Performance of soft-hard-soft (SHS) cement based composite subjected to blast loading with consideration of interface properties

This paper presents a combined experimental and numerical study on the damage and performance of a soft-hard-soft (SHS) multi-layer cement based composite subjected to blast loading which can be used for protective structures and infrastructures to resist extreme loadings, and the composite consists of three layers of construction materials including asphalt concrete (AC) on the top, high strength concrete (HSC) in the middle, and engineered cementitious composites (ECC) at the bottom. To better characterize the material properties under dynamic loading, interface properties of the composite were investigated through direct shear test and also used to validate the interface model. Strain rate effects of the asphalt concrete were also studied and both compressive and tensile dynamic increase factor (DIF) curves were improved based on split Hopkinson pressure bar (SHPB) test. A full-scale field blast test investigated the blast behavior of the composite materials. The numerical model was established by taking into account the strain rate effect of all concrete materials. Furthermore, the interface properties were also considered into the model. The numerical simulation using nonlinear finite element software LS-DYNA agrees closely with the experimental data. Both the numerical and field blast test indicated that the SHS composite exhibited high resistance against blast loading.

Linear programming for large-scale Markov decision problems

We consider the problem of controlling a Markov decision process (MDP) with a large state space, so as to minimize average cost. Since it is intractable to compete with the optimal policy for large scale problems, we pursue the more modest goal of competing with a low-dimensional family of policies. We use the dual linear programming formulation of the MDP average cost problem, in which the variable is a stationary distribution over state-action pairs, and we consider a neighborhood of a low-dimensional subset of the set of stationary distributions (defined in terms of state-action features) as the comparison class. We propose a technique based on stochastic convex optimization and give bounds that show that the performance of our algorithm approaches the best achievable by any policy in the comparison class. Most importantly, this result depends on the size of the comparison class, but not on the size of the state space. Preliminary experiments show the effectiveness of the proposed algorithm in a queuing application.

Grant application: QUT Learning and Teaching scheme 2012 Cracking the Code - A checklist to complement CRAs for first year Justice students.

Widening participation brings with it increasing diversity, increased variation in the level of academic preparedness (Clarke, 2011; Nelson, Clarke, & Kift 2010). Cultural capital coupled with negotiating the academic culture creates an environment based on many assumptions about academic writing and university culture. Variations in staff and student expectations relating to the teaching and learning experience is captured in a range of national and institutional data (AUSSE, CEQ, LEX). Nationally, AUSSE data (2009) indicates that communication, writing, speaking and analytic skills, staff expectations are quite a bit higher than students. The research team noted a recognisable shift in the changing cohort of students and their understanding and engagement with feedback and CRAs, as well as variations in teaching staff and student expectations. The current reality of tutor and student roles is that: - Students self select when/how they access lectures and tutorials. - Shorter tutorial times result in reduced opportunity to develop rapport with students. - CRAs are not always used consistently by staff (different marking styles and levels of feedback). - Marking is not always undertaken by the student’s tutor/lecturer. - Student support services might be recommended to students once a poor grade has been given. Students can perceive this as remedial and a further sense of failure. - CRA sheet has a mark /grade attached to it. Stigma attached to low mark. Hard to focus on the CRA feedback with a poor mark etched next to it. - Limited opportunities for sessionals to access professional development to assist with engaging students and feedback. - FYE resources exist, however academic time is a factor in exploring and embedding these resources. Feedback is another area with differing expectations and understandings. Sadler (2009) contends that students are not equipped to decode the statements properly. For students to be able to apply feedback, they need to understand the meaning of the feedback statement. They also need to identify, the particular aspects of their work that need attention. The proposed Checklist/guide would be one page and submitted with each assessment piece thereby providing an interface to engage students and tutors in managing first year understandings and expectations around CRAs, feedback, and academic practice.

Removal of organic content from diesel exhaust particles alters cellular responses of primary human bronchial epithelial cells cultured at an air-liquid interface

Background Exposure to air pollutants, including diesel particulate matter, has been linked to adverse respiratory health effects. Inhaled diesel particulate matter contains adsorbed organic compounds. It is not clear whether the adsorbed organics or the residual components are more deleterious to airway cells. Using a physiologically relevant model, we investigated the role of diesel organic content on mediating cellular responses of primary human bronchial epithelial cells (HBECs) cultured at an air-liquid interface (ALI). Methods Primary HBECs were cultured and differentiated at ALI for at least 28 days. To determine which component is most harmful, we compared primary HBEC responses elicited by residual (with organics removed) diesel emissions (DE) to those elicited by neat (unmodified) DE for 30 and 60 minutes at ALI, with cigarette smoke condensate (CSC) as the positive control, and filtered air as negative control. Cell viability (WST-1 cell proliferation assay), inflammation (TNF-α, IL-6 and IL-8 ELISA) and changes in gene expression (qRT-PCR for HO-1, CYP1A1, TNF-α and IL-8 mRNA) were measured. Results Immunofluorescence and cytological staining confirmed the mucociliary phenotype of primary HBECs differentiated at ALI. Neat DE caused a comparable reduction in cell viability at 30 or 60 min exposures, whereas residual DE caused a greater reduction at 60 min. When corrected for cell viability, cytokine protein secretion for TNF-α, IL-6 and IL-8 were maximal with residual DE at 60 min. mRNA expression for HO-1, CYP1A1, TNF-α and IL-8 was not significantly different between exposures. Conclusion This study provides new insights into epithelial cell responses to diesel emissions using a physiologically relevant aerosol exposure model. Both the organic content and residual components of diesel emissions play an important role in determining bronchial epithelial cell response in vitro. Future studies should be directed at testing potentially useful interventions against the adverse health effects of air pollution exposure.

Supramolecular control of the magnetic anisotropy in two-dimensional high-spin Fe arrays at a metal interface

Magnetic atoms at surfaces are a rich model system for solid-state magnetic bits exhibiting either classical(1,2) or quantum(3,4) behaviour. Individual atoms, however, are difficult to arrange in regular patterns(1-5). Moreover, their magnetic properties are dominated by interaction with the substrate, which, as in the case of Kondo systems, often leads to a decrease or quench of their local magnetic moment(6,7). Here, we show that the supramolecular assembly of Fe and 1,4-benzenedicarboxylic acid molecules on a Cu surface results in ordered arrays of high-spin mononuclear Fe centres on a 1.5nm square grid. Lateral coordination with the molecular ligands yields unsaturated yet stable coordination bonds, which enable chemical modification of the electronic and magnetic properties of the Fe atoms independently from the substrate. The easy magnetization direction of the Fe centres can be switched by oxygen adsorption, thus opening a way to control the magnetic anisotropy in supramolecular layers akin to that used in metallic thin films.

In situ investigation of explosive crystallization in a-Ge: Experimental determination of the interface response function using dynamic transmission electron microscopy

The crystallization of amorphous semiconductors is a strongly exothermic process. Once initiated the release of latent heat can be sufficient to drive a self-sustaining crystallization front through the material in a manner that has been described as explosive. Here, we perform a quantitative in situ study of explosive crystallization in amorphous germanium using dynamic transmission electron microscopy. Direct observations of the speed of the explosive crystallization front as it evolves along a laser-imprinted temperature gradient are used to experimentally determine the complete interface response function (i.e., the temperature-dependent front propagation speed) for this process, which reaches a peak of 16 m/s. Fitting to the Frenkel-Wilson kinetic law demonstrates that the diffusivity of the material locally/immediately in advance of the explosive crystallization front is inconsistent with those of a liquid phase. This result suggests a modification to the liquid-mediated mechanism commonly used to describe this process that replaces the phase change at the leading amorphous-liquid interface with a change in bonding character (from covalent to metallic) occurring in the hot amorphous material.

Model Predictive Static Programming: A Computationally Efficient Technique For Suboptimal Control Design

Combining the philosophies of nonlinear model predictive control and approximate dynamic programming, a new suboptimal control design technique is presented in this paper, named as model predictive static programming (MPSP), which is applicable for finite-horizon nonlinear problems with terminal constraints. This technique is computationally efficient, and hence, can possibly be implemented online. The effectiveness of the proposed method is demonstrated by designing an ascent phase guidance scheme for a ballistic missile propelled by solid motors. A comparison study with a conventional gradient method shows that the MPSP solution is quite close to the optimal solution.

Stability of Dimeric Interface in Banana Lectin: Insight from Molecular Dynamics Simulations

Banana lectin (Banlec) is a homodimeric non-glycosylated protein. It exhibits the b-prism I structure. High-temperature molecular dynamics simulations have been utilized to monitor and understand early stages of thermally induced unfolding of Banlec. The present study elucidates the behavior of the dimeric protein at four different temperatures and compares the structural and conformational changes to that of the minimized crystal structure. The process of unfolding was monitored by following the radius of gyration, the rms deviation of each residue, change in relative solvent accessibility and the pattern of inter- and intra-subunit interactions. The overall study demonstrates that the Banlec dimer is a highly stable structure, and the stability is mostly contributed by interfacial interactions. It maintains its overall conformation during high-temperature (400–500 K) simulations, with only the unstructured loop regions acquiring greater momentum under such condition. Nevertheless, at still higher temperatures (600 K) the tertiary structure is gradually lost which later extends to loss of secondary structural elements. The pattern of hydrogen bonding within the subunit and at the interface across different stages has been analyzed and has provided rationale for its intrinsic high stability.

Functional correlation of bacterial LuxS with their quaternary associations: interface analysis of the structure networks

Background The genome of a wide variety of prokaryotes contains the luxS gene homologue, which encodes for the protein S-ribosylhomocysteinelyase (LuxS). This protein is responsible for the production of the quorum sensing molecule, AI-2 and has been implicated in a variety of functions such as flagellar motility, metabolic regulation, toxin production and even in pathogenicity. A high structural similarity is present in the LuxS structures determined from a few species. In this study, we have modelled the structures from several other species and have investigated their dimer interfaces. We have attempted to correlate the interface features of LuxS with the phenotypic nature of the organisms. Results The protein structure networks (PSN) are constructed and graph theoretical analysis is performed on the structures obtained from X-ray crystallography and on the modelled ones. The interfaces, which are known to contain the active site, are characterized from the PSNs of these homodimeric proteins. The key features presented by the protein interfaces are investigated for the classification of the proteins in relation to their function. From our analysis, structural interface motifs are identified for each class in our dataset, which showed distinctly different pattern at the interface of LuxS for the probiotics and some extremophiles. Our analysis also reveals potential sites of mutation and geometric patterns at the interface that was not evident from conventional sequence alignment studies. Conclusion The structure network approach employed in this study for the analysis of dimeric interfaces in LuxS has brought out certain structural details at the side-chain interaction level, which were elusive from the conventional structure comparison methods. The results from this study provide a better understanding of the relation between the luxS gene and its functional role in the prokaryotes. This study also makes it possible to explore the potential direction towards the design of inhibitors of LuxS and thus towards a wide range of antimicrobials.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

Nanocrystalline Janus films of inorganic materials prepared at the liquid-liquid interface

The interface between toluene and water has been employed to prepare ultrathin Janus nanocrystalline films of metal oxides, metal chalcogenides and gold, wherein the surface on the organic-side is hydrophobic and the aqueous-side is hydrophilic. We have changed the nature of the metal precursor or capping agent in the organic layer to increase the hydrophobicity. The strategy employed for this purpose is to increase the length of the alkane chain in the precursor or use a perfluroalkane derivative as precursor or as a capping agent. The hydrophobicity and hydrophilicity of the Janus films have been determined by contact angle measurements. The morphology of hydrophobic and hydrophilic sides of the film have been examined by field emission scanning electron microscopy.

Partial discharges at low pressures in a dielectric interface between uniform field electrodes

Partial discharges in a gaseous interface due to the presence of a dielectric between two uniform field electrodes in air at different pressures from 0.5 to 685 mm Hg have been studied and measurements of inception and extinction voltages, number of pulses and their charge magnitudes at inception are reported. It has been observed that the extinction voltage can be as low as 70% of the inception voltage suggesting that the working voltage in such cases should be about 30% lower than the observed inception voltage. Small magnitude pulses are found to be more in number than large magnitude pulses. The charge is found to be pressure dependent. The results have been explained on the basis of an equivalent circuit consisting of resistance and capacitance in which the discharge gap functions as a switch.

Mathematics, programming, and STEM

Learning mathematics is a complex and dynamic process. In this paper, the authors adopt a semiotic framework (Yeh & Nason, 2004) and highlight programming as one of the main aspects of the semiosis or meaning-making for the learning of mathematics. During a 10-week teaching experiment, mathematical meaning-making was enriched when primary students wrote Logo programs to create 3D virtual worlds. The analysis of results found deep learning in mathematics, as well as in technology and engineering areas. This prompted a rethinking about the nature of learning mathematics and a need to employ and examine a more holistic learning approach for the learning in science, technology, engineering, and mathematics (STEM) areas.

Nanostructured Peptide Fibrils Formed at the Organic-Aqueous Interface and Their Use as Templates To Prepare Inorganic Nanostructures

Formation of fibril-type nanostructures of the Alzheimer's beta-amyloid diphenylalanine (L-Phe-L-Phe, FF) at the organic-aqueous interface and the factors affecting their structures have been investigated. Such nanostructures are also formed by bovine serum albumin and bovine pancreas insulin. The concentration of the precursor taken in the aqueous layer plays an important role in determining the morphology of the nanostructures, The addition of curcumin to the organic layer changes the structure of the self-assembled one-dimensional aggregates of diphenylalanine. By coating the diphenylalanine dipeptide fibrils with appropriate precursors followed by calcination in air, it has been possible to obtain one-dimensional nanostructures of inorganic materials.