Viscosity and Thermal Expansion of Mixed-Alkali Borate Glasses

Transformation-range viscosity and thermal expansion measurements were made for five series (Li-Na, Li-K, Li-Cs, Na-Cs, and K-Rb) of mixed-alkali borate glasses containing 30 mol% total alkali oxide. In each case, negative deviations from additivity were observed in the isokom and glass transformation temperatures. Positive deviations from additivity were observed in the thermal expansion coefficients for the Li-Na, Li-K, and K-Rb glasses, while the Li-Cs and Na-Cs glasses exhibited negative deviations. Maximization of the deviation from additivity in the viscosity and glass transformation temperatures occurred when the radius ratio of the two alkali ions was approximately 1.7 to 1.8. Combination of the results of this study with those of earlier studies indicates that the deviations from additivity observed for these properties are independent of the identity of the glass former.     

Lightweight dynamic symmetry breaking

Symmetries in constraint problems present an opportunity for reducing search. This paper presents Lightweight Dynamic Symmetry Breaking, an automatic symmetry breaking method that is efficient enough to be used as a default, since it never yields a major slowdown while often giving major performance improvements. This is achieved by automatically exploiting certain kinds of symmetry that are common, can be compactly represented, easily and efficiently processed, automatically detected, and lead to large reductions in search. Moreover, the method is easy to implement and integrate in any constraint system. Experimental results show the method is competitive with the best symmetry breaking methods without risking poor performance.     

Exploring aspects of cell intelligence with artificial reaction networks

The Artificial Reaction Network (ARN) is a Cell Signalling Network inspired connectionist representation belonging to the branch of A-Life known as Artificial Chemistry. Its purpose is to represent chemical circuitry and to explore computational properties responsible for generating emergent high-level behaviour associated with cells. In this paper, the computational mechanisms involved in pattern recognition and spatio-temporal pattern generation are examined in robotic control tasks. The results show that the ARN has application in limbed robotic control and computational functionality in common with Artificial Neural Networks. Like spiking neural models, the ARN can combine pattern recognition and complex temporal control functionality in a single network, however it offers increased flexibility. Furthermore, the results illustrate parallels between emergent neural and cell intelligence.     

Adaptive relationships of epoxide hydrolase in herbivorous arthropods

Epoxide hydrolase catalyzes a simple hydrolysis of reactive cyclic ethers that may otherwise alkylate and impair critical proteins and nucleic acids required for life. Although much less studied than the cytochrome P-450 monooxygenases that produce epoxides, differences in subcellular, tissue, pH, substrate, and inhibitor specificities argue for at least three forms of insect epoxide hydrolase. Increasing numbers of epoxides are being identified as plant allelochemicals, antifeedants, and essential hormones or precursors for herbivorous arthropods, and in many cases an associated alkene to diol pathway of metabolism is found. A role for epoxide hydrolase in arthropod-plant interactions is strongly supported by species comparisons and by age-activity and induction studies. Two major limitations for study in biochemical ecology of epoxide hydrolase are the lack of an effective in vivo inhibitor and a range of commercially available radiolabeled substrates for the enzymes.     

'Polymorph Method' Determination of Monoclinic Zirconia in Partially Stabilized Zirconia Ceramics

The polymorph method, which provides phase analysis from a small number of integrated intensities in a powder diffraction scan, is adapted for the determination of monoclinic zirconia in a mixture with cubic, tetragonal. and orthorhombic zirconias and the γ-phase (Mg₂Zr₅O₁₂). Such a mixture is representative of Mg-PSZ after subeutectoid aging. The quantitative determination of the monoclinic depends in principle on a knowledge of the relative amounts of the other phases present in the mixture. It is demonstrated, however, that without this knowledge, even in complex mixtures, the traditional polymorph method analysis gives an acceptable estimate of the monoclinic fraction in the sample.     

Ongoing verification of a multiphysics community code: FLASH

When developing a complex, multi‐authored code, daily testing on multiple platforms and under a variety of conditions is essential. It is therefore necessary to have a regression test suite that is easily administered and configured, as well as a way to easily view and interpret the test suite results. We describe the methodology for verification of FLASH, a highly capable multiphysics scientific application code with a wide user base. The methodology uses a combination of unit and regression tests and an in‐house testing software that is optimized for operation under limited resources. Although our practical implementations do not always comply with theoretical regression‐testing research, our methodology provides a comprehensive verification of a large scientific code under resource constraints.Copyright © 2013 John Wiley & Sons, Ltd.     

Visual search tree profiling

Understanding how the search space is explored for a given constraint problem – and how it changes for different models, solvers or search strategies – is crucial for efficient solving. Yet programmers often have to rely on the crude aggregate measures of the search that are provided by solvers, or on visualisation tools that can show the search tree, but do not offer sophisticated ways to navigate and analyse it, particularly for large trees. We present an architecture for profiling a constraint programming search that is based on a lightweight instrumentation of the solver. The architecture combines a visualisation of the search tree with various tools for convenient navigation and analysis of the search. These include identifying repeated subtrees, high-level abstraction and navigation of the tree, and the comparison of two search trees. The resulting system is akin to a traditional program profiler, which helps the user to focus on the parts of the execution where an improvement to their program would have the greatest effect.     

Privacy Preserving Geo-Linkage in the Big Urban Data Era

Big data technologies and a range of Government open data initiatives provide the basis for discovering new insights into cities; how they are planned, how they managed and the day-to-day challenges they face in health, transport and changing population profiles. The Australian Urban Research Infrastructure Network (AURIN – www.aurin.org.au) project is one example of such a big data initiative that is currently running across Australia. AURIN provides a single gateway providing online (live) programmatic access to over 2000 data sets from over 70 major and typically definitive data-driven organizations across federal and State government, across industry and across academia. However whilst open (public) data is useful to bring data-driven intelligence to cities, more often than not, it is the data that is not-publicly accessible that is essential to understand city challenges and needs. Such sensitive (unit-level) data has unique requirements on access and usage to meet the privacy and confidentiality demands of the associated organizations. In this paper we highlight a novel geo-privacy supporting solution implemented as part of the AURIN project that provides seamless and secure access to individual (unit-level) data from the Department of Health in Victoria. We illustrate this solution across a range of typical city challenges in localized contexts around Melbourne. We show how unit level data can be combined with other data in a privacy-protecting manner. Unlike other secure data access and usage solutions that have been developed/deployed, the AURIN solution allows any researcher to access and use the data in a manner that meets all of the associated privacy and confidentiality concerns, without obliging them to obtain ethical approval or any other hurdles that are normally put in place on access to and use of sensitive data. This provides a paradigm shift in secure access to sensitive data with geospatial content.     

Signage Versus Environmental Affordances: Is the Explicit Information Strong Enough to Guide Human Behavior During a Wayfinding Task?

This study aims to explore how people behave when they have to find a location within a complex building and are confronted with situations where directional signage (i.e., explicit information) is in opposition to environmental affordances that naturally direct users towards a specific path, creating a situation with conflicting information (e.g., a brighter corridor vs. a darker corridor but with a directional sign indicating to follow the darker one). A virtual reality–based methodology was used and a between‐subject design was considered. Thus, participants were given the tasks of finding three publicly accessible central points in a virtual hotel and confronted with a two forced‐choice task of local scenes in which environmental variables (i.e., corridor width and brightness) and signage varied systematically, in two experimental conditions (i.e., neutral and signage). For the signage condition, signs were inserted to explicitly point in the opposite direction than that implicitly suggested by the environmental affordances, creating situations with conflicting information. Results indicate that environmental variables were able to direct people indoors acting as environmental affordances. Users preferred to follow the wider and brighter paths. However, when directional signage pointed in the opposite direction of the paths preferred by the participants, most of them complied with signage.     

Assisting comprehension of animation programs through interactive code visualization

Visual languages have been widely used to help people create animation programs. However, current programming environments lack features supporting efficient code exploration and program comprehension, particularly for understanding relationships among parts of animation programs. In this paper, we present novel interactive visualizations aimed at helping people to understand animation programs. We conducted an empirical study to evaluate the impact of these visualizations on programmer comprehension of the code, showing that our approach enabled programmers to comprehend more information with less effort and in less time. This result is potentially significant because it demonstrates an approach for helping users to explore and understand animation code. We anticipate that this approach could be applied in a wide variety of animation programming tools, which could ease common animation programming tasks that require understanding code.