriminant analysis for manifold learning in video-based face recognition

To recognize faces in video, face appearances have been widely modeled as piece-wise local linear models which linearly approximate the smooth yet non-linear low dimensional face appearance manifolds. The choice of representations of the local models is crucial. Most of the existing methods learn each local model individually meaning that they only anticipate variations within each class. In this work, we propose to represent local models as Gaussian distributions which are learned simultaneously using the heteroscedastic probabilistic linear discriminant analysis (PLDA). Each gallery video is therefore represented as a collection of such distributions. With the PLDA, not only the within-class variations are estimated during the training, the separability between classes is also maximized leading to an improved discrimination. The heteroscedastic PLDA itself is adapted from the standard PLDA to approximate face appearance manifolds more accurately. Instead of assuming a single global within-class covariance, the heteroscedastic PLDA learns different within-class covariances specific to each local model. In the recognition phase, a probe video is matched against gallery samples through the fusion of point-to-model distances. Experiments on the Honda and MoBo datasets have shown the merit of the proposed method which achieves better performance than the state-of-the-art technique.

Pt/TiO2 nanotubes/SiC schottky diodes for hydrogen gas sensing applications

Titanium oxide nanotubes Schottky diodes were fabricated for hydrogen gas sensing applications. The TiO2 nanotubes were synthesized via anodization of RF sputtered titanium films on SiC substrates. Two anodization potentials of 5 V and 20 V were used. Scanning electron microscopy of the synthesized films revealed nanotubes with avarage diameters of 20 nm and 75 nm. X-ray diffraction analysis revealed that the composition of the oxide varied with the anodization potential. TiO2 (anatase) being formed preferentially at 5 V and TiO (no anatase) at 20 V. Current-voltage characteristics of the diodes were studied towards hydrogen at temperatures from 25°C to 250°C. At constant current bias of −500 μA and 250°C, the lateral voltage shifts of 800 mV and 520 mV were recorded towards 1% hydrogen for the 5 V and 20 V anodized nanotubes, respectively.

Synthesis, structural analysis, and thermal decomposition studies of [(NH3)2BH2]B3H8

Boron–nitrogen containing compounds with high hydrogen contents as represented by ammonia borane (NH3BH3) have recently attracted intense interest for potential hydrogen storage applications. One such compound is [(NH3)2BH2]B3H8 with a capacity of 18.2 wt% H. Two safe and efficient synthetic routes to [(NH3)2BH2]B3H8 have been developed for the first time since it was discovered 50 years ago. The new synthetic routes avoid a dangerous starting chemical, tetraborane (B4H10), and afford a high yield. Single crystal X-ray diffraction analysis reveals N–Hδ+Hδ−–B dihydrogen interactions in the [(NH3)2BH2]B3H8·18-crown-6 adduct. Extended strong dihydrogen bonds were observed in pure [(NH3)2BH2]B3H8 through crystal structure solution based upon powder X-ray analysis. Pyrolysis of [(NH3)2BH2]B3H8 leads to the formation of hydrogen gas together with appreciable amounts of volatile boranes below 160 °C.

Sustainable infrastructure procurement in Australia : standard vs. project practices

The Australian Government and most Australian road authorities have set ambitious greenhouse gas emission (GHGe) reduction targets for the near future, many of which have translated into action plans. However, previous research has shown that the various Australian state road authorities are at different stages of implementing ‘green’ initiatives in construction planning and development, with considerable gaps in their monitoring, tendering, and contracting. This study illustrates the differences between procurement standards and project specific practices that aim to reduce GHGe from road construction projects in three of the largest Australian road construction clients, with a focus on the tools used, contract type and incentives for better performance.

A comprehensive dual-scale wood torrefaction model : application to the analysis of thermal run-away in industrial heat treatment processes

A dual-scale model of the torrefaction of wood was developed and used to study industrial configurations. At the local scale, the computational code solves the coupled heat and mass transfer and the thermal degradation mechanisms of the wood components. At the global scale, the two-way coupling between the boards and the stack channels is treated as an integral component of the process. This model is used to investigate the effect of the stack configuration on the heat treatment of the boards. The simulations highlight that the exothermic reactions occurring in each single board can be accumulated along the stack. This phenomenon may result in a dramatic eterogeneity of the process and poses a serious risk of thermal runaway, which is often observed in industrial plants. The model is used to explain how thermal runaway can be lowered by increasing the airflow velocity, the sticker thickness or by gas flow reversal.

Intelligent reliability analysis with incomplete covariates

The reliability analysis is crucial to reducing unexpected down time, severe failures and ever tightened maintenance budget of engineering assets. Hazard based reliability methods are of particular interest as hazard reflects the current health status of engineering assets and their imminent failure risks. Most existing hazard models were constructed using the statistical methods. However, these methods were established largely based on two assumptions: one is the assumption of baseline failure distributions being accurate to the population concerned and the other is the assumption of effects of covariates on hazards. These two assumptions may be difficult to achieve and therefore compromise the effectiveness of hazard models in the application. To address this issue, a non-linear hazard modelling approach is developed in this research using neural networks (NNs), resulting in neural network hazard models (NNHMs), to deal with limitations due to the two assumptions for statistical models. With the success of failure prevention effort, less failure history becomes available for reliability analysis. Involving condition data or covariates is a natural solution to this challenge. A critical issue for involving covariates in reliability analysis is that complete and consistent covariate data are often unavailable in reality due to inconsistent measuring frequencies of multiple covariates, sensor failure, and sparse intrusive measurements. This problem has not been studied adequately in current reliability applications. This research thus investigates such incomplete covariates problem in reliability analysis. Typical approaches to handling incomplete covariates have been studied to investigate their performance and effects on the reliability analysis results. Since these existing approaches could underestimate the variance in regressions and introduce extra uncertainties to reliability analysis, the developed NNHMs are extended to include handling incomplete covariates as an integral part. The extended versions of NNHMs have been validated using simulated bearing data and real data from a liquefied natural gas pump. The results demonstrate the new approach outperforms the typical incomplete covariates handling approaches. Another problem in reliability analysis is that future covariates of engineering assets are generally unavailable. In existing practices for multi-step reliability analysis, historical covariates were used to estimate the future covariates. Covariates of engineering assets, however, are often subject to substantial fluctuation due to the influence of both engineering degradation and changes in environmental settings. The commonly used covariate extrapolation methods thus would not be suitable because of the error accumulation and uncertainty propagation. To overcome this difficulty, instead of directly extrapolating covariate values, projection of covariate states is conducted in this research. The estimated covariate states and unknown covariate values in future running steps of assets constitute an incomplete covariate set which is then analysed by the extended NNHMs. A new assessment function is also proposed to evaluate risks of underestimated and overestimated reliability analysis results. A case study using field data from a paper and pulp mill has been conducted and it demonstrates that this new multi-step reliability analysis procedure is able to generate more accurate analysis results.

Association analysis of a highly polymorphic CAG Repeat in the human potassium channel gene KCNN3 and migraine susceptibility

Background Migraine is a polygenic multifactorial disease, possessing environmental and genetic causative factors with multiple involved genes. Mutations in various ion channel genes are responsible for a number of neurological disorders. KCNN3 is a neuronal small conductance calcium-activated potassium channel gene that contains two polyglutamine tracts, encoded by polymorphic CAG repeats in the gene. This gene plays a critical role in determining the firing pattern of neurons and acts to regulate intracellular calcium channels. Methods The present association study tested whether length variations in the second (more 3') polymorphic CAG repeat in exon 1 of the KCNN3 gene, are involved in susceptibility to migraine with and without aura (MA and MO). In total 423 DNA samples from unrelated individuals, of which 202 consisted of migraine patients and 221 non-migraine controls, were genotyped and analysed using a fluorescence labelled primer set on an ABI310 Genetic Analyzer. Allele frequencies were calculated from observed genotype counts for the KCNN3 polymorphism. Analysis was performed using standard contingency table analysis, incorporating the chi-squared test of independence and CLUMP analysis. Results Overall, there was no convincing evidence that KCNN3 CAG lengths differ between Caucasian migraineurs and controls, with no significant difference in the allelic length distribution of CAG repeats between the population groups (P = 0.090). Also the MA and MO subtypes did not differ significantly between control allelic distributions (P > 0.05). The prevalence of the long CAG repeat (>19 repeats) did not reach statistical significance in migraineurs (P = 0.15), nor was there a significant difference between the MA and MO subgroups observed compared to controls (P = 0.46 and P = 0.09, respectively), or between MA vs MO (P = 0.40). Conclusion This association study provides no evidence that length variations of the second polyglutamine array in the N-terminus of the KCNN3 channel exert an effect in the pathogenesis of migraine.

The measurement of adenosine and estrogen receptor expression in rat brains following ovariectomy using quantitative PCR analysis

In our laboratory we have developed a quantitative-polymerase chain reaction (Q-PCR) strategy to examine the differential expression of adenosine receptor (ADOR), A(1), A(2A), A(2B) and A(3), and estrogen receptors (ER) alpha and beta. Brain and uterine mRNA were first used to optimise specific amplification conditions prior to SYBR Green I real time analysis of receptor subtype expression. SYBR Green I provided a convenient and sensitive means of examining specific PCR amplification product in real time, and allowed the generation of standard curves from which relative receptor abundance could be determined. Real time Q-PCR analysis was then performed, to examine changes in receptor expression levels in brains of adult female Wistar rats 3-month post ovariectomy. Comparison with sham-operated age-matched control rats demonstrated both comparative and absolute-copy number changes in receptor levels. Evaluation of both analytical methods investigated 18S rRNA as an internal reference for comparative gene expression analysis in the brain. The results of this study revealed preferential repression of ADORA(2A) (>4-fold down) and consistent (>2-fold) down-regulation of ADORA(1), ADORA(3), and ER-beta, following ovariectomy. No change was found in ADORA(2B) or ER-alpha. Analysis of absolute copy number in this study revealed a correlation between receptor expression in response to ovariectomy, and relative receptor subtype abundance in the brain.

Identification and simultaneous analysis of harmane, harmol, isovitexin and vitexin in Passiflora incarnata extracts with a novel HLPC method

A high performance liquid chromatographic method for the simultaneous analysis of two flavonoids (iso-vitexin and vitexin), and three indole alkaloids (harmane, harmine, and harmol) was developed. This method was then utilised to quantitate levels of these five constituents in methanolic extracts of Australian Passiflora incarnata. HPLC analysis was performed using a Waters™ Novapak C18 (150 × 4 mm, 4 μm) column, with a gradient solvent system of methanol-water-acetic acid. Detection was achieved by PDA UV (254 nm) and fluorescence (excitation 254 nm, emission 414 nm), utilising the external standard method to obtain quantification.

Vehicle energy throughput analysis as a drivetrain motor design aid

There are many variables to consider in the design of an electric motor. However, meeting the performance requirements for an electric vehicle drive may cause a designer to loose focus on its typical operation and hence fail to optimise the motor in the region where it processes the most power. This paper investigates operating requirements of electric vehicle motor drives using the University concept vehicle as an example. The paper outlines a methodology for determining primary operating region of a vehicle drive. The methodology is applied to standard driving cycles that are commonly used in the design and testing of vehicles.

Environmental sustainability of urban road transport : an integrated analysis for life cycle emission impact

Despite of significant contributions of urban road transport to global economy and society, it is one of the largest sources of local and global emission impact. In order to address the environmental concerns of urban road transport it is imperative to achieve a holistic understanding of contributory factors causing emissions which requires a complete look onto its whole life cycle. Previous studies were mainly based on segmental views which mostly studied environmental impacts of individual transport modes and very few considered impacts other than operational phase. This study develops an integrated life cycle inventory model for urban road transport emissions from a holistic modal perspective. Singapore case was used to demonstrate the model. Results show that total life cycle greenhouse gas emission from Singapore’s road transport sector is 7.8 million tons per year. The total amount of criteria air pollutants are also estimated in this study.

Fracture analysis of wind turbine main shaft

Shaft fracture at an early stage of operation is a common problem for a certain type of wind turbine. To determine the cause of shaft failure a series of experimental tests were conducted to evaluate the chemical composition and mechanical properties. A detail analysis involving macroscopic feature and microstructure analysis of the material of the shaft was also performed to have an in depth knowledge of the cause of fracture. The experimental tests and analysis results show that there are no significant differences in the material property of the main shaft when comparing it with the Standard, EN10083-3:2006. The results show that stress concentration on the shaft surface close to the critical section of the shaft due to rubbing of the annular ring and coupled with high stress concentration caused by the change of inner diameter of the main shaft are the main reasons that result in fracture of the main shaft. In addition, inhomogeneity of the main shaft micro-structure also accelerates up the fracture process of the main shaft. In addition, the theoretical calculation of equivalent stress at the end of the shaft was performed, which demonstrate that cracks can easily occur under the action of impact loads. The contribution of this paper is to provide a reference in fracture analysis of similar main shaft of wind turbines.

Interventions for increasing ankle joint dorsiflexion : a systematic review and meta-analysis

BACKGROUND: Ankle joint equinus, or restricted dorsiflexion range of motion (ROM), has been linked to a range of pathologies of relevance to clinical practitioners. This systematic review and meta-analysis investigated the effects of conservative interventions on ankle joint ROM in healthy individuals and athletic populations. METHODS: Keyword searches of Embase Medline Cochrane and CINAHL databases were performed with the final search being run in August 2013. Studies were eligible for inclusion if they assessed the effect of a non-surgical intervention on ankle joint dorsiflexion in healthy populations. Studies were quality rated using a standard quality assessment scale. Standardised mean differences (SMDs) and 95% confidence intervals (CIs) were calculated and results were pooled where study methods were homogenous. RESULTS: Twenty-three studies met eligibility criteria, with a total of 734 study participants. Results suggest that there is some evidence to support the efficacy of static stretching alone (SMDs: range 0.70 to 1.69) and static stretching in combination with ultrasound (SMDs: range 0.91 to 0.95), diathermy (SMD 1.12), diathermy and ice (SMD 1.16), heel raise exercises (SMDs: range 0.70 to 0.77), superficial moist heat (SMDs: range 0.65 to 0.84) and warm up (SMD 0.87) in improving ankle joint dorsiflexion ROM. CONCLUSIONS: Some evidence exists to support the efficacy of stretching alone and stretching in combination with other therapies in increasing ankle joint ROM in healthy individuals. There is a paucity of quality evidence to support the efficacy of other non-surgical interventions, thus further research in this area is warranted.

SRL 172 (killed Mycobacterium vaccae) in addition to standard chemotherapy improves quality of life without affecting survival, in patients with advanced non-small-cell lung cancer : phase III results

Background: This open-label, randomised phase III study was designed to further investigate the clinical activity and safety of SRL172 (killed Mycobacterium vaccae suspension) with chemotherapy in the treatment of non-small-cell lung cancer (NSCLC). Patients and methods: Patients were randomised to receive platinum-based chemotherapy, consisting of up to six cycles of MVP (mitomycin, vinblastine and cisplatin or carboplatin) with (210 patients) or without (209 patients) monthly SRL172. Results: There was no statistical difference between the two groups in overall survival (primary efficacy end point) over the course of the study (median overall survival of 223 days versus 225 days; P = 0.65). However, a higher proportion of patients were alive at the end of the 15-week treatment phase in the chemotherapy plus SRL172 group (90%), than in the chemotherapy alone group (83%) (P = 0.061). At the end of the treatment phase, the response rate was 37% in the combined group and 33% in the chemotherapy alone group. Patients in the chemotherapy alone group had greater deterioration in their Global Health Status score (-14.3) than patients in the chemotherapy plus SRL172 group (-6.6) (P = 0.02). Conclusion: In this non-placebo controlled trial, SRL172 when added to standard cancer chemotherapy significantly improved patient quality of life without affecting overall survival times. © 2004 European Society for Medical Oncology.