Hylaluronan-based heparin-incorporated hydrogels for generation of axially vascularized bioartificial bone tissues : in vitro and in vivo evaluation in a PLDLLA-TCP-PCL-composite system

Smart matrices are required in bone tissueengineered grafts that provide an optimal environment for cells and retain osteo-inductive factors for sustained biological activity. We hypothesized that a slow-degrading heparin-incorporated hyaluronan (HA) hydrogel can preserve BMP-2; while an arterio–venous (A–V) loop can support axial vascularization to provide nutrition for a bioartificial bone graft. HA was evaluated for osteoblast growth and BMP-2 release. Porous PLDLLA–TCP–PCL scaffolds were produced by rapid prototyping technology and applied in vivo along with HA-hydrogel, loaded with either primary osteoblasts or BMP-2. A microsurgically created A–V loop was placed around the scaffold, encased in an isolation chamber in Lewis rats. HA-hydrogel supported growth of osteoblasts over 8 weeks and allowed sustained release of BMP-2 over 35 days. The A–V loop provided an angiogenic stimulus with the formation of vascularized tissue in the scaffolds. Bone-specific genes were detected by real time RT-PCR after 8 weeks. However, no significant amount of bone was observed histologically. The heterotopic isolation chamber in combination with absent biomechanical stimulation might explain the insufficient bone formation despite adequate expression of bone-related genes. Optimization of the interplay of osteogenic cells and osteo-inductive factors might eventually generate sufficient amounts of axially vascularized bone grafts for reconstructive surgery.

Structural reliability prediction of a steel bridge element using Dynamic Object Oriented Bayesian Network (DOOBN)

Different from conventional methods for structural reliability evaluation, such as, first/second-order reliability methods (FORM/SORM) or Monte Carlo simulation based on corresponding limit state functions, a novel approach based on dynamic objective oriented Bayesian network (DOOBN) for prediction of structural reliability of a steel bridge element has been proposed in this paper. The DOOBN approach can effectively model the deterioration processes of a steel bridge element and predict their structural reliability over time. This approach is also able to achieve Bayesian updating with observed information from measurements, monitoring and visual inspection. Moreover, the computational capacity embedded in the approach can be used to facilitate integrated management and maintenance optimization in a bridge system. A steel bridge girder is used to validate the proposed approach. The predicted results are compared with those evaluated by FORM method.

Computational fluid dynamics analysis of a flat plate photocatalytic reactor for storm and wastewater reuse

A computational fluid dynamics (CFD) analysis has been performed for a flat plate photocatalytic reactor using CFD code FLUENT. Under the simulated conditions (Reynolds number, Re around 2650), a detailed time accurate computation shows the different stages of flow evolution and the effects of finite length of the reactor in creating flow instability, which is important to improve the performance of the reactor for storm and wastewater reuse. The efficiency of a photocatalytic reactor for pollutant decontamination depends on reactor hydrodynamics and configurations. This study aims to investigate the role of different parameters on the optimization of the reactor design for its improved performance. In this regard, more modelling and experimental efforts are ongoing to better understand the interplay of the parameters that influence the performance of the flat plate photocatalytic reactor.

Personalized recommender system based on item taxonomy and folksonomy

Item folksonomy or tag information is popularly available on the web now. However, since tags are arbitrary words given by users, they contain a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise brings difficulties to improve the accuracy of item recommendations. In this paper, we propose to combine item taxonomy and folksonomy to reduce the noise of tags and make personalized item recommendations. The experiments conducted on the dataset collected from Amazon.com demonstrated the effectiveness of the proposed approaches. The results suggested that the recommendation accuracy can be further improved if we consider the viewpoints and the vocabularies of both experts and users.

HIFiRE re-entry observation using an image-based visual servoing system

This paper presents an image based visual servoing system that is intended to be used for tracking and obtaining scientific observations of the HIFiRE vehicles. The primary aim of this tracking platform is to acquire and track the thermal signature emitted from the surface of the vehicle during the re-entry phase of the mission using an infra-red camera. The implemented visual servoing scheme uses a classical image based approach to identify and track the target using visual kinematic control. The paper utilizes simulation and experimental results to show the tracking performance of the system using visual feedback. Discussions on current implementation and control techniques to further improve the performance of the system are also explored.

Rough sets based reasoning and pattern mining for a two-stage information filtering system

This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern- based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experiments have been conducted to compare the proposed two-stage filtering (T-SM) model with other possible "term-based + pattern-based" or "term-based + term-based" IF models. The results based on the RCV1 corpus show that the T-SM model significantly outperforms other types of "two-stage" IF models.

Flow field investigation in a water treatment reactor using computational fluid dynamics

The hydrodynamic behaviour of a novel flat plate photocatalytic reactor for water treatment is investigated using CFD code FLUENT. The reactor consists of a reactive section that features negligible pressure drop and uniform illumination of the photocatalyst to ensure enhanced photocatalytic efficiency. The numerical simulations allowed the identification of several design issues in the original reactor, which include extensive boundary layer separation near the photocatalyst support and regions of flow recirculation that render a significant portion of the reactive area. The simulations reveal that this issue could be addressed by selecting the appropriate inlet positions and configurations. This modification can cause minimal pressure drop across the reactive zone and achieves significant uniformization of the tested pollutant on the photocatalyst surface. The influence of roughness elements type has also been studied with a view to identify their role on the distribution of pollutant concentration on the photocatalyst surface. The results presented here indicate that the flow and pollutant concentration field strongly depend on the geometric parameters and flow conditions.

Maintenance chain integration using Petri-net enabled multiagent system modeling and implementation approach

Engineering asset management (EAM) is a broad discipline and the EAM functions and processes are characterized by its distributed nature. However, engineering asset nowadays mostly relies on self-maintained experiential rule bases and periodic maintenance, which is lacking a collaborative engineering approach. This research proposes a collaborative environment integrated by a service center with domain expertise such as diagnosis, prognosis, and asset operations. The collaborative maintenance chain combines asset operation sites, service center (i.e., maintenance operation coordinator), system provider, first tier collaborators, and maintenance part suppliers. Meanwhile, to realize the automation of communication and negotiation among organizations, multiagent system (MAS) technique is applied to enhance the entire service level. During the MAS design processes, this research combines Prometheus MAS modeling approach with Petri-net modeling methodology and unified modeling language to visualize and rationalize the design processes of MAS. The major contributions of this research include developing a Petri-net enabled Prometheus MAS modeling methodology and constructing a collaborative agent-based maintenance chain framework for integrated EAM.

Automated proof for formal indistinguishability and its applications

Bana et al. proposed the relation formal indistinguishability (FIR), i.e. an equivalence between two terms built from an abstract algebra. Later Ene et al. extended it to cover active adversaries and random oracles. This notion enables a framework to verify computational indistinguishability while still offering the simplicity and formality of symbolic methods. We are in the process of making an automated tool for checking FIR between two terms. First, we extend the work by Ene et al. further, by covering ordered sorts and simplifying the way to cope with random oracles. Second, we investigate the possibility of combining algebras together, since it makes the tool scalable and able to cover a wide class of cryptographic schemes. Specially, we show that the combined algebra is still computationally sound, as long as each algebra is sound. Third, we design some proving strategies and implement the tool. Basically, the strategies allow us to find a sequence of intermediate terms, which are formally indistinguishable, between two given terms. FIR between the two given terms is then guaranteed by the transitivity of FIR. Finally, we show applications of the work, e.g. on key exchanges and encryption schemes. In the future, the tool should be extended easily to cover many schemes. This work continues previous research of ours on use of compilers to aid in automated proofs for key exchange.

Assessment of corneal dynamics with high-speed swept source optical coherence tomography combined with an air puff system

We present a novel method and instrument for in vivo imaging and measurement of the human corneal dynamics during an air puff. The instrument is based on high-speed swept source optical coherence tomography (ssOCT) combined with a custom adapted air puff chamber from a non-contact tonometer, which uses an air stream to deform the cornea in a non-invasive manner. During the short period of time that the deformation takes place, the ssOCT acquires multiple A-scans in time (M-scan) at the center of the air puff, allowing observation of the dynamics of the anterior and posterior corneal surfaces as well as the anterior lens surface. The dynamics of the measurement are driven by the biomechanical properties of the human eye as well as its intraocular pressure. Thus, the analysis of the M-scan may provide useful information about the biomechanical behavior of the anterior segment during the applanation caused by the air puff. An initial set of controlled clinical experiments are shown to comprehend the performance of the instrument and its potential applicability to further understand the eye biomechanics and intraocular pressure measurements. Limitations and possibilities of the new apparatus are discussed.

Sustainable assessment for large science classes : non-multiple choice, randomised assignments through a Learning Management System

This paper reports on the development of a tool that generates randomised, non-multiple choice assessment within the BlackBoard Learning Management System interface. An accepted weakness of multiple-choice assessment is that it cannot elicit learning outcomes from upper levels of Biggs’ SOLO taxonomy. However, written assessment items require extensive resources for marking, and are susceptible to copying as well as marking inconsistencies for large classes. This project developed an assessment tool which is valid, reliable and sustainable and that addresses the issues identified above. The tool provides each student with an assignment assessing the same learning outcomes, but containing different questions, with responses in the form of words or numbers. Practice questions are available, enabling students to obtain feedback on their approach before submitting their assignment. Thus, the tool incorporates automatic marking (essential for large classes), randomised tasks to each student (reducing copying), the capacity to give credit for working (feedback on the application of theory), and the capacity to target higher order learning outcomes by requiring students to derive their answers rather than choosing them. Results and feedback from students are presented, along with technical implementation details.

Design and development of automatic visual inspection system for PCB manufacturing

Inspection of solder joints has been a critical process in the electronic manufacturing industry to reduce manufacturing cost, improve yield, and ensure product quality and reliability. This paper proposes two inspection modules for an automatic solder joint classification system. The “front-end” inspection system includes illumination normalisation, localisation and segmentation. The “back-end” inspection involves the classification of solder joints using the Log Gabor filter and classifier fusion. Five different levels of solder quality with respect to the amount of solder paste have been defined. The Log Gabor filter has been demonstrated to achieve high recognition rates and is resistant to misalignment. This proposed system does not need any special illumination system, and the images are acquired by an ordinary digital camera. This system could contribute to the development of automated non-contact, non-destructive and low cost solder joint quality inspection systems.

Probability distributed time delays: integrating spatial effects into temporal models

Background In order to provide insights into the complex biochemical processes inside a cell, modelling approaches must find a balance between achieving an adequate representation of the physical phenomena and keeping the associated computational cost within reasonable limits. This issue is particularly stressed when spatial inhomogeneities have a significant effect on system's behaviour. In such cases, a spatially-resolved stochastic method can better portray the biological reality, but the corresponding computer simulations can in turn be prohibitively expensive. Results We present a method that incorporates spatial information by means of tailored, probability distributed time-delays. These distributions can be directly obtained by single in silico or a suitable set of in vitro experiments and are subsequently fed into a delay stochastic simulation algorithm (DSSA), achieving a good compromise between computational costs and a much more accurate representation of spatial processes such as molecular diffusion and translocation between cell compartments. Additionally, we present a novel alternative approach based on delay differential equations (DDE) that can be used in scenarios of high molecular concentrations and low noise propagation. Conclusions Our proposed methodologies accurately capture and incorporate certain spatial processes into temporal stochastic and deterministic simulations, increasing their accuracy at low computational costs. This is of particular importance given that time spans of cellular processes are generally larger (possibly by several orders of magnitude) than those achievable by current spatially-resolved stochastic simulators. Hence, our methodology allows users to explore cellular scenarios under the effects of diffusion and stochasticity in time spans that were, until now, simply unfeasible. Our methodologies are supported by theoretical considerations on the different modelling regimes, i.e. spatial vs. delay-temporal, as indicated by the corresponding Master Equations and presented elsewhere.