Aspects of cardiovascular risk in an Australian population study

Prevention of cardiovascular disease (CVD), a leading cause of death in men and women, is both a global and national public health priority. Prevention efforts have generally focused on well-known lifestyle (e.g., physical inactivity, unhealthy diet, smoking) and metabolic (e.g., overweight/obesity, hypertension, hyperlipidaemia) risk factors. It is also important for public health strategies to consider emerging risk factors, innovative approaches to risk factors, and evidence in middle-aged men and women, to develop effective prevention strategies. This thesis explored innovative aspects of cardiovascular risk in a large cohort of middle-aged and older Australian men and women (“the 45 and Up Study”) by examining: 1) emerging or lesser known risk factors such as raw vegetable intake (Chapter 3), sedentary behaviour (Chapter 4, Appendix 1) and psychological distress (Chapter 5); 2) the single versus joint influence of lifestyle risk factors on incident type 2 diabetes (Chapter 4, Appendix 1) and hypertension (Chapter 5); 3) potential gender differences (Chapters 3-5, Appendix 1), and female-specific behaviours such as breastfeeding (Chapters 6-7). Overall, findings support Australian recommendations for fruit and vegetable intake, physical activity, alcohol intake and infant breastfeeding. While the importance of reducing known risk factors for CVD prevention was evident, the role of raw vegetable intake, sedentary behaviour and psychological distress was inconclusive. Breastfeeding was associated with a lower maternal risk of CVD. Findings confirmed that adopting a cluster of healthy lifestyle behaviours can reduce CVD risk in the middle-aged and older population. Potential gender differences were explored and identified. This thesis contributes to the literature by exploring innovative aspects of cardiovascular risk that are relevant to middle-aged adults, particularly women, as well as informs health care providers, researchers and policy makers

EFL teachers’ perceptions of professional development activities and their effects in a non-anglosphere context

Providing teachers with adequate professional development (PD) is a central tenet to enhance education quality. In Vietnam, despite the blossoming of PD activities promoted over the past decade, the central question of how effectively these existing activities facilitate changes in teachers’ practice has been under-researched. This mixed-method study responded to the scarcity in understanding the effectiveness of PD activities in the Vietnamese setting by employing a questionnaire administered to 80 high school teachers and six semi-structured interviews. Evidence from the questionnaire and interviews revealed that EFL teachers participated in PD activities on an occasional basis. Institution-internal or in-house professional activities were most common, while joining a professional affiliation such as a TESOL association was the rarest. Also, PD activities have positively reinforced the teachers’ language proficiency, teaching practice, and planning practical lessons to meet students’ learning needs. The discussions and recommendations are made for enhancing the quality of PD activities

LusRegTes: A Regression Testing Tool for Lustre Programs

Lustre is a synchronous data-flow declarative language widely used for safety-critical applications (avionics, energy, transport...). In such applications, the testing activity for detecting errors of the system plays a crucial role. During the development and maintenance processes, Lustre programs are often evolving, so regression testing should be performed to detect bugs. In this paper, we present a tool for automatic regression testing of Lustre programs. We have defined an approach to generate test cases in regression testing of Lustre programs.  In this approach, a Lustre program is represented by an operator network, then the set of paths is identified and the path activation conditions are symbolically computed for each version. Regression test cases are generated by comparing paths between versions. The approach was implemented in a tool, called LusRegTes, in order to automate the test process for Lustre programs

A deep local and global scene-graph matching for image-text retrieval

Conventional approaches to image-text retrieval mainly focus on indexing visual objects appearing in pictures but ignore the interactions between these objects. Such objects' occurrences and interactions are equivalently useful and important in this field as they are usually mentioned in the text. Scene graph presentation is a suitable method for the image-text matching challenge and obtained good results due to its ability to capture the inter-relationship information. Both images and text are represented in scene graph levels and formulate the retrieval challenge as a scene graph matching challenge. In this paper, we introduce the Local and Global Scene Graph Matching (LGSGM) model that enhances the state-of-the-art method by integrating an extra graph convolution network to capture the general information of a graph. Specifically, for a pair of scene graphs of an image and its caption, two separate models are used to learn the features of each graph’s nodes and edges. Then a Siamese-structure graph convolution model is employed to embed graphs into vector forms. We finally combine the graph-level and the vector-level to calculate the similarity of this image text pair. The empirical experiments show that our enhancement with the combination of levels can improve the performance of the baseline method by increasing the recall by more than 10% on the Flickr30k dataset. Our implementation code can be found at https://github.com/m2man/LGSGM

Graph-based indexing and retrieval of lifelog data

Understanding the relationship between objects in an image is an important challenge because it can help to describe actions in the image. In this paper, a graphical data structure, named “Scene Graph”, is utilized to represent an encoded informative visual relationship graph for an image, which we suggest has a wide range of potential applications. This scene graph is applied and tested in the popular domain of lifelogs, and specifically in the challenge of known-item retrieval from lifelogs. In this work, every lifelog image is represented by a scene graph, and at retrieval time, this scene graph is compared with the semantic graph, parsed from a textual query. The result is combined with location or date information to determine the matching items. The experiment shows that this technique can outperform a conventional method

Quality of Water used at pig farms in the Red River delta

peer reviewedA research was carried out to evaluate water quality using at 12 different pig farms in Bac Ninh, Hung Yen and Hai Duong provinces. Water samples were taken in two periods from October to December 2006 and from March to April 2007. Physical and chemical parameters were analysed at the laboratory of the Department of Veterinary Parasitology-Inspection and Hygiene - Hanoi University of Agriculture. The results showed that, all water sources using the pig farms came from underground and a half of which was not processed. Contents of COD(H+), COD(OH-), CO2, Cl- in water in Hai Duong and Bac Ninh were exceeded the hygiene standard. Iron content in water in all three provinces was exceeded the hygiene standard. After using a processed system including artificial rain, H2O2 supplement and filter the content of DO, CO2 and Fe in the water reached the permitted hygiene standard

Performance of multi-hop cognitive MIMO relaying networks with joint constraint of intercept probability and limited interference

In this paper, we propose a multi-hop multiple input multiple output (MIMO) decode-and-forward relaying protocol in cognitive radio networks. In this protocol, a multi-antenna secondary source attempts to send its data to a multi-antenna secondary destination with assistance of multiple intermediate multi-antenna nodes, in presence of a multi-antenna secondary eavesdropper. A primary network includes a primary transmitter and a primary receiver which are equipped with multiple antennas, and use transmit antenna selection (TAS) and selection combining (SC) to communicate with each other. Operating on the underlay spectrum sharing method, the secondary source and relay nodes have to adjust their transmit power so that the outage performance of the primary network is not harmful and satisfy the quality of service (QoS). Moreover, these secondary nodes also reduce their transmit power so that the intercept probability (IP) at the eavesdropper at each hop is below a desired value. To improve the outage performance of the secondary network under the joint constraint of IP and limited interference, the TAS/SC method is employed to relay the source data hop-by-hop to the destination. We derived exact closed-form expressions of the end-to-end (e2e) outage probability (OP) and IP of the proposed protocol over Rayleigh fading channels. Monte Carlo simulations are then performed to verify the theoretical derivations