Carbon saturation of arrays of Ni catalyst nanoparticles of different size and pattern uniformity on a silicon substrate

The kinetics of saturation of Ni catalyst nanoparticle patterns of the three different degrees of order, used as a model for the growth of carbon nanotips on Si, is investigated numerically using a complex model that involves surface diffusion and ion motion equations. It is revealed that Ni catalyst patterns of different degrees of order, with Ni nanoparticle sizes up to 12.5 nm, exhibit different kinetics of saturation with carbon on the Si surface. It is shown that in the cases examined (surface coverage in the range of 1-50%, highly disordered Ni patterns) the relative pattern saturation factor calculated as the ratio of average incubation times for the processes conducted in the neutral and ionized gas environments reaches 14 and 3.4 for Ni nanoparticles of 2.5 and 12.5 nm, respectively. In the highly ordered Ni patterns, the relative pattern saturation factor reaches 3 for nanoparticles of 2.5 nm and 2.1 for nanoparticles of 12.5 nm. Thus, more simultaneous saturation of Ni catalyst nanoparticles of sizes in the range up to 12.5 nm, deposited on the Si substrate, can be achieved in the low-temperature plasma environment than with the neutral gas-based process.

Size-selected Ni catalyst islands for single-walled carbon nanotube arrays

Many properties of single-walled carbon nanotube (SWCNT) arrays are determined by the size and surface coverage of the metal catalyst islands from which they are nucleated. Methods using thermal fragmentation of continuous metal films frequently fail to produce size-uniform islands. Hybrid numerical simulations are used to propose a new approach to controlled self-assembly of Ni islands of the required size and surface coverage using tailored gas-phase generated nanocluster fluxes and adjusted surface temperatures. It is shown that a maximum surface coverage of 0.359 by 0.96-1.02 nm Ni catalyst islands can be achieved at a low surface temperature of 500 K. Optimized growth of Ni catalyst islands can lead to fabrication of size-uniform SWCNT arrays, suitable for numerous nanoelectronic applications. This approach is deterministic and is applicable to a range of nanoassemblies where high surface coverage and island size uniformity are required.

Brain decoding based on functional magnetic resonance imaging using machine learning : a comparative study

Brain decoding of functional Magnetic Resonance Imaging data is a pattern analysis task that links brain activity patterns to the experimental conditions. Classifiers predict the neural states from the spatial and temporal pattern of brain activity extracted from multiple voxels in the functional images in a certain period of time. The prediction results offer insight into the nature of neural representations and cognitive mechanisms and the classification accuracy determines our confidence in understanding the relationship between brain activity and stimuli. In this paper, we compared the efficacy of three machine learning algorithms: neural network, support vector machines, and conditional random field to decode the visual stimuli or neural cognitive states from functional Magnetic Resonance data. Leave-one-out cross validation was performed to quantify the generalization accuracy of each algorithm on unseen data. The results indicated support vector machine and conditional random field have comparable performance and the potential of the latter is worthy of further investigation.

Global start-ups profile : one size fits all?

Our research aims to answer the research questions “How do we commonly describe the global start-ups profile as evidenced in prior inductive research?” and “Does this global start-ups profile can effectively explain phenomena in Australian global start-up firms?” We systematically review 29 global start-ups (144 firms) qualitative articles to understand descriptive definitions of global-startup firms. We then triangulate this finding with an Australian high-tech firm. Our contribution is to form a descriptive profile of global start-up phenomenon and raise interesting issues that have potentially fruitful findings for both research and practice. This profile might well be just a deviant from the traditional model that describes how firms establish their footprints, first in their domestic markets followed by moves into cross-border activities. Regardless, government agencies, consultants, and entrepreneurs need to understand the phenomenon. Thus we anticipate that this phenomenon will continue to provide interesting issues for pursuit, both by researchers as well as the practitioner community.

Using informative priors in the estimation of mixtures over time with application to aerosol particle size distributions

The issue of using informative priors for estimation of mixtures at multiple time points is examined. Several different informative priors and an independent prior are compared using samples of actual and simulated aerosol particle size distribution (PSD) data. Measurements of aerosol PSDs refer to the concentration of aerosol particles in terms of their size, which is typically multimodal in nature and collected at frequent time intervals. The use of informative priors is found to better identify component parameters at each time point and more clearly establish patterns in the parameters over time. Some caveats to this finding are discussed.

Quality assurance of aerial applications of larvicides for mosquito control : effects of granule and catch tray size on field monitoring programs

Aerial applications of granular insecticides are preferable because they can effectively penetrate vegetation, there is less drift, and no loss of product due to evaporation. We aimed to 1) assess the field efficacy ofVectoBac G to control Aedes vigilax (Skuse) in saltmarsh pools, 2) develop a stochastic-modeling procedure to monitor application quality, and 3) assess the distribution of VectoBac G after an aerial application. Because ground-based studies with Ae. vigilax immatures found that VectoBac G provided effective control below the recommended label rate of 7 kg/ha, we trialed a nominated aerial rate of 5 kg/ha as a case study. Our distribution pattern modeling method indicated that the variability in the number of VectoBac G particles captured in catch-trays was greater than expected for 5 kg/ha and that the widely accepted contour mapping approach to visualize the deposition pattern provided spurious results and therefore was not statistically appropriate. Based on the results of distribution pattern modeling, we calculated the catch tray size required to analyze the distribution of aerially applied granular formulations. The minimum catch tray size for products with large granules was 4 m2 for Altosid pellets and 2 m2 for VectoBac G. In contrast, the minimum catch-tray size for Altosid XRG, Aquabac G, and Altosand, with smaller granule sizes, was 1 m2. Little gain in precision would be made by increasing the catch-tray size further, when the increased workload and infrastructure is considered. Our improved methods for monitoring the distribution pattern of aerially applied granular insecticides can be adapted for use by both public health and agricultural contractors.

Demographic faultlines in boards : impact of diversity and board size

Negative board diversity-organizational outcomes research findings have highlighted the importance of studying board demographic faultlines. Based on research gaps, this study focuses on gender diversity, age diversity, board size and faultlines formation in corporate boards. It proposes a positive linear diversity-faultlines relationship based on self-categorization and social identity theories, interaction effects of gender diversity and age diversity on faultlines based on contingency theories, and a U-shaped board size-faultlines strength relationship. The hypotheses were tested in 288 large companies listed on the Australian Securities Exchange using archival data. The results provided partial support for the interaction effects relationships and support to the U-shaped board size-faultlines strength relationship. The findings indicate that boards with low levels of age diversity experience a negative linear relationship between gender diversity and faultlines such that higher representation of women leads to weaker faultlines. The results also suggest that small- and large-sized boards experience stronger faultlines strength than medium-sized board. These results inform practice and underline implications of board demographic diversity and board size.

Metal artifacts from titanium and steel screws in CT, 1.5T and 3T MR images of the tibial Pilon: A quantitative assessment in 3D

Radiographs are commonly used to assess articular reduction of the distal tibia (pilon) fractures postoperatively, but may reveal malreductions inaccurately. While Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) are potential 3D alternatives they generate metal-related artifacts. This study aims to quantify the artifact size from orthopaedic screws using CT, 1.5T and 3T MRI data. Three screws were inserted into one intact human cadaver ankle specimen proximal to and along the distal articular surface, then CT, 1.5T and 3T MRI scanned. Four types of screws were investigated: titanium alloy (TA), stainless steel (SS) (Ø = 3.5 mm), cannulated TA (CTA) and cannulated SS (CSS)(Ø = 4.0 mm, Ø empty core = 2.6 mm). 3D artifact models were reconstructed using adaptive thresholding. The artifact size was measured by calculating the perpendicular distance from the central screw axis to the boundary of the artifact in four anatomical directions with respect to the distal tibia. The artifact sizes (in the order of TA, SS, CTA and CSS) from CT were 2.0 mm, 2.6 mm, 1.6 mm and 2.0 mm; from 1.5T MRI they were 3.7 mm, 10.9 mm, 2.9 mm, and 9 mm; and 3T MRI they were 4.4 mm, 15.3 mm, 3.8 mm, and 11.6 mm respectively. Therefore, CT can be used as long as the screws are at a safe distance of about 2 mm from the articular surface. MRI can be used if the screws are at least 3 mm away from the articular surface except SS and CSS. Artifacts from steel screws were too large thus obstructed the pilon from being visualised in MRI. Significant differences (P < 0.05) were found in the size of artifacts between all imaging modalities, screw types and material types, except 1.5T versus 3T MRI for the SS screws (P = 0.063). CTA screws near the joint surface can improve postoperative assessment in CT and MRI. MRI presents a favourable non-ionising alternative when using titanium hardware. Since these factors may influence the quality of postoperative assessment, potential improvements in operative techniques should be considered.

Particle size distribution effects on preferential deposition areas in metal foam wrapped tube bundle

This paper presents a numerical model for understanding particle transport and deposition in metal foam heat exchangers. Two-dimensional steady and unsteady numerical simulations of a standard single row metal foam-wrapped tube bundle are performed for different particle size distributions, i.e. uniform and normal distributions. Effects of different particle sizes and fluid inlet velocities on the overall particle transport inside and outside the foam layer are also investigated. It was noted that the simplification made in the previously-published numerical works in the literature, e.g. uniform particle deposition in the foam, is not necessarily accurate at least for the cases considered here. The results highlight the preferential particle deposition areas both along the tube walls and inside the foam using a developed particle deposition likelihood matrix. This likelihood matrix is developed based on three criteria being particle local velocity, time spent in the foam, and volume fraction. It was noted that the particles tend to deposit near both front and rear stagnation points. The former is explained by the higher momentum and direct exposure of the particles to the foam while the latter only accommodate small particles which can be entrained in the recirculation region formed behind the foam-wrapped tubes.

Size dependent photodegradation of CdS particles deposited onto TiO2 mesoporous films by SILAR method

The properties of CdS nanoparticles incorporated onto mesoporous TiO2 films by a successive ionic layer adsorption and reaction (SILAR) method were investigated by Raman spectroscopy, UV-visible spectroscopy, transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS). High resolution TEM indicated that the synthesized CdS particles were hexagonal phase and the particle sizes were less than 5 nm when SILAR cycles were fewer than 9. Quantum size effect was found with the CdS sensitized TiO2 films prepared with up to 9 SILAR cycles. The band gap of CdS nanoparticles decreased from 2.65 eV to 2.37 eV with the increase of the SILAR cycles from 1 to 11. The investigation of the stability of the CdS/TiO2 films in air under illumination (440.6 µW/cm2) showed that the photodegradation rate was up to 85% per day for the sample prepared with 3 SILAR cycles. XPS analysis indicated that the photodegradation was due to the oxidation of CdS, leading to the transformation from sulphide to sulphate (CdSO4). Furthermore, the degradation rate was strongly dependent upon the particle size of CdS. Smaller particles showed faster degradation rate. The size-dependent photo-induced oxidization was rationalized with the variation of size-dependent distribution of surface atoms of CdS particles. Molecular Dynamics (MD) simulation has indicated that the surface sulphide anion of a large CdS particle such as CdS made with 11 cycles (CdS11, particle size = 5.6 nm) accounts for 9.6% of the material whereas this value is increased to 19.2% for (CdS3) based smaller particles (particle size: 2.7 nm). Nevertheless, CdS nanoparticles coated with ZnS material showed a significantly enhanced stability under illumination in air. A nearly 100% protection of CdS from photon induced oxidation with a ZnS coating layer prepared using four SILAR cycles, suggesting the formation of a nearly complete coating layer on the CdS nanoparticles.

Enhancing MRI of prostate cancer using PSMA-targeting iron oxide magnetic nanoparticles

Introduction Novel imaging techniques for prostate cancer (PCa) are required to improve staging and real-time assessment of therapeutic response. We performed preclinical evaluation of newly-developed, biocompatible magnetic nanoparticles (MNPs) conjugated with J591, an antibody specific for prostate specific membrane antigen (PSMA), to enhance magnetic resonance imaging (MRI) of PCa. PSMA is expressed on ∼90% of PCa, including those that are castrate-resistant, rendering it as a rational target for PCa imaging. Materials and Methods The specificity of J591 for PSMA was confirmed by flow cytometric analysis of several PCa cell lines of known PSMA status. MNPs were prepared, engineered to the appropriate size, labeled with DiR fluorophore, and their toxicity to a panel of PC cells was assessed by in vitro Alamar Blue assay. Immunohistochemistry, fluorescence microscopy and Prussian Blue staining (iron uptake) were used to evaluate PSMA specificity of J591-MNP conjugates. In vivo MRI studies (16.4T MRI system) were performed using live immunodeficient mice bearing orthotopic LNCaP xenografts and injected intravenously with J591-MNPs or MNPs alone. Results MNPs were non-toxic to PCa cells. J591-MNP conjugates showed no compromise in specificity of binding to PSMA+ cells and showed enhanced iron uptake compared with MNPs alone. In vivo, tumour targeting (significant MR image contrast) was evident in mice injected with J591-MNPs, but not MNPs alone. Resected tumours from targeted mice had an accumulation of MNPs, not seen in normal control prostate. Conclusions Application of PSMA-targeting MNPs into conventional MRI has potential to enhance PCa detection and localization in real-time, improving patient management.

Frequency-motivated observer design for the prediction of parametric roll resonance control applications in marine systems

This work deals with estimators for predicting when parametric roll resonance is going to occur in surface vessels. The roll angle of the vessel is modeled as a second-order linear oscillatory system with unknown parameters. Several algorithms are used to estimate the parameters and eigenvalues of the system based on data gathered experimentally on a 1:45 scale model of a tanker. Based on the estimated eigenvalues, the system predicts whether or not parametric roll occurred. A prediction accuracy of 100% is achieved for regular waves, and up to 87.5% for irregular waves.

Functional magnetic resonance brain imaging of executive cognitive performance in young first-episode schizophrenia patients and age-matched long-term cannabis users

Converging evidence from epidemiological, clinical and neuropsychological research suggests a link between cannabis use and increased risk of psychosis. Long-term cannabis use has also been related to deficit-like “negative” symptoms and cognitive impairment that resemble some of the clinical and cognitive features of schizophrenia. The current functional brain imaging study investigated the impact of a history of heavy cannabis use on impaired executive function in first-episode schizophrenia patients. Whilst performing the Tower of London task in a magnetic resonance imaging scanner, event-related blood oxygenation level-dependent (BOLD) brain activation was compared between four age and gender-matched groups: 12 first-episode schizophrenia patients; 17 long-term cannabis users; seven cannabis using first-episode schizophrenia patients; and 17 healthy control subjects. BOLD activation was assessed as a function of increasing task difficulty within and between groups as well as the main effects of cannabis use and the diagnosis of schizophrenia. Cannabis users and non-drug using first-episode schizophrenia patients exhibited equivalently reduced dorsolateral prefrontal activation in response to task difficulty. A trend towards additional prefrontal and left superior parietal cortical activation deficits was observed in cannabis-using first-episode schizophrenia patients while a history of cannabis use accounted for increased activation in the visual cortex. Cannabis users and schizophrenia patients fail to adequately activate the dorsolateral prefrontal cortex, thus pointing to a common working memory impairment which is particularly evident in cannabis-using first-episode schizophrenia patients. A history of heavy cannabis use, on the other hand, accounted for increased primary visual processing, suggesting compensatory imagery processing of the task.