St. Columba, Silnán, and the 'Male Bovine' (VC 2.17)

At Vita Columbae VC 2.17, Adomnán has severely misunderstood a written source which originally described how Columba ordered one party to a dispute, an alleged maleficus ‘evil-doer’ called Silnán, to milk a sick cow in order to settle the dispute by demonstrating that its contaminated milk was the real, hidden cause of the harm which had occasioned the dispute. Adomnán misread a description of a bos maculosus ‘pock-marked bovine’ to refer to a bos masculus ‘male bovine’, and proceeded to misunderstand the story as the description of some form of contest between Columba and a maleficus ‘sorcerer’.

The Barretstown experience

The thesis was prompted by a simple clinical observation. Seriously ill children returning from Barretstown Holiday Camp appeared changed. Barretstown ‘magic’ confuses the issue but indicates real and clinically evident transformations. The project sought to understand the experience and place it in a recognisable framework. The data was collected by interviews, observations as camp Paediatrician, memberships of the Child Advisory Committee and the Association’s criteria assessment team, participation in volunteer training and visits to international camps. The research presents evidence that the concepts of rite of passage, graceful mimesis and salutogenesis clarify operative social processes. The passage stages of separation, transition and reaggregation can be identified. Passage rites reorder personal and social upsets to fresh arrangements that facilitate change. Interviews confirm the reordering impact of achievements in play activities. These are challenging experiences closely guided by their Masters of Ceremonies – the Caras. The Cara/camper relationship is crucial and compatible with Girard’s theory of external mimesis. Visits to four camps confirm an inspirational process in contrast to a reported camp with a predetermined formative influence. Charismatic Caras/Councillors inspire playful mimesis and salutogenic transformations. Health is more than correction of pathogenic deficits and restoration of homeostasis. Salutogenic health promotes heterostasis – a desire for optimal experiences underpinned by a sense of coherence and adequate resources. Some evidence is presented that children have an improved sense of coherence after camp, which enables them to cope better with the demands of ill health. The camps enable sick children to up regulate risk taking towards more heterostatic experiences rather than down regulate their expectations. The heterostatic impulse can explain the disability paradox of good quality of life in the presence of severe disability. The salutogenic power of Barretstown can trump the pathogenic effects of childhood cancer and other serious illnesses.

Neonatal EEG classification using atomic decomposition

The electroencephalogram (EEG) is an important noninvasive tool used in the neonatal intensive care unit (NICU) for the neurologic evaluation of the sick newborn infant. It provides an excellent assessment of at-risk newborns and formulates a prognosis for long-term neurologic outcome.The automated analysis of neonatal EEG data in the NICU can provide valuable information to the clinician facilitating medical intervention. The aim of this thesis is to develop a system for automatic classification of neonatal EEG which can be mainly divided into two parts: (1) classification of neonatal EEG seizure from nonseizure, and (2) classifying neonatal background EEG into several grades based on the severity of the injury using atomic decomposition. Atomic decomposition techniques use redundant time-frequency dictionaries for sparse signal representations or approximations. The first novel contribution of this thesis is the development of a novel time-frequency dictionary coherent with the neonatal EEG seizure states. This dictionary was able to track the time-varying nature of the EEG signal. It was shown that by using atomic decomposition and the proposed novel dictionary, the neonatal EEG transition from nonseizure to seizure states could be detected efficiently. The second novel contribution of this thesis is the development of a neonatal seizure detection algorithm using several time-frequency features from the proposed novel dictionary. It was shown that the time-frequency features obtained from the atoms in the novel dictionary improved the seizure detection accuracy when compared to that obtained from the raw EEG signal. With the assistance of a supervised multiclass SVM classifier and several timefrequency features, several methods to automatically grade EEG were explored. In summary, the novel techniques proposed in this thesis contribute to the application of advanced signal processing techniques for automatic assessment of neonatal EEG recordings.