Ureaplasma colonization of amniotic fluid and efficacy of antenatal corticosteroids for preterm lung maturation in sheep

Objective: To assess the efficacy of maternal betamethasone for improving preterm lung function, in the presence of inflammation induced by amniotic fluid ureaplasma colonization. ----- ----- Study design: Ewes bearing single fetuses were randomized to receive an intra-amniotic injection of Ureaplasma parvum (serovar 6; 2×107 colony forming units) or vehicle at 86±2 days of pregnancy (mean±SD: term is 150d), followed by maternal intramuscular betamethasone (0.5mg/kg) or saline, either 2 or 7 days before delivery of lambs at 123±1d. ----- ----- Results: Amniotic fluid IL-8 was elevated by ureaplasmas (p=0.049) but unaffected by betamethasone. Lung inflammation induced by ureaplasmas was not affected by betamethasone. Lung compliance was increased by ureaplasma colonization (p=0.009) and betamethasone (p=0.042), and effects were additive. Lung surfactant was increased by ureaplasma colonization (p<0.001) and betamethasone 7 days (p=0.001), but not 2 days, before delivery. ----- ----- Conclusion: Inflammation improves preterm lung function due to increases in surfactant. Antenatal corticosteroids further augment lung function, through an apparently independent mechanism.

Integrating qualitative and quantitative approaches in cross-cultural research

The affects associated with culture, the values inherent in cultures and the identification of cultural assumptions are popular topics in recent management and Information Systems (IS) research. The main focus in relevant IS research over the years, has been on the comparison of cultural artifacts in different cultural settings. Despite these studies we need to ask whether there is a general approach to how culture can be researched in a rigorous manner? What are the issues that arise in cross- cultural research that have a bearing on decisions about a suitable research approach? What are the most appropriate methodologies to be used in cross-cultural research? Which is more appropriate, a qualitative, a quantitative or a mixed- method research approach? This paper will discuss important considerations in the process of deciding on the best research approach for cross-cultural projects. A case study will be then be reported as an example revealing the merits of integrating qualitative and quantitative approaches followed by a thorough discussion on the issues which may arise during this process.

Mesenchymal stem cells in osteoarthritis therapy : current status of theory, technology, and applications

Osteoarthritis (OA) is a chronic, non-inflammatory type of arthritis, which usually affects the movable and weight bearing joints of the body. It is the most common joint disease in human beings and common in elderly people. Till date, there are no safe and effective diseases modifying OA drugs (DMOADs) to treat the millions of patients suffering from this serious and debilitating disease. However, recent studies provide strong evidence for the use of mesenchymal stem cell (MSC) therapy in curing cartilage related disorders. Due to their natural differentiation properties, MSCs can serve as vehicles for the delivery of effective, targeted treatment to damaged cartilage in OA disease. In vitro, MSCs can readily be tailored with transgenes with anti-catabolic or pro-anabolic effects to create cartilage-friendly therapeutic vehicles. On the other hand, tissue engineering constructs with scaffolds and biomaterials holds promising biological cartilage therapy. Many of these strategies have been validated in a wide range of in vitro and in vivo studies assessing treatment feasibility or efficacy. In this review, we provide an outline of the rationale and status of stem-cell-based treatments for OA cartilage, and we discuss prospects for clinical implementation and the factors crucial for maintaining the drive towards this goal.

Pressure, oxygen tension and temperature in the periosteal callus during bone healing - An in vivo study in sheep

Adequate blood supply and sufficient mechanical stability are necessary for timely fracture healing. Damage to vessels impairs blood supply; hindering the transport of oxygen which is an essential metabolite for cells involved in repair. The degree of mechanical stability determines the mechanical conditions in the healing tissues. The mechanical conditions can influence tissue differentiation and may also inhibit revascularization. Knowledge of the actual conditions in a healing fracture in vivo is extremely limited. This study aimed to quantify the pressure, oxygen tension and temperature in the external callus during the early phase of bone healing. Six Merino-mix sheep underwent a tibial osteotomy. The tibia was stabilized with a standard mono-lateral external fixator. A multi-parameter catheter was placed adjacent to the osteotomy gap on the medial aspect of the tibia. Measurements of oxygen tension and temperature were performed for ten days post-op. Measurements of pressure were performed during gait on days three and seven. The ground reaction force and the interfragmentary movements were measured simultaneously. The maximum pressure during gait increased (p=0.028) from three (41.3 [29.2-44.1] mm Hg) to seven days (71.8 [61.8-84.8] mm Hg). During the same interval, there was no change (p=0.92) in the peak ground reaction force or in the interfragmentary movement (compression: p=0.59 and axial rotation: p=0.11). Oxygen tension in the haematoma (74.1 mm Hg [68.6-78.5]) was initially high post-op and decreased steadily over the first five days. The temperature increased over the first four days before reaching a plateau at approximately 38.5 degrees C on day four. This study is the first to report pressure, oxygen tension and temperature in the early callus tissues. The magnitude of pressure increased even though weight bearing and IFM remained unchanged. Oxygen tensions were initially high in the haematoma and fell gradually with a low oxygen environment first established after four to five days. This study illustrates that in bone healing the local environment for cells may not be considered constant with regard to oxygen tension, pressure and temperature.

Preclinical animal models for segmental bone defect research and tissue engineering

Currently, well-established clinical therapeutic approaches for bone reconstruction are restricted to the transplantation of autografts and allografts, and the implantation of metal devices or ceramic-based implants to assist bone regeneration. Bone grafts possess osteoconductive and osteoinductive properties, however they are limited in access and availability and associated with donor site morbidity, haemorrhage, risk of infection, insufficient transplant integration, graft devitalisation, and subsequent resorption resulting in decreased mechanical stability. As a result, recent research focuses on the development of alternative therapeutic concepts. Analysing the tissue engineering literature it can be concluded that bone regeneration has become a focus area in the field. Hence, a considerable number of research groups and commercial entities work on the development of tissue engineered constructs for bone regeneration. However, bench to bedside translations are still infrequent as the process towards approval by regulatory bodies is protracted and costly, requiring both comprehensive in vitro and in vivo studies. In translational orthopaedic research, the utilisation of large preclinical animal models is a conditio sine qua non. Consequently, to allow comparison between different studies and their outcomes, it is essential that animal models, fixation devices, surgical procedures and methods of taking measurements are well standardized to produce reliable data pools as a base for further research directions. The following chapter reviews animal models of the weight-bearing lower extremity utilized in the field which include representations of fracture-healing, segmental bone defects, and fracture non-unions.

Translating competency statements into desired outcomes : a representational model for conceptualising the competency acquisition process

The need to develop effective and efficient training programs has been recognised by all sectors engaged in training. In responding to the above need, focus has been directed to developing good competency statements and performance indicators to measure the outcomes. Very little has been done to understand how the competency statements get translated into good performance. To conceptualise this translation process, a representational model based on an information processing paradigm is proposed and discussed. It is argued that learners’ prior knowledge and the effectiveness of the instructional material are two variables that have significant bearing on how effectively the competency knowledge is translated into outcomes. To contextualise the model examples from apprentice training are used.

Validation Gating for Non-Linear Non-Gaussian Target Tracking

This paper develops a general theory of validation gating for non-linear non-Gaussian mod- els. Validation gates are used in target tracking to cull very unlikely measurement-to-track associa- tions, before remaining association ambiguities are handled by a more comprehensive (and expensive) data association scheme. The essential property of a gate is to accept a high percentage of correct associ- ations, thus maximising track accuracy, but provide a su±ciently tight bound to minimise the number of ambiguous associations. For linear Gaussian systems, the ellipsoidal vali- dation gate is standard, and possesses the statistical property whereby a given threshold will accept a cer- tain percentage of true associations. This property does not hold for non-linear non-Gaussian models. As a system departs from linear-Gaussian, the ellip- soid gate tends to reject a higher than expected pro- portion of correct associations and permit an excess of false ones. In this paper, the concept of the ellip- soidal gate is extended to permit correct statistics for the non-linear non-Gaussian case. The new gate is demonstrated by a bearing-only tracking example.

Machine prognostics based on health state probability estimation

The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation and can also improve productivity and enhance system’s safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. Although a variety of prognostic methodologies have been reported recently, their application in industry is still relatively new and mostly focused on the prediction of specific component degradations. Furthermore, they required significant and sufficient number of fault indicators to accurately prognose the component faults. Hence, sufficient usage of health indicators in prognostics for the effective interpretation of machine degradation process is still required. Major challenges for accurate longterm prediction of remaining useful life (RUL) still remain to be addressed. Therefore, continuous development and improvement of a machine health management system and accurate long-term prediction of machine remnant life is required in real industry application. This thesis presents an integrated diagnostics and prognostics framework based on health state probability estimation for accurate and long-term prediction of machine remnant life. In the proposed model, prior empirical (historical) knowledge is embedded in the integrated diagnostics and prognostics system for classification of impending faults in machine system and accurate probability estimation of discrete degradation stages (health states). The methodology assumes that machine degradation consists of a series of degraded states (health states) which effectively represent the dynamic and stochastic process of machine failure. The estimation of discrete health state probability for the prediction of machine remnant life is performed using the ability of classification algorithms. To employ the appropriate classifier for health state probability estimation in the proposed model, comparative intelligent diagnostic tests were conducted using five different classifiers applied to the progressive fault data of three different faults in a high pressure liquefied natural gas (HP-LNG) pump. As a result of this comparison study, SVMs were employed in heath state probability estimation for the prediction of machine failure in this research. The proposed prognostic methodology has been successfully tested and validated using a number of case studies from simulation tests to real industry applications. The results from two actual failure case studies using simulations and experiments indicate that accurate estimation of health states is achievable and the proposed method provides accurate long-term prediction of machine remnant life. In addition, the results of experimental tests show that the proposed model has the capability of providing early warning of abnormal machine operating conditions by identifying the transitional states of machine fault conditions. Finally, the proposed prognostic model is validated through two industrial case studies. The optimal number of health states which can minimise the model training error without significant decrease of prediction accuracy was also examined through several health states of bearing failure. The results were very encouraging and show that the proposed prognostic model based on health state probability estimation has the potential to be used as a generic and scalable asset health estimation tool in industrial machinery.

Real-time volume estimation of a dragline payload

This paper presents a method for measuring the in-bucket payload volume on a dragline excavator for the purpose of estimating the material's bulk density in real-time. Knowledge of the payload's bulk density can provide feedback to mine planning and scheduling to improve blasting and therefore provide a more uniform bulk density across the excavation site. This allows a single optimal bucket size to be used for maximum overburden removal per dig and in turn reduce costs and emissions in dragline operation and maintenance. The proposed solution uses a range bearing laser to locate and scan full buckets between the lift and dump stages of the dragline cycle. The bucket is segmented from the scene using cluster analysis, and the pose of the bucket is calculated using the Iterative Closest Point (ICP) algorithm. Payload points are identified using a known model and subsequently converted into a height grid for volume estimation. Results from both scaled and full scale implementations show that this method can achieve an accuracy of above 95%.

Preliminary characterisation of the surface of cartilage following exposure to saturated and unsaturated synthetic lipids

Articular cartilage is covered by a microscopic structure known as surface amorphous layer. This surface structure is often the first victim of attack during cartilage degeneration, thereby resulting in a gross impairment in cartilage function such as lubrication and load bearing. We hypothesize that incubation of degraded cartilage in solutions of different species of synthetic surface active phospholipids (saturated and unsaturated species) can remodel this lost surface structure. To test this hypothesis, the structural configuration of the surface of articular cartilage was studied and characterised with the lipid filled surface amorphous layer intact using the AFM. The results were then compared with those obtained following a systematic removal (delipidization) and replacement (relipidization) of this layer. Our results show that the unsaturated surfactant partially restored the lost surface amorphous layer while the saturated surfactant specie settled on the surface due to its poor solubility in aqueous solution.

Plantar fasciitis : are pain and fascial thickness associated with arch shape and loading?

Background and Purpose Although plantar fascial thickening is a sonographic criterion for the diagnosis of plantar fasciitis, the effect of local loading and structural factors on fascial morphology are unknown. The purposes of this study were to compare sonographic measures of fascial thickness and radiographic measures of arch shape and regional loading of the foot during gait in individuals with and without unilateral plantar fasciitis and to investigate potential relationships between these loading and structural factors and the morphology of the plantar fascia in individuals with and without heel pain. Subjects The participants were 10 subjects with unilateral plantar fasciitis and 10 matched asymptomatic controls. Methods Heel pain on weight bearing was measured by a visual analog scale. Fascial thickness and static arch angle were determined from bilateral sagittal sonograms and weight-bearing lateral foot roentgenograms. Regional plantar loading was estimated from a pressure plate. Results On average, the plantar fascia of the symptomatic limb was thicker than the plantar fascia of the asymptomatic limb (6.1±1.4 mm versus 4.2±0.5 mm), which, in turn, was thicker than the fascia of the matched control limbs (3.4±0.5 mm and 3.5±0.6 mm). Pain was correlated with fascial thickness, arch angle, and midfoot loading in the symptomatic foot. Fascial thickness, in turn, was positively correlated with arch angle in symptomatic and asymptomatic feet and with peak regional loading of the midfoot in the symptomatic limb. Discussion and Conclusion The findings indicate that fascial thickness and pain in plantar fasciitis are associated with the regional loading and static shape of the arch.

Digital signal processing

Signal Processing (SP) is a subject of central importance in engineering and the applied sciences. Signals are information-bearing functions, and SP deals with the analysis and processing of signals (by dedicated systems) to extract or modify information. Signal processing is necessary because signals normally contain information that is not readily usable or understandable, or which might be disturbed by unwanted sources such as noise. Although many signals are non-electrical, it is common to convert them into electrical signals for processing. Most natural signals (such as acoustic and biomedical signals) are continuous functions of time, with these signals being referred to as analog signals. Prior to the onset of digital computers, Analog Signal Processing (ASP) and analog systems were the only tool to deal with analog signals. Although ASP and analog systems are still widely used, Digital Signal Processing (DSP) and digital systems are attracting more attention, due in large part to the significant advantages of digital systems over the analog counterparts. These advantages include superiority in performance,s peed, reliability, efficiency of storage, size and cost. In addition, DSP can solve problems that cannot be solved using ASP, like the spectral analysis of multicomonent signals, adaptive filtering, and operations at very low frequencies. Following the recent developments in engineering which occurred in the 1980's and 1990's, DSP became one of the world's fastest growing industries. Since that time DSP has not only impacted on traditional areas of electrical engineering, but has had far reaching effects on other domains that deal with information such as economics, meteorology, seismology, bioengineering, oceanology, communications, astronomy, radar engineering, control engineering and various other applications. This book is based on the Lecture Notes of Associate Professor Zahir M. Hussain at RMIT University (Melbourne, 2001-2009), the research of Dr. Amin Z. Sadik (at QUT & RMIT, 2005-2008), and the Note of Professor Peter O'Shea at Queensland University of Technology. Part I of the book addresses the representation of analog and digital signals and systems in the time domain and in the frequency domain. The core topics covered are convolution, transforms (Fourier, Laplace, Z. Discrete-time Fourier, and Discrete Fourier), filters, and random signal analysis. There is also a treatment of some important applications of DSP, including signal detection in noise, radar range estimation, banking and financial applications, and audio effects production. Design and implementation of digital systems (such as integrators, differentiators, resonators and oscillators are also considered, along with the design of conventional digital filters. Part I is suitable for an elementary course in DSP. Part II (which is suitable for an advanced signal processing course), considers selected signal processing systems and techniques. Core topics covered are the Hilbert transformer, binary signal transmission, phase-locked loops, sigma-delta modulation, noise shaping, quantization, adaptive filters, and non-stationary signal analysis. Part III presents some selected advanced DSP topics. We hope that this book will contribute to the advancement of engineering education and that it will serve as a general reference book on digital signal processing.

Vulnerability assessment of reinforced concrete columns subjected to vehicular impacts

Columns are one of the key load bearing elements that are highly susceptible to vehicle impacts. The resulting severe damages to columns may leads to failures of the supporting structure that are catastrophic in nature. However, the columns in existing structures are seldom designed for impact due to inadequacies of design guidelines. The impact behaviour of columns designed for gravity loads and actions other than impact is, therefore, of an interest. A comprehensive investigation is conducted on reinforced concrete column with a particular focus on investigating the vulnerability of the exposed columns and to implement mitigation techniques under low to medium velocity car and truck impacts. The investigation is based on non-linear explicit computer simulations of impacted columns followed by a comprehensive validation process. The impact is simulated using force pulses generated from full scale vehicle impact tests. A material model capable of simulating triaxial loading conditions is used in the analyses. Circular columns adequate in capacity for five to twenty story buildings, designed according to Australian standards are considered in the investigation. The crucial parameters associated with the routine column designs and the different load combinations applied at the serviceability stage on the typical columns are considered in detail. Axially loaded columns are examined at the initial stage and the investigation is extended to analyse the impact behaviour under single axis bending and biaxial bending. The impact capacity reduction under varying axial loads is also investigated. Effects of the various load combinations are quantified and residual capacity of the impacted columns based on the status of the damage and mitigation techniques are also presented. In addition, the contribution of the individual parameter to the failure load is scrutinized and analytical equations are developed to identify the critical impulses in terms of the geometrical and material properties of the impacted column. In particular, an innovative technique was developed and introduced to improve the accuracy of the equations where the other techniques are failed due to the shape of the error distribution. Above all, the equations can be used to quantify the critical impulse for three consecutive points (load combinations) located on the interaction diagram for one particular column. Consequently, linear interpolation can be used to quantify the critical impulse for the loading points that are located in-between on the interaction diagram. Having provided a known force and impulse pair for an average impact duration, this method can be extended to assess the vulnerability of columns for a general vehicle population based on an analytical method that can be used to quantify the critical peak forces under different impact durations. Therefore the contribution of this research is not only limited to produce simplified yet rational design guidelines and equations, but also provides a comprehensive solution to quantify the impact capacity while delivering new insight to the scientific community for dealing with impacts.

Generation of profluorescent isoindoline nitroxides using click chemistry

Novel profluorescent nitroxides bearing a triazole linker between the coumarin fluorophore and an isoindoline nitroxide were prepared in good yields using the coppercatalyzed azide�alkyne 1,3-dipolar cycloaddition reaction (CuAAC). Nitroxides containing 7-hydroxy and 7-diethylamino substitution on their coumarin rings displayed significant fluorescence suppression, and upon reaction with methyl radicals, normal fluorescence emission was returned. The fluorescence emission for the 7-hydroxycoumarin nitroxide and its diamagnetic analogue was found to be strongly influenced by pH with maximal fluorescence emission achieved in basic solution. Solvent polarity was also shown to affect fluorescence emission. The significant difference in fluorescence output between the nitroxides and their corresponding diamagnetic analogues makes these compounds ideal tools for monitoring processes involving free-radical species.