Comparison of eight published lumbar spine finite element models

Due to its ability to represent intricate systems with material nonlinearities as well as irregular loading, boundary, geometrical and material domains, the finite element (FE) method has been recognized as an important computational tool in spinal biomechanics. Current FE models generally account for a single distinct spinal geometry with one set of material properties despite inherently large inter-subject variability. The uncertainty and high variability in tissue material properties, geometry, loading and boundary conditions has cast doubt on the reliability of their predictions and comparability with reported in vitro and in vivo values. A multicenter study was undertaken to compare the results of eight well-established models of the lumbar spine that have been developed, validated and applied for many years. Models were subjected to pure and combined loading modes and their predictions were compared to in vitro and in vivo measurements for intervertebral rotations, disc pressures and facet joint forces. Under pure moment loading, the predicted L1-5 rotations of almost all models fell within the reported in vitro ranges; their median values differed on average by only 2° for flexion-extension, 1° for lateral bending and 5° for axial rotation. Predicted median facet joint forces and disc pressures were also in good agreement with previously published median in vitro values. However, the ranges of predictions were larger and exceeded the in vitro ranges, especially for facet joint forces. For all combined loading modes, except for flexion, predicted median segmental intervertebral rotations and disc pressures were in good agreement with in vivo values. The simulations yielded median facet joint forces of 0 N in flexion, 38 N in extension, 14 N in lateral bending and 60 N in axial rotation that could not be validated due to the paucity of in vivo facet joint forces. In light of high inter-subject variability, one must be cautious when generalizing predictions obtained from one deterministic model. This study demonstrates however that the predictive power increases when FE models are combined together. The median of individual numerical results can hence be used as an improved tool in order to estimate the response of the lumbar spine.

A new approach to estimating trends in chlamydia incidence

Objectives Directly measuring disease incidence in a population is difficult and not feasible to do routinely. We describe the development and application of a new method of estimating at a population level the number of incident genital chlamydia infections, and the corresponding incidence rates, by age and sex using routine surveillance data. Methods A Bayesian statistical approach was developed to calibrate the parameters of a decision-pathway tree against national data on numbers of notifications and tests conducted (2001-2013). Independent beta probability density functions were adopted for priors on the time-independent parameters; the shape parameters of these beta distributions were chosen to match prior estimates sourced from peer-reviewed literature or expert opinion. To best facilitate the calibration, multivariate Gaussian priors on (the logistic transforms of) the time-dependent parameters were adopted, using the Matérn covariance function to favour changes over consecutive years and across adjacent age cohorts. The model outcomes were validated by comparing them with other independent empirical epidemiological measures i.e. prevalence and incidence as reported by other studies. Results Model-based estimates suggest that the total number of people acquiring chlamydia per year in Australia has increased by ~120% over 12 years. Nationally, an estimated 356,000 people acquired chlamydia in 2013, which is 4.3 times the number of reported diagnoses. This corresponded to a chlamydia annual incidence estimate of 1.54% in 2013, increased from 0.81% in 2001 (~90% increase). Conclusions We developed a statistical method which uses routine surveillance (notifications and testing) data to produce estimates of the extent and trends in chlamydia incidence.

Deformation of a three-dimensional red blood cell in a stenosed micro-capillary

Red blood cells (RBCs) exhibit different types of motions and deformations when the blood flows through capillaries. Interestingly, due to the complex three-dimensional structure of the RBC membrane, RBCs show three-dimensional motions and deformations in the blood flow. These motions and deformations of the RBCs highly depend on the stiffness of the RBC membrane and on the geometrical parameters of the capillary through which blood flows. However, capillaries always do not have uniform cross sections and some capillaries have stenosed segments, where cross sectional area suddenly reduces. Further, some diseases can alter the stiffness of the RBC membrane drastically. In this study, the deformation behaviour of a single three-dimensional RBC is examined, when it moves through a stenosed capillary. A three-dimensional spring network is used to model the RBC membrane. The RBC’s inside and outside fluids are discretized into a finite number of mass points and treated by smoothed particle hydrodynamics (SPH) method. The capillary is considered as a rigid tube with a stenosed section. The deformation index, mean velocity and total energy of the RBC are analysed when it flows through the stenosed capillary. Further, motion and deformation of the RBCs with different membrane stiffness (KB) are compared when they flow through the stenosed segment of the capillary. The simulation results demonstrate the RBCs are subjected to a larger deformation when they move through the stenosed part of the capillary and the RBCs with lower KBvalues easily pass through the stenosed segment of the capillary. Further, RBCs having higher KBvalues have a lower mean velocity and it leads to slow down the overall blood flow rate

Formation of the three-dimensional geometry of the red blood cell membrane

Red blood cells (RBCs) are nonnucleated liquid capsules, enclosed in deformable viscoelastic membranes with complex three dimensional geometrical structures. Generally, RBC membranes are highly incompressible and resistant to areal changes. However, RBC membranes show a planar shear deformation and out of plane bending deformation. The behaviour of RBCs in blood vessels is investigated using numerical models. All the characteristics of RBC membranes should be addressed to develop a more accurate and stable model. This article presents an effective methodology to model the three dimensional geometry of the RBC membrane with the aid of commercial software COMSOL Multiphysics 4.2a and Fortran programming. Initially, a mesh is generated for a sphere using the COMSOL Multiphysics software to represent the RBC membrane. The elastic energy of the membrane is considered to determine a stable membrane shape. Then, the actual biconcave shape of the membrane is obtained based on the principle of virtual work, when the total energy is minimised. The geometry of the RBC membrane could be used with meshfree particle methods to simulate motion and deformation of RBCs in micro-capillaries

Structural damage detection method using frequency response functions

Structural damage detection using measured dynamic data for pattern recognition is a promising approach. These pattern recognition techniques utilize artificial neural networks and genetic algorithm to match pattern features. In this study, an artificial neural network–based damage detection method using frequency response functions is presented, which can effectively detect nonlinear damages for a given level of excitation. The main objective of this article is to present a feasible method for structural vibration–based health monitoring, which reduces the dimension of the initial frequency response function data and transforms it into new damage indices and employs artificial neural network method for detecting different levels of nonlinearity using recognized damage patterns from the proposed algorithm. Experimental data of the three-story bookshelf structure at Los Alamos National Laboratory are used to validate the proposed method. Results showed that the levels of nonlinear damages can be identified precisely by the developed artificial neural networks. Moreover, it is identified that artificial neural networks trained with summation frequency response functions give higher precise damage detection results compared to the accuracy of artificial neural networks trained with individual frequency response functions. The proposed method is therefore a promising tool for structural assessment in a real structure because it shows reliable results with experimental data for nonlinear damage detection which renders the frequency response function–based method convenient for structural health monitoring.

Design of stiffened plates with openings

The load-deflection and ultimate strength behaviour of longitudinally stiffened plates with openings was studied using a second-order elastic post-buckling analysis and a rigid-plastic analysis. The ultimate strength was predicted from the intersection point of elastic and rigid-plastic curves and the Perry strut formula. Comparison with experimental results shows that satisfactory prediction of ultimate strength can be obtained by this simple method. Effects of the size of opening, the initial geometrical imperfections and the plate slenderness ratio on the strength of perforated stiffened plates were also studied.

Searching for semantic person queries using channel representations

It is not uncommon to hear a person of interest described by their height, build, and clothing (i.e. type and colour). These semantic descriptions are commonly used by people to describe others, as they are quick to relate and easy to understand. However such queries are not easily utilised within intelligent surveillance systems as they are difficult to transform into a representation that can be searched for automatically in large camera networks. In this paper we propose a novel approach that transforms such a semantic query into an avatar that is searchable within a video stream, and demonstrate state-of-the-art performance for locating a subject in video based on a description.

Numerical investigation of motion and deformation of a single red blood cell in a stenosed capillary

It is generally assumed that influence of the red blood cells (RBCs) is predominant in blood rheology. The healthy RBCs are highly deformable and can thus easily squeeze through the smallest capillaries having internal diameter less than their characteristic size. On the other hand, RBCs infected by malaria or other diseases are stiffer and so less deformable. Thus it is harder for them to flow through the smallest capillaries. Therefore, it is very important to critically and realistically investigate the mechanical behavior of both healthy and infected RBCs which is a current gap in knowledge. The motion and the steady state deformed shape of the RBCs depend on many factors, such as the geometrical parameters of the capillary through which blood flows, the membrane bending stiffness and the mean velocity of the blood flow. In this study, motion and deformation of a single two-dimensional RBC in a stenosed capillary is explored by using smoothed particle hydrodynamics (SPH) method. An elastic spring network is used to model the RBC membrane, while the RBC's inside fluid and outside fluid are treated as SPH particles. The effect of RBC's membrane stiffness (kb), inlet pressure (P) and geometrical parameters of the capillary on the motion and deformation of the RBC is studied. The deformation index, RBC's mean velocity and the cell membrane energy are analyzed when the cell passes through the stenosed capillary. The simulation results demonstrate that the kb, P and the geometrical parameters of the capillary have a significant impact on the RBCs' motion and deformation in the stenosed section.

Searching for people using semantic soft biometric descriptions

It is not uncommon to hear a person of interest described by their height, build, and clothing (i.e. type and colour). These semantic descriptions are commonly used by people to describe others, as they are quick to communicate and easy to understand. However such queries are not easily utilised within intelligent video surveillance systems, as they are difficult to transform into a representation that can be utilised by computer vision algorithms. In this paper we propose a novel approach that transforms such a semantic query into an avatar in the form of a channel representation that is searchable within a video stream. We show how spatial, colour and prior information (person shape) can be incorporated into the channel representation to locate a target using a particle-filter like approach. We demonstrate state-of-the-art performance for locating a subject in video based on a description, achieving a relative performance improvement of 46.7% over the baseline. We also apply this approach to person re-detection, and show that the approach can be used to re-detect a person in a video steam without the use of person detection.

Making the profitable transition towards sustainable business practice

The last three decades have been difficult for companies and industry. In an increasingly competitive international business climate with shifting national environmental regulations, higher standards are being demanded by the consumer and community groups, not-to-mention the escalating cost of primary resources such as water, steel and minerals. The cause of these pressures is the traditional notion held by business executives and engineers that there is an inherent trade off between eco-efficiency and improving the economic bottom line. However there is significant evidence and examples of best practice to show that there is in fact no trade-off between the environment and the economy if sustainable development through continual improvement is adopted. It is highly possible therefore for companies to make a profitable transition towards sustainable business practice, where along the transition significant business opportunities can be taken advantage of. Companies are by their very nature dynamic, influential and highly capable of adapting to change. Making an organisational transformation to a sustainable business is not outside the capacity of the typical company, who know much of what is needed already to change their activities to satisfy current market demands while achieving competitiveness. However in order to make the transition towards sustainable business practice companies require some key mechanisms such as accurate information on methodologies and opportunities, understanding of the financial and non-financial incentives, permission from stakeholders and shareholders, understanding of the emerging market opportunities, a critical mass of leaders in their sector and demonstrated case studies, and awarding appropriate risk-taking activities undertaken by engineers and CEOs. Satisfying these requirements will adopt an innovative culture within the company that strives for continual improvement and successfully transforms itself to achieve competitiveness in the 21st Century. This paper will summarise the experiences of The Natural Edge Project (TNEP) and its partners in assisting organisations to make a profitable transition towards sustainable business practice through several initiatives. The Natural Advantage of Nations publication provides the critical information required by business leaders and engineers to set the context of sustainable business practice. The Profiting in a Carbon Constrained World report, developed with Natural Capitalism Inc led by Hunter Lovins, summarises the opportunities available to companies to take advantage of the carbon trading market mechanisms such as the Chicago Climate Exchange and European Climate Exchange. The Sustainability Helix then guides the company through the transition by identifying the key tools and methodologies required by companies to reduce environmental loading while dramatically improving resource productivity and achieving competitiveness. Finally, the Engineering Sustainable Solutions Program delivers the key engineering information required by companies and university departments to deliver sustainable engineering solutions. The initiatives are of varying complexity and level of application, however all are designed to provide key staff the critical information required to make a profitable transition towards sustainable business practice. It is then their responsibility to apply and teach their knowledge to the rest of the organisation.

Learned ultra-wideband RADAR sensor model for augmented LIDAR-based traversability mapping in vegetated environments

In vegetated environments, reliable obstacle detection remains a challenge for state-of-the-art methods, which are usually based on geometrical representations of the environment built from LIDAR and/or visual data. In many cases, in practice field robots could safely traverse through vegetation, thereby avoiding costly detours. However, it is often mistakenly interpreted as an obstacle. Classifying vegetation is insufficient since there might be an obstacle hidden behind or within it. Some Ultra-wide band (UWB) radars can penetrate through vegetation to help distinguish actual obstacles from obstacle-free vegetation. However, these sensors provide noisy and low-accuracy data. Therefore, in this work we address the problem of reliable traversability estimation in vegetation by augmenting LIDAR-based traversability mapping with UWB radar data. A sensor model is learned from experimental data using a support vector machine to convert the radar data into occupancy probabilities. These are then fused with LIDAR-based traversability data. The resulting augmented traversability maps capture the fine resolution of LIDAR-based maps but clear safely traversable foliage from being interpreted as obstacle. We validate the approach experimentally using sensors mounted on two different mobile robots, navigating in two different environments.

Numerical investigation of aerosol particle transport and deposition in realistic lung airway

Different human activities like combustion of fossil fuels, biomass burning, industrial and agricultural activities, emit a large amount of particulates into the atmosphere. As a consequence, the air we inhale contains significant amount of suspended particles, including organic and inorganic solids and liquids, as well as various microorganism, which are solely responsible for a number of pulmonary diseases. Developing a numerical model for transport and deposition of foreign particles in realistic lung geometry is very challenging due to the complex geometrical structure of the human lung. In this study, we have numerically investigated the airborne particle transport and its deposition in human lung surface. In order to obtain the appropriate results of particle transport and deposition in human lung, we have generated realistic lung geometry from the CT scan obtained from a local hospital. For a more accurate approach, we have also created a mucus layer inside the geometry, adjacent to the lung surface and added all apposite mucus layer properties to the wall surface. The Lagrangian particle tracking technique is employed by using ANSYS FLUENT solver to simulate the steady-state inspiratory flow. Various injection techniques have been introduced to release the foreign particles through the inlet of the geometry. In order to investigate the effects of particle size on deposition, numerical calculations are carried out for different sizes of particles ranging from 1 micron to 10 micron. The numerical results show that particle deposition pattern is completely dependent on its initial position and in case of realistic geometry; most of the particles are deposited on the rough wall surface of the lung geometry instead of carinal region.

Microbial oil production from palm oil empty fruit bunch hydrolysates

This study explores the potential use of empty fruit bunch (EFB) residues from palm oil processing residues, as an alternative feedstock for microbial oil production. EFB is a readily available, lignocellulosic biomass that provides cheaper substrates for oil production in comparison to the use of pure sugars. In this study, potential oleaginous microorganisms were selected based on a multi-criteria analysis (MCA) framework which utilised Analytical Hierarchy Process (AHP) with Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) aided by Geometrical Analysis for Interactive Aid (GAIA). The MCA framework was used to evaluate several strains of microalgae (Chlorella protothecoides and Chlorella zofingiensis), yeasts (Cryptococcus albidus and Rhodotorula mucilaginosa) and fungi (Aspergillus oryzae and Mucor plumbeus) on glucose, xylose and glycerol. Based on the results of PROMETHEE rankings and GAIA plane, fungal strains A. oryzae and M. plumbeus and yeast strain R. mucilaginosa showed great promise for oil production from lignocellulosic hydrolysates. The study further cultivated A. oryzae, M. plumbeus and R. mucilaginosa on EFB hydrolysates for oil production. EFB was pretreated with dilute sulfuric acid, followed by enzymatic saccharification of solid residue. Hydrolysates tested in this study are detoxified liquid hydrolysates (LH) and enzymatic hydrolysate (EH).

A dynamic navigation model for unmanned aircraft systems and an application to autonomous front-on environmental sensing and photography using low-cost sensor systems

This paper presents an unmanned aircraft system (UAS) that uses a probabilistic model for autonomous front-on environmental sensing or photography of a target. The system is based on low-cost and readily-available sensor systems in dynamic environments and with the general intent of improving the capabilities of dynamic waypoint-based navigation systems for a low-cost UAS. The behavioural dynamics of target movement for the design of a Kalman filter and Markov model-based prediction algorithm are included. Geometrical concepts and the Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of a target, thus delivering a new waypoint for autonomous navigation. The results of the application to aerial filming with low-cost UAS are presented, achieving the desired goal of maintained front-on perspective without significant constraint to the route or pace of target movement.

Free-standing alumina nanobottles and nanotubes pre-integrated into nanoporous alumina membranes

A novel interfacial structure consisting of long (up to 5 μm), thin (about 300 nm), highly-ordered, free-standing, highly-reproducible aluminum oxide nanobottles and long tubular nanocapsules attached to a rigid, thin (less than 1 μm) nanoporous anodic alumina membrane is fabricated by simple, fast, catalyst-free, environmentally friendly voltage-pulse anodization. A growth mechanism is proposed based on the formation of straight channels in alumina membrane by anodization, followed by neck formation due to a sophisticated voltage control during the process. This process can be used for the fabrication of alumina nanocontainers with highly controllable geometrical size and volume, vitally important for various applications such as material and energy storage, targeted drug and diagnostic agent delivery, controlled drug and active agent release, gene and biomolecule reservoirs, micro-biologically protected platforms, nano-bioreactors, tissue engineering and hydrogen storage.