Calculate excess mortality during heatwaves using Hilbert-Huang transform algorithm

Background Heatwaves could cause the population excess death numbers to be ranged from tens to thousands within a couple of weeks in a local area. An excess mortality due to a special event (e.g., a heatwave or an epidemic outbreak) is estimated by subtracting the mortality figure under ‘normal’ conditions from the historical daily mortality records. The calculation of the excess mortality is a scientific challenge because of the stochastic temporal pattern of the daily mortality data which is characterised by (a) the long-term changing mean levels (i.e., non-stationarity); (b) the non-linear temperature-mortality association. The Hilbert-Huang Transform (HHT) algorithm is a novel method originally developed for analysing the non-linear and non-stationary time series data in the field of signal processing, however, it has not been applied in public health research. This paper aimed to demonstrate the applicability and strength of the HHT algorithm in analysing health data. Methods Special R functions were developed to implement the HHT algorithm to decompose the daily mortality time series into trend and non-trend components in terms of the underlying physical mechanism. The excess mortality is calculated directly from the resulting non-trend component series. Results The Brisbane (Queensland, Australia) and the Chicago (United States) daily mortality time series data were utilized for calculating the excess mortality associated with heatwaves. The HHT algorithm estimated 62 excess deaths related to the February 2004 Brisbane heatwave. To calculate the excess mortality associated with the July 1995 Chicago heatwave, the HHT algorithm needed to handle the mode mixing issue. The HHT algorithm estimated 510 excess deaths for the 1995 Chicago heatwave event. To exemplify potential applications, the HHT decomposition results were used as the input data for a subsequent regression analysis, using the Brisbane data, to investigate the association between excess mortality and different risk factors. Conclusions The HHT algorithm is a novel and powerful analytical tool in time series data analysis. It has a real potential to have a wide range of applications in public health research because of its ability to decompose a nonlinear and non-stationary time series into trend and non-trend components consistently and efficiently.

Institutional determinants of growth-aspiration entrepreneurship

The thesis is a country-level study on the institutional and human capital determinants of growth-aspiration entrepreneurial activity. By using country-level panel-data analysis, the study is to our knowledge the first to test to what extent country-level human capital accumulation is associated with the prevalence of growth-aspiration entrepreneurship. Overall findings of the study suggest that there are different effects of the institutional determinants on the prevalence of growth-aspiration entrepreneurship in developing countries and developed countries. The study also found that country-level human capital moderates the effects of the institutional environment.

A hypothesis test using bias-adjusted AR estimators for classifying time series in small samples

A new test of hypothesis for classifying stationary time series based on the bias-adjusted estimators of the fitted autoregressive model is proposed. It is shown theoretically that the proposed test has desirable properties. Simulation results show that when time series are short, the size and power estimates of the proposed test are reasonably good, and thus this test is reliable in discriminating between short-length time series. As the length of the time series increases, the performance of the proposed test improves, but the benefit of bias-adjustment reduces. The proposed hypothesis test is applied to two real data sets: the annual real GDP per capita of six European countries, and quarterly real GDP per capita of five European countries. The application results demonstrate that the proposed test displays reasonably good performance in classifying relatively short time series.

Polarization of forecast densities : a new approach to time series classification

Time series classification has been extensively explored in many fields of study. Most methods are based on the historical or current information extracted from data. However, if interest is in a specific future time period, methods that directly relate to forecasts of time series are much more appropriate. An approach to time series classification is proposed based on a polarization measure of forecast densities of time series. By fitting autoregressive models, forecast replicates of each time series are obtained via the bias-corrected bootstrap, and a stationarity correction is considered when necessary. Kernel estimators are then employed to approximate forecast densities, and discrepancies of forecast densities of pairs of time series are estimated by a polarization measure, which evaluates the extent to which two densities overlap. Following the distributional properties of the polarization measure, a discriminant rule and a clustering method are proposed to conduct the supervised and unsupervised classification, respectively. The proposed methodology is applied to both simulated and real data sets, and the results show desirable properties.

The effect of the histological properties of tumors on transfection efficiency of electrically assisted gene delivery to solid tumors in mice

Uniform DNA distribution in tumors is a prerequisite step for high transfection efficiency in solid tumors. To improve the transfection efficiency of electrically assisted gene delivery to solid tumors in vivo, we explored how tumor histological properties affected transfection efficiency. In four different tumor types (B16F1, EAT, SA-1 and LPB), proteoglycan and collagen content was morphometrically analyzed, and cell size and cell density were determined in paraffin-embedded tumor sections under a transmission microscope. To demonstrate the influence of the histological properties of solid tumors on electrically assisted gene delivery, the correlation between histological properties and transfection efficiency with regard to the time interval between DNA injection and electroporation was determined. Our data demonstrate that soft tumors with larger spherical cells, low proteoglycan and collagen content, and low cell density are more effectively transfected (B16F1 and EAT) than rigid tumors with high proteoglycan and collagen content, small spindle-shaped cells and high cell density (LPB and SA-1). Furthermore, an optimal time interval for increased transfection exists only in soft tumors, this being in the range of 5-15 min. Therefore, knowledge about the histology of tumors is important in planning electrogene therapy with respect to the time interval between DNA injection and electroporation.

Pteridine-, thymidine-, choline- and imidazole-derived alkaloids from the Australian ascidian, Leptoclinides durus

Four new acylated pteridine alkaloids, duramidines A-D, two new acylated thymidine alkaloids, leptoclinidines A and B, two new 1-acylglyceryl-3-(O- carboxyhydroxymethylcholine) alkaloids, durabetaines A and B, three new 1,3-dimethyl-5-methylsulfanylimidazole alkaloids, leptoclinidamines D-F, and the known alkaloids leptoclinidamines B and C and 6-bromo-1H-indolo-3-yl-oxoacetic acid methyl ester were isolated from the Australian ascidian Leptoclinides durus. The duramidines are the first pteridine alkaloids, possessing a three carbon side chain esterified at C-1′ with a 4-hydroxy-2′- methoxycinnamic acid, and are either hydroxylated or sulfated at C-2′. The leptoclinidines are the first 3′-indole-3-carboxylic acid ester derivatives of thymidine to be reported in the literature. The durabetaines are the first glyceryl-3-(O-carboxyhydroxymethylcholine) alkaloids to be reported from an animal source and are also the only known derivatives from this class to be acylated with aromatic carboxylic acids. MS and NMR data analysis established the structures of the new compounds. All compounds were shown to be inactive when tested for cytotoxic activity against prostate (LNCaP) and breast (MDA-MB-231) cancer cell lines and antimicrobial activity against Pseudomonas aeruginosa and Staphylococcus aureus.

Development of gas sensing technology for ground and airborne applications powered by solar energy : methodology and experimental results

Monitoring gases for environmental, industrial and agricultural fields is a demanding task that requires long periods of observation, large quantity of sensors, data management, high temporal and spatial resolution, long term stability, recalibration procedures, computational resources, and energy availability. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) are currently representing the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialised gas sensing systems, and offer the possibility of geo-located and time stamp samples. However, these technologies are not fully functional for scientific and commercial applications as their development and availability is limited by a number of factors: the cost of sensors required to cover large areas, their stability over long periods, their power consumption, and the weight of the system to be used on small UAVs. Energy availability is a serious challenge when WSN are deployed in remote areas with difficult access to the grid, while small UAVs are limited by the energy in their reservoir tank or batteries. Another important challenge is the management of data produced by the sensor nodes, requiring large amount of resources to be stored, analysed and displayed after long periods of operation. In response to these challenges, this research proposes the following solutions aiming to improve the availability and development of these technologies for gas sensing monitoring: first, the integration of WSNs and UAVs for environmental gas sensing in order to monitor large volumes at ground and aerial levels with a minimum of sensor nodes for an effective 3D monitoring; second, the use of solar energy as a main power source to allow continuous monitoring; and lastly, the creation of a data management platform to store, analyse and share the information with operators and external users. The principal outcomes of this research are the creation of a gas sensing system suitable for monitoring any kind of gas, which has been installed and tested on CH4 and CO2 in a sensor network (WSN) and on a UAV. The use of the same gas sensing system in a WSN and a UAV reduces significantly the complexity and cost of the application as it allows: a) the standardisation of the signal acquisition and data processing, thereby reducing the required computational resources; b) the standardisation of calibration and operational procedures, reducing systematic errors and complexity; c) the reduction of the weight and energy consumption, leading to an improved power management and weight balance in the case of UAVs; d) the simplification of the sensor node architecture, which is easily replicated in all the nodes. I evaluated two different sensor modules by laboratory, bench, and field tests: a non-dispersive infrared module (NDIR) and a metal-oxide resistive nano-sensor module (MOX nano-sensor). The tests revealed advantages and disadvantages of the two modules when used for static nodes at the ground level and mobile nodes on-board a UAV. Commercial NDIR modules for CO2 have been successfully tested and evaluated in the WSN and on board of the UAV. Their advantage is the precision and stability, but their application is limited to a few gases. The advantages of the MOX nano-sensors are the small size, low weight, low power consumption and their sensitivity to a broad range of gases. However, selectivity is still a concern that needs to be addressed with further studies. An electronic board to interface sensors in a large range of resistivity was successfully designed, created and adapted to operate on ground nodes and on-board UAV. The WSN and UAV created were powered with solar energy in order to facilitate outdoor deployment, data collection and continuous monitoring over large and remote volumes. The gas sensing, solar power, transmission and data management systems of the WSN and UAV were fully evaluated by laboratory, bench and field testing. The methodology created to design, developed, integrate and test these systems was extensively described and experimentally validated. The sampling and transmission capabilities of the WSN and UAV were successfully tested in an emulated mission involving the detection and measurement of CO2 concentrations in a field coming from a contaminant source; the data collected during the mission was transmitted in real time to a central node for data analysis and 3D mapping of the target gas. The major outcome of this research is the accomplishment of the first flight mission, never reported before in the literature, of a solar powered UAV equipped with a CO2 sensing system in conjunction with a network of ground sensor nodes for an effective 3D monitoring of the target gas. A data management platform was created using an external internet server, which manages, stores, and shares the data collected in two web pages, showing statistics and static graph images for internal and external users as requested. The system was bench tested with real data produced by the sensor nodes and the architecture of the platform was widely described and illustrated in order to provide guidance and support on how to replicate the system. In conclusion, the overall results of the project provide guidance on how to create a gas sensing system integrating WSNs and UAVs, how to power the system with solar energy and manage the data produced by the sensor nodes. This system can be used in a wide range of outdoor applications, especially in agriculture, bushfires, mining studies, zoology, and botanical studies opening the way to an ubiquitous low cost environmental monitoring, which may help to decrease our carbon footprint and to improve the health of the planet.

Technology, Natural Resources and Economic Growth: Improving the Environment for a Greener Future

Description Through a combination of global data analysis and focused country level analysis, this timely book provides answers to the most pertinent country and industry specific questions defining the current relationship between technology, natural resources and economic growth. Contents Contents: Preface Part I: Global Analysis 1. Economic Growth and the Environment 2. Energy Substitution and Carbon Dioxide Emissions 3. Pollution, Natural Resources, and Economic Growth 4. Trade Openness and Environmental Quality 5. Environmental Productivity 6. Energy Price-induced Technological Change 7. Trade-induced Technological Change 8. Regional Economic Integration Part II: Country-Level Analysis 9. Emissions Trading in the United States 10. Increasing Returns to Pollution Abatement in the United States 11. Policy-induced Competitiveness in the United States 12. Trade Liberalization, Technology, and the Environment 13. Policy Implementation and its Effectiveness in China 14. Clean Technological Inventions in Japan 15. Intervention of Economic Policy and its Nonlinear Effects in Japan 16. The Next Emerging Giants: India and Africa 17. Conclusion Index Further information Through a combination of global data analysis and focused country level analysis, this timely book provides answers to the most pertinent country and industry specific questions defining the current relationship between technology, natural resources and economic growth. Shunsuke Managi takes a distinctive approach by focusing on the design and implementation of environmental regulations that encourage technological progress and, in doing so, looks at ways to ensure productivity improvements in the face of increasingly stringent environmental regulations and natural resource depletion. The findings in this important book demonstrate how successful environmental policies can contribute to efficiency by encouraging, rather than inhibiting, technological innovation. Technology, Natural Resources and Economic Growth will provide a valuable resource for a wide readership including postgraduate students, researchers, academics and policy makers working in the fields of environmental and ecological economics.

Isolation, structure determination and cytotoxicity studies of tryptophan alkaloids from an Australian marine sponge Hyrtios sp

Mass-guided fractionation of the MeOH extract from a specimen of the Australian marine sponge Hyrtios sp. resulted in the isolation of two new tryptophan alkaloids, 6-oxofascaplysin (2), and secofascaplysic acid (3), in addition to the known metabolites fascaplysin (1) and reticulatate (4). The structures of all molecules were determined following NMR and MS data analysis. Structural ambiguities in 2 were addressed through comparison of experimental and DFT-generated theoretical NMR spectral values. Compounds 1–4 were evaluated for their cytotoxicity against a prostate cancer cell line (LNCaP) and were shown to display IC50 values ranging from 0.54 to 44.9 μM.

Untangling the evidence : introducing an empirical model for evidence-based library and information practice

Introduction This research is the first to investigate the experiences of teacher-librarians as evidence-based practice. An empirically derived model is presented in this paper. Method This qualitative study utilised the expanded critical incident approach, and investigated the real-life experiences of fifteen Australian teacher-librarians, through semi-structured interviews and inductive data analysis. Data collection utilised semi-structured interviews, on-site observations, journaling and the rubric for contextual information. These approaches allowed each of the interviewees to tell their own story and provided richness to the data. Analysis The analysis involved two types of data categorisation: binary and thematic. Binary classification was used to identify factual details. Thematic analysis involved categorising the emerging themes. Results An empirically derived model for evidence-based practice was devised and associated critical findings identified. The results demonstrate that evidence-based practice for teacher-librarians is a holistic practice. It is not a linear, step-by-step process. Conclusions This study is significant for teacher-librarians and library and information professionals as it provides new understanding of evidence-based practice.

Evaluation of assessment in the context of work-based learning: Qualitative perspectives of new graduates

Aim Evaluation or assessment of competence is an important step to ensure the safety and efficacy of health professionals, including dietitians. Most competency-based assessment studies are focussed on valid and reliable methods of assessment for the preparation of entry-level dietitians, few papers have explored student dietitians’ perceptions of these evaluations. This study aimed to explore the perceptions of recent graduates from accredited nutrition and dietetics training programs in Australia. It also aimed to establish the relevance of competency-based assessment to adequately prepare them for entry-level work roles. Methods A purposive sample of newly-graduated dietitians with a range of assessment experiences and varied employment areas was recruited. A qualitative approach, using in-depth interviews with 13 graduates, with differing assessment experiences was undertaken. Graduates were asked to reflect upon their competency-based assessment experiences whilst a student. Data was thematically analysed by multiple authors. Results Four themes emerged from the data analysis: (i) Transparency and consistency are critical elements of work-based competency assessment. (ii) Students are willing to take greater responsibility in their assessment process. (iii) Work-based competency assessment prepares students for employment. (iv) The relationship between students and their assessors can impact on the student experience and their assessment performance. Conclusions Understanding this unique perspective of students can improve evaluation of future health professionals and assist in designing valid competency-based assessment approaches.

Theoretical frameworks to support research of health service innovation

Health service managers and policy makers are increasingly concerned about the sustainability of innovations implemented in health care settings. The increasing demand on health services requires that innovations are both effective and sustainable however research in this field is limited with multiple disciplines, approaches and paradigms influencing the field. These variations prevent a cohesive approach and therefore the accumulation of research findings in development of a body of knowledge. A theoretical framework serves to guide research, determine variables, influence data analysis and is central to the quest for ongoing knowledge development. If left unaddressed, health services research will continue in an ad hoc manner preventing full utilisation of outcomes, recommendations and knowledge for effective provision of health services. The purpose of this paper is to provide an integrative review of the literature and introduce a theoretical framework for health services innovation sustainability research based on integration and synthesis of the literature. Finally recommendations for operationalising and testing this theory will be presented.