A simple method for EPID-based in vivo dosimetry for radiotherapy treatments of head-and-neck cancers

This study used a homogeneous water-equivalent model of an electronic portal imaging device (EPID), contoured as a structure in a radiotherapy treatment plan, to produce reference dose images for comparison with in vivo EPID dosimetry images. Head and neck treatments were chosen as the focus of this study, due to the heterogeneous anatomies involved and the consequent difficulty of rapidly obtaining reliable reference dose images by other means. A phantom approximating the size and heterogeneity of a typical neck, with a maximum radiological thickness of 8.5 cm, was constructed for use in this study. This phantom was CT scanned and a simple treatment including five square test fields and one off-axis IMRT field was planned. In order to allow the treatment planning system to calculate dose in a model EPID positioned a distance downstream from the phantom to achieve a source-to-detector distance (SDD) of 150 cm, the CT images were padded with air and the phantom’s “body” contour was extended to encompass the EPID contour. Comparison of dose images obtained from treatment planning calculations and experimental irradiations showed good agreement, with more than 90% of points in all fields passing a gamma evaluation, at γ (3%, 3mm )Similar agreement was achieved when the phantom was over-written with air in the treatment plan and removed from the experimental beam, suggesting that water EPID model at 150 cm SDD is capable of providing accurate reference images for comparison with clinical IMRT treatment images, for patient anatomies with radiological thicknesses ranging from 0 up to approximately 9 cm. This methodology therefore has the potential to be used for in vivo dosimetry during treatments to tissues in the neck as well as the oral and nasal cavities, in the head-and-neck region.

A method for risk analysis across governance systems : a great barrier reef case study

Healthy governance systems are key to delivering sound environmental management outcomes from global to local scales. There are, however, surprisingly few risk assessment methods that can pinpoint those domains and sub-domains within governance systems that are most likely to influence good environmental outcomes at any particular scale, or those if absent or dysfunctional, most likely to prevent effective environmental management. This paper proposes a new risk assessment method for analysing governance systems. This method is then tested through its preliminary application to a significant real-world context: governance as it relates to the health of Australia's Great Barrier Reef (GBR). The GBR exists at a supra-regional scale along most of the north eastern coast of Australia. Brodie et al (2012 Mar. Pollut. Bull. 65 81-100) have recently reviewed the state and trend of the health of the GBR, finding that overall trends remain of significant concern. At the same time, official international concern over the governance of the reef has recently been signalled globally by the International Union for the Conservation of Nature (IUCN). These environmental and political contexts make the GBR an ideal candidate for use in testing and reviewing the application of improved tools for governance risk assessment. © 2013 IOP Publishing Ltd.

High pressure in situ diffraction studies of metal–hydrogen systems

“Hybrid” hydrogen storage, where hydrogen is stored in both the solid material and as a high pressure gas in the void volume of the tank can improve overall system efficiency by up to 50% compared to either compressed hydrogen or solid materials alone. Thermodynamically, high equilibrium hydrogen pressures in metal–hydrogen systems correspond to low enthalpies of hydrogen absorption–desorption. This decreases the calorimetric effects of the hydride formation–decomposition processes which can assist in achieving high rates of heat exchange during hydrogen loading—removing the bottleneck in achieving low charging times and improving overall hydrogen storage efficiency of large hydrogen stores. Two systems with hydrogenation enthalpies close to −20 kJ/mol H2 were studied to investigate the hydrogenation mechanism and kinetics: CeNi5–D2 and ZrFe2−xAlx (x = 0.02; 0.04; 0.20)–D2. The structure of the intermetallics and their hydrides were studied by in situ neutron powder diffraction at pressures up to 1000 bar and complementary X-ray diffraction. The deuteration of the hexagonal CeNi5 intermetallic resulted in CeNi5D6.3 with a volume expansion of 30.1%. Deuterium absorption filled three different types of interstices, Ce2Ni2 and Ni4 tetrahedra, and Ce2Ni3 half-octahedra and was accompanied by a valence change for Ce. Significant hysteresis was observed between deuterium absorption and desorption which profoundly decreased on a second absorption cycle. For the Al-modified Laves-type C15 ZrFe2−xAlx intermetallics, deuteration showed very fast kinetics of H/D exchange and resulted in a volume increase of the FCC unit cells of 23.5% for ZrFe1.98Al0.02D2.9(1). Deuterium content, hysteresis of H/D uptake and release, unit cell expansion and stability of the hydrides systematically change with the amount of Al content. In the deuteride D atoms exclusively occupy the Zr2(Fe,Al)2 tetrahedra. Observed interatomic distances are Zr–D = 1.98–2.11; (Fe, Al)–D = 1.70–1.75A˚ . Hydrogenation slightly increases the magnetic moment of the Fe atoms in ZrFe1.98Al0.02 and ZrFe1.96Al0.04 from 1.9 �B at room temperature for the alloy to 2.2 �B for its deuteride.

Wind pressure measurements on a cube subjected to pulsed impinging jet flow

A pulsed impinging jet is used to simulate the gust front of a thunderstorm downburst. This work concentrates on investigating the peak transient loading conditions on a 30 mm cubic model submerged in the simulated downburst flow. The outflow induced pressures are recorded and compared to those from boundary layer and steady wall jet flow. Given that peak winds associated with downburst events are often located in the transient frontal region, the importance of using a non-stationary modelling technique for assessing peak downburst wind loads is highlighted with comparisons.

Simulation of plant cell shrinkage during drying : A SPH–DEM approach

Plant based dried food products are popular commodities in global market where much research is focused to improve the products and processing techniques. In this regard, numerical modelling is highly applicable and in this work, a coupled meshfree particle-based two-dimensional (2-D) model was developed to simulate micro-scale deformations of plant cells during drying. Smoothed Particle Hydrodynamics (SPH) was used to model the viscous cell protoplasm (cell fluid) by approximating it to an incompressible Newtonian fluid. The visco-elastic characteristic of the cell wall was approximated to a Neo-Hookean solid material augmented with a viscous term and modelled with a Discrete Element Method (DEM). Compared to a previous work [H. C. P. Karunasena, W. Senadeera, Y. T. Gu and R. J. Brown, Appl. Math. Model., 2014], this study proposes three model improvements: linearly decreasing positive cell turgor pressure during drying, cell wall contraction forces and cell wall drying. The improvements made the model more comparable with experimental findings on dried cell morphology and geometric properties such as cell area, diameter, perimeter, roundness, elongation and compactness. This single cell model could be used as a building block for advanced tissue models which are highly applicable for product and process optimizations in Food Engineering.

A meshfree-based local Galerkin method with condensation of degree of freedom for elastic dynamic analysis

Condensation technique of degree of freedom is first proposed to improve the computational efficiency of meshfree method with Galerkin weak form for elastic dynamic analysis. In the present method, scattered nodes without connectivity are divided into several subsets by cells with arbitrary shape. Local discrete equation is established over each cell by using moving Kriging interpolation, in which the nodes that located in the cell are used for approximation. Then local discrete equations can be simplified by condensation of degree of freedom, which transfers equations of inner nodes to equations of boundary nodes based on cells. The global dynamic system equations are obtained by assembling all local discrete equations and are solved by using the standard implicit Newmark’s time integration scheme. In the scheme of present method, the calculation of each cell is carried out by meshfree method, and local search is implemented in interpolation. Numerical examples show that the present method has high computational efficiency and good accuracy in solving elastic dynamic problems.

CoRE : a context-aware relation extraction method for relation completion

We identify relation completion (RC) as one recurring problem that is central to the success of novel big data applications such as Entity Reconstruction and Data Enrichment. Given a semantic relation, RC attempts at linking entity pairs between two entity lists under the relation. To accomplish the RC goals, we propose to formulate search queries for each query entity α based on some auxiliary information, so that to detect its target entity β from the set of retrieved documents. For instance, a pattern-based method (PaRE) uses extracted patterns as the auxiliary information in formulating search queries. However, high-quality patterns may decrease the probability of finding suitable target entities. As an alternative, we propose CoRE method that uses context terms learned surrounding the expression of a relation as the auxiliary information in formulating queries. The experimental results based on several real-world web data collections demonstrate that CoRE reaches a much higher accuracy than PaRE for the purpose of RC.

Mini-scale method for nuclear run-on transcription assay in plants

We present a mini-scale method for nuclear run-on transcription assay. In our method, all the centrifuge steps can be carried out by using micro-tubes for short time (5 min each) throughout the process, including isolation of transcriptionally active nuclei and purification of labeled RNA after synthesis of RNA in isolated nuclei. The assay can be performed using a small amount of plant tissue, which enables analysis of developmental changes in transcriptional status of given genes in a single individual plant. Successful results were obtained using the tissues of flower and leaf of petunia and embryo of pea, suggesting that the method is potentially applicable to a variety of plant tissues.

DUTCH : teaching method-based design

All design classes followed a systematic design approach, that, in an abstract way, can be characterized by figure 1. This approach is based on our design approach [1] that we labeled DUTCH (design for users and tasks, from concepts to handles).Consequently, each course starts with collecting, modeling, and analyzing an existing situation. The next step is the development of a vision on a future domain world where new technology and / or new representations have been implemented. This second step is the first tentative global design that will be represented in scenarios or prototypes and can be assessed. This second design model is based on both the client’s requirements and technological possibilities and challenges. In an iterative way multiple instantiations of detail design may follow, that each can be assessed and evaluated again...

Synthesis of MgB2 at low temperature and autogenous pressure

High quality, micron-sized interpenetrating grains of MgB2 with high density are produced at low temperatures (~420oC < T < ~500oC) under autogenous pressure by pre-mixing Mg powder and NaBH4 and heating in an Inconel 601 alloy reactor for 5−15 hours. Optimum production of MgB2 with yields greater than 75% occurs for autogenous pressure in the range 1.0 MPa to 2.0 MPa with the reactor at ~500oC. Autogenous pressure is induced by the decomposition of NaBH4 in the presence of Mg and/or other Mg-based compounds. The morphology, transition temperature and magnetic properties of MgB2 are dependent on the heating regime. Significant improvement in physical properties accrues when the reactor temperature is held at 250oC for >20minutes prior to a hold at 500oC.

Protocol : A highly sensitive RT-PCR method for detection and quantification of microRNAs

MicroRNAs (miRNAs) are a class of small non-coding RNAs with a critical role in development and environmental responses. Efficient and reliable detection of miRNAs is an essential step towards understanding their roles in specific cells and tissues. However, gel-based assays currently used to detect miRNAs are very limited in terms of throughput, sensitivity and specificity. Here we provide protocols for detection and quantification of miRNAs by RT-PCR. We describe an end-point and real-time looped RT-PCR procedure and demonstrate detection of miRNAs from as little as 20 pg of plant tissue total RNA and from total RNA isolated from as little as 0.1 l of phloem sap. In addition, we have developed an alternative real-time PCR assay that can further improve specificity when detecting low abundant miRNAs. Using this assay, we have demonstrated that miRNAs are differentially expressed in the phloem sap and the surrounding vascular tissue. This method enables fast, sensitive and specific miRNA expression profiling and is suitable for facilitation of high-throughput detection and quantification of miRNA expression.

The ranking based constrained document clustering method and its application to social event detection

With the growing size and variety of social media files on the web, it’s becoming critical to efficiently organize them into clusters for further processing. This paper presents a novel scalable constrained document clustering method that harnesses the power of search engines capable of dealing with large text data. Instead of calculating distance between the documents and all of the clusters’ centroids, a neighborhood of best cluster candidates is chosen using a document ranking scheme. To make the method faster and less memory dependable, the in-memory and in-database processing are combined in a semi-incremental manner. This method has been extensively tested in the social event detection application. Empirical analysis shows that the proposed method is efficient both in computation and memory usage while producing notable accuracy.

Physical activity recognition from accelerometer data using a multi-scale ensemble method

Accurate and detailed measurement of an individual's physical activity is a key requirement for helping researchers understand the relationship between physical activity and health. Accelerometers have become the method of choice for measuring physical activity due to their small size, low cost, convenience and their ability to provide objective information about physical activity. However, interpreting accelerometer data once it has been collected can be challenging. In this work, we applied machine learning algorithms to the task of physical activity recognition from triaxial accelerometer data. We employed a simple but effective approach of dividing the accelerometer data into short non-overlapping windows, converting each window into a feature vector, and treating each feature vector as an i.i.d training instance for a supervised learning algorithm. In addition, we improved on this simple approach with a multi-scale ensemble method that did not need to commit to a single window size and was able to leverage the fact that physical activities produced time series with repetitive patterns and discriminative features for physical activity occurred at different temporal scales.

A sensor fault detection and isolation method in interior permanent-magnet synchronous motor drives based on an extended Kalman filter

Interior permanent-magnet synchronous motors (IPMSMs) become attractive candidates in modern hybrid electric vehicles and industrial applications. Usually, to obtain good control performance, the electric drives of this kind of motor require one position, one dc link, and at least two current sensors. Failure of any of these sensors might lead to degraded system performance or even instability. As such, sensor fault resilient control becomes a very important issue in modern drive systems. This paper proposes a novel sensor fault detection and isolation algorithm based on an extended Kalman filter. It is robust to system random noise and efficient in real-time implementation. Moreover, the proposed algorithm is compact and can detect and isolate all the sensor faults for IPMSM drives. Thorough theoretical analysis is provided, and the effectiveness of the proposed approach is proven by extensive experimental results.

Non-linear principal components analysis : an alternative method for finding patterns in environmental data

The main purpose of this article is to gain an insight into the relationships between variables describing the environmental conditions of the Far Northern section of the Great Barrier Reef, Australia. Several of the variables describing these conditions had different measurement levels and often they had non-linear relationships. Using non-linear principal component analysis, it was possible to acquire an insight into these relationships. Furthermore, three geographical areas with unique environmental characteristics could be identified.