A collagen network phase improves cell seeding of open-pore structure scaffolds under perfusion

Scaffolds with open-pore morphologies offer several advantages in cell-based tissue engineering, but their use is limited by a low cell seeding efficiency. We hypothesized that inclusion of a collagen network as filling material within the open-pore architecture of polycaprolactone-tricalcium phosphate (PCL-TCP) scaffolds increases human bone marrow stromal cells (hBMSC) seeding efficiency under perfusion and in vivo osteogenic capacity of the resulting constructs. PCL-TCP scaffolds, rapid prototyped with a honeycomb-like architecture, were filled with a collagen gel and subsequently lyophilized, with or without final crosslinking. Collagen-free scaffolds were used as controls. The seeding efficiency was assessed after overnight perfusion of expanded hBMSC directly through the scaffold pores using a bioreactor system. By seeding and culturing freshly harvested hBMSC under perfusion for 3 weeks, the osteogenic capacity of generated constructs was tested by ectopic implantation in nude mice. The presence of the collagen network, independently of the crosslinking process, significantly increased the cell seeding efficiency (2.5-fold), and reduced the loss of clonogenic cells in the supernatant. Although no implant generated frank bone tissue, possibly due to the mineral distribution within the scaffold polymer phase, the presence of a non crosslinked collagen phase led to in vivo formation of scattered structures of dense osteoids. Our findings verify that the inclusion of a collagen network within open morphology porous scaffolds improves cell retention under perfusion seeding. In the context of cell-based therapies, collagen-filled porous scaffolds are expected to yield superior cell utilization, and could be combined with perfusion-based bioreactor devices to streamline graft manufacture.

A circuit-breaker restrike diagnostic algorithm using ATP and wavelet transforms

Circuit breaker restrikes are unwanted occurrence, which can ultimately lead to breaker. Before 2008, there was little evidence in the literature of monitoring techniques based on restrike measurement and interpretation produced during switching of capacitor banks and shunt reactor banks. In 2008 a non-intrusive radiometric restrike measurement method, as well a restrike hardware detection algorithm was developed. The limitations of the radiometric measurement method are a band limited frequency response as well as limitations in amplitude determination. Current detection methods and algorithms required the use of wide bandwidth current transformers and voltage dividers. A novel non-intrusive restrike diagnostic algorithm using ATP (Alternative Transient Program) and wavelet transforms is proposed. Wavelet transforms are the most common use in signal processing, which is divided into two tests, i.e. restrike detection and energy level based on deteriorated waveforms in different types of restrike. A ‘db5’ wavelet was selected in the tests as it gave a 97% correct diagnostic rate evaluated using a database of diagnostic signatures. This was also tested using restrike waveforms simulated under different network parameters which gave a 92% correct diagnostic responses. The diagnostic technique and methodology developed in this research can be applied to any power monitoring system with slight modification for restrike detection.

Social network and aesthetic reflexivity in the creative industries

This article reviews some key critical writing about the commodification or exploitation of networked social relations in the creative industries. Through a comparative case study of networks in fashion and new media industries in the city of Manchester, UK, the article draws attention to the social, cultural and aesthetic aspects of the networks among creative practitioners. It argues that within the increasing commercialisation in the creative industries there are networked spaces within which non-instrumental values are created. The building of social networks reflects on the issue of how creatives perceive their work in these industries both economically and socially/culturally.

Super-orbital re-entry in Australia : laboratory measurement, simulation and flight observation

There are large uncertainties in the aerothermodynamic modelling of super-orbital re-entry which impact the design of spacecraft thermal protection systems (TPS). Aspects of the thermal environment of super-orbital re-entry flows can be simulated in the laboratory using arc- and plasma jet facilities and these devices are regularly used for TPS certification work [5]. Another laboratory device which is capable of simulating certain critical features of both the aero and thermal environment of super-orbital re-entry is the expansion tube, and three such facilities have been operating at the University of Queensland in recent years[10]. Despite some success, wind tunnel tests do not achieve full simulation, however, a virtually complete physical simulation of particular re-entry conditions can be obtained from dedicated flight testing, and the Apollo era FIRE II flight experiment [2] is the premier example which still forms an important benchmark for modern simulations. Dedicated super-orbital flight testing is generally considered too expensive today, and there is a reluctance to incorporate substantial instrumentation for aerothermal diagnostics into existing missions since it may compromise primary mission objectives. An alternative approach to on-board flight measurements, with demonstrated success particularly in the ‘Stardust’ sample return mission, is remote observation of spectral emissions from the capsule and shock layer [8]. JAXA’s ‘Hayabusa’ sample return capsule provides a recent super-orbital reentry example through which we illustrate contributions in three areas: (1) physical simulation of super-orbital re-entry conditions in the laboratory; (2) computational simulation of such flows; and (3) remote acquisition of optical emissions from a super-orbital re entry event.

The sample complexity of pattern classification with neural networks: the size of the weights is more important than the size of the network

Sample complexity results from computational learning theory, when applied to neural network learning for pattern classification problems, suggest that for good generalization performance the number of training examples should grow at least linearly with the number of adjustable parameters in the network. Results in this paper show that if a large neural network is used for a pattern classification problem and the learning algorithm finds a network with small weights that has small squared error on the training patterns, then the generalization performance depends on the size of the weights rather than the number of weights. For example, consider a two-layer feedforward network of sigmoid units, in which the sum of the magnitudes of the weights associated with each unit is bounded by A and the input dimension is n. We show that the misclassification probability is no more than a certain error estimate (that is related to squared error on the training set) plus A3 √((log n)/m) (ignoring log A and log m factors), where m is the number of training patterns. This may explain the generalization performance of neural networks, particularly when the number of training examples is considerably smaller than the number of weights. It also supports heuristics (such as weight decay and early stopping) that attempt to keep the weights small during training. The proof techniques appear to be useful for the analysis of other pattern classifiers: when the input domain is a totally bounded metric space, we use the same approach to give upper bounds on misclassification probability for classifiers with decision boundaries that are far from the training examples.

Neural network learning:theoretical foundations

This important work describes recent theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistical and computational questions. Chapters survey research on pattern classification with binary-output networks, including a discussion of the relevance of the Vapnik Chervonenkis dimension, and of estimates of the dimension for several neural network models. In addition, Anthony and Bartlett develop a model of classification by real-output networks, and demonstrate the usefulness of classification with a "large margin." The authors explain the role of scale-sensitive versions of the Vapnik Chervonenkis dimension in large margin classification, and in real prediction. Key chapters also discuss the computational complexity of neural network learning, describing a variety of hardness results, and outlining two efficient, constructive learning algorithms. The book is self-contained and accessible to researchers and graduate students in computer science, engineering, and mathematics

Group maintenance scheduling : a case study for a pipeline network

This paper presents a group maintenance scheduling case study for a water distributed network. This water pipeline network presents the challenge of maintaining aging pipelines with the associated increases in annual maintenance costs. The case study focuses on developing an effective maintenance plan for the water utility. Current replacement planning is difficult as it needs to balance the replacement needs under limited budgets. A Maintenance Grouping Optimization (MGO) model based on a modified genetic algorithm was utilized to develop an optimum group maintenance schedule over a 20-year cycle. The adjacent geographical distribution of pipelines was used as a grouping criterion to control the searching space of the MGO model through a Judgment Matrix. Based on the optimum group maintenance schedule, the total cost was effectively reduced compared with the schedules without grouping maintenance jobs. This optimum result can be used as a guidance to optimize the current maintenance plan for the water utility.

Measurement and correlates of caregiver self-efficacy amongst family caregivers of persons with dementia living in Shanghai, China

Background: Caring for family members with dementia can be a long-term, burdensome task resulting in physical and emotional distress and impairment. Research has demonstrated significantly lower levels of selfefficacy among family caregivers of people with dementia (CGs) than caregivers of relatives with non-dementia diseases. Intervention studies have also suggested that the mental and physical health of dementia CGs could be improved through the enhancement of their self-efficacy. However, studies are limited in terms of the influences of caregiver self-efficacy on caregiver behaviour, subjective burden and health-related quality of life. Of particular note is that there are no studies on the applicability of caregiver self-efficacy in the social context of China. Objective: The purpose of this thesis was to undertake theoretical exploration using Bandura’s (1997) self-efficacy theory to 1) revise the Revised Caregiving Self-Efficacy Scale (C-RCSES) (Steffen, McKibbin, Zeiss, Gallagher-Thompson, & Bandura, 2002), and 2) explore determinants of caregiver self-efficacy and the role of caregiver self-efficacy and other conceptual constructs (including CGs’ socio-demographic characteristics, CRs’ impairment and CGs’ social support) in explaining and predicting caregiver behaviour, subjective burden and health-related quality of life among CGs in China. Methodology: Two studies were undertaken: a qualitative elicitation study with 10 CGs; and a cross-sectional survey with 196 CGs. In the first study, semi-structured interviews were conducted to explore caregiver behaviours and corresponding challenges for their performance. The findings of the study assisted in the development of the initial items and domains of the Chinese version of the Revised Caregiving Self-Efficacy Scale (C-RCSES). Following changes to items in the scale, the second study, a cross-sectional survey with 196 CGs was conducted to evaluate the psychometric properties of C-RCSES and to test a hypothesised self-efficacy model of family caregiving adapted from Bandura’s theory (1997). Results: 35 items were generated from the qualitative data. The content validity of the C-RCSES was assessed and ensured in Study One before being used for the cross-sectional survey. Eight items were removed and five subscales (caregiver self-efficacy for gathering information about treatment, symptoms and health care; obtaining support; responding to problematic behaviours; management of household, personal and medical care; and controlling upsetting thoughts about caregiving) were identified after principal component factor analysis on the cross-sectional survey data. The reliability of the scale is acceptable: the Cronbach’s alpha coefficients for the whole scale and for each subscale were all over .80; and the fourweek test-retest reliabilities for the whole scale and for each subscale ranged from .64 to .85. The concurrent, convergent and divergent validity were also acceptable. CGs reported moderate levels of caregiver self-efficacy. Furthermore, the level of self-efficacy for management of household, personal and medical care was relatively high in comparison to those of the other four domains of caregiver self-efficacy. Caregiver self-efficacy was also significantly influenced by CGs’ socio-demographic characteristics and the caregiving external factors (CR impairment and social support that CGs obtained). The level of caregiver behaviour that CGs reported was higher than that reported in other Chinese research. CGs’ socio-demographics significantly influenced caregiver behaviour, whereas caregiver self-efficacy did not influence caregiver behaviour. Regarding the two external factors, CGs who cared for highly impaired relatives reported high levels of caregiver behaviour, but social support did not influence caregiver behaviour. Regarding caregiver subjective burden and health-related quality of life, CGs reported moderate levels of subjective burden, and their level of healthrelated quality of life was significantly lower than that of the general population in China. The findings also indicated that CGs’ subjective burden and health-related quality of life were influenced by all major factors in the hypothesised model, including CGs’ socio-demographics, CRs’ impairment, social support that CGs obtained, caregiver self-efficacy and caregiver behaviour. Of these factors, caregiver self-efficacy and social support significantly improved their subjective burden and health-related quality of life; whereas caregiver behaviour and CRs’ impairment were detrimental to CGs, such as increasing subjective burden and worsening health-related quality of life. Conclusion: While requiring further exploration, the qualitative study was the first qualitative research conducted in China to provide an in-depth understanding of CGs’ caregiving experience, including their major caregiver behaviours and the corresponding challenges. Meanwhile, although the C-RCSES needs further psychometric testing, it is a useful tool for assessing caregiver self-efficacy in Chinese populations. Results of the qualitative and quantitative study provide useful information for future studies regarding the explanatory power of caregiver self-efficacy to caregiver behaviour, subjective burden and health-related quality of life. Additionally, integrated with Bandura’s theory, the findings from the quantitative study also suggested a further study exploring the role of outcome expectations in caregiver behaviour, subjective burden and healthrelated quality of life.

Measurement of total body water (TBW) and total energy expenditure (TEE) using stable isotopes

Understanding the relationship between diet, physical activity and health in humans requires accurate measurement of body composition and daily energy expenditure. Stable isotopes provide a means of measuring total body water and daily energy expenditure under free-living conditions. While the use of isotope ratio mass spectrometry (IRMS) for the analysis of 2H (Deuterium) and 18O (Oxygen-18) is well established in the field of human energy metabolism research, numerous questions remain regarding the factors which influence analytical and measurement error using this methodology. This thesis was comprised of four studies with the following emphases. The aim of Study 1 was to determine the analytical and measurement error of the IRMS with regard to sample handling under certain conditions. Study 2 involved the comparison of TEE (Total daily energy expenditure) using two commonly employed equations. Further, saliva and urine samples, collected at different times, were used to determine if clinically significant differences would occur. Study 3 was undertaken to determine the appropriate collection times for TBW estimates and derived body composition values. Finally, Study 4, a single case study to investigate if TEE measures are affected when the human condition changes due to altered exercise and water intake. The aim of Study 1 was to validate laboratory approaches to measure isotopic enrichment to ensure accurate (to international standards), precise (reproducibility of three replicate samples) and linear (isotope ratio was constant over the expected concentration range) results. This established the machine variability for the IRMS equipment in use at Queensland University for both TBW and TEE. Using either 0.4mL or 0.5mL sample volumes for both oxygen-18 and deuterium were statistically acceptable (p>0.05) and showed a within analytical variance of 5.8 Delta VSOW units for deuterium, 0.41 Delta VSOW units for oxygen-18. This variance was used as “within analytical noise” to determine sample deviations. It was also found that there was no influence of equilibration time on oxygen-18 or deuterium values when comparing the minimum (oxygen-18: 24hr; deuterium: 3 days) and maximum (oxygen-18: and deuterium: 14 days) equilibration times. With regard to preparation using the vacuum line, any order of preparation is suitable as the TEE values fall within 8% of each other regardless of preparation order. An 8% variation is acceptable for the TEE values due to biological and technical errors (Schoeller, 1988). However, for the automated line, deuterium must be assessed first followed by oxygen-18 as the automated machine line does not evacuate tubes but merely refills them with an injection of gas for a predetermined time. Any fractionation (which may occur for both isotopes), would cause a slight elevation in the values and hence a lower TEE. The purpose of the second and third study was to investigate the use of IRMS to measure the TEE and TBW of and to validate the current IRMS practices in use with regard to sample collection times of urine and saliva, the use of two TEE equations from different research centers and the body composition values derived from these TEE and TBW values. Following the collection of a fasting baseline urine and saliva sample, 10 people (8 women, 2 men) were dosed with a doubly labeled water does comprised of 1.25g 10% oxygen-18 and 0.1 g 100% deuterium/kg body weight. The samples were collected hourly for 12 hrs on the first day and then morning, midday, and evening samples were collected for the next 14 days. The samples were analyzed using an isotope ratio mass spectrometer. For the TBW, time to equilibration was determined using three commonly employed data analysis approaches. Isotopic equilibration was reached in 90% of the sample by hour 6, and in 100% of the sample by hour 7. With regard to the TBW estimations, the optimal time for urine collection was found to be between hours 4 and 10 as to where there was no significant difference between values. In contrast, statistically significant differences in TBW estimations were found between hours 1-3 and from 11-12 when compared with hours 4-10. Most of the individuals in this study were in equilibrium after 7 hours. The TEE equations of Prof Dale Scholler (Chicago, USA, IAEA) and Prof K.Westerterp were compared with that of Prof. Andrew Coward (Dunn Nutrition Centre). When comparing values derived from samples collected in the morning and evening there was no effect of time or equation on resulting TEE values. The fourth study was a pilot study (n=1) to test the variability in TEE as a result of manipulations in fluid consumption and level of physical activity; the magnitude of change which may be expected in a sedentary adult. Physical activity levels were manipulated by increasing the number of steps per day to mimic the increases that may result when a sedentary individual commences an activity program. The study was comprised of three sub-studies completed on the same individual over a period of 8 months. There were no significant changes in TBW across all studies, even though the elimination rates changed with the supplemented water intake and additional physical activity. The extra activity may not have sufficiently strenuous enough and the water intake high enough to cause a significant change in the TBW and hence the CO2 production and TEE values. The TEE values measured show good agreement based on the estimated values calculated on an RMR of 1455 kcal/day, a DIT of 10% of TEE and activity based on measured steps. The covariance values tracked when plotting the residuals were found to be representative of “well-behaved” data and are indicative of the analytical accuracy. The ratio and product plots were found to reflect the water turnover and CO2 production and thus could, with further investigation, be employed to identify the changes in physical activity.