Managing the Ethical Dimensions of Brain-Computer Interfaces in eHealth: An SDLC-based Approach

A growing range of brain-computer interface (BCI) technologies is being employed for purposes of therapy and human augmentation. While much thought has been given to the ethical implications of such technologies at the ‘macro’ level of social policy and ‘micro’ level of individual users, little attention has been given to the unique ethical issues that arise during the process of incorporating BCIs into eHealth ecosystems. In this text a conceptual framework is developed that enables the operators of eHealth ecosystems to manage the ethical components of such processes in a more comprehensive and systematic way than has previously been possible. The framework’s first axis defines five ethical dimensions that must be successfully addressed by eHealth ecosystems: 1) beneficence; 2) consent; 3) privacy; 4) equity; and 5) liability. The second axis describes five stages of the systems development life cycle (SDLC) process whereby new technology is incorporated into an eHealth ecosystem: 1) analysis and planning; 2) design, development, and acquisition; 3) integration and activation; 4) operation and maintenance; and 5) disposal. Known ethical issues relating to the deployment of BCIs are mapped onto this matrix in order to demonstrate how it can be employed by the managers of eHealth ecosystems as a tool for fulfilling ethical requirements established by regulatory standards or stakeholders’ expectations. Beyond its immediate application in the case of BCIs, we suggest that this framework may also be utilized beneficially when incorporating other innovative forms of information and communications technology (ICT) into eHealth ecosystems

Bioinformatics tools in predictive ecology: Applications to fisheries

This article is made available throught the Brunel Open Access Publishing Fund - Copygith @ 2012 Tucker et al.There has been a huge effort in the advancement of analytical techniques for molecular biological data over the past decade. This has led to many novel algorithms that are specialized to deal with data associated with biological phenomena, such as gene expression and protein interactions. In contrast, ecological data analysis has remained focused to some degree on off-the-shelf statistical techniques though this is starting to change with the adoption of state-of-the-art methods, where few assumptions can be made about the data and a more explorative approach is required, for example, through the use of Bayesian networks. In this paper, some novel bioinformatics tools for microarray data are discussed along with their ‘crossover potential’ with an application to fisheries data. In particular, a focus is made on the development of models that identify functionally equivalent species in different fish communities with the aim of predicting functional collapse

Article Modelling potential impacts of bottom trawl fisheries on soft sediment biogeochemistry in the North Sea{

Bottom trawling causes physical disturbance to sediments particularly in shelf areas. The disturbance due to trawling is most significant in deeper areas with softer sediments where levels of natural disturbance due to wave and tidal action are low. In heavily fished areas, trawls may impact the same area of seabed more than four times per year. A single pass of a beam trawl, the heaviest gear routinely used in shelf sea fisheries, can kill 5-65% of the resident fauna and mix the top few cm of sediment. We expect that sediment community function, carbon mineralisation and biogeochemical fluxes will be strongly affected by trawling activity because the physical effects of trawling are equivalent to those of an extreme bioturbator, and yet, unlike bioturbating macrofauna, trawling does not directly contribute to community metabolism. We used an existing box-model of a generalised soft sediment system to examine the effects of trawling disturbance on carbon mineralisation and chemical concentrations. We contrasted the effects of a natural scenario, where bioturbation is a function of macrobenthos biomass, with an anthropogenic impact scenario where physical disturbance results from trawling rather than the action of bioturbating macrofauna. Simulation results suggest that the effects of low levels of trawling disturbance will be similar to those of natural bioturbators but that high levels of trawling disturbance prevent the modelled system from reaching equilibrium due to large carbon fluxes between oxic and anoxic carbon compartments. The presence of macrobenthos in the natural disturbance scenario allowed sediment chemical storage and fluxes to reach equilibrium. This is because the macrobenthos are important carbon consumers in the system whose presence reduces the magnitude of available carbon fluxes. In soft sediment systems, where the level physical disturbance due to waves and tides is low, model results suggest that intensive trawling disturbance could cause large fluctuations in benthic chemical fluxes and storage

Species richness in North Atlantic fish: Process concealed by pattern

International audiencePrevious analyses of marine fish species richness based on presence‐absence data have shown changes with latitude and average species size, but little is known about the underlying processes. To elucidate these processes we use metabolic, neutral and descriptive statistical models to analyse how richness responds to maximum species length, fish abundance, temperature, primary production, depth, latitude and longitude, while accounting for differences in species catchability, sampling effort and mesh size

Species richness in North Atlantic fish: Process concealed by pattern.

Aim: Previous analyses of marine fish species richness based on presence-absence data have shown changes with latitude and average species size, but little is known about the underlying processes. To elucidate these processes we use metabolic, neutral and descriptive statistical models to analyse how richness responds to maximum species length, fish abundance, temperature, primary production, depth, latitude and longitude, while accounting for differences in species catchability, sampling effort and mesh size. Data: Results from 53,382 bottom trawl hauls representing 50 fish assemblages. Location: The northern Atlantic from Nova Scotia to Guinea. Time period: 1977–2013. Methods: A descriptive generalized additive model was used to identify functional relationships between species richness and potential drivers, after which nonlinear estimation techniques were used to parameterize: (a) a ‘best’ fitting model of species richness built on the functional relationships, (b) an environmental model based on latitude, longitude and depth, and mechanistic models based on (c) metabolic and (d) neutral theory. Results: In the ‘best’ model the number of species observed is a lognormal function of maximum species length. It increases significantly with temperature, primary production, sampling effort, and abundance, and declines with depth and, for small species, with the mesh size in the trawl. The ‘best’ model explains close to 90% of the deviance and the neutral, metabolic and environmental models 89%. In all four models, maximum species length and either temperature or latitude account for more than half of the deviance explained. Main conclusions: The two mechanistic models explain the patterns in demersal fish species richness in the northern Atlantic almost equally well. A better understanding of the underlying drivers is likely to require development of dynamic mechanistic models of richness and size evolution, fit not only to extant distributions, but also to historical environmental conditions and to past speciation and extinction ratesS

Eliminating implausible fisheries assessment models using fishers’ knowledge

Peer review of competing redfish (Sebastes mentella) assessment models revealed data inconsistencies where stock biomass decline shown by the survey in the 1990s was too rapid to be explained solely by reported catch. The assessments invoked different techniques to achieve fits, one my change mortality at age and the other by survey weighting. The former fitted reported catch well while the latter accepted a mismatch between reported and estimated catch. The assessments produced different estimates of historical stock size and future productivity (3X). Interviews conducted with fishers of the stock suggests that catch was at least twice as high as the official record. In light of the fishers' evidence, the model that invoked a large change in mortality with age but followed reported catch closely now appears less credible and serves as a warning against introducing new biological mechanisms without credible justification. This is an example of how indicators derived from fisherâ s knowledge, even if only from a small number of interviews, can be used to eliminate less plausible models.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Extinction Debt and Colonizer Credit on a Habitat Perturbed Fishing Bank.

Temporal changes in occupancy of the Georges Bank (NE USA) fish and invertebrate community were examined and interpreted in the context of systems ecological theory of extinction debt (EDT). EDT posits that in a closed system with a mix of competitor and colonizer species and experiencing habitat fragmentation and loss, the competitor species will show a gradual decline in fitness (occupancy) eventually leading to their extinction (extirpation) over multiple generations. A corollary of this is a colonizer credit, where colonizer species occupancy may increase with fragmentation because the disturbance gives that life history a transient relative competitive advantage. We found that competitor species occupancy decreased in time concomitant with an increase in occupancy of colonizer species and this may be related to habitat fragmentation or loss owing to industrialized bottom trawl fishing. Mean species richness increased over time which suggests less specialization (decreased dominance) of the assemblage that may result from habitat homogenization. These analyses also showed that when abundance of species was decreased by fishing but eventually returned to previous levels, on average it had a lower occupancy than earlier in the series which could increase their vulnerability to depletion by fishing. Changing occupancy and diversity patterns of the community over time is consistent with EDT which can be exacerbated by direct impacts of fishery removals as well as climate change impacts on the fish community assemblage