Application of micro CT and computation modeling in bone tissue engineering

Computer aided technologies, medical imaging, and rapid prototyping has created new possibilities in biomedical engineering. The systematic variation of scaffold architecture as well as the mineralization inside a scaffold/bone construct can be studied using computer imaging technology and CAD/CAM and micro computed tomography (CT). In this paper, the potential of combining these technologies has been exploited in the study of scaffolds and osteochondral repair. Porosity, surface area per unit volume and the degree of interconnectivity were evaluated through imaging and computer aided manipulation of the scaffold scan data. For the osteochondral model, the spatial distribution and the degree of bone regeneration were evaluated. In this study the versatility of two softwares Mimics (Materialize), CTan and 3D realistic visualization (Skyscan) were assessed, too.

Direct writing of chitosan scaffolds using a robotic system

Purpose – This paper aims to present a novel rapid prototyping (RP) fabrication methods and preliminary characterization for chitosan scaffolds. Design – A desktop rapid prototyping robot dispensing (RPBOD) system has been developed to fabricate scaffolds for tissue engineering (TE) applications. The system is a computer-controlled four-axis machine with a multiple-dispenser head. Neutralization of the acetic acid by the sodium hydroxide results in a precipitate to form a gel-like chitosan strand. The scaffold properties were characterized by scanning electron microscopy, porosity calculation and compression test. An example of fabrication of a freeform hydrogel scaffold is demonstrated. The required geometric data for the freeform scaffold were obtained from CT-scan images and the dispensing path control data were converted form its volume model. The applications of the scaffolds are discussed based on its potential for TE. Findings – It is shown that the RPBOD system can be interfaced with imaging techniques and computational modeling to produce scaffolds which can be customized in overall size and shape allowing tissue-engineered grafts to be tailored to specific applications or even for individual patients. Research limitations/implications – Important challenges for further research are the incorporation of growth factors, as well as cell seeding into the 3D dispensing plotting materials. Improvements regarding the mechanical properties of the scaffolds are also necessary. Originality/value – One of the important aspects of TE is the design scaffolds. For customized TE, it is essential to be able to fabricate 3D scaffolds of various geometric shapes, in order to repair tissue defects. RP or solid free-form fabrication techniques hold great promise for designing 3D customized scaffolds; yet traditional cell-seeding techniques may not provide enough cell mass for larger constructs. This paper presents a novel attempt to fabricate 3D scaffolds, using hydrogels which in the future can be combined with cells.

Cluster-based network model for time-course gene expression data

We propose a model-based approach to unify clustering and network modeling using time-course gene expression data. Specifically, our approach uses a mixture model to cluster genes. Genes within the same cluster share a similar expression profile. The network is built over cluster-specific expression profiles using state-space models. We discuss the application of our model to simulated data as well as to time-course gene expression data arising from animal models on prostate cancer progression. The latter application shows that with a combined statistical/bioinformatics analyses, we are able to extract gene-to-gene relationships supported by the literature as well as new plausible relationships.

The ontological deficiencies of process modeling in practice

Business process modeling is widely regarded as one of the most popular forms of conceptual modeling. However, little is known about the capabilities and deficiencies of process modeling grammars and how existing deficiencies impact actual process modeling practice. This paper is a first contribution towards a theory-driven, exploratory empirical investigation of the ontological deficiencies of process modeling with the industry standard Business Process Modeling Notation (BPMN). We perform an analysis of BPMN using a theory of ontological expressiveness. Through a series of semi-structured interviews with BPMN adopters we explore empirically the actual use of this grammar. Nine ontological deficiencies related to the practice of modeling with BPMN are identified, for example, the capture of business rules and the specification of process decompositions. We also uncover five contextual factors that impact on the use of process modeling grammars, such as tool support and modeling conventions. We discuss implications for research and practice, highlighting the need for consideration of representational issues and contextual factors in decisions relating to BPMN adoption in organizations.

Multi-linear strategies for (re)presenting the complexity of young people in research

Within the current climate of unpredictability and constant change, young people at school are faced with a multitude of choices and contradictory influences. In this article, I argue that (re)presentations of young people in youth research need to reflect the complexity and multiplicity of their lives and changing priorities, and I attempt to (re)present a small group of young people in this particular milieu. I illustrate some of the competing influences in their lives, and I outline some specific strategies that are useful for (re)presenting these contextual worlds. The strategies I advocate disrupt the homogenous representations of ‘youth’ as a developmental phase and instead reflect the diverse spheres of influence which shape their subjectivities and practices.

Soil carbon saturation : concept, evidence and evaluation

Current estimates of soil C storage potential are based on models or factors that assume linearity between C input levels and C stocks at steady-state, implying that SOC stocks could increase without limit as C input levels increase. However, some soils show little or no increase in steady-state SOC stock with increasing C input levels suggesting that SOC can become saturated with respect to C input. We used long-term field experiment data to assess alternative hypotheses of soil carbon storage by three simple models: a linear model (no saturation), a one-pool whole-soil C saturation model, and a two-pool mixed model with C saturation of a single C pool, but not the whole soil. The one-pool C saturation model best fit the combined data from 14 sites, four individual sites were best-fit with the linear model, and no sites were best fit by the mixed model. These results indicate that existing agricultural field experiments generally have too small a range in C input levels to show saturation behavior, and verify the accepted linear relationship between soil C and C input used to model SOM dynamics. However, all sites combined and the site with the widest range in C input levels were best fit with the C-saturation model. Nevertheless, the same site produced distinct effective stabilization capacity curves rather than an absolute C saturation level. We conclude that the saturation of soil C does occur and therefore the greatest efficiency in soil C sequestration will be in soils further from C saturation.

Vision based control for fixed wing UAVs inspecting locally linear infrastructure using skid-to-turn maneuvers

The following paper proposes a novel application of Skid-to-Turn maneuvers for fixed wing Unmanned Aerial Vehicles (UAVs) inspecting locally linear infrastructure. Fixed wing UAVs, following the design of manned aircraft, commonly employ Bank-to-Turn ma- neuvers to change heading and thus direction of travel. Whilst effective, banking an aircraft during the inspection of ground based features hinders data collection, with body fixed sen- sors angled away from the direction of turn and a panning motion induced through roll rate that can reduce data quality. By adopting Skid-to-Turn maneuvers, the aircraft can change heading whilst maintaining wings level flight, thus allowing body fixed sensors to main- tain a downward facing orientation. An Image-Based Visual Servo controller is developed to directly control the position of features as captured by onboard inspection sensors. This improves on the indirect approach taken by other tracking controllers where a course over ground directly above the feature is assumed to capture it centered in the field of view. Performance of the proposed controller is compared against that of a Bank-to-Turn tracking controller driven by GPS derived cross track error in a simulation environment developed to replicate the field of view of a body fixed camera.

The application of neural networks to induction machine control

Neural networks (NNs) are discussed in connection with their possible use in induction machine drives. The mathematical model of the NN as well as a commonly used learning algorithm is presented. Possible applications of NNs to induction machine control are discussed. A simulation of an NN successfully identifying the nonlinear multivariable model of an induction-machine stator transfer function is presented. Previously published applications are discussed, and some possible future applications are proposed.

Vector control of a high power induction machine

The design and implementation of a high-power (2 MW peak) vector control drive is described. The inverter switching frequency is low, resulting in high-harmonic-content current waveforms. A block diagram of the physical system is given, and each component is described in some detail. The problem of commanded slip noise sensitivity, inherent in high-power vector control drives, is discussed, and a solution is proposed. Results are given which demonstrate the successful functioning of the system

Statistical modeling to determine resonant frequency information present in combustion chamber pressure signals

A statistical modeling method to accurately determine combustion chamber resonance is proposed and demonstrated. This method utilises Markov-chain Monte Carlo (MCMC) through the use of the Metropolis-Hastings (MH) algorithm to yield a probability density function for the combustion chamber frequency and find the best estimate of the resonant frequency, along with uncertainty. The accurate determination of combustion chamber resonance is then used to investigate various engine phenomena, with appropriate uncertainty, for a range of engine cycles. It is shown that, when operating on various ethanol/diesel fuel combinations, a 20% substitution yields the least amount of inter-cycle variability, in relation to combustion chamber resonance.

Flow modeling in a novel non-perfusion conical bioreactor

We have developed a bioreactor vessel design which has the advantages of simplicity and ease of assembly and disassembly, and with the appropriately determined flow rate, even allows for a scaffold to be suspended freely regardless of its weight. This article reports our experimental and numerical investigations to evaluate the performance of a newly developed non-perfusion conical bioreactor by visualizing the flow through scaffolds with 45° and 90° fiber lay down patterns. The experiments were conducted at the Reynolds numbers (Re) 121, 170, and 218 based on the local velocity and width of scaffolds. The flow fields were captured using short-time exposures of 60 µm particles suspended in the bioreactor and illuminated using a thin laser sheet. The effects of scaffold fiber lay down pattern and Reynolds number were obtained and correspondingly compared to results obtained from a computational fluid dynamics (CFD) software package. The objectives of this article are twofold: to investigate the hypothesis that there may be an insufficient exchange of medium within the interior of the scaffold when using our non-perfusion bioreactor, and second, to compare the flows within and around scaffolds of 45° and 90° fiber lay down patterns. Scaffold porosity was also found to influence flow patterns. It was therefore shown that fluidic transport could be achieved within scaffolds with our bioreactor design, being a non-perfusion vessel. Fluid velocities were generally same of the same or one order lower in magnitude as compared to the inlet flow velocity. Additionally, the 90° fiber lay down pattern scaffold was found to allow for slightly higher fluid velocities within, as compared to the 45° fiber lay down pattern scaffold. This was due to the architecture and pore arrangement of the 90° fiber lay down pattern scaffold, which allows for fluid to flow directly through (channel-like flow).

Modeling crash outcome probabilities at rural intersections: Application of hierarchical binomial logistic models

It is important to examine the nature of the relationships between roadway, environmental, and traffic factors and motor vehicle crashes, with the aim to improve the collective understanding of causal mechanisms involved in crashes and to better predict their occurrence. Statistical models of motor vehicle crashes are one path of inquiry often used to gain these initial insights. Recent efforts have focused on the estimation of negative binomial and Poisson regression models (and related deviants) due to their relatively good fit to crash data. Of course analysts constantly seek methods that offer greater consistency with the data generating mechanism (motor vehicle crashes in this case), provide better statistical fit, and provide insight into data structure that was previously unavailable. One such opportunity exists with some types of crash data, in particular crash-level data that are collected across roadway segments, intersections, etc. It is argued in this paper that some crash data possess hierarchical structure that has not routinely been exploited. This paper describes the application of binomial multilevel models of crash types using 548 motor vehicle crashes collected from 91 two-lane rural intersections in the state of Georgia. Crash prediction models are estimated for angle, rear-end, and sideswipe (both same direction and opposite direction) crashes. The contributions of the paper are the realization of hierarchical data structure and the application of a theoretically appealing and suitable analysis approach for multilevel data, yielding insights into intersection-related crashes by crash type.

Governors highway safety associations and transportation planning: Exploratory factor analysis and structural equation modeling

The Intermodal Surface Transportation Efficiency Act (ISTEA) of 1991 mandated the consideration of safety in the regional transportation planning process. As part of National Cooperative Highway Research Program Project 8-44, "Incorporating Safety into the Transportation Planning Process," we conducted a telephone survey to assess safety-related activities and expertise at Governors Highway Safety Associations (GHSAs), and GHSA relationships with metropolitan planning organizations (MPOs) and state departments of transportation (DOTs). The survey results were combined with statewide crash data to enable exploratory modeling of the relationship between GHSA policies and programs and statewide safety. The modeling objective was to illuminate current hurdles to ISTEA implementation, so that appropriate institutional, analytical, and personnel improvements can be made. The study revealed that coordination of transportation safety across DOTs, MPOs, GHSAs, and departments of public safety is generally beneficial to the implementation of safety. In addition, better coordination is characterized by more positive and constructive attitudes toward incorporating safety into planning.

Modeling crash types: New insights into the effects of covariates on crashes at rural intersections

Many studies focused on the development of crash prediction models have resulted in aggregate crash prediction models to quantify the safety effects of geometric, traffic, and environmental factors on the expected number of total, fatal, injury, and/or property damage crashes at specific locations. Crash prediction models focused on predicting different crash types, however, have rarely been developed. Crash type models are useful for at least three reasons. The first is motivated by the need to identify sites that are high risk with respect to specific crash types but that may not be revealed through crash totals. Second, countermeasures are likely to affect only a subset of all crashes—usually called target crashes—and so examination of crash types will lead to improved ability to identify effective countermeasures. Finally, there is a priori reason to believe that different crash types (e.g., rear-end, angle, etc.) are associated with road geometry, the environment, and traffic variables in different ways and as a result justify the estimation of individual predictive models. The objectives of this paper are to (1) demonstrate that different crash types are associated to predictor variables in different ways (as theorized) and (2) show that estimation of crash type models may lead to greater insights regarding crash occurrence and countermeasure effectiveness. This paper first describes the estimation results of crash prediction models for angle, head-on, rear-end, sideswipe (same direction and opposite direction), and pedestrian-involved crash types. Serving as a basis for comparison, a crash prediction model is estimated for total crashes. Based on 837 motor vehicle crashes collected on two-lane rural intersections in the state of Georgia, six prediction models are estimated resulting in two Poisson (P) models and four NB (NB) models. The analysis reveals that factors such as the annual average daily traffic, the presence of turning lanes, and the number of driveways have a positive association with each type of crash, whereas median widths and the presence of lighting are negatively associated. For the best fitting models covariates are related to crash types in different ways, suggesting that crash types are associated with different precrash conditions and that modeling total crash frequency may not be helpful for identifying specific countermeasures.

Computer simulation and modeling in railway applications

An electrified railway system includes complex interconnections and interactions of several subsystems. Computer simulation is the only viable means for system evaluation and analysis. This paper discusses the difficulties and requirements of effective simulation models for this specialized industrial application; and the development of a general-purpose multi-train simulator.