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A mechanochemical synthesis process has been used to synthesise aluminium nanoparticles. The aluminium is synthesised via a solid state chemical reaction which is initiated inside a ball mill at room temperature between either lithium (Li) or sodium (Na) metal which act as reducing agents with unreduced aluminium chloride (AlCl3). The reaction product formed consists of aluminium nanoparticles embedded within a by-product salt phase (LiCl or NaCl, respectively). The LiCl is washed with a suitable solvent resulting in aluminium (Al) nanoparticles which are not oxidised and are separated from the byproduct phase. Synthesis and washing was confirmed using X-ray diffraction (XRD). Nanoparticles were found to be ∼25–100nm from transmission electron microscopy (TEM) and an average size of 55nm was determined fromsmall angle X-ray scattering (SAXS) measurements. As synthesised Al/NaCl composites, washed Al nanoparticles, and purchased Al nanoparticles were deuterium (D2) absorption tested up to 2 kbar at a variety of temperatures, with no absorption detected within system resolution.

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A catchment-scale multivariate statistical analysis of hydrochemistry enabled assessment of interactions between alluvial groundwater and Cressbrook Creek, an intermittent drainage system in southeast Queensland, Australia. Hierarchical cluster analyses and principal component analysis were applied to time-series data to evaluate the hydrochemical evolution of groundwater during periods of extreme drought and severe flooding. A simple three-dimensional geological model was developed to conceptualise the catchment morphology and the stratigraphic framework of the alluvium. The alluvium forms a two-layer system with a basal coarse-grained layer overlain by a clay-rich low-permeability unit. In the upper and middle catchment, alluvial groundwater is chemically similar to streamwater, particularly near the creek (reflected by high HCO3/Cl and K/Na ratios and low salinities), indicating a high degree of connectivity. In the lower catchment, groundwater is more saline with lower HCO3/Cl and K/Na ratios, notably during dry periods. Groundwater salinity substantially decreased following severe flooding in 2011, notably in the lower catchment, confirming that flooding is an important mechanism for both recharge and maintaining groundwater quality. The integrated approach used in this study enabled effective interpretation of hydrological processes and can be applied to a variety of hydrological settings to synthesise and evaluate large hydrochemical datasets.

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JS-2 is a novel gene located at 5p15.2 and originally detected in primary oesophageal cancer. There is no study on the role of JS-2 in colorectal cancer. The aim of this study is to determine the gene copy number and expression of JS-2 in a large cohort of patients with colorectal tumours and correlate these to the clinicopathological features of the cancer patients. We evaluated the DNA copy number and mRNA expression of JS-2 in 176 colorectal tissues (116 adenocarcinomas, 30 adenomas and 30 non-neoplastic tissues) using real-time polymerase chain reaction. JS-2 expression was also evaluated in two colorectal cancer cell lines and a benign colorectal cell line. JS-2 amplification was noted in 35% of the colorectal adenocarcinomas. Significant differences in relative expression levels for JS-2 mRNA between different colorectal tissues were noted (p = 0.05). Distal colorectal adenocarcinoma had significantly higher copy number than proximal adenocarcinoma (p = 0.005). The relative expression level of JS-2 was different between colonic and rectal adenocarcinoma (p = 0.007). Mucinous adenocarcinoma showed higher JS-2 expression than non-mucinous adenocarcinoma (p = 0.02). Early T-stage cancers appear to have higher JS-2 copy number and lower expression of JS-2 mRNA than later stage cancers (p = 0.001 and 0.03 respectively). Colorectal cancer cell lines showed lower expression of JS-2 than the benign colorectal cell line. JS-2 copy number change and expression were shown for the first time to be altered in the carcinogenesis of colorectal cancer. In addition, genetic alteration of JS-2 was found to be related to location, pathological subtypes and staging of colorectal cancer.

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This chapter describes decentralized data fusion algorithms for a team of multiple autonomous platforms. Decentralized data fusion (DDF) provides a useful basis with which to build upon for cooperative information gathering tasks for robotic teams operating in outdoor environments. Through the DDF algorithms, each platform can maintain a consistent global solution from which decisions may then be made. Comparisons will be made between the implementation of DDF using two probabilistic representations. The first, Gaussian estimates and the second Gaussian mixtures are compared using a common data set. The overall system design is detailed, providing insight into the overall complexity of implementing a robust DDF system for use in information gathering tasks in outdoor UAV applications.

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An International Society of Sugar Cane Technologists (ISSCT) Engineering Workshop was held in Piracicaba, Brazil from 30 June to 4 July 2008. The theme of the workshop was Design, manufacturing and maintenance of sugar mill equipment. The workshop consisted of a series of technical sessions and site visits. The Brazilian sugar industry is growing rapidly. The growth has occurred as the result of the sugar industry’s position as a key provider of renewable energy in the form of ethanol and, more recently, electricity. The increased focus on electricity is seeing investment in high pressure (100 bar) boilers, cane cleaning plants that allow an increased biomass supply from trash and digesters that produce biogas from dunder. It is clear that the Brazilian sugar industry has a well defined place in the country’s future. The ISSCT workshop provided a good opportunity to gain information from equipment suppliers and discuss new technology that may have application in Australia. The new technologies of interest included IMCO sintered carbide shredder hammer tips, Fives Cail MillMax mills, planetary mill gearboxes, Bosch Projects chainless diffusers, Fives Cail Zuka centrifugals and Vaperma Siftek membrane systems.

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Directional cell migration requires force generation that relies on the coordinated remodeling of interactions with the extracellular matrix (ECM), which is mediated by integrin-based focal adhesions (FAs). Normal FA turnover requires dynamic microtubules, and three members of the diverse group of microtubule plus-end-tracking proteins are principally involved in mediating microtubule interactions with FAs. Microtubules also alter the assembly state of FAs by modulating Rho GTPase signaling, and recent evidence suggests that microtubule-mediated clathrin-dependent and -independent endocytosis regulates FA dynamics. In addition, FA-associated microtubules may provide a polarized microtubule track for localized secretion of matrix metalloproteases (MMPs). Thus, different aspects of the molecular mechanisms by which microtubules control FA turnover in migrating cells are beginning to emerge.

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Background Summarizing the epidemiology of major depressive disorder (MDD) at a global level is complicated by significant heterogeneity in the data. The aim of this study is to present a global summary of the prevalence and incidence of MDD, accounting for sources of bias, and dealing with heterogeneity. Findings are informing MDD burden quantification in the Global Burden of Disease (GBD) 2010 Study. Method A systematic review of prevalence and incidence of MDD was undertaken. Electronic databases Medline, PsycINFO and EMBASE were searched. Community-representative studies adhering to suitable diagnostic nomenclature were included. A meta-regression was conducted to explore sources of heterogeneity in prevalence and guide the stratification of data in a meta-analysis. Results The literature search identified 116 prevalence and four incidence studies. Prevalence period, sex, year of study, depression subtype, survey instrument, age and region were significant determinants of prevalence, explaining 57.7% of the variability between studies. The global point prevalence of MDD, adjusting for methodological differences, was 4.7% (4.4–5.0%). The pooled annual incidence was 3.0% (2.4–3.8%), clearly at odds with the pooled prevalence estimates and the previously reported average duration of 30 weeks for an episode of MDD. Conclusions Our findings provide a comprehensive and up-to-date profile of the prevalence of MDD globally. Region and study methodology influenced the prevalence of MDD. This needs to be considered in the GBD 2010 study and in investigations into the ecological determinants of MDD. Good-quality estimates from low-/middle-income countries were sparse. More accurate data on incidence are also required.

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Although the effect of adverse environments on the well-being of children is an important global health issue, it remains underrecognized in health care and underconsidered in terms of both research and public policy. Children have developmentally distinct patterns of environmental exposure and susceptibilities that increase their risk of disease. Young children, especially those who are impoverished, have disproportionately heavier exposures to environmental threats in a given environment. They also have decreased metabolic capacity to detoxify and eliminate contaminants. Furthermore, rapid growth and development before and after birth and the continuing growth and postnatal maturation of the respiratory, immune, and neurological systems, in particular, make them increasingly vulnerable to environmental threats...

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Nowadays, demand for automated Gas metal arc welding (GMAW) is growing and consequently need for intelligent systems is increased to ensure the accuracy of the procedure. To date, welding pool geometry has been the most used factor in quality assessment of intelligent welding systems. But, it has recently been found that Mahalanobis Distance (MD) not only can be used for this purpose but also is more efficient. In the present paper, Artificial Neural Networks (ANN) has been used for prediction of MD parameter. However, advantages and disadvantages of other methods have been discussed. The Levenberg–Marquardt algorithm was found to be the most effective algorithm for GMAW process. It is known that the number of neurons plays an important role in optimal network design. In this work, using trial and error method, it has been found that 30 is the optimal number of neurons. The model has been investigated with different number of layers in Multilayer Perceptron (MLP) architecture and has been shown that for the aim of this work the optimal result is obtained when using MLP with one layer. Robustness of the system has been evaluated by adding noise into the input data and studying the effect of the noise in prediction capability of the network. The experiments for this study were conducted in an automated GMAW setup that was integrated with data acquisition system and prepared in a laboratory for welding of steel plate with 12 mm in thickness. The accuracy of the network was evaluated by Root Mean Squared (RMS) error between the measured and the estimated values. The low error value (about 0.008) reflects the good accuracy of the model. Also the comparison of the predicted results by ANN and the test data set showed very good agreement that reveals the predictive power of the model. Therefore, the ANN model offered in here for GMA welding process can be used effectively for prediction goals.

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M r= 470.46, rhombohedral, R3, a =8.710(4)A, a=91.10(3) o, V= 660.4 (9) A 3, Z= 1,D m= 1.170 (flotation in KI solution), D x=1.183 Mg m -a, Mo Kct, 2 = 0.7107/~,, /t =0.033 mm -1, F(000) - 248.0, T= 293 K, R -- 4.6%(481 unique reflections). The molecule has C a symmetry and is propeller shaped, the angle of twist about the B-C bond being 41.5 (7) °. The space group being chiral, this is yet another example of spontaneous resolution. The results of a thermal-motion analysis are discussed.

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Robust estimation often relies on a dispersion function that is more slowly varying at large values than the square function. However, the choice of tuning constant in dispersion functions may impact the estimation efficiency to a great extent. For a given family of dispersion functions such as the Huber family, we suggest obtaining the "best" tuning constant from the data so that the asymptotic efficiency is maximized. This data-driven approach can automatically adjust the value of the tuning constant to provide the necessary resistance against outliers. Simulation studies show that substantial efficiency can be gained by this data-dependent approach compared with the traditional approach in which the tuning constant is fixed. We briefly illustrate the proposed method using two datasets.

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The potential of near infra-red (NIR) spectroscopy for non-invasive measurement of fruit quality of pineapple (Ananas comosus var. Smooth Cayenne) and mango (Magnifera indica var. Kensington) fruit was assessed. A remote reflectance fibre optic probe, placed in contact with the fruit skin surface in a light-proof box, was used to deliver monochromatic light to the fruit, and to collect NIR reflectance spectra (760–2500 nm). The probe illuminated and collected reflected radiation from an area of about 16 cm2. The NIR spectral attributes were correlated with pineapple juice Brix and with mango flesh dry matter (DM) measured from fruit flesh directly underlying the scanned area. The highest correlations for both fruit were found using the second derivative of the spectra (d2 log 1/R) and an additive calibration equation. Multiple linear regression (MLR) on pineapple fruit spectra (n = 85) gave a calibration equation using d2 log 1/R at wavelengths of 866, 760, 1232 and 832 nm with a multiple coefficient of determination (R2) of 0.75, and a standard error of calibration (SEC) of 1.21 °Brix. Modified partial least squares (MPLS) regression analysis yielded a calibration equation with R2 = 0.91, SEC = 0.69, and a standard error of cross validation (SECV) of 1.09 oBrix. For mango, MLR gave a calibration equation using d2 log 1/R at 904, 872, 1660 and 1516 nm with R2 = 0.90, and SEC = 0.85% DM and a bias of 0.39. Using MPLS analysis, a calibration equation with R2 = 0.98, SEC = 0.54 and SECV = 1.19 was obtained. We conclude that NIR technology offers the potential to assess fruit sweetness in intact whole pineapple and DM in mango fruit, respectively, to within 1° Brix and 1% DM, and could be used for the grading of fruit in fruit packing sheds.

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Mounting levels of insecticide resistance within Australian Helicoverpa spp. populations have resulted in the adoption of non-chemical IPM control practices such as trap cropping with chickpea, Cicer arietinum (L.). However, a new leaf blight disease affecting chickpea in Australia has the potential to limit its use as a trap crop. Therefore this paper evaluates the potential of a variety of winter-active legume crops for use as an alternative spring trap crop to chickpea as part of an effort to improve the area-wide management strategy for Helicoverpa spp. in central Queensland’s cotton production region. The densities of Helicoverpa eggs and larvae were compared over three seasons on replicated plantings of chickpea, Cicer arietinum (L.), field pea Pisum sativum (L), vetch, Vicia sativa (L.) and faba bean, Vicia faba (L.). Of these treatments, field pea was found to harbour the highest densities of eggs. A partial life table study of the fate of eggs oviposited on field pea and chickpea suggested that large proportions of the eggs laid on field pea suffered mortality due to dislodgment from the plants after oviposition. Plantings of field pea as a replacement trap crop for chickpea under commercial conditions confirmed the high level of attractiveness of this crop to ovipositing moths. The use of field pea as a trap crop as part of an areawide management programme for Helicoverpa spp. is discussed.