Analyzing multi-fiber reconstruction in high angular resolution diffusion imaging using the tensor distribution function

High-angular resolution diffusion imaging (HARDI) can reconstruct fiber pathways in the brain with extraordinary detail, identifying anatomical features and connections not seen with conventional MRI. HARDI overcomes several limitations of standard diffusion tensor imaging, which fails to model diffusion correctly in regions where fibers cross or mix. As HARDI can accurately resolve sharp signal peaks in angular space where fibers cross, we studied how many gradients are required in practice to compute accurate orientation density functions, to better understand the tradeoff between longer scanning times and more angular precision. We computed orientation density functions analytically from tensor distribution functions (TDFs) which model the HARDI signal at each point as a unit-mass probability density on the 6D manifold of symmetric positive definite tensors. In simulated two-fiber systems with varying Rician noise, we assessed how many diffusionsensitized gradients were sufficient to (1) accurately resolve the diffusion profile, and (2) measure the exponential isotropy (EI), a TDF-derived measure of fiber integrity that exploits the full multidirectional HARDI signal. At lower SNR, the reconstruction accuracy, measured using the Kullback-Leibler divergence, rapidly increased with additional gradients, and EI estimation accuracy plateaued at around 70 gradients.

Text segmentation in unconstrained hand-drawings in whiteboard photos

In this paper we present a robust method to detect handwritten text from unconstrained drawings on normal whiteboards. Unlike printed text on documents, free form handwritten text has no pattern in terms of size, orientation and font and it is often mixed with other drawings such as lines and shapes. Unlike handwritings on paper, handwritings on a normal whiteboard cannot be scanned so the detection has to be based on photos. Our work traces straight edges on photos of the whiteboard and builds graph representation of connected components. We use geometric properties such as edge density, graph density, aspect ratio and neighborhood similarity to differentiate handwritten text from other drawings. The experiment results show that our method achieves satisfactory precision and recall. Furthermore, the method is robust and efficient enough to be deployed in a mobile device. This is an important enabler of business applications that support whiteboard-centric visual meetings in enterprise scenarios. © 2012 IEEE.

The grand philosopher of the Commons: In memory of Elinor Ostrom

The grand philosopher of the Commons, Elinor Ostrom, passed away on the 12th June 2012. She was a brilliant, creative polymath; a theoretician of fine precision and great intellectual power; a deviser of masterful empirical studies; and an energetic collaborator and networker. Ostrom posed a formidable intellectual challenge to the fields of economics and the social sciences - and the advocates of central regulation, privatization, and enclosure.

Investigating sea level rise due to global warming in the teaching laboratory using Archimedes’ principle

A teaching laboratory experiment is described that uses Archimedes’ principle to precisely investigate the effect of global warming on the oceans. A large component of sea level rise is due to the increase in the volume of water due to the decrease in water density with increasing temperature. Water close to 0 °C is placed in a beaker and a glass marble hung from an electronic balance immersed in the water. As the water warms, the weight of the marble increases as the water is less buoyant due to the decrease in density. In the experiment performed in this paper a balance with a precision of 0.1 mg was used with a marble 40.0 cm3 and mass of 99.3 g, yielding water density measurements with an average error of -0.008 ± 0.011%.

Visual openness in urban environments: Measuring visual openness and visibility to natural landscapes in a changing urban landscape in Gold Coast, Australia

The visual characteristics of urban environments have been changing dramatically with the growth of cities around the world. Protection and enhancement of landscape character in urban environments have been one of the challenges for policy makers in addressing sustainable urban growth. Visual openness and enclosure in urban environments are important attributes in perception of visual space which affect the human interaction with physical space and which can be often modified by new developments. Measuring visual openness in urban areas results in more accurate, reliable, and systematic approach to manage and control visual qualities in growing cities. Recent advances in techniques in geographic information systems (GIS) and survey systems make it feasible to measure and quantify this attribute with a high degree of realism and precision. Previous studies in this field do not take full advantage of these improvements. This paper proposes a method to measure the visual openness and enclosure in a changing urban landscape in Australia, on the Gold Coast, by using the improved functionality in GIS. Using this method, visual openness is calculated and described for all publicly accessible areas in the selected study area. A final map is produced which shows the areas with highest visual openness and visibility to natural landscape resources. The output of this research can be used by planners and decision-makers in managing and controlling views in complex urban landscapes. Also, depending on the availability of GIS data, this method can be applied to any region including non-urban landscapes to help planners and policy-makers manage views and visual qualities.

Emotional food design: From designing food products to designing food systems

Contemporary food systems promote the consumption of highly processed foods of limited nutrition, contributing to overweight and obesity, diet-related disease and significant financial burden on healthcare systems. In part, this has resulted from highly successful design, development and marketing strategies for processed foods. The successful application of such strategies to healthy food options, and the services and business plans that accompany them, could assist in enhancing health and alleviating burden on health care systems. Product designers have long been aware of the importance of intertwining emotional experiences with new products. However, a lack of theoretical precision exists for applying emotional design beyond food products, to the food systems, services and business models that drive them. This article explores emotional design within the context of food and food systems and proposes a new concept – Emotional Food Design (EFD), through which emotional design is integrated across levels of a food system. EFD complements the dominating deductive view of food systems research with an abductive iterative design approach contextualized within the creation of new food products, services and business models and their associated emotional attachments. This paper concludes by outlining what EFD can offer to reorient food systems to successfully promote healthy eating.

Determination of dimethyl sulfide in gas samples by single photon ionization time of flight mass spectrometry

It is difficult to determine sulfur-containing volatile organic compounds in the atmosphere because of their reactivity. Primary off-line techniques may suffer losses of analytes during the transportation from field to laboratory and sample preparation. In this study, a novel method was developed to directly measure dimethyl sulfide at parts-per-billion concentration levels in the atmosphere using vacuum ultraviolet single photon ionization time-of-flight mass spectrometry. This technique offers continuous sampling at a response rate of one measurement per second, or cumulative measurements over longer time periods. Laboratory prepared samples of different concentrations of dimethyl sulfide in pure nitrogen gas were analyzed at several sampling frequencies. Good precision was achieved using sampling periods of at least 60 seconds with a relative standard deviation of less than 25%. The detection limit for dimethyl sulfide was below the 3 ppb olfactory threshold. These results demonstrate that single photon ionization time-of-flight mass spectrometry is a valuable tool for rapid, real-time measurements of sulfur-containing organic compounds in the air.

A suitable method for journal bearing wear measurement

Purpose – Ideally, there is no wear in hydrodynamic lubrication regime. A small amount of wear occurs during start and stop of the machines and the amount of wear is so small that it is difficult to measure with accuracy. Various wear measuring techniques have been used where out-of-roundness was found to be the most reliable method of measuring small wear quantities in journal bearings. This technique was further developed to achieve higher accuracy in measuring small wear quantities. The method proved to be reliable as well as inexpensive. The paper aims to discuss these issues. Design/methodology/approach – In an experimental study, the effect of antiwear additives was studied on journal bearings lubricated with oil containing solid contaminants. The test duration was too long and the wear quantities achieved were too small. To minimise the test duration, short tests of about 90 min duration were conducted and wear was measured recording changes in variety of parameters related to weight, geometry and wear debris. The out-of-roundness was found to be the most effective method. This method was further refined by enlarging the out-of-roundness traces on a photocopier. The method was proved to be reliable and inexpensive. Findings – Study revealed that the most commonly used wear measurement techniques such as weight loss, roughness changes and change in particle count were not adequate for measuring small wear quantities in journal bearings. Out-of-roundness method with some refinements was found to be one of the most reliable methods for measuring small wear quantities in journal bearings working in hydrodynamic lubrication regime. By enlarging the out-of-roundness traces and determining the worn area of the bearing cross-section, weight loss in bearings was calculated, which was repeatable and reliable. Research limitations/implications – This research is a basic in nature where a rudimentary solution has been developed for measuring small wear quantities in rotary devices such as journal bearings. The method requires enlarging traces on a photocopier and determining the shape of the worn area on an out-of-roundness trace on a transparency, which is a simple but a crude method. This may require an automated procedure to determine the weight loss from the out-of-roundness traces directly. This method can be very useful in reducing test duration and measuring wear quantities with higher precision in situations where wear quantities are very small. Practical implications – This research provides a reliable method of measuring wear of circular geometry. The Talyrond equipment used for measuring the change in out-of-roundness due to wear of bearings indicates that this equipment has high potential to be used as a wear measuring device also. Measurement of weight loss from the traces is an enhanced capability of this equipment and this research may lead to the development of a modified version of Talyrond type of equipment for wear measurements in circular machine components. Originality/value – Wear measurement in hydrodynamic bearings requires long duration tests to achieve adequate wear quantities. Out-of-roundness is one of the geometrical parameters that changes with progression of wear in a circular shape components. Thus, out-of-roundness is found to be an effective wear measuring parameter that relates to change in geometry. Method of increasing the sensitivity and enlargement of out-of-roundness traces is original work through which area of worn cross-section can be determined and weight loss can be derived for materials of known density with higher precision.

Determination of tricyclazole in water using solid phase extraction and liquid chromatography

A method for determination of tricyclazole in water using solid phase extraction and high performance liquid chromatography (HPLC) with UV detection at 230nm and a mobile phase of acetonitrile:water (20:80, v/v) was developed. A performance comparison between two types of solid phase sorbents, the C18 sorbent of Supelclean ENVI-18 cartridge and the styrene-divinyl benzene copolymer sorbent of Sep-Pak PS2-Plus cartridge was conducted. The Sep-Pak PS2-Plus cartridges were found more suitable for extracting tricyclazole from water samples than the Supelclean ENVI-18 cartridges. For this cartridge, both methanol and ethyl acetate produced good results. The method was validated with good linearity and with a limit of detection of 0.008gL-1 for a 500-fold concentration through the SPE procedure. The recoveries of the method were stable at 80% and the precision was from 1.1-6.0% within the range of fortified concentrations. The validated method was also applied to measure the concentrations of tricyclazole in real paddy water.

The in vivo fate of nanoparticles and nanoparticle-loaded microcapsules after oral administration in mice: Evaluation of their potential for colon-specific delivery

Anti-cancer drug loaded-nanoparticles (NPs) or encapsulation of NPs in colon-targeted delivery systems shows potential for increasing the local drug concentration in the colon leading to improved treatment of colorectal cancer. To investigate the potential of the NP-based strategies for colon-specific delivery, two formulations, free Eudragit® NPs and enteric-coated NP-loaded chitosan–hypromellose microcapsules (MCs) were fluorescently-labelled and their tissue distribution in mice after oral administration was monitored by multispectral small animal imaging. The free NPs showed a shorter transit time throughout the mouse digestive tract than the MCs, with extensive excretion of NPs in faeces at 5 h. Conversely, the MCs showed complete NP release in the lower region of the mouse small intestine at 8 h post-administration. Overall, the encapsulation of NPs in MCs resulted in a higher colonic NP intensity from 8 h to 24 h post-administration compared to the free NPs, due to a NP ‘guarding’ effect of MCs during their transit along mouse gastrointestinal tract which decreased NP excretion in faeces. These imaging data revealed that this widely-utilised colon-targeting MC formulation lacked site-precision for releasing its NP load in the colon, but the increased residence time of the NPs in the lower gastrointestinal tract suggests that it is still useful for localised release of chemotherapeutics, compared to NP administration alone. In addition, both formulations resided in the stomach of mice at considerable concentrations over 24 h. Thus, adhesion of NP- or MC-based oral delivery systems to gastric mucosa may be problematic for colon-specific delivery of the cargo to the colon and should be carefully investigated for a full evaluation of particulate delivery systems.

Structure matters: Adoption of structured classification Approach in the context of cognitive presence classification

Within online learning communities, receiving timely and meaningful insights into the quality of learning activities is an important part of an effective educational experience. Commonly adopted methods – such as the Community of Inquiry framework – rely on manual coding of online discussion transcripts, which is a costly and time consuming process. There are several efforts underway to enable the automated classification of online discussion messages using supervised machine learning, which would enable the real-time analysis of interactions occurring within online learning communities. This paper investigates the importance of incorporating features that utilise the structure of on-line discussions for the classification of "cognitive presence" – the central dimension of the Community of Inquiry framework focusing on the quality of students' critical thinking within online learning communities. We implemented a Conditional Random Field classification solution, which incorporates structural features that may be useful in increasing classification performance over other implementations. Our approach leads to an improvement in classification accuracy of 5.8% over current existing techniques when tested on the same dataset, with a precision and recall of 0.630 and 0.504 respectively.

Biomimicking natural nanopatterned topology by 3D laser lithography

Natural nanopatterned surfaces (nNPS) present on insect wings have demonstrated bactericidal activity [1, 2]. Fabricated nanopatterned surfaces (fNPS) derived by characterization of these wings have also shown superior bactericidal activity [2]. However bactericidal NPS topologies vary in both geometry and chemical characteristics of the individual features in different insects and fabricated surfaces, rendering it difficult to ascertain the optimum geometrical parameters underling bactericidal activity. This situation calls for the adaptation of new and emerging techniques, which are capable of fabricating and characterising comparable structures to nNPS from biocompatible materials. In this research, CAD drawn nNPS representing an area of 10 μm x10 μm was fabricated on a fused silica glass by Nanoscribe photonic professional GT 3D laser lithography system using two photon polymerization lithography. The glass was cleaned with acetone and isopropyl alcohol thrice and a drop of IP-DIP photoresist from Nanoscribe GmbH was cast onto the glass slide prior to patterning. Photosensitive IP-DIP resist was polymerized with high precision to make the surface nanopatterns using a 780 nm wavelength laser. Both moving-beam fixedsample (MBFS) and fixed-beam moving-sample (FBMS) fabrication approaches were tested during the fabrication process to determine the best approach for the precise fabrication of the required nanotopological pattern. Laser power was also optimized to fabricate the required fNPS, where this was changed from 3mW to 10mW to determine the optimum laser power for the polymerization of the photoresist for fabricating FNPS...

Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach

Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.

Target acquired: Progress and promise of targeted therapeutics in the treatment of prostate cancer

Cancer is fundamentally a genomic disease caused by mutations or rearrangements in the DNA or epigenetic machinery of a patient. An emerging field in cancer treatment targets key aberrations arising from the mutational landscape of an individual patient’s disease rather than employing a cancer-wide cytotoxic therapy approach. In prostate cancer in particular, where there is an observed variation in response to standard treatments between patients with disease of a similar pathological stage and grade, mutationdirected treatment may grow to be a viable tool for clinicians to tailor more effective treatments. This review will describe a number of mutations across multiple forms of cancer that have been successfully antagonised by targeted therapeutics including their identification, the development of targeted compounds to combat them and the development of resistance to these therapies. This review will continue to examine these same mutations in the treatment and management of prostate cancer; the prevalence of targetable mutations in prostate cancer, recent clinical trials of targeted-agents and the potential or limitations for their use.

Building instance knowledge network for word sense disambiguation

In this paper, a new high precision focused word sense disambiguation (WSD) approach is proposed, which not only attempts to identify the proper sense for a word but also provides the probabilistic evaluation for the identification confidence at the same time. A novel Instance Knowledge Network (IKN) is built to generate and maintain semantic knowledge at the word, type synonym set and instance levels. Related algorithms based on graph matching are developed to train IKN with probabilistic knowledge and to use IKN for probabilistic word sense disambiguation. Based on the Senseval-3 all-words task, we run extensive experiments to show the performance enhancements in different precision ranges and the rationality of probabilistic based automatic confidence evaluation of disambiguation. We combine our WSD algorithm with five best WSD algorithms in senseval-3 all words tasks. The results show that the combined algorithms all outperform the corresponding algorithms.