Examining the impact of climate change on dengue transmission in the Asia-Pacific region

Dengue fever (DF) is a serious public health concern in many parts of the world. An increase in DF incidence has been observed globally over the past decades. Multiple factors including urbanisation, increased international travels and global climate change are thought to be responsible for increased DF. However, little research has been conducted in the Asia-Pacific region about the impact of these changes on dengue transmission. The overarching aim of this thesis is to explore the spatiotemporal pattern of DF transmission in the Asia-Pacific region and project the future risk of DF attributable to climate change. Annual data of DF outbreaks for sixteen countries in the Asia-Pacific region over the last fifty years were used in this study. The results show that the geographic range of DF in this region increased significantly over the study period. Thailand, Vietnam and Laos were identified as the highest risk areas and there was a southward expansion observed in the transmission pattern of DF which might have originated from Philippines or Thailand. Additionally, the detailed DF data were obtained and the space-time clustering of DF transmission was examined in Bangladesh. Monthly DF data were used for the entire country at the district level during 2000-2009. Dhaka district was identified as the most likely DF cluster in Bangladesh and several districts of the southern part of Bangladesh were identified as secondary clusters in the years 2000-2002. In order to examine the association between meteorological factors and DF transmission and to project the future risk of DF using different climate change scenarios, the climate-DF relationship was examined in Dhaka, Bangladesh. The results show that climate variability (particularly maximum temperature and relative humidity) was positively associated with DF transmission in Dhaka. The effects of climate variability were observed at a lag of four months which might help to potentially control and prevent DF outbreaks through effective vector management and community education. Based on the quantitative assessment of the climate-DF relationship, projected climate change will likely increase mosquito abundance and activity and DF in this area. Assuming a temperature increase of 3.3oC without any adaptation measures and significant changes in socio-economic conditions, the consequence will be devastating, with a projected annual increase of 16,030 cases in Dhaka, Bangladesh by the end of this century. Therefore, public health authorities need to be prepared for likely increase of DF transmission in this region. This study adds to the literature on the recent trends of DF and impacts of climate change on DF transmission. These findings may have significant public health implications for the control and prevention of DF, particularly in the Asia- Pacific region.

Teacher Evidence Matrix : an evaluation using multiple lines of evidence

Welcome to the Teacher evidence matrix. This matrix is designed for highly qualified discipline experts to evaluate their teaching in a systematic manner. The primary purpose of the Teacher evidence matrix is to provide a tool that an academic staff member at university can annually review their teaching. The annual review will result in you being ready for performance, planning and review; promotion; awards; or employment application. This tool is designed for individual use and will lead to an action plan for implementation.

Networked identity work as project development among co-creative communities

Networked identity work is the conscious negotiation or co-creation of identity, enacted by speaking and listening across differences among multiple publics, including those real and imagined, familiar and unknown, on and offline, present and future. It is a concept I explore extensively in research with queer Digital Storytellers who share their personal stories in public places to catalyse social change (Vivienne 2013). In this article I consider distinctions between ‘story’ and ‘identity’; ‘networking’ and ‘networked identity work’ and argue that the two concepts may be usefully employed in development of co-creative community projects. Finally I consider how variable definitions of co-creativity influence project development.

A coordinated voltage control approach for coordination of OLTC, voltage regulator and DG to regulate voltage in a distribution feeder

Integration of small-scale electricity generators, known as Distributed Generation (DG), into the distribution networks has become increasingly popular at the present. This tendency together with the falling price of synchronous-type generator has potential to give the DG a better chance in participating in the voltage regulation process together with other devices already available in the system. The voltage control issue turns out to be a very challenging problem for the distribution engineers since existing control coordination schemes would need to be reconsidered to take into account the DG operation. In this paper, we propose a control coordination technique, which is able to utilize the ability of the DG as a voltage regulator, and at the same time minimizes interaction with other active devices, such as On-load Tap Changing Transformer (OLTC) and voltage regulator. The technique has been developed based on the concept of control zone, Line Drop Compensation (LDC), as well as the choice of controller's parameters. Simulations carried out on an Australian system show that the technique is suitable and flexible for any system with multiple regulating devices including DG.

Towards bio-inspired place recognition over multiple spatial scales

This paper presents a new multi-scale place recognition system inspired by the recent discovery of overlapping, multi-scale spatial maps stored in the rodent brain. By training a set of Support Vector Machines to recognize places at varying levels of spatial specificity, we are able to validate spatially specific place recognition hypotheses against broader place recognition hypotheses without sacrificing localization accuracy. We evaluate the system in a range of experiments using cameras mounted on a motorbike and a human in two different environments. At 100% precision, the multiscale approach results in a 56% average improvement in recall rate across both datasets. We analyse the results and then discuss future work that may lead to improvements in both robotic mapping and our understanding of sensory processing and encoding in the mammalian brain.

A recommendation approach dealing with multiple market segments

A new community and communication type of social networks - online dating - are gaining momentum. With many people joining in the dating network, users become overwhelmed by choices for an ideal partner. A solution to this problem is providing users with partners recommendation based on their interests and activities. Traditional recommendation methods ignore the users’ needs and provide recommendations equally to all users. In this paper, we propose a recommendation approach that employs different recommendation strategies to different groups of members. A segmentation method using the Gaussian Mixture Model (GMM) is proposed to customize users’ needs. Then a targeted recommendation strategy is applied to each identified segment. Empirical results show that the proposed approach outperforms several existing recommendation methods.

Slicing big data - Twitter, gambling and time sensitive information

Big Data presents many challenges related to volume, whether one is interested in studying past datasets or, even more problematically, attempting to work with live streams of data. The most obvious challenge, in a ‘noisy’ environment such as contemporary social media, is to collect the pertinent information; be that information for a specific study, tweets which can inform emergency services or other responders to an ongoing crisis, or give an advantage to those involved in prediction markets. Often, such a process is iterative, with keywords and hashtags changing with the passage of time, and both collection and analytic methodologies need to be continually adapted to respond to this changing information. While many of the data sets collected and analyzed are preformed, that is they are built around a particular keyword, hashtag, or set of authors, they still contain a large volume of information, much of which is unnecessary for the current purpose and/or potentially useful for future projects. Accordingly, this panel considers methods for separating and combining data to optimize big data research and report findings to stakeholders. The first paper considers possible coding mechanisms for incoming tweets during a crisis, taking a large stream of incoming tweets and selecting which of those need to be immediately placed in front of responders, for manual filtering and possible action. The paper suggests two solutions for this, content analysis and user profiling. In the former case, aspects of the tweet are assigned a score to assess its likely relationship to the topic at hand, and the urgency of the information, whilst the latter attempts to identify those users who are either serving as amplifiers of information or are known as an authoritative source. Through these techniques, the information contained in a large dataset could be filtered down to match the expected capacity of emergency responders, and knowledge as to the core keywords or hashtags relating to the current event is constantly refined for future data collection. The second paper is also concerned with identifying significant tweets, but in this case tweets relevant to particular prediction market; tennis betting. As increasing numbers of professional sports men and women create Twitter accounts to communicate with their fans, information is being shared regarding injuries, form and emotions which have the potential to impact on future results. As has already been demonstrated with leading US sports, such information is extremely valuable. Tennis, as with American Football (NFL) and Baseball (MLB) has paid subscription services which manually filter incoming news sources, including tweets, for information valuable to gamblers, gambling operators, and fantasy sports players. However, whilst such services are still niche operations, much of the value of information is lost by the time it reaches one of these services. The paper thus considers how information could be filtered from twitter user lists and hash tag or keyword monitoring, assessing the value of the source, information, and the prediction markets to which it may relate. The third paper examines methods for collecting Twitter data and following changes in an ongoing, dynamic social movement, such as the Occupy Wall Street movement. It involves the development of technical infrastructure to collect and make the tweets available for exploration and analysis. A strategy to respond to changes in the social movement is also required or the resulting tweets will only reflect the discussions and strategies the movement used at the time the keyword list is created — in a way, keyword creation is part strategy and part art. In this paper we describe strategies for the creation of a social media archive, specifically tweets related to the Occupy Wall Street movement, and methods for continuing to adapt data collection strategies as the movement’s presence in Twitter changes over time. We also discuss the opportunities and methods to extract data smaller slices of data from an archive of social media data to support a multitude of research projects in multiple fields of study. The common theme amongst these papers is that of constructing a data set, filtering it for a specific purpose, and then using the resulting information to aid in future data collection. The intention is that through the papers presented, and subsequent discussion, the panel will inform the wider research community not only on the objectives and limitations of data collection, live analytics, and filtering, but also on current and in-development methodologies that could be adopted by those working with such datasets, and how such approaches could be customized depending on the project stakeholders.

Scrub typhus in mainland China, 2006–2012 : the need for targeted public health interventions

Scrub typhus is a vector-borne disease carried by the chigger mite. The aetiological agent is the rickettsia Orientia tsutsugamushi, which is endemic to several countries in the Asia-Pacific region, including China [1]. It is also a travel-associated disease [2] and of great importance among military personnel [3], [4]. During the Second World War, scrub typhus was associated with a higher case fatality ratio than any other infectious disease in the China-Burma-India theatre of operations 1,3. Clinical presentation in patients varies from asymptomatic to life-threatening disease [5], including acute hearing loss and multiple organ failure [6], [7]. To date, there is still no effective and reliable human vaccine against scrub typhus and no point-of-care diagnostics available [1].

Self-efficacy partially mediates between social support and health-related quality of life in family caregivers for dementia patients in Shanghai

Background: There is a paucity of research assessing health-related quality of life (HRQoL) and self-efficacy in caregivers of relatives with dementia in mainland China. Aims: To compare the level of HRQoL between caregivers and the general population in mainland China and to assess the role of caregiver self-efficacy in the relationship between caregiver social support and HRQoL. Methods: A cross-sectional study was conducted in Shanghai, China. The caregivers were recruited from the outpatient department of a teaching hospital. A total of 195 participants were interviewed, using a survey package including the Chinese version of the 36-Item Short-Form Health Survey (SF-36), demographic data, the variables associated with the impairments of care recipients, perceived social support and caregiver self-efficacy. The caregivers' SF-36 scores were compared with those of the general population in China. Results: The results indicated that the HRQoL of the caregivers was poorer compared with that of the general population when matched for age and gender. Multiple regression analyses revealed that caregiver self-efficacy is a partial mediator between social support and HRQoL, and a partial mediator between behavioral and psychological symptoms of dementia (BPSD) and caregiver mental health. Conclusion: Assisting with managing BPSD and enhancing caregiver self-efficacy can be considered integral parts of interventions to improve caregiver HRQoL.

Business Innovation and Disruption in Publishing

This is the first volume in a book series examining how organizations in the creative industries respond to disruptive change and how they themselves generate business innovations. The aspiration of this book series is to understand some of the common forces behind the disruptions occurring in so many creative industries today and identifying the most promising strategies and responses by organizations to create new value propositions, business models and business practices that can enable these industry participants to cope with and eventually thrive as their industries and sectors are transformed. The chapters included in the volume examine the processes of disruption and transformation due to the technology of the Internet, social forces driven by social media, the development of new portable digital devices with greater capabilities and smaller size, the decreasing costs of new information, and the creation of new business models and forms of intellectual property ownership rights for a digitized industry. The context for this volume is the publishing industries, understood as the industries for the publishing of fiction and non-fiction books, academic literature, consumer as well as trade magazines, and daily newspapers. This volume includes chapters by an internationally diverse array of media scholars whose chapters provide insights into these phenomena in Eastern Europe, Finland, France, Germany, Norway, Portugal, Russia, and the United States, using different methodological frameworks including, but not limited to, surveys, in-depth interviews and multiple-case studies. One gap that this book series seeks to fill is that between the study of business innovation and disruption by innovation scholars largely based in business school settings and similar studies by scholarly experts from non-business school disciplines, including the broader social sciences (e.g. sociology, political science, economic geography) and creative industry based professional school disciplines (e.g. architecture, communications, design, film making, journalism, media studies, performing arts, photography and television). Future volumes of this book series will examine disruption and business innovation in the film, video and photography sectors (volume two), the music sector (volume three) and interactive entertainment (volume four), with subsequent volumes focusing on the most relevant developments in creative industry business innovation and disruption that emerge.

Volcanic architecture and chemostratigraphy within the Kalkarindji Continental Flood Basalt Province, Northern Territory : implications for eruption style from multiple fissure eruptions

This thesis was the first to define individual lava flow chemical variation and a detailed definition of the Kalkarindji Continental Flood Basalt Province, a lesser known province of the Phanerozoic eon. This thesis conducted an intensive field study that yielded numerous samples for petrography and chemical analyses as well as the generation of a detailed map of a portion of the Kalkarindji province.

Selective combination of visual and thermal imaging for resilient localization in adverse conditions : day and night, smoke and fire

Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.

Sensor Data Integrity : Multi-Sensor Perception for Unmanned Ground Vehicles

This document describes large, accurately calibrated and time-synchronised datasets, gathered in controlled environmental conditions, using an unmanned ground vehicle equipped with a wide variety of sensors. These sensors include: multiple laser scanners, a millimetre wave radar scanner, a colour camera and an infra-red camera. Full details of the sensors are given, as well as the calibration parameters needed to locate them with respect to each other and to the platform. This report also specifies the format and content of the data, and the conditions in which the data have been gathered. The data collection was made in two different situations of the vehicle: static and dynamic. The static tests consisted of sensing a fixed ’reference’ terrain, containing simple known objects, from a motionless vehicle. For the dynamic tests, data were acquired from a moving vehicle in various environments, mainly rural, including an open area, a semi-urban zone and a natural area with different types of vegetation. For both categories, data have been gathered in controlled environmental conditions, which included the presence of dust, smoke and rain. Most of the environments involved were static, except for a few specific datasets which involve the presence of a walking pedestrian. Finally, this document presents illustrations of the effects of adverse environmental conditions on sensor data, as a first step towards reliability and integrity in autonomous perceptual systems.

Progesterone activates multiple innate immune pathways inChlamydia trachomatis-Infected endocervical cells

Problem Susceptibility to Chlamydia trachomatis infection is increased by oral con- traceptives and modulated by sex hormones. We therefore sought to determine the effects of female sex hormones on the innate immune response to C. trachomatis infection. Method of study ECC-1 endometrial cells, pre-treated with oestradiol or progesterone, were infected with C. trachomatis and the host transcriptome analysed by Illumina Sentrix HumanRef-8 microarray. Primary endocervical epithe- lial cells, prepared at either the proliferative or secretory phase of the menstrual cycle, were infected with C. trachomatis and cytokine gene expression determined by quantitative RT-PCR analysis. Results Chlamydia trachomatis yield from progesterone-primed ECC-1 cells was significantly reduced compared with oestradiol-treated cells. Genes upregulated in progesterone-treated and Chlamydia-infected cells only included multiple CC and CXC chemokines, IL-17C, IL-29, IL-32, TNF-a, DEFB4B, LCN2, S100A7-9, ITGAM, NOD2, JAK1, IL-6ST, type I and II interferon receptors, numerous interferon-stimulated genes and STAT6. CXCL10, CXCL11, CX3CL1 and IL-17C, which were also upregu- lated in infected secretory-stage primary cells, and there was a trend towards higher levels of immune mediators in infected secretory-phase compared with proliferative-phase cells. Conclusion Progesterone treatment primes multiple innate immune pathways in hormone-responsive epithelial cells that could potentially increase resis- tance to chlamydial infection.

T helper cell cytokine profiles following endurance exercise

Endurance exercise can cause immunosuppression and increase the risk of upper respiratory illness. The present study examined changes in the secretion of T helper (Th) cell cytokines after endurance exercise. Ten highly trained road cyclists [mean±SEM: age 24.2±1.7 years; height 1.82±0.02 m; body mass 73.8±2.0 kg; peak oxygen uptake 65.9±2.3 mL/(kg•min)] performed 2 h of cycling exercise at 90% of the second ventilatory threshold. Peripheral blood mononuclear cells were isolated and stimulated with phytohemagglutinin. Plasma cortisol concentrations and the concentration of Th1/Th2/Th17 cell cytokines were examined. Data were analyzed using both traditional statistics and magnitude-based inferences. Results revealed a significant decrease in plasma cortisol at 4–24 h postexercise compared with pre-exercise values. Qualitative analysis revealed postexercise changes in concentrations of plasma cortisol, IL-2, TNF, IL-4, IL-6, IL-10, and IL-17A compared with pre-exercise values. A Th1/Th2 shift was evident immediately postexercise. Furthermore, for multiple cytokines, including IL-2 and TNF (Th1), IL-6 and IL-10 (Th2), and IL-17 (Th17), no meaningful change in concentration occurred until more than 4 h postexercise, highlighting the duration of exercise-induced changes in immune function. These results demonstrate the importance of considering “clinically” significant versus statistically significant changes in immune cell function after exercise.