CREACAL will realise an unprecedented study of chemical reactions from the perspective of causation and lawhood, with the aim to establish a rigorous framework for the philosophical investigation of chemical reactions. Chemical reactions are fundamental to science and engineering as they identify the causes of the transformation of a specific set of chemical substances, while at the same time representing lawlike generalisations about transformations of types of chemical substances. However philosophers have neglected chemical reactions; they have not examined them either with respect to causation or with lawhood. This is a clear lacuna in the philosophical literature given that reactions are the main means with which scientists explain chemical transformation. CREACAL will synthesise these two fields to offer an account of laws and causation that not only does justice to the rich yet under-explored knowledge of reactions, but that also deepens our understanding of causation and laws themselves. CREACAL’s results will contribute to science by illuminating the intricate features of chemical reactions that are revealed by viewing them as causes and laws. Moreover, it will fill a significant gap in philosophy by introducing a new case study for the investigation of causation and lawhood, while also achieving genuine progress in philosophy of chemistry that will further consolidate the latter as an important field within philosophy.

Modern advanced and high value fuel cell systems are monitored by multiple embedded sensors which transmit a large amount of data every few seconds. Unfortunately, service engineers are still faced with the challenging task of identifying the causes of a failure by manually investigating not only the streaming sensor data but also a wide range of structured, semi-structured and unstructured monitoring data. At the same time, they are required to have a thorough knowledge of the full operating mechanism. Our overarching aim is to utilise next generation deep learning and knowledge technology paradigms (i.e. ontology-based systems, knowledge-graph based systems) to represent this monitoring knowledge in a human and machine processible form such that decision-making processes can be automated and deeper engineering insights can be obtained. To achieve this, we will implement a radically cross-disciplinary methodological approach, by developing new spatio-temporal knowledge representations and reasoning and instilling them with natural language processing techniques. This will result in a novel paradigm for truly intelligent cyber physical systems. The QuAre paradigm will be put to test and fine tuned on the diagnosis and prognosis of polymer electrolyte fuel cell systems. On the training side, this project is designed to instill the applicant with a niche set of core skills on question answering over knowledge graph embeddings, knowledge management retrieval, and natural language generation; these will position the researcher at the fore-front of intelligent knowledge representation and establish her as a leading researcher in the field of question answering. The project is further designed to provide the researcher with cutting edge teaching, leadership, and communication skills so that by the end of this project she will be ready to pursue her first permanent academic position.

The ability of the failing human heart to recover after mechanical unloading with left ventricular assist devices (LVADs) has been insufficiently exploited. To fill this void, we engineered the Pressure Unloading LVAD (PULVAD) system, designed to promote myocardial recovery. The overall objective of the proposed translational investigation is to evaluate the feasibility, safety and efficacy of this innovative pressure unloading approach as a bridge to recovery from heart failure. We will first investigate the effects of short-term PULVAD support on systemic hemodynamics and left ventricular mechanoenergetics in a large animal model of acute heart failure. We will then perform a pivotal randomized controlled study to investigate the safety and efficacy of long-term PULVAD support in promoting sustained cardiac recovery in a large animal model of chronic heart failure. If validated, this new technology has the potential to improve quality of life and ease the socioeconomic burden of advanced heart failure. In addition, histological, cellular and molecular analysis of paired myocardial biopsies obtained pre/post-PULVAD unloading will provide insight into mechanisms underlying cardiac reverse remodeling and myocardial recovery.