Telomerase activity : detection and clinical implications in human cancer

Telomerase is an extremely important enzyme required for the immortalisation of tumour cells. Because the gene is activated in the vast majority of tumour tissues and remains unused in most somatic cells, it represents a marker with huge diagnostic, prognostic and treatment implications in cancer. This article summarises the basic structure and functions of telomerase and considers its clinical implications in colorectal and other cancers.

Detection of dynamic primary user with cooperative spectrum sensing

In this paper we demonstrate that existing cooperative spectrum sensing formulated for static primary users cannot accurately detect dynamic primary users regardless of the information fusion method. Performance error occurs as the sensing parameters calculated by the conventional detector result in sensing performance that violates the sensing requirements. Furthermore, the error is accumulated and compounded by the number of cooperating nodes. To address this limitation, we design and implement the duty cycle detection model for the context of cooperative spectrum sensing to accurately calculate the sensing parameters that satisfy the sensing requirements. We show that longer sensing duration is required to compensate for dynamic primary user traffic.

Modelling total duration of traffic incidents including incident detection and recovery time

Traffic incidents are key contributors to non-recurrent congestion, potentially generating significant delay. Factors that influence the duration of incidents are important to understand so that effective mitigation strategies can be implemented. To identify and quantify the effects of influential factors, a methodology for studying total incident duration based on historical data from an ‘integrated database’ is proposed. Incident duration models are developed using a selected freeway segment in the Southeast Queensland, Australia network. The models include incident detection and recovery time as components of incident duration. A hazard-based duration modelling approach is applied to model incident duration as a function of a variety of factors that influence traffic incident duration. Parametric accelerated failure time survival models are developed to capture heterogeneity as a function of explanatory variables, with both fixed and random parameters specifications. The analysis reveals that factors affecting incident duration include incident characteristics (severity, type, injury, medical requirements, etc.), infrastructure characteristics (roadway shoulder availability), time of day, and traffic characteristics. The results indicate that event type durations are uniquely different, thus requiring different responses to effectively clear them. Furthermore, the results highlight the presence of unobserved incident duration heterogeneity as captured by the random parameter models, suggesting that additional factors need to be considered in future modelling efforts.

Succession law keeping pace with changes in technology and community expectations – informal wills

Purpose - The purpose of this paper is to provide insights into recent developments in the way the law of succession allows people to use new technologies to document their testamentary intentions in an informal way. Design/methodology/approach – This article considers one area in which the law has arguably kept good pace with advances in society’s expectations and technological change – the law of succession. This article examines the legislative reforms in Queensland and other jurisdictions permitting the recognition of informal wills and the decided cases in the area. In particular, the article examines the decision in a Queensland Supreme Court case in which the court recognised the validity of a will made on an iPhone. Research limitations/implications – This is a doctrinal analysis, not an empirical study, and accordingly is limited to providing details specific to the legislation and the court cases selected.

Community arts in early childhood

Community arts can take many forms, including murals, installations, festivals and performances. The work can be produced by artists solely, by artists working with community groups, or by community groups. Community arts can be on a grand-scale covering whole streets, parks or even towns, or small- scale, such as a mosaic in the corner of a play area. It can be extremely impacting and a permanent fixture, or fragile and small and designed to blow away in the wind. But, common to all these different forms of community arts are the criteria that community arts are made in, for and/or by, the local community.

Outbreak detection algorithms for seasonal disease data : a case study using Ross River virus disease

Background Detection of outbreaks is an important part of disease surveillance. Although many algorithms have been designed for detecting outbreaks, few have been specifically assessed against diseases that have distinct seasonal incidence patterns, such as those caused by vector-borne pathogens. Methods We applied five previously reported outbreak detection algorithms to Ross River virus (RRV) disease data (1991-2007) for the four local government areas (LGAs) of Brisbane, Emerald, Redland and Townsville in Queensland, Australia. The methods used were the Early Aberration Reporting System (EARS) C1, C2 and C3 methods, negative binomial cusum (NBC), historical limits method (HLM), Poisson outbreak detection (POD) method and the purely temporal SaTScan analysis. Seasonally-adjusted variants of the NBC and SaTScan methods were developed. Some of the algorithms were applied using a range of parameter values, resulting in 17 variants of the five algorithms. Results The 9,188 RRV disease notifications that occurred in the four selected regions over the study period showed marked seasonality, which adversely affected the performance of some of the outbreak detection algorithms. Most of the methods examined were able to detect the same major events. The exception was the seasonally-adjusted NBC methods that detected an excess of short signals. The NBC, POD and temporal SaTScan algorithms were the only methods that consistently had high true positive rates and low false positive and false negative rates across the four study areas. The timeliness of outbreak signals generated by each method was also compared but there was no consistency across outbreaks and LGAs. Conclusions This study has highlighted several issues associated with applying outbreak detection algorithms to seasonal disease data. In lieu of a true gold standard, a quantitative comparison is difficult and caution should be taken when interpreting the true positives, false positives, sensitivity and specificity.

Systematic Review Protocol : "Are community-based interventions effective in identifying and responding to emerging zoonotic infectious diseases?"

Review question/objective The objective of this review is to identify the effectiveness of surveillance systems and community-based interventions in identifying and responding to emerging and re-emerging zoonotic infections in Southeast Asia (SE Asia). More specifically the research questions are: 1. What is the effectiveness of community-based surveillance interventions designed to identify emerging zoonotic infectious diseases? 2. What is the effectiveness of non-pharmaceutical community-based interventions designed to prevent transmission of emerging zoonotic infectious diseases? 3. How do factors related to the emergence and management of emerging zoonotic infectious diseases impact the effectiveness of interventions designed to identify and respond to them?

Collaborative extension of biodiversity monitoring protocols in the bird watching community

Citizen science projects have demonstrated the advantages of people with limited relevant prior knowledge participating in research. However, there is a difference between engaging the general public in a scientific project and entering an established expert community to conduct research. This paper describes our ongoing acoustic biodiversity monitoring collaborations with the bird watching community. We report on findings gathered over six years from participation in bird walks, observing conservation efforts, and records of personal activities of experienced birders. We offer an empirical study into extending existing protocols through in-context collaborative design involving scientists and domain experts.

Topic dependent language modelling for spoken term detection

This paper investigates the effect of topic dependent language models (TDLM) on phonetic spoken term detection (STD) using dynamic match lattice spotting (DMLS). Phonetic STD consists of two steps: indexing and search. The accuracy of indexing audio segments into phone sequences using phone recognition methods directly affects the accuracy of the final STD system. If the topic of a document in known, recognizing the spoken words and indexing them to an intermediate representation is an easier task and consequently, detecting a search word in it will be more accurate and robust. In this paper, we propose the use of TDLMs in the indexing stage to improve the accuracy of STD in situations where the topic of the audio document is known in advance. It is shown that using TDLMs instead of the traditional general language model (GLM) improves STD performance according to figure of merit (FOM) criteria.

Submission to the Legal Affairs and Community Safety Committee Youth Justice and Other Legislation Amendment Bill

This submission addresses the Youth Justice and Other Legislation Amendment Bill 2014 the objectives of which are to: 1. Permit repeat offenders’ identifying information to be published and open the Children’s Court for youth justice matters involving repeat offenders; 2. Create a new offence where a child commits a further offence while on bail; 3. Permit childhood findings of guilt for which no conviction was recorded to be admissible in court when sentencing a person for an adult offence; 4. Provide for the automatic transfer from detention to adult corrective services facilities of 17 year olds who have six months or more left to serve in detention; 5. Provide that, in sentencing any adult or child for an offence punishable by imprisonment, the court must not have regard to any principle, whether under statute or at law, that a sentence of imprisonment (in the case of an adult) or detention (in the case of a child) should only be imposed as a last resort; 6. Allow children who have absconded from Sentenced Youth Boot Camps to be arrested and brought before a court for resentencing without first being given a warning; and 7. Make a technical amendment to the Youth Justice Act 1992.

Building a community of learners within the STEM higher education classroom

Building rich and authentic learning experiences in the STEM classroom, is a challenge for many educators within Higher Education. While many Higher Education Institutions have embraced the need to transform current teaching and learning practices and include a range of online tools, this has often been met with some resistance and approaches that do not always recognise the academic who are a critical component to the success of the transformational process. Over the last decade the Internet has evolved from being a tool used by a few dedicated educators to one that is being used by the majority of educators. However, what is important is how this great resource is used in teaching and learning to allow students to build knowledge. The ability for students to construct knowledge and engage in higher order thinking skills is at the heart of educational practices, and building a community of learners has the potential to support these practices, especially within STEM education. This paper explores the relationship between students and an academic teaching in a technology rich STEM learning environment and their adoption of social community and shared tools. In particular the paper reports on the critical components that make a successful community of learners and the educational tools and approaches that were successfully used to enhance the student learning experience in a STEM classroom.

Impact of community pharmacist intervention discussing patients’ beliefs to improve medication adherence

Background Adherence to evidence based medicines in patients who have experienced a myocardial infarction remains low. Individual’s beliefs towards their medicines are a strong predictor of adherence and may influence other factors that impact on adherence. Objective To investigate if community pharmacists discussing patients’ beliefs about their medicines improved medication adherence at 12 months post myocardial infarction. Setting This study included 200 patients discharged from a public teaching hospital in Queensland, Australia, following a myocardial infarction. Patients were randomised into intervention (n = 100) and control groups (n = 100) and followed for 12 months. Method All patients were interviewed between 5 to 6 weeks, at 6 and 12 months post discharge by the researcher using the repertory grid technique. This technique was used to elicit the patient’s individualised beliefs about their medicines for their myocardial infarction. In the intervention group, patients’ beliefs about their medicines were communicated by the researcher to their community pharmacist. The pharmacist used this information to tailor their discussion with the patient about their medication beliefs at designated time points (3 and 6 months post discharge). The control group was provided with usual care. Main outcome measure The difference in non-adherence measured using a medication possession ratio between the intervention and control groups at 12 months post myocardial infarction. Results There were 137 patients remaining in the study (intervention group n = 72, control group n = 65) at 12 months. In the intervention group 29 % (n = 20) of patients were non-adherent compared to 25 % (n = 16) of patients in control group. Conclusion Discussing patients’ beliefs about their medicines for their myocardial infarction did not improve medication adherence. Further research on patients beliefs should focus on targeting non-adherent patients whose reasons for their non-adherence is driven by their medication beliefs.

Community engagement for disaster resilience : flood risk management in Jakarta, Indonesia

Understanding dynamics of interactions between community groups and government agencies is crucial to improve community resilience for flood risk reduction through effective community engagement strategies. Overall, a variety of approaches are available, however they are limited in their application. Based on research of a case study in Kampung Melayu Village in Jakarta, further complexity in engaging community emerges in planning policy which requires the relocation of households living in floodplains. This complexity arises in decision-making processes due to barriers to communication. This obstacle highlights the need for a simplified approach for an effective flood risk management which will be further explored in this paper. Qualitative analyses will be undertaken following semi-structured interviews conducted with key actors within government agencies, non-governmental organisations (NGOs), and representatives of communities. The analyses involve investigation of barriers and constraints on community engagement in flood risk management, particularly relevant to collaboration mechanism, perception of risk, and technical literacy to flood risk. These analyses result in potential redirection of community consultation strategies to lead to a more effective collaboration among stakeholders in the decision-making processes. As a result, greater effectiveness in plan implementation of flood risk management potentially improves disaster resilience in the future.

Surviving the electronic panopticon: New lessons in democracy, surveillance, and community in young adult fiction

The ability of new information and communication technologies to pierce previously impenetrable physical, personal, and social boundaries has particular relevance to contemporary society and young people as there is now more information that can be collected, accessed, and distributed about individuals and groups. The ability to know about each other has become a central feature of many young people’s lives. The need to know is further complicated by other questions – Who knows? What do they know? What are the implications of this knowledge?. These questions are a consequence of society having become more mobile and networked enabling increased surveillance, tracking, and spreading of dis/information. With the acceleration of new pervasive and immersive technologies, these questions have taken on a new urgency and significance that go beyond an Orwellian Big Brother scenario. This chapter extends Foucault’s notion of the panopticon to take account of the challenges of an AmI environment of smart networked devices. By drawing on examples of recent young adult fiction, I examine some of the ways in which these texts invite their readers to reflect and speculate on the uneasy relationship between surveillance and democracy and what this means for individual rights and freedom, and a sense of place and belonging.

Unusual event detection in crowded scenes

Novel computer vision techniques have been developed to automatically detect unusual events in crowded scenes from video feeds of surveillance cameras. The research is useful in the design of the next generation intelligent video surveillance systems. Two major contributions are the construction of a novel machine learning model for multiple instance learning through compressive sensing, and the design of novel feature descriptors in the compressed video domain.