Finite element shoulder models

Shoulder joint is a complex integration of soft and hard tissues. It plays an important role in performing daily activities and can be considered as a perfect compromise between mobility and stability. However, shoulder is vulnerable to complications such as dislocations and osteoarthritis. Finite element (FE) models have been developed to understand shoulder injury mechanisms, implications of disease on shoulder complex and in assessing the quality of shoulder implants. Further, although few, Finite element shoulder models have also been utilized to answer important clinical questions such as the difference between a normal and osteoarthritic shoulder joint. However, due to the absence of experimental validation, it is questionable whether the constitutive models applied in these FE models are adequate to represent mechanical behaviors of shoulder elements (Cartilages, Ligaments, Muscles etc), therefore the confidence of using current models in answering clinically relevant question. The main objective of this review is to critically evaluate the existing FE shoulder models that have been used to investigate clinical problems. Due concern is given to check the adequacy of representative constitutive models of shoulder elements in drawing clinically relevant conclusion. Suggestions have been given to improve the existing shoulder models by inclusion of adequate constitutive models for shoulder elements to confidently answer clinically relevant questions.

Near infrared (NIR) absorption spectra correlates with subchondral bone micro-CT parameters in osteoarthritic rat models

Determining the properties and integrity of subchondral bone in the developmental stages of osteoarthritis, especially in a form that can facilitate real-time characterization for diagnostic and decision-making purposes, is still a matter for research and development. This paper presents relationships between near infrared absorption spectra and properties of subchondral bone obtained from 3 models of osteoarthritic degeneration induced in laboratory rats via: (i) menisectomy (MSX); (ii) anterior cruciate ligament transaction (ACL); and (iii) intra-articular injection of mono-ido-acetate (1 mg) (MIA), in the right knee joint, with 12 rats per model group (N = 36). After 8 weeks, the animals were sacrificed and knee joints were collected. A custom-made diffuse reflectance NIR probe of diameter 5 mm was placed on the tibial surface and spectral data were acquired from each specimen in the wavenumber range 4000–12 500 cm− 1. After spectral acquisition, micro computed tomography (micro-CT) was performed on the samples and subchondral bone parameters namely: bone volume (BV) and bone mineral density (BMD) were extracted from the micro-CT data. Statistical correlation was then conducted between these parameters and regions of the near infrared spectra using multivariate techniques including principal component analysis (PCA), discriminant analysis (DA), and partial least squares (PLS) regression. Statistically significant linear correlations were found between the near infrared absorption spectra and subchondral bone BMD (R2 = 98.84%) and BV (R2 = 97.87%). In conclusion, near infrared spectroscopic probing can be used to detect, qualify and quantify changes in the composition of the subchondral bone, and could potentially assist in distinguishing healthy from OA bone as demonstrated with our laboratory rat models.

Eyes on 3D-Current 3D biomimetic disease concept models and potential applications in age-related macular degeneration

Three dimensional cellular models that mimic disease are being increasingly investigated and have opened an exciting new research area into understanding pathomechanisms. The advantage of 3D in vitro disease models is that they allow systematic and in-depth studies of physiological and pathophysiological processes with less costs and ethical concerns that have arisen with animal models. The purpose of the 3D approach is to allow crosstalk between cells and microenvironment, and with cues from the microenvironment, cells can assemble their niche similar to in vivo conditions. The use of 3D models for mimicking disease processes such as cancer, osteoarthritis etc., is only emerging and allows multidisciplinary teams consisting of tissue engineers, biologist biomaterial scientists and clinicians to work closely together. While in vitro systems require rigorous testing before they can be considered as replicates of the in vivo model, major steps have been made, suggesting that they will become powerful tools for studying physiological and pathophysiological processes. This paper aims to summarize some of the existing 3D models and proposes a novel 3D model of the eye structures that are involved in the most common cause of blindness in the Western World, namely age-related macular degeneration (AMD).

Reasoning about component similarity in building product models from the construction perspective

Identifying the design features that impact construction is essential to developing cost effective and constructible designs. The similarity of building components is a critical design feature that affects method selection, productivity, and ultimately construction cost and schedule performance. However, there is limited understanding of what constitutes similarity in the design of building components and limited computer-based support to identify this feature in a building product model. This paper contributes a feature-based framework for representing and reasoning about component similarity that builds on ontological modelling, model-based reasoning and cluster analysis techniques. It describes the ontology we developed to characterize component similarity in terms of the component attributes, the direction, and the degree of variation. It also describes the generic reasoning process we formalized to identify component similarity in a standard product model based on practitioners' varied preferences. The generic reasoning process evaluates the geometric, topological, and symbolic similarities between components, creates groupings of similar components, and quantifies the degree of similarity. We implemented this reasoning process in a prototype cost estimating application, which creates and maintains cost estimates based on a building product model. Validation studies of the prototype system provide evidence that the framework is general and enables a more accurate and efficient cost estimating process.

Paleomagnetic data support Early Permian age for the Abor Volcanics in the lower Siang Valley, NE India; significance for Gondwana-related break-up models

Confusion exists as to the age of the Abor Volcanics of NE India. Some consider the unit to have been emplaced in the Early Permian, others the Early Eocene, a difference of ∼230 million years. The divergence in opinion is significant because fundamentally different models explaining the geotectonic evolution of India depend on the age designation of the unit. Paleomagnetic data reported here from several exposures in the type locality of the formation in the lower Siang Valley indicate that steep dipping primary magnetizations (mean = 72.7 ± 6.2°, equating to a paleo-latitude of 58.1°) are recorded in the formation. These are only consistent with the unit being of Permian age, possibly Artinskian based on a magnetostratigraphic argument. Plate tectonic models for this time consistently show the NE corner of the sub-continent >50°S; in the Early Eocene it was just north of the equator, which would have resulted in the unit recording shallow directions. The mean declination is counter-clockwise rotated by ∼94°, around half of which can be related to the motion of the Indian block; the remainder is likely due local Himalayan-age thrusting in the Eastern Syntaxis. Several workers have correlated the Abor Volcanics with broadly coeval mafic volcanic suites in Oman, NE Pakistan–NW India and southern Tibet–Nepal, which developed in response to the Cimmerian block peeling-off eastern Gondwana in the Early-Middle Permian, but we believe there are problems with this model. Instead, we suggest that the Abor basalts relate to India–Antarctica/India–Australia extension that was happening at about the same time. Such an explanation best accommodates the relevant stratigraphical and structural data (present-day position within the Himalayan thrust stack), as well as the plate tectonic model for Permian eastern Gondwana.

Sources of ultrafine particles and chemical species along a traffic corridor : comparison of the results from two receptor models

Particulate matter is common in our environment and has been linked to human health problems particularly in the ultrafine size range. A range of chemical species have been associated with particulate matter and of special concern are the hazardous chemicals that can accentuate health problems. If the sources of such particles can be identified then strategies can be developed for the reduction of air pollution and consequently, the improvement of the quality of life. In this investigation, particle number size distribution data and the concentrations of chemical species were obtained at two sites in Brisbane, Australia. Source apportionment was used to determine the sources (or factors) responsible for the particle size distribution data. The apportionment was performed by Positive Matrix Factorisation (PMF) and Principal Component Analysis/Absolute Principal Component Scores (PCA/APCS), and the results were compared with information from the gaseous chemical composition analysis. Although PCA/APCS resolved more sources, the results of the PMF analysis appear to be more reliable. Six common sources identified by both methods include: traffic 1, traffic 2, local traffic, biomass burning, and two unassigned factors. Thus motor vehicle related activities had the most impact on the data with the average contribution from nearly all sources to the measured concentrations higher during peak traffic hours and weekdays. Further analyses incorporated the meteorological measurements into the PMF results to determine the direction of the sources relative to the measurement sites, and this indicated that traffic on the nearby road and intersection was responsible for most of the factors. The described methodology which utilised a combination of three types of data related to particulate matter to determine the sources could assist future development of particle emission control and reduction strategies.

Comparative study of analytical rental model and statistical models for predicting house rental levels

The need for a house rental model in Townsville, Australia is addressed. Models developed for predicting house rental levels are described. An analytical model is built upon a priori selected variables and parameters of rental levels. Regression models are generated to provide a comparison to the analytical model. Issues in model development and performance evaluation are discussed. A comparison of the models indicates that the analytical model performs better than the regression models.

Slice, mine and dice : complexity-aware automated discovery of business process models

Automated process discovery techniques aim at extracting models from information system logs in order to shed light into the business processes supported by these systems. Existing techniques in this space are effective when applied to relatively small or regular logs, but otherwise generate large and spaghetti-like models. In previous work, trace clustering has been applied in an attempt to reduce the size and complexity of automatically discovered process models. The idea is to split the log into clusters and to discover one model per cluster. The result is a collection of process models -- each one representing a variant of the business process -- as opposed to an all-encompassing model. Still, models produced in this way may exhibit unacceptably high complexity. In this setting, this paper presents a two-way divide-and-conquer process discovery technique, wherein the discovered process models are split on the one hand by variants and on the other hand hierarchically by means of subprocess extraction. The proposed technique allows users to set a desired bound for the complexity of the produced models. Experiments on real-life logs show that the technique produces collections of models that are up to 64% smaller than those extracted under the same complexity bounds by applying existing trace clustering techniques.

Groundwater visualisation system (GVS) : a software framework for integrated display and interrogation of conceptual hydrogeological models, data and time-series animation

Management of groundwater systems requires realistic conceptual hydrogeological models as a framework for numerical simulation modelling, but also for system understanding and communicating this to stakeholders and the broader community. To help overcome these challenges we developed GVS (Groundwater Visualisation System), a stand-alone desktop software package that uses interactive 3D visualisation and animation techniques. The goal was a user-friendly groundwater management tool that could support a range of existing real-world and pre-processed data, both surface and subsurface, including geology and various types of temporal hydrological information. GVS allows these data to be integrated into a single conceptual hydrogeological model. In addition, 3D geological models produced externally using other software packages, can readily be imported into GVS models, as can outputs of simulations (e.g. piezometric surfaces) produced by software such as MODFLOW or FEFLOW. Boreholes can be integrated, showing any down-hole data and properties, including screen information, intersected geology, water level data and water chemistry. Animation is used to display spatial and temporal changes, with time-series data such as rainfall, standing water levels and electrical conductivity, displaying dynamic processes. Time and space variations can be presented using a range of contouring and colour mapping techniques, in addition to interactive plots of time-series parameters. Other types of data, for example, demographics and cultural information, can also be readily incorporated. The GVS software can execute on a standard Windows or Linux-based PC with a minimum of 2 GB RAM, and the model output is easy and inexpensive to distribute, by download or via USB/DVD/CD. Example models are described here for three groundwater systems in Queensland, northeastern Australia: two unconfined alluvial groundwater systems with intensive irrigation, the Lockyer Valley and the upper Condamine Valley, and the Surat Basin, a large sedimentary basin of confined artesian aquifers. This latter example required more detail in the hydrostratigraphy, correlation of formations with drillholes and visualisation of simulation piezometric surfaces. Both alluvial system GVS models were developed during drought conditions to support government strategies to implement groundwater management. The Surat Basin model was industry sponsored research, for coal seam gas groundwater management and community information and consultation. The “virtual” groundwater systems in these 3D GVS models can be interactively interrogated by standard functions, plus production of 2D cross-sections, data selection from the 3D scene, rear end database and plot displays. A unique feature is that GVS allows investigation of time-series data across different display modes, both 2D and 3D. GVS has been used successfully as a tool to enhance community/stakeholder understanding and knowledge of groundwater systems and is of value for training and educational purposes. Projects completed confirm that GVS provides a powerful support to management and decision making, and as a tool for interpretation of groundwater system hydrological processes. A highly effective visualisation output is the production of short videos (e.g. 2–5 min) based on sequences of camera ‘fly-throughs’ and screen images. Further work involves developing support for multi-screen displays and touch-screen technologies, distributed rendering, gestural interaction systems. To highlight the visualisation and animation capability of the GVS software, links to related multimedia hosted online sites are included in the references.

Experimental and computer simulation validation of ultrasound phase interference created by lateral inhomogeneity of transit time in replica bone marrow composite models

Purpose: The measurement of broadband ultrasonic attenuation (BUA) in cancellous bone for the assessment of osteoporosis follows a parabolic-type dependence with bone volume fraction; having minima values corresponding to both entire bone and entire marrow. Langton has recently proposed that the primary BUA mechanism may be significant phase interference due to variations in propagation transit time through the test sample as detected over the phase-sensitive surface of the receive ultrasound transducer. This fundamentally simple concept assumes that the propagation of ultrasound through a complex solid : liquid composite sample such as cancellous bone may be considered by an array of parallel ‘sonic rays’. The transit time of each ray is defined by the proportion of bone and marrow propagated, being a minimum (tmin) solely through bone and a maximum (tmax) solely through marrow. A Transit Time Spectrum (TTS), ranging from tmin to tmax, may be defined describing the proportion of sonic rays having a particular transit time, effectively describing lateral inhomogeneity of transit time over the surface of the receive ultrasound transducer. Phase interference may result from interaction of ‘sonic rays’ of differing transit times. The aim of this study was to test the hypothesis that there is a dependence of phase interference upon the lateral inhomogenity of transit time by comparing experimental measurements and computer simulation predictions of ultrasound propagation through a range of relatively simplistic solid:liquid models exhibiting a range of lateral inhomogeneities. Methods: A range of test models was manufactured using acrylic and water as surrogates for bone and marrow respectively. The models varied in thickness in one dimension normal to the direction of propagation, hence exhibiting a range of transit time lateral inhomogeneities, ranging from minimal (single transit time) to maximal (wedge; ultimately the limiting case where each sonic ray has a unique transit time). For the experimental component of the study, two unfocused 1 MHz ¾” broadband diameter transducers were utilized in transmission mode; ultrasound signals were recorded for each of the models. The computer simulation was performed with Matlab, where the transit time and relative amplitude of each sonic ray was calculated. The transit time for each sonic ray was defined as the sum of transit times through acrylic and water components. The relative amplitude considered the reception area for each sonic ray along with absorption in the acrylic. To replicate phase-sensitive detection, all sonic rays were summed and the output signal plotted in comparison with the experimentally derived output signal. Results: From qualtitative and quantitative comparison of the experimental and computer simulation results, there is an extremely high degree of agreement of 94.2% to 99.0% between the two approaches, supporting the concept that propagation of an ultrasound wave, for the models considered, may be approximated by a parallel sonic ray model where the transit time of each ray is defined by the proportion of ‘bone’ and ‘marrow’. Conclusions: This combined experimental and computer simulation study has successfully demonstrated that lateral inhomogeneity of transit time has significant potential for phase interference to occur if a phase-sensitive ultrasound receive transducer is implemented as in most commercial ultrasound bone analysis devices.

Modelling word activation in semantic networks : three scaled entanglement models compared

Modelling how a word is activated in human memory is an important requirement for determining the probability of recall of a word in an extra-list cueing experiment. Previous research assumed a quantum-like model in which the semantic network was modelled as entangled qubits, however the level of activation was clearly being over-estimated. This paper explores three variations of this model, each of which are distinguished by a scaling factor designed to compensate the overestimation.

Empirical investigation of the usefulness of Gateway constructs in process models

Process modeling grammars are used to create scripts of a business domain that a process-aware information system is intended to support. A key grammatical construct of such grammars is known as a Gateway. A Gateway construct is used to describe scenarios in which the workflow of a process diverges or converges according to relevant conditions. Gateway constructs have been subjected to much academic discussion about their meaning, role and usefulness, and have been linked to both process-modeling errors and process-model understandability. This paper examines perceptual discriminability effects of Gateway constructs on an individual's abilities to interpret process models. We compare two ways of expressing two convergence and divergence patterns – Parallel Split and Simple Merge – implemented in a process modeling grammar. On the basis of an experiment with 98 students, we provide empirical evidence that Gateway constructs aid the interpretation of process models due to a perceptual discriminability effect, especially when models are complex. We discuss the emerging implications for research and practice, in terms of revisions to grammar specifications, guideline development and design choices in process modeling.