Management of heterogeneous UAVs through a capability framework of UAV’s functional autonomy

An increased interest in utilising groups of Unmanned Aerial Vehicles (UAVs) with heterogeneous capabilities and autonomy is presenting the challenge to effectively manage such during missions and operations. This has been the focus of research in recent years, moving from a traditional UAV management paradigm of n-to-1 (n operators for one UAV, with n being at least two operators) toward 1-to-n (one operator, multiple UAVs). This paper has expanded on the authors’ previous work on UAV functional capability framework, by incorporating the concept of Functional Level of Autonomy (F-LOA) with two configurations: The lower F-LOA configuration contains sufficient information for the operator to generate solutions and make decisions to address perturbation events. Alternatively, the higher F-LOA configuration presents information reflecting on the F-LOA of the UAV, allowing the operator to interpret solutions and decisions generated autonomously, and decide whether to veto from this decision.

Changes in profit as market conditions change : an historical study of a building firm

This paper analyses the profits from 221 construction projects undertaken by an Australian building firm in the period 1910–1938 and examines the factors that influence the firm's profit levels. This involves a series of multiple regression analyses with three dependent variables representing profit and 26 independent variables representing economic conditions and project characteristics. From these, 11 models are derived of which two are chosen as having the best explanatory power in explaining approximately 72% of the variability in profit levels movements. The results show that unemployment, interest rates, level of construction activity in the state, change of wage level, inflation rate of building material and project value significantly influenced the firm's profit level during the period.

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.

Effects of wireless sensor network uncertainties on output-only modal analysis employing merged data of multiple tests

The use of Wireless Sensor Networks (WSNs) for Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data synchronization error and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research verifying the applicability of those WSNs with respect to demanding SHM applications like modal analysis and damage identification. This paper first presents a brief review of the most inherent uncertainties of the SHM-oriented WSN platforms and then investigates their effects on outcomes and performance of the most robust Output-only Modal Analysis (OMA) techniques when employing merged data from multiple tests. The two OMA families selected for this investigation are Frequency Domain Decomposition (FDD) and Data-driven Stochastic Subspace Identification (SSI-data) due to the fact that they both have been widely applied in the past decade. Experimental accelerations collected by a wired sensory system on a large-scale laboratory bridge model are initially used as clean data before being contaminated by different data pollutants in sequential manner to simulate practical SHM-oriented WSN uncertainties. The results of this study show the robustness of FDD and the precautions needed for SSI-data family when dealing with SHM-WSN uncertainties. Finally, the use of the measurement channel projection for the time-domain OMA techniques and the preferred combination of the OMA techniques to cope with the SHM-WSN uncertainties is recommended.

Ureaplasma parvum multiple banded antigen (MBA) size variation - association with fetal inflammation in a sheep model (Published abstract)

Background: Ureaplasma species are the most prevalent isolates from women who deliver preterm. The MBA, a surface exposed lipoprotein, is a key virulence factor of ureaplasmas. We investigated MBA variation after chronic and acute intra-amniotic (IA) ureaplasma infections. Method: U. parvum serovar 3 (2x104 colony-forming-units) was injected IA into pregnant ewes at: 55 days gestation (d, term = 145d) (n=8); 117d (n=8) and 121d (n=8). Fetuses were delivered surgically (124d) and ureaplasmas cultured from amniotic fluid (AF), chorioamnion, fetal lung (FL) and umbilical cord were tested by western blot and PCR assays to demonstrate MBA and mba gene variation respectively. Tissue sections were sectioned and stained by haemotoxylin and eosin and inflammatory cell counts and pathology were reported (blinded to outcome). Results: Numerous MBA/mba variants were generated in vivo after chronic exposure to ureaplasma infection but after acute infection no variants (3d) or very few variants (7d) were generated. Identical MBA variants were detected within the AF and FL but different ureaplasma variants were detected within chorioamnion specimens. The severity of inflammation within chronically infected tissues varied between animals ranging from no inflammation to severe inflammation with/without fibrosis. Chorioamnion, FL and cord from the same animal demonstrated the same degree of inflammation. Conclusions: MBA/mba variation in vivo occurred after the initiation of the host immune response and we propose that ureaplasmas vary the MBA antigen to evade the host immune response. In some animals there was no inflammation despite colonisation with high numbers of ureaplasmas.

Sport biomechanics

Biomechanics involves research and analysis of the mechanisms of living organisms. This can be conducted on multiple levels and represents a continuum from the molecular, wherein biomaterials such as collagen and elastin are considered, to the tissue, organ and whole body level. Some simple applications of Newtonian mechanics can supply correct approximations on each level, but precise details demand the use of continuum mechanics. Sport biomechanics uses the scientific methods of mechanics to study the effects of forces on the sports performer and considers aspects of the behaviour of sports implements, equipment, footwear and surfaces. There are two main aims of sport biomechanics, that is, the reduction of injury and the improvement of performance (Bartlett, 1999). Aristotle (384-322 BC) wrote the first book on biomechanics, De Motu Animalium, translated as On the Movement of Animals. He saw animals' bodies as mechanical systems, but also pursued questions that might explain the physiological difference between imagining the performance of an action and actually doing it. Some simple examples of biomechanics research include the investigation of the forces that act on limbs, the aerodynamics of animals in flight, the hydrodynamics of objects moving through water and locomotion in general across all forms of life, from individual cells to whole organisms...

Ureaplasma parvum serovar 3 multiple banded antigen size variation after chronic intra-amniotic infection/colonization

Ureaplasma species are the microorganisms most frequently associated with adverse pregnancy outcomes. The multiple banded antigen (MBA), a surface-exposed lipoprotein, is a key virulence factor of ureaplasmas. The MBA demonstrates size variation, which we have shown previously to be correlated with the severity of chorioamnion inflammation. We aimed to investigate U. parvum serovar 3 pathogenesis in vivo, using a sheep model, by investigating: MBA variation after long term (chronic) and short term (acute) durations of in utero ureaplasma infections, and the severity of chorioamnionitis and inflammation in other fetal tissues. Inocula of 2x107 colony-forming-units (CFU) of U. parvum serovar 3 (Up) or media controls (C) were injected intra-amniotically into pregnant ewes at one of three time points: day 55 (69d Up, n=8; C69, n=4); day 117 (7d Up, n=8; C7, n=2); and day 121 (3d Up, n=8; C3, n=2) of gestation (term=145-150d). At day 124, preterm fetuses were delivered surgically. Samples of chorioamnion, fetal lung, and umbilical cord were: (i) snap frozen for subsequent ureaplasma culture, and (ii) fixed, embedded, sectioned and stained by haematoxylin and eosin stain for histological analysis. Selected fetal lung clinical ureaplasma isolates were cloned and filtered to obtain cultures from a single CFU. Passage 1 and clone 2 ureaplasma cultures were tested by western blot to demonstrate MBA variation. In acute durations of ureaplasma infection no MBA variants (3d Up) or very few MBA variants (7d Up) were present when compared to the original inoculum. However, numerous MBA size variants were generated in vivo (alike within contiguous tissues, amniotic fluid and fetal lung, but different variants were present within chorioamnion), during chronic, 69d exposure to ureaplasma infection. For the first time we have shown that the degree of ureaplasma MBA variation in vivo increased with the duration of gestation.

Sunlight and other determinants of circulating 25-hydroxyvitamin D levels in black and white participants in a nationwide U.S. study

Circulating 25-hydroxyvitamin D (25(OH)D), a marker for vitamin D status, is associated with bone health and possibly cancers and other diseases; yet, the determinants of 25(OH)D status, particularly ultraviolet radiation (UVR) exposure, are poorly understood. Determinants of 25(OH)D were analyzed in a subcohort of 1,500 participants of the US Radiologic Technologists (USRT) Study that included whites (n 842), blacks (n 646), and people of other races/ethnicities (n 12). Participants were recruited monthly (20082009) across age, sex, race, and ambient UVR level groups. Questionnaires addressing UVR and other exposures were generally completed within 9 days of blood collection. The relation between potential determinants and 25(OH)D levels was examined through regression analysis in a random two-thirds sample and validated in the remaining one third. In the regression model for the full study population, age, race, body mass index, some seasons, hours outdoors being physically active, and vitamin D supplement use were associated with 25(OH)D levels. In whites, generally, the same factors were explanatory. In blacks, only age and vitamin D supplement use predicted 25(OH)D concentrations. In the full population, determinants accounted for 25 of circulating 25(OH)D variability, with similar correlations for subgroups. Despite detailed data on UVR and other factors near the time of blood collection, the ability to explain 25(OH)D was modest.

Ureaplasma species multiple banded antigen (MBA) variation is associated with the severity of chorioamnionitis in late preterm placentas

Background: Intra-amniotic infection accounts for 30% of all preterm births (PTB), with the human Ureaplasma species being the most frequently identified microorganism from the placentas of women who deliver preterm. The highest prevalence of PTB occurs late preterm (32-36 weeks) but no studies have investigated the role of infectious aetiologies associated with late preterm birth. Method: Placentas from women with late PTB were dissected aseptically and samples of chorioamnion tissue and membrane swabs were collected. These were tested for Ureaplasma spp. and aerobic/anaerobic bacteria by culture and real-time PCR. Western blot was used to assess MBA variation in ureaplasma clinical isolates. The presence of microorganisms was correlated with histological chorioamnionitis. Results: Ureaplasma spp. were isolated from 33/466 (7%) of placentas by culture or PCR. The presence of ureaplasmas, but not other microorganisms, was associated with histological chorioamnionitis (21/33 ureaplasma-positive vs. 8/42 other bacteria; p= 0.001). Ureaplasma clinical isolates demonstrating no MBA variation were associated with histological chorioamnionitis. By contrast, ureaplasmas displaying MBA variation were isolated from placentas with no significant histological chorioamnionitis (p= 0.001). Conclusion: Ureaplasma spp. within placentas delivered late preterm (7%) is associated with histological chorioamnionitis (p = 0.001). Decreased inflammation within chorioamnion was observed when the clinical ureaplasma isolates demonstrated variation of their surface-exposed lipoproteins (MBA). This variation may be a mechanism by which ureaplasmas modulate and evade the host immune response. So whilst ureaplasmas are present intra-amniotically they are not suspected because of the normal macroscopic appearance of the placentas and the amniotic fluid.

A multivariate approach to bidding strategies

A multivariate approach to bidding strategy is presented in comparison with previous standard approaches. An optimal formulation is derived and a method of parameter estimation proposed. A case study illustrates the derivation of optimal and other strategic mark up values against a single bidder. Concluding remarks concern extensions to multiple competitors differing levels of information, and sensitivity analysis.

Intracellular trafficking and secretion of inflammatory cytokines

The secretion of cytokines by immune cells plays a significant role in determining the course of an inflammatory response. The levels and timing of each cytokine released are critical for mounting an effective but confined response, whereas excessive or dysregulated inflammation contributes to many diseases. Cytokines are both culprits and targets for effective treatments in some diseases. The multiple points and mechanisms that have evolved for cellular control of cytokine secretion highlight the potency of these mediators and the fine tuning required to manage inflammation. Cytokine production in cells is regulated by cell signaling, and at mRNA and protein synthesis levels. Thereafter, the intracellular transport pathways and molecular trafficking machinery have intricate and essential roles in dictating the release and activity of cytokines. The trafficking machinery and secretory (exocytic) pathways are complex and highly regulated in many cells, involving specialized membranes, molecules and organelles that enable these cells to deliver cytokines to often-distinct areas of the cell surface, in a timely manner. This review provides an overview of secretory pathways - both conventional and unconventional - and key families of trafficking machinery. The prevailing knowledge about the trafficking and secretion of a number of individual cytokines is also summarized. In conclusion, we present emerging concepts about the functional plasticity of secretory pathways and their modulation for controlling cytokines and inflammation.

Estimating the effects of ambient temperature on mortality : methodological challenges and proposed solutions

The health impacts of exposure to ambient temperature have been drawing increasing attention from the environmental health research community, government, society, industries, and the public. Case-crossover and time series models are most commonly used to examine the effects of ambient temperature on mortality. However, some key methodological issues remain to be addressed. For example, few studies have used spatiotemporal models to assess the effects of spatial temperatures on mortality. Few studies have used a case-crossover design to examine the delayed (distributed lag) and non-linear relationship between temperature and mortality. Also, little evidence is available on the effects of temperature changes on mortality, and on differences in heat-related mortality over time. This thesis aimed to address the following research questions: 1. How to combine case-crossover design and distributed lag non-linear models? 2. Is there any significant difference in effect estimates between time series and spatiotemporal models? 3. How to assess the effects of temperature changes between neighbouring days on mortality? 4. Is there any change in temperature effects on mortality over time? To combine the case-crossover design and distributed lag non-linear model, datasets including deaths, and weather conditions (minimum temperature, mean temperature, maximum temperature, and relative humidity), and air pollution were acquired from Tianjin China, for the years 2005 to 2007. I demonstrated how to combine the case-crossover design with a distributed lag non-linear model. This allows the case-crossover design to estimate the non-linear and delayed effects of temperature whilst controlling for seasonality. There was consistent U-shaped relationship between temperature and mortality. Cold effects were delayed by 3 days, and persisted for 10 days. Hot effects were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. It is still unclear whether spatiotemporal models using spatial temperature exposure produce better estimates of mortality risk compared with time series models that use a single site’s temperature or averaged temperature from a network of sites. Daily mortality data were obtained from 163 locations across Brisbane city, Australia from 2000 to 2004. Ordinary kriging was used to interpolate spatial temperatures across the city based on 19 monitoring sites. A spatiotemporal model was used to examine the impact of spatial temperature on mortality. A time series model was used to assess the effects of single site’s temperature, and averaged temperature from 3 monitoring sites on mortality. Squared Pearson scaled residuals were used to check the model fit. The results of this study show that even though spatiotemporal models gave a better model fit than time series models, spatiotemporal and time series models gave similar effect estimates. Time series analyses using temperature recorded from a single monitoring site or average temperature of multiple sites were equally good at estimating the association between temperature and mortality as compared with a spatiotemporal model. A time series Poisson regression model was used to estimate the association between temperature change and mortality in summer in Brisbane, Australia during 1996–2004 and Los Angeles, United States during 1987–2000. Temperature change was calculated by the current day's mean temperature minus the previous day's mean. In Brisbane, a drop of more than 3 �C in temperature between days was associated with relative risks (RRs) of 1.16 (95% confidence interval (CI): 1.02, 1.31) for non-external mortality (NEM), 1.19 (95% CI: 1.00, 1.41) for NEM in females, and 1.44 (95% CI: 1.10, 1.89) for NEM aged 65.74 years. An increase of more than 3 �C was associated with RRs of 1.35 (95% CI: 1.03, 1.77) for cardiovascular mortality and 1.67 (95% CI: 1.15, 2.43) for people aged < 65 years. In Los Angeles, only a drop of more than 3 �C was significantly associated with RRs of 1.13 (95% CI: 1.05, 1.22) for total NEM, 1.25 (95% CI: 1.13, 1.39) for cardiovascular mortality, and 1.25 (95% CI: 1.14, 1.39) for people aged . 75 years. In both cities, there were joint effects of temperature change and mean temperature on NEM. A change in temperature of more than 3 �C, whether positive or negative, has an adverse impact on mortality even after controlling for mean temperature. I examined the variation in the effects of high temperatures on elderly mortality (age . 75 years) by year, city and region for 83 large US cities between 1987 and 2000. High temperature days were defined as two or more consecutive days with temperatures above the 90th percentile for each city during each warm season (May 1 to September 30). The mortality risk for high temperatures was decomposed into: a "main effect" due to high temperatures using a distributed lag non-linear function, and an "added effect" due to consecutive high temperature days. I pooled yearly effects across regions and overall effects at both regional and national levels. The effects of high temperature (both main and added effects) on elderly mortality varied greatly by year, city and region. The years with higher heat-related mortality were often followed by those with relatively lower mortality. Understanding this variability in the effects of high temperatures is important for the development of heat-warning systems. In conclusion, this thesis makes contribution in several aspects. Case-crossover design was combined with distribute lag non-linear model to assess the effects of temperature on mortality in Tianjin. This makes the case-crossover design flexibly estimate the non-linear and delayed effects of temperature. Both extreme cold and high temperatures increased the risk of mortality in Tianjin. Time series model using single site’s temperature or averaged temperature from some sites can be used to examine the effects of temperature on mortality. Temperature change (no matter significant temperature drop or great temperature increase) increases the risk of mortality. The high temperature effect on mortality is highly variable from year to year.

Supporting the development of inclusive products : the effects of everyday ambient illumination levels and contrast on older adults' near visual acuity

Current older adult capability data-sets fail to account for the effects of everyday environmental conditions on capability. This article details a study that investigates the effects of everyday ambient illumination conditions (overcast, 6000 lx; in-house lighting, 150 lx and street lighting, 7.5 lx) and contrast (90%, 70%, 50% and 30%) on the near visual acuity (VA) of older adults (n= 38, 65-87 years). VA was measured at a 1-m viewing distance using logarithm of minimum angle of resolution (LogMAR) acuity charts. Results from the study showed that for all contrast levels tested, VA decreased by 0.2 log units between the overcast and street lighting conditions. On average, in overcast conditions, participants could detect detail around 1.6 times smaller on the LogMAR charts compared with street lighting. VA also significantly decreased when contrast was reduced from 70% to 50%, and from 50% to 30% in each of the ambient illumination conditions. Practitioner summary: This article presents an experimental study that investigates the impact of everyday ambient illumination levels and contrast on older adults' VA. Results show that both factors have a significant effect on their VA. Findings suggest that environmental conditions need to be accounted for in older adult capability data-sets/designs.