Fabrication and in vitro characterisation of bioactive glass composite scaffolds for bone regeneration

Here we fabricate and characterise bioactive composite scaffolds for bone tissue engineering applications. 45S5 Bioglass® (45S5) or strontium-substituted bioactive glass (SrBG) were incorporated into polycaprolactone (PCL) and fabricated into 3D bioactive composite scaffolds utilising additive manufacturing technology. We show that composite scaffolds (PCL/45S5 and PCL/SrBG) can be reproducibly manufactured with a scaffold morphology highly resembling that of PCL scaffolds. Additionally, micro-CT analysis reveals BG particles were homogeneously distributed throughout the scaffolds. Mechanical data suggested that PCL/45S5 and PCL/SrBG composite scaffolds have higher compressive Young’s modulus compared to PCL scaffolds at similar porosity (~75%). After 1 day in accelerated degradation conditions using 5M NaOH, PCL/SrBG, PCL/45S5 and PCL lost 48.6 ±3.8%, 12.1 ±1% and 1.6 ±1% of its original mass, respectively. In vitro studies were conducted using MC3T3 cells under normal and osteogenic conditions. All scaffolds were shown to be non-cytotoxic, and supported cell attachment and proliferation. Our results also indicate that the inclusion of bioactive glass (BG) promotes precipitation of calcium phosphate on the scaffold surfaces which leads to earlier cell differentiation and matrix mineralisation when compared to PCL scaffolds. However, as indicated by ALP activity, no significant difference in osteoblast differentiation was found between PCL/45S5 and PCL/SrBG scaffolds. These results suggest that PCL/45S5 and PCL/SrBG composite scaffold shows potential as a next generation bone scaffold.

Composite SaaS resource management in cloud computing using evolutionary computation

Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.

Aligned poly(L-lactic-co-ε-caprolactone) electrospun microfibers and knitted structure: a novel composite scaffold for ligament tissue engineering

We developed a novel technique involving knitting and electrospinning to fabricate a composite scaffold for ligament tissue engineering. Knitted structures were coated with poly(L-lactic-co-e-caprolactone) (PLCL) and then placed onto a rotating cylinder and a PLCL solution was electrospun onto the structure. Highly aligned 2-μm-diameter microfibers covered the space between the stitches and adhered to the knitted scaffolds. The stress–strain tensile curves exhibited an initial toe region similar to the tensile behavior of ligaments. Composite scaffolds had an elastic modulus (150 ± 14 MPa) similar to the modulus of human ligaments. Biological evaluation showed that cells proliferated on the composite scaffolds and they spontaneously orientated along the direction of microfiber alignment. The microfiber architecture also induced a high level of extracellular matrix secretion, which was characterized by immunostaining. We found that cells produced collagen type I and type III, two main components found in ligaments. After 14 days of culture, collagen type III started to form a fibrous network. We fabricated a composite scaffold having the mechanical properties of the knitted structure and the morphological properties of the aligned microfibers. It is difficult to seed a highly macroporous structure with cells, however the technique we developed enabled an easy cell seeding due to presence of the microfiber layer. Therefore, these scaffolds presented attractive properties for a future use in bioreactors for ligament tissue engineering.

A simple method for fabricating 3-D multilayered composite scaffolds

One limitation of electrospinning stems from the charge build-up that occurs during processing, preventing further fibre deposition and limiting the scaffold overall thickness and hence their end-use in tissue engineering applications targeting large tissue defect repair. To overcome this, we have developed a technique in which thermally induced phase separation (TIPS) and electrospinning are combined. Thick three-dimensional, multilayered composite scaffolds were produced by simply stacking individual polycaprolactone (PCL) microfibrous electrospun discs into a cylindrical holder that was filled with a 3% poly(lactic-co-glycolic acid) (PLGA) solution in dimethylsulfoxide (a good solvent for PLGA but a poor one for PCL). The construct was quenched in liquid nitrogen and the solvent removed by leaching out in cold water. This technique enables the fabrication of scaffolds composed principally of electrospun membranes that have no limit to their thickness. The mechanical properties of these scaffolds were assessed under both quasi-static and dynamic conditions. The multilayered composite scaffolds had similar compressive properties to 5% PCL scaffolds fabricated solely by the TIPS methodology. However, tensile tests demonstrated that the multilayered construct outperformed a scaffold made purely by TIPS, highlighting the contribution of the electrospun component of the composite scaffold to enhancing the overall mechanical property slate. Cell studies revealed cell infiltration principally from the scaffold edges under static seeding conditions. This fabrication methodology permits the rapid construction of thick, strong scaffolds from a range of biodegradable polymers often used in tissue engineering, and will be particularly useful when large dimension electrospun scaffolds are required.

Precedent-free fault isolation in a diesel engine EGR valve system

In this paper, a framework for isolating unprecedented faults for an EGR valve system is presented. Using normal behavior data generated by a high fidelity engine simulation, the recently introduced Growing Structure Multiple Model System (GSMMS) is used to construct models of normal behavior for an EGR valve system and its various subsystems. Using the GSMMS models as a foundation, anomalous behavior of the entire system is then detected as statistically significant departures of the most recent modeling residuals from the modeling residuals during normal behavior. By reconnecting anomaly detectors to the constituent subsystems, the anomaly can be isolated without the need for prior training using faulty data. Furthermore, faults that were previously encountered (and modeled) are recognized using the same approach as the anomaly detectors.

Precedent-free fault isolation in a diesel engine exhaust gas recirculation system

In this paper, a recently introduced model-based method for precedent-free fault detection and isolation (FDI) is modified to deal with multiple input, multiple output (MIMO) systems and is applied to an automotive engine with exhaust gas recirculation (EGR) system. Using normal behavior data generated by a high fidelity engine simulation, the growing structure multiple model system (GSMMS) approach is used to construct dynamic models of normal behavior for the EGR system and its constituent subsystems. Using the GSMMS models as a foundation, anomalous behavior is detected whenever statistically significant departures of the most recent modeling residuals away from the modeling residuals displayed during normal behavior are observed. By reconnecting the anomaly detectors (ADs) to the constituent subsystems, EGR valve, cooler, and valve controller faults are isolated without the need for prior training using data corresponding to particular faulty system behaviors.

Mussel-inspired bioceramics with self-assembled Ca-P/polydopamine composite nanolayer : preparation, formation mechanism, improved cellular bioactivity and osteogenic differentiation of bone marrow stromal cells

The nanostructured surface of biomaterials plays an important role in improving their in vitro cellular bioactivity as well as stimulating in vivo tissue regeneration. Inspired by the mussel’s adhesive versatility, which is thought to be due to the plaque–substrate interface being rich in 3,4-dihydroxy-L-phenylalamine (DOPA) and lysine amino acids, in this study we developed a self-assembly method to prepare a uniform calcium phosphate (Ca-P)/polydopamine composite nanolayer on the surface of b-tricalcium phosphate (b-TCP) bioceramics by soaking b-TCP bioceramics in Tris–dopamine solution. It was found that the addition of dopamine, reaction temperature and reaction time are three key factors inducing the formation of a uniform Ca-P/polydopamine composite nanolayer. The formation mechanism of a Ca-P/polydopamine composite nanolayer involved two important steps: (i) the addition of dopamine to Tris–HCl solution decreases the pH value and accelerates Ca and P ionic dissolution from the crystal boundaries of b-TCP ceramics; (ii) dopamine is polymerized to form self-assembled polydopamine film and, at the same time, nanosized Ca-P particles are mineralized with the assistance of polydopamine, in which the formation of polydopamine occurs simultaneously with Ca-P mineralization (formation of nanosized microparticles composed of calcium phosphate-based materials), and finally a self-assembled Ca-P/polydopamine composite nanolayer forms on the surface of the b-TCP ceramics. Furthermore, the formed self-assembled Ca-P/polydopamine composite nanolayer significantly enhances the surface roughness and hydrophilicity of b-TCP ceramics, and stimulates the attachment, proliferation, alkaline phosphate (ALP) activity and bone-related gene expression (ALP, OCN, COL1 and Runx2) of human bone marrow stromal cells. Our results suggest that the preparation of self-assembled Ca-P/polydopamine composite nanolayers is a viable method to modify the surface of biomaterials by significantly improving their surface physicochemical properties and cellular bioactivity for bone regeneration application.

Formation of polyaniline/Pt nanoparticle composite films and their electrocatalytic properties

Polyaniline (PANI) thin films modified with platinum nanoparticles have been prepared by several methods, characterised and assessed in terms of electrocatalytic properties. These composite materials have been prepared by the in situ reduction of a platinum salt (K2PtCl4) by PANI, in a variety of solvents, resulting in the formation of platinum nanoparticles and clusters of different sizes. The further deposition of platinum clusters at spin cast thin films of PANI/Pt composites from a neutral aqueous solution of K2PtCl4 has also been demonstrated. Thin-film electrodes prepared from these materials have been investigated for their electrocatalytic activity by studying hydrazine oxidation and dichromate reduction. The properties of the composite materials have been determined using UV–visible spectroscopy, atomic force microscopy and transmission electron microscopy. The nature of the material formed is strongly dependent on the solvent used to dissolve PANI, the method of preparation of the PANI/Pt solution and the composition of the spin cast thin film before subsequent deposition of platinum from the aqueous solution of K2PtCl4.

Modeling the viability of the free-ranging cheetah population in Namibia : an object-oriented Bayesian network approach

Conservation of free-ranging cheetah (Acinonyx jubatus) populations is multi faceted and needs to be addressed from an ecological, biological and management perspective. There is a wealth of published research, each focusing on a particular aspect of cheetah conservation. Identifying the most important factors, making sense of various (and sometimes contrasting) findings, and taking decisions when little or no empirical data is available, are everyday challenges facing conservationists. Bayesian networks (BN) provide a statistical modeling framework that enables analysis and integration of information addressing different aspects of conservation. There has been an increased interest in the use of BNs to model conservation issues, however the development of more sophisticated BNs, utilizing object-oriented (OO) features, is still at the frontier of ecological research. We describe an integrated, parallel modeling process followed during a BN modeling workshop held in Namibia to combine expert knowledge and data about free-ranging cheetahs. The aim of the workshop was to obtain a more comprehensive view of the current viability of the free-ranging cheetah population in Namibia, and to predict the effect different scenarios may have on the future viability of this free-ranging cheetah population. Furthermore, a complementary aim was to identify influential parameters of the model to more effectively target those parameters having the greatest impact on population viability. The BN was developed by aggregating diverse perspectives from local and independent scientists, agents from the national ministry, conservation agency members and local fieldworkers. This integrated BN approach facilitates OO modeling in a multi-expert context which lends itself to a series of integrated, yet independent, subnetworks describing different scientific and management components. We created three subnetworks in parallel: a biological, ecological and human factors network, which were then combined to create a complete representation of free-ranging cheetah population viability. Such OOBNs have widespread relevance to the effective and targeted conservation management of vulnerable and endangered species.

Superior piezoelectric composite films : taking advantage of carbon nanomaterials

Piezoelectric composites comprising an active phase of ferroelectric ceramic and a polymer matrix have recently attracted numerous sensory applications. However, it remains a major challenge to further improve their electromechanical response for advanced applications such as precision control and monitoring systems. We hereby investigated the incorporation of graphene platelets (GnPs) and multi-walled carbon nanotubes (MWNTs), each with various weight fractions, into PZT (lead zirconate titanate)/epoxy composites to produce three-phase nanocomposites. The nanocomposite films show markedly improved piezoelectric coefficients and electromechanical responses (50%) besides an enhancement of ~200% in stiffness. Carbon nanomaterials strengthened the impact of electric field on the PZT particles by appropriately raising the electrical conductivity of epoxy. GnPs have been proved far more promising in improving the poling behavior and dynamic response than MWNTs. The superior dynamic sensitivity of GnP-reinforced composite may be caused by GnPs’ high load transfer efficiency arising from their two-dimensional geometry and good compatibility with the matrix. Reduced acoustic impedance mismatch resulted from the improved thermal conductance may also contribute to the higher sensitivity of GnP-reinforced composite. This research pointed out the potential of employing GnPs to develop highly sensitive piezoelectric composites for sensing applications.

Lattice-free descriptions of collective motion with crowding and adhesion

Cell-to-cell adhesion is an important aspect of malignant spreading that is often observed in images from the experimental cell biology literature. Since cell-to-cell adhesion plays an important role in controlling the movement of individual malignant cells, it is likely that cell-to-cell adhesion also influences the spatial spreading of populations of such cells. Therefore, it is important for us to develop biologically realistic simulation tools that can mimic the key features of such collective spreading processes to improve our understanding of how cell-to-cell adhesion influences the spreading of cell populations. Previous models of collective cell spreading with adhesion have used lattice-based random walk frameworks which may lead to unrealistic results, since the agents in the random walk simulations always move across an artificial underlying lattice structure. This is particularly problematic in high-density regions where it is clear that agents in the random walk align along the underlying lattice, whereas no such regular alignment is ever observed experimentally. To address these limitations, we present a lattice-free model of collective cell migration that explicitly incorporates crowding and adhesion. We derive a partial differential equation description of the discrete process and show that averaged simulation results compare very well with numerical solutions of the partial differential equation.

Degradation of simazine from aqueous solutions by diatomite-supported nanosized zero-valent iron composite materials

A novel composite material based on deposition of nanosized zero-valent iron (nZVI) particles on acid-leached diatomite was synthesised for the removal of a chlorinated contaminant in water. The nZVI /diatomite composites were characterized by X-ray diffraction, scanning electron microscopy, elemental analysis, transmission electron microscopy and X-ray photoelectron spectroscopy. Compared with the pure nZVI particles, better dispersion of nZVI particles on the surface or inside the pores of diatom shells was observed. The herbicide simazine was selected as the model chlorinated contaminant and the removal efficiency by nZVI /diatomite composite was compared with that of the pristine nZVI and commercial iron powder. It was found that the diatomite supported nZVI composite material prepared by centrifugation exhibits relatively better efficient activity in decomposition of simazine than commercial Fe, lab synthesized nZVI and composite material prepared via rotary evaporation, and the optimum experimental conditions were obtained based on a series of batch experiments. This study on immobilizing nZVI particles onto diatomite opens a new avenue for the practical application of nZVI and the diatomite-supported nanosized zero-valent iron composite materials have potential applications in environmental remediation.

Assessing land-use and transport integration via a spatial composite indexing model

Achieving sustainable urban development is identified as one ultimate goal of many contemporary planning endeavours and has become central to formulation of urban planning policies. Within this concept, land-use and transport integration is highlighted as one of the most important and attainable policy objectives. In many cities, integration is embraced as an integral part of local development plans, and a number of key integration principles are identified. However, the lack of available evaluation methods to measure extent of urban sustainability levels prevents successful implementation of these principles. This paper introduces a new indicator-based spatial composite indexing model developed to measure sustainability performance of urban settings by taking into account land-use and transport integration principles. Model indicators are chosen via a thorough selection process in line with key principles of land-use and transport integration. These indicators are grouped into categories and themes according to their topical relevance. These indicators are then aggregated to form a spatial composite index to portray an overview of the sustainability performance of the pilot study area used for model demonstration. The study results revealed that the model is a practical instrument for evaluating success of local integration policies and visualizing sustainability performance of built environments and useful in both identifying problematic areas as well as formulating policy interventions.

Training-free probability models for whole-image based place recognition

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.

Second-order inelastic analysis of composite framed structures based on the refined plastic hinge method

Composite steel-concrete structures experience non-linear effects which arise from both instability-related geometric non-linearity and from material non-linearity in all of their component members. Because of this, conventional design procedures cannot capture the true behaviour of a composite frame throughout its full loading range, and so a procedure to account for those non-linearities is much needed. This paper therefore presents a numerical procedure capable of addressing geometric and material non-linearities at the strength limit state based on the refined plastic hinge method. Different material non-linearity for different composite structural components such as T-beams, concrete-filled tubular (CFT) and steel-encased reinforced concrete (SRC) sections can be treated using a routine numerical procedure for their section properties in this plastic hinge approach. Simple and conservative initial and full yield surfaces for general composite sections are proposed in this paper. The refined plastic hinge approach models springs at the ends of the element which are activated when the surface defining the interaction of bending and axial force at first yield is reached; a transition from the first yield interaction surface to the fully plastic interaction surface is postulated based on a proposed refined spring stiffness, which formulates the load-displacement relation for material non-linearity under the interaction of bending and axial actions. This produces a benign method for a beam-column composite element under general loading cases. Another main feature of this paper is that, for members containing a point of contraflexure, its location is determined with a simple application of the method herein and a node is then located at this position to reproduce the real flexural behaviour and associated material non-linearity of the member. Recourse is made to an updated Lagrangian formulation to consider geometric non-linear behaviour and to develop a non-linear solution strategy. The formulation with the refined plastic hinge approach is efficacious and robust, and so a full frame analysis incorporating geometric and material non-linearity is tractable. By way of contrast, the plastic zone approach possesses the drawback of strain-based procedures which rely on determining plastic zones within a cross-section and which require lengthwise integration. Following development of the theory, its application is illustrated with a number of varied examples.