Thermal tweezers for manipulation of adatoms and nanoparticles on surfaces heated by interfering laser pulses

We conduct the detailed numerical investigation of a nanomanipulation and nanofabrication technique—thermal tweezers with dynamic evolution of surface temperature, caused by absorption of interfering laser pulses in a thin metalfilm or any other absorbing surface. This technique uses random Brownian forces in the presence of strong temperature modulation (surfacethermophoresis) for effective manipulation of particles/adatoms with nanoscale resolution. Substantial redistribution of particles on the surface is shown to occur with the typical size of the obtained pattern elements of ∼100 nm, which is significantly smaller than the wavelength of the incident pulses used (532 nm). It is also demonstrated that thermal tweezers based on surfacethermophoresis of particles/adatoms are much more effective in achieving permanent high maximum-to-minimum concentration ratios than bulk thermophoresis, which is explained by the interaction of diffusing particles with the periodic lattice potential on the surface. Typically required pulse regimes including pulse lengths and energies are also determined. The approach is applicable for reproducing any holographically achievable surfacepatterns, and can thus be used for engineering properties of surfaces including nanopatterning and design of surface metamaterials.

Thin film deposition and characterization of pure and iron-doped electron-beam evaporated tungsten oxide for gas sensors

Pure Tungsten Oxide (WO3) and Iron-doped (10 at%) Tungsten Oxide (WO3:Fe) nanostructured thin films were prepared using a dual crucible Electron Beam Evaporation techniques. The films were deposited at room temperature in high vacuum condition on glass substrate and post-heat treated at 300 oC for 1 hour. From the study of X-ray diffraction and Raman the characteristics of the as-deposited WO3 and WO3:Fe films indicated non-crystalline nature. The surface roughness of all the films showed in the order of 2.5 nm as observed using Atomic Force Microscopy (AFM). X-Ray Photoelectron Spectroscopy (XPS) analysis revealed tungsten oxide films with stoichiometry close to WO3. The addition of Fe to WO3 produced a smaller particle size and lower porosity as observed using Transmission Electron Microscopy (TEM). A slight difference in optical band gap energies of 3.22 eV and 3.12 eV were found between the as-deposited WO3 and WO3:Fe films, respectively. However, the difference in the band gap energies of the annealed films were significantly higher having values of 3.12 eV and 2.61 eV for the WO3 and WO3:Fe films, respectively. The heat treated samples were investigated for gas sensing applications using noise spectroscopy and doping of Fe to WO3 reduced the sensitivity to certain gasses. Detailed study of the WO3 and WO3:Fe films gas sensing properties is the subject of another paper.

25th anniversary of BUA for the assessment of osteoporosis : time for a new paradigm?

The measurement of broadband ultrasonic attenuation (BUA) in cancellous bone at the calcaneus for the assessment of osteoporosis was first described within this journal 25 years ago. It was recognized in 2006 by Universities UK as being one of the ‘100 discoveries and developments in UK Universities that have changed the world’ over the past 50 years. In 2008, the UK's Department of Health also recognized BUA assessment of osteoporosis in a publication highlighting 11 projects that have contributed to ‘60 years of NHS research benefiting patients’. The BUA technique has been extensively clinically validated and is utilized worldwide, with at least seven commercial systems currently providing calcaneal BUA measurement. However, there is still no fundamental understanding of the dependence of BUA upon the material and structural properties of cancellous bone. This review aims to provide an ‘engineering in medicine’ perspective and proposes a new paradigm based upon phase cancellation due to variation in propagation transit time across the receive transducer face to explain the non-linear relationship between BUA and bone volume fraction in cancellous bone.

Learning to avoid indoor obstacles from optical flow

Optical flow (OF) is a powerful motion cue that captures the fusion of two important properties for the task of obstacle avoidance − 3D self-motion and 3D environmental surroundings. The problem of extracting such information for obstacle avoidance is commonly addressed through quantitative techniques such as time-to-contact and divergence, which are highly sensitive to noise in the OF image. This paper presents a new strategy towards obstacle avoidance in an indoor setting, using the combination of quantitative and structural properties of the OF field, coupled with the flexibility and efficiency of a machine learning system.The resulting system is able to effectively control the robot in real-time, avoiding obstacles in familiar and unfamiliar indoor environments, under given motion constraints. Furthermore, through the examination of the networks internal weights, we show how OF properties are being used toward the detection of these indoor obstacles.

Electron beam evaporation of tungsten oxide films for gas sensors

Pure and Iron incorporated nanostructured Tungsten Oxide (WO3) thin films were investigated for gas sensing applications using noise spectroscopy. The WO3 sensor was able to detect lower concentrations (1 ppm-10 ppm) of NH3, CO, CH4 and Acetaldehyde gases at operating temperatures between 100 degrees celcius to 250 degrees celcius. The iron doped Tungsten Oxide sensor (WO3:Fe) showed some response to Acetaldehyde gas at relatively higher operating temperature (250 degrees celcius) and gas concentration of 10 ppm. The sensitivity of the WO3 sensor towards NH3, CH4 and Acetaldehyde at lower operating temperatures (50 degrees celcius - 100 degrees celcius) was significant when the sensor was photo-activated using blue-light emitting diode (Blue-LED). From the results, photo-activated WO3 thin film that operates at room temperature appeared to be a promising gas sensor. The overall results indicated that the WO3 sensor exhibited reproducibility for the detection of various gases and the WO3:Fe indicated some response towards Acetaldehyde gas.

Carbon nanotube synthesis from germanium nanoparticles on patterned substrates

Controlled synthesis of carbon nanotubes (CNTs) is highly desirable for nanoelectronic applications. To date, metallic catalyst particles have been deemed unavoidable for the nucleation and growth of any kind of CNTs. Ordered arrays of nanotubes have been obtained by controlled deposition of the metallic catalyst particles. However, the presence of metal species mixed with the CNTs represents a shortcoming for most electronic applications, as metal particles are incompatible with silicon semiconductor technology. In the present paper we report on a metal-catalyst-free synthesis of CNTs, obtained through Ge nanoparticles on a Si(001) surface patterned by nanoindentation. By using acetylene as the carbon feed gas in a low-pressure Chemical Vapor Deposition (CVD) system, multi-walled carbon nanotubes (MWNT) have been observed to arise from the smallest Ge islands. The CNTs and the Ge three-dimensional structures have been analysed by SEM, EDX and AFM in order to assess their elemental features and properties. EDX and SEM results allow confirmation of the absence of any metallic contamination on the surface, indicating that the origin of the CNT growth is due to the Ge nanocrystals.

Azo- and butadiyne-linked 5,10-diarylporphyrins

Porphyrins are one of Nature’s essential building blocks that play an important role in several biological systems including oxygen transport, photosynthesis, and enzymes. Their capacity to absorb visible light, facilitate oxidation and reduction, and act as energy- and electron-transfer agents, in particular when several are held closely together, is of interest to chemists who seek to mimic Nature and to make and use these compounds in order to synthesise novel advanced materials. During this project 26 new 5,10-diarylsubstituted porphyrin monomers, 10 dimers, and 1 tetramer were synthesised. The spectroscopic and structural properties of these compounds were investigated using 1D/2D 1H NMR, UV/visible, ATR-IR and Raman spectroscopy, mass spectrometry, X-ray crystallography, electrochemistry and gel permeation chromatography. Nitration, amination, bromination and alkynylation of only one as well as both of the meso positions of the porphyrin monomers have resulted in the expansion of the synthetic possibilities for the 5,10-diarylsubstituted porphyrins. The development of these new porphyrin monomers has led to the successful synthesis of new azo- and butadiyne-linked dimers. The functionalisation of these compounds was investigated, in particular nitration, amination, and bromination. The synthesised dimers containing the azo bridge have absorption spectra that show a large split in the Soret bands and intense Q-bands that have been significantly redshifted. The butadiyne dimers also have intense, red-shifted Q-bands but smaller Soret band splittings. Crystal structures of two new azoporphyrins have been acquired and compared to the azoporphyrin previously synthesised from 5,10,15- triarylsubstituted porphyrin monomers. A completely new cyclic porphyrin oligomer (CPO) was synthesised comprising four porphyrin monomers linked by azo and butadiyne bridges. This is the first cyclic tetramer that has both the azo and butadiyne linking groups. The absorption spectrum of the tetramer exhibits a large Soret split making it more similar to the azo- dimers than the butadiyne-linked dimers. The spectroscopic characteristics of the synthesised tetramer have been compared to the characteristics of other cyclic porphyrin tetramers. The collected data indicate that the new synthesised cyclic tetramer has a more efficient ð-overlap and a better ground state electronic communication between the porphyrin rings.

Modelling and solving train scheduling problems under capacity constraints

Many large coal mining operations in Australia rely heavily on the rail network to transport coal from mines to coal terminals at ports for shipment. Over the last few years, due to the fast growing demand, the coal rail network is becoming one of the worst industrial bottlenecks in Australia. As a result, this provides great incentives for pursuing better optimisation and control strategies for the operation of the whole rail transportation system under network and terminal capacity constraints. This PhD research aims to achieve a significant efficiency improvement in a coal rail network on the basis of the development of standard modelling approaches and generic solution techniques. Generally, the train scheduling problem can be modelled as a Blocking Parallel- Machine Job-Shop Scheduling (BPMJSS) problem. In a BPMJSS model for train scheduling, trains and sections respectively are synonymous with jobs and machines and an operation is regarded as the movement/traversal of a train across a section. To begin, an improved shifting bottleneck procedure algorithm combined with metaheuristics has been developed to efficiently solve the Parallel-Machine Job- Shop Scheduling (PMJSS) problems without the blocking conditions. Due to the lack of buffer space, the real-life train scheduling should consider blocking or hold-while-wait constraints, which means that a track section cannot release and must hold a train until the next section on the routing becomes available. As a consequence, the problem has been considered as BPMJSS with the blocking conditions. To develop efficient solution techniques for BPMJSS, extensive studies on the nonclassical scheduling problems regarding the various buffer conditions (i.e. blocking, no-wait, limited-buffer, unlimited-buffer and combined-buffer) have been done. In this procedure, an alternative graph as an extension of the classical disjunctive graph is developed and specially designed for the non-classical scheduling problems such as the blocking flow-shop scheduling (BFSS), no-wait flow-shop scheduling (NWFSS), and blocking job-shop scheduling (BJSS) problems. By exploring the blocking characteristics based on the alternative graph, a new algorithm called the topological-sequence algorithm is developed for solving the non-classical scheduling problems. To indicate the preeminence of the proposed algorithm, we compare it with two known algorithms (i.e. Recursive Procedure and Directed Graph) in the literature. Moreover, we define a new type of non-classical scheduling problem, called combined-buffer flow-shop scheduling (CBFSS), which covers four extreme cases: the classical FSS (FSS) with infinite buffer, the blocking FSS (BFSS) with no buffer, the no-wait FSS (NWFSS) and the limited-buffer FSS (LBFSS). After exploring the structural properties of CBFSS, we propose an innovative constructive algorithm named the LK algorithm to construct the feasible CBFSS schedule. Detailed numerical illustrations for the various cases are presented and analysed. By adjusting only the attributes in the data input, the proposed LK algorithm is generic and enables the construction of the feasible schedules for many types of non-classical scheduling problems with different buffer constraints. Inspired by the shifting bottleneck procedure algorithm for PMJSS and characteristic analysis based on the alternative graph for non-classical scheduling problems, a new constructive algorithm called the Feasibility Satisfaction Procedure (FSP) is proposed to obtain the feasible BPMJSS solution. A real-world train scheduling case is used for illustrating and comparing the PMJSS and BPMJSS models. Some real-life applications including considering the train length, upgrading the track sections, accelerating a tardy train and changing the bottleneck sections are discussed. Furthermore, the BPMJSS model is generalised to be a No-Wait Blocking Parallel- Machine Job-Shop Scheduling (NWBPMJSS) problem for scheduling the trains with priorities, in which prioritised trains such as express passenger trains are considered simultaneously with non-prioritised trains such as freight trains. In this case, no-wait conditions, which are more restrictive constraints than blocking constraints, arise when considering the prioritised trains that should traverse continuously without any interruption or any unplanned pauses because of the high cost of waiting during travel. In comparison, non-prioritised trains are allowed to enter the next section immediately if possible or to remain in a section until the next section on the routing becomes available. Based on the FSP algorithm, a more generic algorithm called the SE algorithm is developed to solve a class of train scheduling problems in terms of different conditions in train scheduling environments. To construct the feasible train schedule, the proposed SE algorithm consists of many individual modules including the feasibility-satisfaction procedure, time-determination procedure, tune-up procedure and conflict-resolve procedure algorithms. To find a good train schedule, a two-stage hybrid heuristic algorithm called the SE-BIH algorithm is developed by combining the constructive heuristic (i.e. the SE algorithm) and the local-search heuristic (i.e. the Best-Insertion- Heuristic algorithm). To optimise the train schedule, a three-stage algorithm called the SE-BIH-TS algorithm is developed by combining the tabu search (TS) metaheuristic with the SE-BIH algorithm. Finally, a case study is performed for a complex real-world coal rail network under network and terminal capacity constraints. The computational results validate that the proposed methodology would be very promising because it can be applied as a fundamental tool for modelling and solving many real-world scheduling problems.

Towards controlled growth of carbon nanotubes from germanium on nanoindented silicon substrates

In this paper, we report on a metal-catalyst-free synthesis of carbon nanotubes (CNTs) on a pre-patterned Si(001) surface. Arrays of triangular-shaped holes were created by nanoindentation in specific sites of the sample. After germanium deposition and chemical vapor deposition (CVD) of acetylene, a few CNTs nucleated and grew from germanium nanoparticles. These results illustrate that it is possible to control the growth of CNTs without the use of any metal catalyst. By leading the assembly of Ge nanoparticles with a patterning technique, a precise control over the growth order is also attainable.

Ordering of Ge islands on Si(001) substrates patterned by nanoindentation

Spatial organization of Ge islands, grown by physical vapor deposition, on prepatterned Si(001) substrates has been investigated. The substrates were patterned prior to Ge deposition by nanoindentation. Characterization of Ge dots is performed by atomic force microscopy and scanning electron microscopy. The nanoindents act as trapping sites, allowing ripening of Ge islands at those locations during subsequent deposition and diffusion of Ge on the surface. The results show that island ordering is intrinsically linked to the nucleation and growth at indented sites and it strongly depends on pattern parameters.

A hierarchical security assessment model for object-oriented programs

We present a hierarchical model for assessing an object-oriented program's security. Security is quantified using structural properties of the program code to identify the ways in which `classified' data values may be transferred between objects. The model begins with a set of low-level security metrics based on traditional design characteristics of object-oriented classes, such as data encapsulation, cohesion and coupling. These metrics are then used to characterise higher-level properties concerning the overall readability and writability of classified data throughout the program. In turn, these metrics are then mapped to well-known security design principles such as `assigning the least privilege' and `reducing the size of the attack surface'. Finally, the entire program's security is summarised as a single security index value. These metrics allow different versions of the same program, or different programs intended to perform the same task, to be compared for their relative security at a number of different abstraction levels. The model is validated via an experiment involving five open source Java programs, using a static analysis tool we have developed to automatically extract the security metrics from compiled Java bytecode.

Inciting the social imagination to realising the dream : An unfolding story of reform in a low-socioeconomic school

This paper presentation addresses design-based research that became a catalyst for social change among a disadvantaged school community. The aim of the longitudinal research was to protoype an evidence-based model for whole school digital and print literacy pedagogy renewal among students from low socioeconomic, Indigenous, and migrant backgrounds. Applying Anthony Gidden’s principle of the “duality of structure”, the paper presentation interprets how the collective agency of researchers and the school community began to transform the structural properties of the institution in a two-way dynamism, so that the structural properties of the school were not outside of individual action, but were implicated in its reproduction and transformation.

On the optimality of sample-based estimates of the expectation of the empirical minimizer

We study sample-based estimates of the expectation of the function produced by the empirical minimization algorithm. We investigate the extent to which one can estimate the rate of convergence of the empirical minimizer in a data dependent manner. We establish three main results. First, we provide an algorithm that upper bounds the expectation of the empirical minimizer in a completely data-dependent manner. This bound is based on a structural result due to Bartlett and Mendelson, which relates expectations to sample averages. Second, we show that these structural upper bounds can be loose, compared to previous bounds. In particular, we demonstrate a class for which the expectation of the empirical minimizer decreases as O(1/n) for sample size n, although the upper bound based on structural properties is Ω(1). Third, we show that this looseness of the bound is inevitable: we present an example that shows that a sharp bound cannot be universally recovered from empirical data.

Predicting residue-wise contact orders in proteins by support vector regression

Background The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.