"Going back to our roots": second generation biocomputing

Researchers in the field of biocomputing have, for many years, successfully "harvested and exploited" the natural world for inspiration in developing systems that are robust, adaptable and capable of generating novel and even "creative" solutions to human-defined problems. However, in this position paper we argue that the time has now come for a reassessment of how we exploit biology to generate new computational systems. Previous solutions (the "first generation" of biocomputing techniques), whilst reasonably effective, are crude analogues of actual biological systems. We believe that a new, inherently inter-disciplinary approach is needed for the development of the emerging "second generation" of bio-inspired methods. This new modus operandi will require much closer interaction between the engineering and life sciences communities, as well as a bidirectional flow of concepts, applications and expertise. We support our argument by examining, in this new light, three existing areas of biocomputing (genetic programming, artificial immune systems and evolvable hardware), as well as an emerging area (natural genetic engineering) which may provide useful pointers as to the way forward.Comment: Submitted to the International Journal of Unconventional Computin

Current and Future Advances in Surgical Therapy for Pituitary Adenoma

The vital physiological role of the pituitary gland, alongside its proximal critical neurovascular structures means pituitary adenomas cause significant morbidity or mortality. Whilst enormous advancements have been made in the surgical care of pituitary adenomas, treatment failure and recurrence remain challenges. To meet these clinical challenges, there has been an enormous expansion of novel medical technologies (e.g. endoscopy, advanced imaging, artificial intelligence). These innovations have the potential to benefit each step of the patient journey, and ultimately, drive improved outcomes. Earlier and more accurate diagnosis addresses this in part. Analysis of novel patient data sets, such as automated facial analysis or natural language processing of medical records holds potential in achieving an earlier diagnosis. After diagnosis, treatment decision-making and planning will benefit from radiomics and multimodal machine learning models. Surgical safety and effectiveness will be transformed by smart simulation methods for trainees. Next-generation imaging techniques and augmented reality will enhance surgical planning and intraoperative navigation. Similarly, the future armamentarium of pituitary surgeons, including advanced optical devices, smart instruments and surgical robotics, will augment the surgeon's abilities. Intraoperative support to team members will benefit from a surgical data science approach, utilising machine learning analysis of operative videos to improve patient safety and orientate team members to a common workflow. Postoperatively, early detection of individuals at risk of complications and prediction of treatment failure through neural networks of multimodal datasets will support earlier intervention, safer hospital discharge, guide follow-up and adjuvant treatment decisions. Whilst advancements in pituitary surgery hold promise to enhance the quality of care, clinicians must be the gatekeepers of technological translation, ensuring systematic assessment of risk and benefit. In doing so, the synergy between these innovations can be leveraged to drive improved outcomes for patients of the future

A Framework for a Robot's Emotion Engine

An Emotions Engine is a modelling and a simplification of the Brain circuitry that generate emotions. It should produce a variety of responses including rapid reaction-like emotions as well as slower moods. We introduce such an engine and then propose a framework for its translated equivalent for a robot. We then define key issues that need addressing and provide guidelines via the framework, for its implementation onto an actual robot’s Emotions Engine

A Framework for a Robot's Emotion Engine

An Emotions Engine is a modelling and a simplification of the Brain circuitry that generate emotions. It should produce a variety of responses including rapid reaction-like emotions as well as slower moods. We introduce such an engine and then propose a framework for its translated equivalent for a robot. We then define key issues that need addressing and provide guidelines via the framework, for its implementation onto an actual robot’s Emotions Engine

The Software Continuum Concept: Towards a Biologically Inspired Model for Robust E-Business Software Automation

This paper introduces a new concept, the software continuum concept based on the observation that exists a general parallelism between the software continuum from bits to business/Internet ecosystems and the natural continuum from particles to ecosystems. The general parallelism suggests that homeomorphisms may be identified and therefore some concepts, processes, and/or mechanisms in one continuum can be investigated for application in the other continuum. We argue that the homeomorphisms give rise to a biologically-inspired architectural framework for addressing robust control, robust intelligence, and robust autonomy issues in e-business software and other business-IT integration challenges. As application, we examine the mapping of a major enterprise-level architecture framework to the biologically-inspired framework. Design considerations for robust intelligence and autonomy in large-scale software automation and some major systemic features for flexible business-IT integration are also discussed

Aerospace Medicine and Biology: A continuing bibliography with indexes (supplement 153)

This bibliography lists 175 reports, articles, and other documents introduced into the NASA scientific and technical information system in March 1976

The Mental Database

This article uses database, evolution and physics considerations to suggest how the mind stores and processes its data. Its innovations in its approach lie in:- A) The comparison between the capabilities of the mind to those of a modern relational database while conserving phenomenality. The strong functional similarity of the two systems leads to the conclusion that the mind may be profitably described as being a mental database. The need for material/mental bridging and addressing indexes is discussed. B) The consideration of what neural correlates of consciousness (NCC) between sensorimotor data and instrumented observation one can hope to obtain using current biophysics. It is deduced that what is seen using the various brain scanning methods reflects only that part of current activity transactions (e.g. visualizing) which update and interrogate the mind, but not the contents of the integrated mental database which constitutes the mind itself. This approach yields reasons why there is much neural activity in an area to which a conscious function is ascribed (e.g. the amygdala is associated with fear), yet there is no visible part of its activity which can be clearly identified as phenomenal. The concept is then situated in a Penrosian expanded physical environment, requiring evolutionary continuity, modularity and phenomenality.Several novel Darwinian advantages arising from the approach are described

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 297)

This bibliography lists 89 reports, articles and other documents introduced into the NASA scientific and technical information system in April, 1987

Systems Cell: a Testable Model for Systems Holism

The equations of physical world are bereft of causality. On the other hand, the relational matrix between two or more organelles or organisms is inclusively causal because of operational presence of consciousness and other potent factors like ‘life’, self, mind and information within the system. Standing on the computational platform of informational molecules of systems biology what is that decisionmaking ware which makes cell’s response solution centric as well as holographic?Embedded within what is observable, measurable and reducible into parts, this paper tries to answer this question and develops how the causal operations of information, mind, self, life and consciousness connect signature informational molecules with wisdom of cellular consciousness. The entire relationship has been presented as multilayered and hierarchically nested labyrinthine ware. Systems cell can be used as a model of systems holism and be tested with the credible data from molecular mapping and multidimensional live cell image analysis