Mechanochemical synthesis of TiO2/NiFe2O4 magnetic catalysts for operation under RF field

Composite NiFe2O4–TiO2 magnetic catalysts were prepared by mechanochemical synthesis from a mixture of titania supported nickel ferrite nanoparticles and P25 titania (Evonic). The former provides fast and efficient heating under radiofrequency field, while the latter serves as an active catalyst or catalyst support. The highest heating rate was observed over a catalyst prepared for a milling time of 30 min. The catalytic activity was measured over the sulfated composite catalysts in the condensation of aniline and 3-phenylbutyric acid in a stirred tank reactor and in a continuous RF heated flow reactor in the 140–170 °C range. The product yield of 47% was obtained over the sulfated P25 titania catalyst in the flow reactor.

Insight into the mechanism of galactokinase: role of a critical glutamate residue and helix/coil transitions

Galactokinase, the enzyme which catalyses the first committed step in the Leloir pathway, has attracted interest due to its potential as a biocatalyst and as a possible drug target in the treatment of type I galactosemia. The mechanism of the enzyme is not fully elucidated. Molecular dynamics (MD) simulations of galactokinase with the active site residues Arg-37 and Asp-186 altered predicted that two regions (residues 174-179 and 231-240) had different dynamics as a consequence. Interestingly, the same two regions were also affected by alterations in Arg-105, Glu-174 and Arg- 228. These three residues were identified as important in catalysis in previous computational studies on human galactokinase. Alteration of Arg-105 to methionine resulted in a modest reduction in activity with little change in stability. When Arg-228 was changed to methionine, the enzyme’s interaction with both ATP and galactose was affected. This variant was significantly less stable than the wild-type protein. Changing Glu-174 to glutamine (but not to aspartate) resulted in no detectable activity and a less stable enzyme. Overall, these combined in silico and in vitro studies demonstrate the importance of a negative charge at position 174 and highlight the critical role of the dynamics in to key regions of the protein. We postulate that these regions may be critical for mediating the enzyme’s structure and function. 

SPACE-DEPLOYED, THIN-WALLED ENCLOSURE FOR A CRYOGENICALLY-COOLED HIGH TEMPERATURE SUPERCONDUCTING COIL

The interaction of magnetic fields generated by large superconducting coils has multiple applications in space, including actuation of spacecraft or spacecraft components, wireless power transfer, and shielding of spacecraft from radiation and high energy particles. These applications require coils with major diameters as large as 20 meters and a thermal management system to maintain the superconducting material of the coil below its critical temperature. Since a rigid thermal management system, such as a heat pipe, is unsuitable for compact stowage inside a 5 meter payload fairing, a thin-walled thermal enclosure is proposed. A 1.85 meter diameter test article consisting of a bladder layer for containing chilled nitrogen vapor, a restraint layer, and multilayer insulation was tested in a custom toroidal vacuum chamber. The material properties found during laboratory testing are used to predict the performance of the test article in low Earth orbit. Deployment motion of the same test article was measured using a motion capture system and the results are used to predict the deployment in space. A 20 meter major diameter and coil current of 6.7 MA is selected as a point design case. This design point represents a single coil in a high energy particle shielding system. Sizing of the thermal and structural components of the enclosure is completed. The thermal and deployment performance is predicted.

Amplificador de RF Doherty assimétrico de 2-vias

Os atuais esquemas de modulação e acesso ao meio, tais como o Wide- Band Code-Division Multiple Access (WCDMA) ou Orthogonal Frequency- Division Multiple Access (OFDMA), que são otimizados para a gestão eficiente do espetro electromagnético e elevada taxa de transmissão, originam sinais de elevado Peak-to-Average Power Ratio (PAPR) e requisitos de linearidade rigorosos. As arquiteturas de amplificação tradicionais, i.e. baseadas no operação em modo de corrente do dispositivo ativo, são incapazes de satisfazer estes requisitos em simultâneo. Assim, o amplificador de potência (do inglês, Power Ampli_er (PA)) incorre numa degradação significativa de rendimento energético em favor de maior linearidade, aumentando simultaneamente os custos de operação das estacões base para os operadores de telecomunicações móveis e o impacte ambiental. Este trabalho foca-se no estudo da arquitetura Doherty, a principal solução encontrada para melhorar o compromisso linearidade/rendimento para aplicações em estações-base de comunicações móveis. Para tal, são expostos os princípios básicos de amplificadores de rádio frequência assim como a análise teórica do tradicional PA Doherty (do inglês, Doherty Power Amplifier (DhPA)) de duas vias e suas variantes. O estudo _e complementado com o projeto e implementação de um PA excitador, em classe-AB, e de um DhPA de elevada potência, colocando-se em prática a teoria e técnicas de projeto estudadas ao longo deste trabalho, aliadas aos desafios da implementação com dispositivos reais de elevada potência.

Experimental study on the impact of using a fan coil in the evaluation of contaminant removal effectiveness of common air diffusion strategies

Indoor Air 2016 - The 14th International Conference Indoor Air Quality and Climate

Evaluation of tumor recurrences after radical prostatectomy using 18F-Choline PET/CT and 3T multiparametric MRI without endorectal coil: a single center experience

The aim os this study is to evaluate and compare the utility of 18F-fluorocholine (18F-CH) PET/CT versus 3-Tesla multiparametric MRI (mpMRI) without endorectal coil to detect tumor recurrences in patients with biochemical relapse following radical prostatectomy (RP). Secondarily, to identify possible prognostic variables associated with mpMRI and 18F-CH PET/CT findings. Retrospective study of 38 patients who developed biochemical recurrence after RP between the years 2011 and 2015 at our institution. PET/CT and mpMRI were both performed within 30 days of each other in all patients. The PET/CT was reviewed by a nuclear medicine specialist while the mpMRI was assessed by a radiologist, both of whom were blinded to outcomes. The median prostate-specific antigen (PSA) value pre-MRI/PET-CT was 0.9 ng/mL (interquartile range 0.4–2.2 ng/mL). There were no differences in the detection rate between 18F-CH PET/CT and mpMRI for local recurrence (LR), lymph node recurrence (LNR) and bone metastases (BM). Separately, mpMRI and 18F-CH PET/CT were positive for recurrence in 55.2% and 52.6% of cases, respectively, and in 65.7% of cases when findings from both modalities were considered together. The detection of LR was better with combined mpMRI and choline PET/CT versus choline PET/CT alone (34.2% vs 18.4%, p = 0.04). Salvage treatment was modified in 22 patients (57.8%) based on the imaging findings. PSA values on the day of biochemical failure were significantly associated with mpMRI positivity (adjusted odds ratio (OR): 30.9; 95% confidence interval (CI): 1.5–635.8). Gleason score > 7 was significantly associated with PET/CT positivity (OR: 13.9; 95% CI: 1.5–125.6). A significant association was found between PSA doubling time (PSADT) (OR: 1.3; 95% CI: 1.0–1.7), T stage (OR: 21.1; 95% CI: 1.6–272.1), and LR. Multiparametric MRI and 18F-CH PET/CT yield similar detection rates for LR, LNR and pelvic BM. The combination of both imaging techniques provides a better LR detection versus choline PET/CT alone. The initially planned salvage treatment was modified in 57.8% of patients due to imaging findings. In addition to PSA values, Gleason score, T stage, and PSADT may provide valuable data to identify those patients that are most likely to benefit from undergoing both imaging procedures.

A miniaturised wideband frequency synthesiser

Wideband frequency synthesisers have application in many areas, including test instrumentation and defence electronics. Miniaturisation of these devices provides many advantages to system designers, particularly in applications where extra space and weight are expensive. The purpose of this project was to miniaturise a wideband frequency synthesiser and package it for operation in several different environmental conditions while satisfying demanding technical specifications. The four primary and secondary goals to be achieved were: 1. an operating frequency range from low MHz to greater than 40 GHz, with resolution better than 1 MHz, 2. typical RF output power of +10 dBm, with maximum DC supply of 15 W, 3. synthesiser package of only 150  100  30 mm, and 4. operating temperatures from 20C to +71C, and vibration levels over 7 grms. This task was approached from multiple angles. Electrically, the system is designed to have as few functional blocks as possible. Off the shelf components are used for active functions instead of customised circuits. Mechanically, the synthesiser package is designed for efficient use of the available space. Two identical prototype synthesisers were manufactured to evaluate the design methodology and to show the repeatability of the design. Although further engineering development will improve the synthesiser’s performance, this project has successfully demonstrated a level of miniaturisation which sets a new benchmark for wideband synthesiser design. These synthesisers will meet the demands for smaller, lighter wideband sources. Potential applications include portable test equipment, radar and electronic surveillance systems on unmanned aerial vehicles. They are also useful for reducing the overall weight and power consumption of other systems, even if small dimensions are not essential.

Flexible high-power multi DC-DC converters for train systems

This thesis reports on the investigations, simulations and analyses of novel power electronics topologies and control strategies. The research is financed by an Australian Research Council (ARC) Linkage (07-09) grant. Therefore, in addition to developing original research and contributing to the available knowledge of power electronics, it also contributes to the design of a DC-DC converter for specific application to the auxiliary power supply in electric trains. Specifically, in this regard, it contributes to the design of a 7.5 kW DC-DC converter for the industrial partner (Schaffler and Associates Ltd) who supported this project. As the thesis is formatted as a ‘thesis by publication’, the contents are organized around published papers. The research has resulted in eleven papers, including seven peer reviewed and published conference papers, one published journal paper, two journal papers accepted for publication and one submitted journal paper (provisionally accepted subject to few changes). In this research, several novel DC-DC converter topologies are introduced, analysed, and tested. The similarity of all of the topologies devised lies in their ‘current circulating’ switching state, which allows them to store some energy in the inductor, as extra inductor current. The stored energy may be applied to enhance the performance of the converter in the occurrence of load current or input voltage disturbances. In addition, when there is an alternating load current, the ability to store energy allows the converter to perform satisfactorily despite frequently and highly varying load current. In this research, the capability of current storage has been utilised to design topologies for specific applications, and the enhancement of the performance of the considered applications has been illustrated. The simplest DC-DC converter topology, which has a ‘current circulating’ switching state, is the Positive Buck-Boost (PBB) converter (also known as the non-inverting Buck-Boost converter). Usually, the topology of the PBB converter is operating as a Buck or a Boost converter in applications with widely varying input voltage or output reference voltage. For example, in electric railways (the application of our industrial partner), the overhead line voltage alternates from 1000VDC to 500VDC and the required regulated voltage is 600VDC. In the course of this research, our industrial partner (Schaffler and Associates Ltd) industrialized a PBB converter–the ‘Mudo converter’–operating at 7.5 kW. Programming the onboard DSP and testing the PBB converter in experimental and nominal power and voltage was part of this research program. In the earlier stages of this research, the advantages and drawbacks of utilization of the ‘current circulating’ switching state in the positive Buck-Boost converter were investigated. In brief, the advantages were found to be robustness against input voltage and current load disturbances, and the drawback was extra conduction and switching loss. Although the robustness against disturbances is desirable for many applications, the price of energy loss must be minimized to attract attention to the utilization of the PBB converter. In further stages of this research, two novel control strategies for different applications were devised to minimise the extra energy loss while the advantages of the positive Buck-Boost converter were fully utilized. The first strategy is Smart Load Controller (SLC) for applications with pre-knowledge or predictability of input voltage and/or load current disturbances. A convenient example of these applications is electric/hybrid cars where a master controller commands all changes in loads and voltage sources. Therefore, the master controller has a pre-knowledge of the load and input voltage disturbances so it can apply the SLC strategy to utilize robustness of the PBB converter. Another strategy aiming to minimise energy loss and maximise the robustness in the face of disturbance is developed to cover applications with unexpected disturbances. This strategy is named Dynamic Hysteresis Band (DHB), and is used to manipulate the hysteresis band height after occurrence of disturbance to reduce dynamics of the output voltage. When no disturbance has occurred, the PBB converter works with minimum inductor current and minimum energy loss. New topologies based on the PBB converter have been introduced to address input voltage disturbances for different onboard applications. The research shows that the performance of applications of symmetrical/asymmetrical multi-level diode-clamped inverters, DC-networks, and linear-assisted RF amplifiers may be enhanced by the utilization of topologies based on the PBB converter. Multi-level diode-clamped inverters have the problem of DC-link voltage balancing when the power factor of their load closes to unity. This research has shown that this problem may be solved with a suitable multi-output DC-DC converter supplying DClink capacitors. Furthermore, the multi-level diode-clamped inverters supplied with asymmetrical DC-link voltages may improve the quality of load voltage and reduce the level of Electromagnetic Interference (EMI). Mathematical analyses and experiments on supplying symmetrical and asymmetrical multi-level inverters by specifically designed multi-output DC-DC converters have been reported in two journal papers. Another application in which the system performance can be improved by utilization of the ‘current circulating’ switching state is linear-assisted RF amplifiers in communicational receivers. The concept of ‘linear-assisted’ is to divide the signal into two frequency domains: low frequency, which should be amplified by a switching circuit; and the high frequency domain, which should be amplified by a linear amplifier. The objective is to minimize the overall power loss. This research suggests using the current storage capacity of a PBB based converter to increase its bandwidth, and to increase the domain of the switching converter. The PBB converter addresses the industrial demand for a DC-DC converter for the application of auxiliary power supply of a typical electric train. However, after testing the industrial prototype of the PBB converter, there were some voltage and current spikes because of switching. To attenuate this problem without significantly increasing the switching loss, the idea of Active Gate Signalling (AGS) is presented. AGS suggests a smart gate driver that selectively controls the switching process to reduce voltage/current spikes, without unacceptable reduction in the efficiency of switching.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

Pastureland use in the southeastern US: Implications for carbon sequestration

More than 13 Mha of nonfederal land in the southeastern U.S. are devoted to pastureland. Between 1982 and 1992, pastureland increased by 100,000 ha, with nearly 70% converted from cultivated land. We examined the potential for carbon (C) sequestration with improved pasture management and conversion into pastureland from cultivated land. Improved pasture management techniques, such as intensive grazing, fertilization, introduction of improved grass and legume species, and better irrigation systems can lead to sequestration of atmospheric C in soil. Literature values for the influence of changes in pasture management on soil C were summarized for several potential management changes in the Southeast. Soil C sequestration estimates for the Southeast were based on current pasture management practices and evaluated for a range of different adoption rates of improved practices. Conversion into pasture can also potentially sequester significant amounts of atmospheric C in soils. Land-use data from the National Resources Inventory and literature estimates of soil C changes following conversion to pasture were used to estimate historical (1982 to 1992) soil C sequestration in pastures. Potential future sequestration was estimated based on extrapolation of land-use trends between 1982 and 1992. With continued conversion into pasture and improvement of pasture management, southeastern U.S. pasture soils may be a significant C sink for several years.

Assessment of the suitability of public mobile data networks for aircraft telemetry and control purposes

This paper provides a review of the state of the art relevant work on the use of public mobile data networks for aircraft telemetry and control proposes. Moreover, it describes the characterisation for airborne uses of the public mobile data communication systems known broadly as 3G. The motivation for this study was the explore how this mature public communication systems could be used for aviation purposes. An experimental system was fitted to a light aircraft to record communication latency, line speed, RF level, packet loss and cell tower identifier. Communications was established using internet protocols and connection was made to a local server. The aircraft was flown in both remote and populous areas at altitudes up to 8500 ft in a region located in South East Queensland, Australia. Results show that the average airborne RF levels are better than those on the ground by 21% and in the order of - 77dbm. Latencies were in the order of 500ms (1/2 the latency of Iridium), an average download speed of 0.48Mb/s, average uplink speed of 0.85Mb/s, a packet of information loss of 6.5%. The maximum communication range was also observed to be 70km from a single cell station. The paper also describes possible limitations and utility of using such communications architecture for both manned and unmanned aircraft systems.

A myosin from a higher plant has structural similarities to class V myosins

In plant cells, myosin is believed to be the molecular motor responsible for actin-based motility processes such as cytoplasmic streaming and directed vesicle transport. In an effort to characterize plant myosin, a cDNA encoding a myosin heavy chain was isolated from Arabidopsis thaliana. The predicted product of the MYA1 gene is 173 kDa and is structurally similar to the class V myosins. It is composed of the highly-conserved NH2-terminal "head" domain, a putative calmodulin-binding "neck" domain an alpha-helical coiled-coil domain, and a COOH-terminal domain. Northern blot analysis shows that the Arabidopsis MYA1 gene is expressed in all the major plant tissues (flower, leaf, root, and stem). We suggest that the MYA1 myosin may be involved in a general intracellular transport process in plant cells.

Characterisation of public mobile data networks for aeronautical telemetry purposes

This paper describes the characterisation for airborne uses of the public mobile data communication systems known broadly as 3G. The motivation for this study was to explore how this mature public communication systems could be used for aviation purposes. An experimental system was fitted to a light aircraft to record communication latency, line speed, RF level, packet loss and cell tower identifier. Communications was established using internet protocols and connection was made to a local server. The aircraft was flown in both remote and populous areas at altitudes up to 8500ft in a region located in South East Queensland, Australia. Results show that the average airborne RF levels are better than those on the ground by 21% and in the order of -77 dbm. Latencies were in the order of 500 ms (1/2 the latency of Iridium), an average download speed of 0.48 Mb/s, average uplink speed of 0.85 Mb/s, a packet of information loss of 6.5%. The maximum communication range was also observed to be 70km from a single cell station. The paper also describes possible limitations and utility of using such a communications architecture for both manned and unmanned aircraft systems.

Selected new training documents to update user profile

Relevance Feedback (RF) has been proven very effective for improving retrieval accuracy. Adaptive information filtering (AIF) technology has benefited from the improvements achieved in all the tasks involved over the last decades. A difficult problem in AIF has been how to update the system with new feedback efficiently and effectively. In current feedback methods, the updating processes focus on updating system parameters. In this paper, we developed a new approach, the Adaptive Relevance Features Discovery (ARFD). It automatically updates the system's knowledge based on a sliding window over positive and negative feedback to solve a nonmonotonic problem efficiently. Some of the new training documents will be selected using the knowledge that the system currently obtained. Then, specific features will be extracted from selected training documents. Different methods have been used to merge and revise the weights of features in a vector space. The new model is designed for Relevance Features Discovery (RFD), a pattern mining based approach, which uses negative relevance feedback to improve the quality of extracted features from positive feedback. Learning algorithms are also proposed to implement this approach on Reuters Corpus Volume 1 and TREC topics. Experiments show that the proposed approach can work efficiently and achieves the encouragement performance.