971 research outputs found

    Multidisciplinary perspectives on Artificial Intelligence and the law

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    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    Modern meat: the next generation of meat from cells

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    Modern Meat is the first textbook on cultivated meat, with contributions from over 100 experts within the cultivated meat community. The Sections of Modern Meat comprise 5 broad categories of cultivated meat: Context, Impact, Science, Society, and World. The 19 chapters of Modern Meat, spread across these 5 sections, provide detailed entries on cultivated meat. They extensively tour a range of topics including the impact of cultivated meat on humans and animals, the bioprocess of cultivated meat production, how cultivated meat may become a food option in Space and on Mars, and how cultivated meat may impact the economy, culture, and tradition of Asia

    Biomaterials for Bone Tissue Engineering 2020

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    This book presents recent advances in the field of bone tissue engineering, including molecular insights, innovative biomaterials with regenerative properties (e.g., osteoinduction and osteoconduction), and physical stimuli to enhance bone regeneration

    Multimodal assessment of neonatal pain

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    Pain assessment is critical to prevent suffering and harm in infants admitted to the neonatal care unit. As pain is a subjective experience, its assessment in nonverbal infants relies on surrogate measures. Current infant pain assessment tools that are based on behaviour and autonomic nervous system measurements lack face validity — they are unlikely to reflect pain in all its dimensions. In recent years, EEG-derived measures of pain have been developed in late preterm and term infants. Multimodal tools which include these cerebral measurements are conceptually more appropriate to measure pain. Yet, their use is still limited to specific research applications. This thesis focuses on outstanding questions that need to be addressed in order to advance the development of multimodal pain assessment tools that incorporate cerebral measurements. In the first part of this thesis, I focus on the characterisation of preterm infants’ noxious-evoked responses and their development. Across several modalities, premature infants have dampened or altered responsiveness compared to term infants, and it is uncertain if these responses can be reliably discriminated from tactile-evoked responses. In particular, a discriminative pattern of noxious-evoked EEG activity that is present in term infants, is unlikely to be present in preterm infants. In addition, it is unclear how noxious-evoked responses, especially brainderived responses, change with age. In this thesis, I use a classification model to show that infants aged 28–40 weeks postmenstrual age display discriminable multimodal responses to a noxious clinical procedure and a tactile control procedure, and I provide examples of how a such a model could be used in clinical trials of analgesics. I show that noxious-evoked responses change magnitude and morphology across this age range, and that discriminative brain activity emerges in early prematurity. In the second part of this thesis, I focus on improving the neuroscientific validity of a noxious-evoked EEG response measured at the cot-side, as the spatial neural correlates of these responses are still poorly understood. I present an EEG-fMRI pilot study to investigate the spatial neural correlates of inter-individual differences in noxious-evoked EEG responses and provide recommendations for a larger follow-up study. Overall, this thesis provides a characterisation of infants’ noxious-evoked responses and their development across multiple modalities, a crucial next step in improving multimodal neonatal pain assessment

    Stretch sensors for measuring knee kinematics in sports

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    The popularity of wearable technology in sport has increased, due to its ability to provide unobtrusive monitoring of athletes. This technology has been used to objectively measure kinetic and kinematic variables, with the aim of preventing injury, maximising athletic performance and classifying the skill level of athletes, all of which can influence training and coaching practices. Wearable technologies overcome the limitations of motion capture systems which are limited in their capture volume, enabling the collection of data in-field, during training and competition. Inertial sensors are a common form of technology used in these environments however, their high-cost and complex calibration due to multiple sensor integration can make them prohibitive for widespread use. This thesis focuses on the development of a strain sensor that can be used to measure knee range of motion in sports, specifically rowing and cycling, as a potential low-cost, lightweight alternative to inertial sensors which can also be integrated into clothing, making them more discreet. A systematic review highlighted the lack of alternate technologies to inertial sensors such as strain sensors, as well as the limited use of wearable technologies in both rowing and cycling. Strain sensors were fabricated from a carbon nanotube-natural rubber composite using solvent exchange techniques and employed a piezoresistive sensing mechanism. These were then characterised using mechanical testing, to determine their electrical properties under cyclical strain. The strain sensors displayed hysteretic behaviour, but were durable, withstanding over 4500 strain cycles. Statistical analysis indicated that over 60% of the tests conducted had good intra-test variability with regards to the resistance response range in each strain cycle and sensor response deviating by less than 10% at strain rates below 100 mm/min and less than 20% at a strain rate of 350 mm/min. These sensors were integrated into a wearable sensor system and tested on rowing and cycling cohorts consisting of ten athletes each, to assess the translational use of the strain sensor. This preliminary testing indicated that strain sensors were able to track the motion of the knee during the rowing stroke and cycling pedalling motion, when compared to the output of a motion capture system. Perspectives of participants on the wearable system were collected, which indicated their desire for a system that they could use in their sport, and they considered the translation of this system for real-life use with further development to improve comfort of the system and consistency of the sensor response. The strain sensors developed in this project, when integrated into a wearable sensor system, have the potential to provide an unobtrusive method of measuring knee kinematics, helping athletes, coaches and other support staff make technical changes that can reduce injury risk and improve performance.Open Acces

    Endotracheal tube placement with fibre optic sensing

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    Unrecognised oesophageal intubation is often described as a ‘Never Event’; an entirely preventable and extremely serious incident. However, there is still prevalence, with severe consequences for the patient. The current gold standards of visually confirming passage through the vocal cords, observing chest movement, and end-tidal capnography all have limitations. There is an opportunity for an alternative method to determine the correct endotracheal tube placement in the trachea. One such solution is described here, through the development of a compact fibre optic sensor integrated into a standard endotracheal tube. The sensor contains no electrical components inside the invasive portion of the device, and it is magnetic resonance imaging safe. The spectral characteristics of the trachea and oesophagus are observed using a fibre optic probe, with the presence of oxyhaemoglobin being used to distinguish the tissues. A novel epoxy sensor is then designed using plastic optical fibres. A rounded top with a square base sensor shape had the least impact on the overall performance of the ETT. Furthermore, by forming the sensor with two illumination fibres, pulse oximetry can be performed. A fibre separation distance between 1.27 and 2.54 mm is optimal. However, a Monte Carlo simulation demonstrates a viable separation of 0.5 to 3 mm. ThereforeHowever, by reducing this to 0.88 mm, a more compact sensor can be produced whilst still retaining a classification rate (average correct identification of trachea and oesophagus) of >89.2% in ex-vivo models. Two methods for emitting light perpendicularly to the fibre axis are explored, demonstrating that bending the fibres caused an optical power loss of 29.0%, whereas cleaving the fibres at 45° produced an 81.9% loss. The position of the sensor on the endotracheal tube is investigated, finding that integration behind the cuff is preferable. However, placement outside the main lumen of the ETT is also a viable option. Computational methods to process spectral measurements are developed. Data for these methods was provided by two experiments on two different sensor types, providing a high tissue classification rate for both the trachea and oesophagus. The first experiment consisted of 9 ex-vivo porcine samples, producing a correct tissue identification of up to 100.0%. The second consisted of 10 sensors on 1 ex-vivo porcine sample, yielding a maximum correct tissue identification of 89.2% when a support vector machine classifier was used. Application of the sensor in an animal study, which consisted of 3 porcine subjects, generated a maximum correct tissue identification of 98.31.6% using principal component analysis and aa support vector machine. The data were recorded over a combined time of 348 minutes, obtained during varying cuff pressures, endotracheal tube orientations, and movement. Finally, suggested future developments to the sensor design and computational methods demonstrate a potential route to improving tissue identification rates. Changes to the experimental protocol are described to verify classification rates. Concepts for exchanging the spectrometer for photodiodes and optical filters to reduce the cost of the opto-electronic units display potential. The technology has applications in wider healthcare, with examples of integration within naso-/oro- gastric tubes and other invasive medical devices given

    Brain Computations and Connectivity [2nd edition]

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    This is an open access title available under the terms of a CC BY-NC-ND 4.0 International licence. It is free to read on the Oxford Academic platform and offered as a free PDF download from OUP and selected open access locations. Brain Computations and Connectivity is about how the brain works. In order to understand this, it is essential to know what is computed by different brain systems; and how the computations are performed. The aim of this book is to elucidate what is computed in different brain systems; and to describe current biologically plausible computational approaches and models of how each of these brain systems computes. Understanding the brain in this way has enormous potential for understanding ourselves better in health and in disease. Potential applications of this understanding are to the treatment of the brain in disease; and to artificial intelligence which will benefit from knowledge of how the brain performs many of its extraordinarily impressive functions. This book is pioneering in taking this approach to brain function: to consider what is computed by many of our brain systems; and how it is computed, and updates by much new evidence including the connectivity of the human brain the earlier book: Rolls (2021) Brain Computations: What and How, Oxford University Press. Brain Computations and Connectivity will be of interest to all scientists interested in brain function and how the brain works, whether they are from neuroscience, or from medical sciences including neurology and psychiatry, or from the area of computational science including machine learning and artificial intelligence, or from areas such as theoretical physics
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