Globally, cancer is the second leading cause of death and approximately 70% of the cancer deaths occur in low- and middle-income countries (LMICs). The death numbers are continuing to increase, which puts a tremendous burden on individuals and the healthcare system in LMICs. Workplace is an important channel for cancer prevention and control. Several high-income countries, such as the US and the UK, have established workplace health promotion programmes to address behaviour risk factors of cancer. These programmes have been successfully implemented, resulting in a significant improvement not only in behaviour changes of the employees, but also in the work-related outcomes, including economic returns of the employers. Based on the international experience and local assessment, our research will adapt existing evidence-based strategies and establish a scalable model for cancer prevention that can be widely applied in Chinese workplaces. A comprehensive workplace intervention package, which will address major behaviour risks of cancer for the employees, such as tobacco and alcohol use, unhealthy diet, obesity and lack of physical activity, will be developed, implemented and evaluated through a series of multilevel involvement strategies covering individual programmes, organizational policies and supportive environment and with the support of a tailored smartphone application. In this research, we will test the adaptability of the intervention package across various workplaces in diverse regions with different diets and lifestyles. We will select 15 workplaces with approximately 1500 employees from three cities located in the northern, central and southern provinces of China respectively - mostly in the economically underdeveloped areas. By full engagement of employers and employees in a staggered design with the intervention duration lasting for 1 year, 1.5 years and 2 years respectively, the research aims to achieve the individual behaviour changes in modifiable risk factors of cancer. In the long term, the research outcome will also be demonstrated by the reduction of occurrence of cancer and other major non-communicable diseases, such as stroke and heart attacks of employees, the productivities of the employees and their work performance, as well as the economic benefits of the employers. The comprehensive workplace intervention will bring enormous benefits to millions of Chinese workplace population and furthermore, will have a great potential to be adapted by many other LMICs with a similar situation of heavy cancer burden. The research will provide evidence and solutions to address the common challenges of these countries, particularly to overcome the barriers in intervention implementation. Ultimately, the research outcome will contribute to the attainment of the United Nations' Sustainable Development Goal 3.4 by reducing a great deal of premature mortality from cancers. The success of this research will lead to significant global health impact in a world with huge health and economic burden caused by cancer.
Quality-Diversity (QD) algorithms are a new branch of high performing search algorithm, the benefits of which make them especially relevant to video-game Procedural Content Generation (PCG). However, at time of writing there have been no studies contrasting and evaluating the performances of alternative QD algorithms within a PCG domain, a gap this project aims to address. Through comparative experimentation I aim to discover which QD algorithm is best able to generate diverse and high quality game content, and which factors are most important for optimising its performance. The project would first focus on the domain of generating Super Mario Bros levels and then extend to multiple different game PCG spaces. Successful completion of this work will substantially deepen understanding of this area, allowing the creation of more powerful and sophisticated content generation tools using QD algorithms.
Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at www.rcuk.ac.uk/StudentshipTerminology. Training grants may be to one organisation or to a consortia of research organisations. This portal will show the lead organisation only.
Irreversible tissue loss is a common feature in a large spectrum of health conditions (e.g. aging, trauma, cancer, degenerative diseases, ischemia, etc), placing huge burdens in patient relatives and health care systems. Therapies aiming to restore tissue function will have a great impact in the health and quality of life of millions of people worldwide. Regenerative medicine is an interdisciplinary endeavour to create functional tissues and organs, where cell biology, biochemistry, chemistry and material sciences are central components to address human tissues complexity. The approach comprises the use of biomaterials that temporarily substitute the extracellular matrix (ECM). However, current engineered biomaterials have not fully matched the diverse functionality of native tissues. Thus, fundamental research in biomaterials for regenerative medicine has great potential to provide smart solutions to current bottlenecks in this scientific area. In this project, biomaterials based on peptide self-assembly will be designed to take advantage of reversible supramolecular interactions, in order to create self-healing ECM substitutes. The dynamic nature of these materials will be addressed systematically in an attempt to copycat ECM turnover. So far, efforts from the materials scientific community have been mainly focused on controlling spatial and geometrical features. Perhaps it is time to start addressing consistently time variable controls in biomaterials design, and to pave the way to fully synchronise the biology and man-made materials’ “watches”. We expect that SynchroSelf will generate a new class of dynamic biomaterials that will enable scientists to study wound healing processes in vitro with unprecedented level of complexity and experimental control.