Linking human and machine brains

A look is taken here at how the use of implant technology is rapidly diminishing the effects of certain neural illnesses and distinctly increasing the range of abilities of those affected. An indication is given of a number of problem areas in which such technology has already had a profound effect, a key element being the need for a clear interface linking the human brain directly with a computer. In order to assess the possible opportunities, both human and animal studies are reported on. The main thrust of the paper is however a discussion of neural implant experimentation linking the human nervous system bi-directionally with the internet. With this in place neural signals were transmitted to various technological devices to directly control them, in some cases via the internet, and feedback to the brain was obtained from such as the fingertips of a robot hand, ultrasonic (extra) sensory input and neural signals directly from another human's nervous system. Consideration is given to the prospects for neural implant technology in the future, both in the short term as a therapeutic device and in the long term as a form of enhancement, including the realistic potential for thought communication potentially opening up commercial opportunities. Clearly though, an individual whose brain is part human - part machine can have abilities that far surpass those with a human brain alone. Will such an individual exhibit different moral and ethical values to those of a human.? If so, what effects might this have on society?

On linking human and machine brains

A look is taken here at how the use of implant technology is rapidly diminishing the effects of certain neural illnesses and distinctly increasing the range of abilities of those affected. An indication is given of a number of problem areas in which such technology has already had a profound effect, a key element being the need for a clear interface linking the human brain directly with a computer. In order to assess the possible opportunities, both human and animal studies are reported on. The main thrust of the paper is, however, a discussion of neural implant experimentation linking the human nervous system bi-directionally with the internet. With this in place, neural signals were transmitted to various technological devices to directly control them, in some cases via the internet, and feedback to the brain was obtained from, for example, the fingertips of a robot hand, and ultrasonic (extra) sensory input and neural signals directly from another human's nervous system. Consideration is given to the prospects for neural implant technology in the future, both in the short term as a therapeutic device and in the long term as a form of enhancement, including the realistic potential for thought communication-potentially opening up commercial opportunities. Clearly though, an individual whose brain is part human-part machine can have abilities that far surpass those with a human brain alone. Will such an individual exhibit different moral and ethical values from those of a human? If so, what effects might this have on society? (C) 2008 Elsevier B.V. All rights reserved.

On the maximal connected component of hypercube with faulty vertices

In evaluating an interconnection network, it is indispensable to estimate the size of the maximal connected components of the underlying graph when the network begins to lose processors. Hypercube is one of the most popular interconnection networks. This article addresses the maximal connected components of an n -dimensional cube with faulty processors. We first prove that an n -cube with a set F of at most 2n - 3 failing processors has a component of size greater than or equal to2(n) - \F\ - 1. We then prove that an n -cube with a set F of at most 3n - 6 missing processors has a component of size greater than or equal to2(n) - \F\ - 2.

On the maximal connected component of hypercube with faulty vertices (II)

evaluating the fault tolerance of an interconnection network, it is essential to estimate the size of a maximal connected component of the network at the presence of faulty processors. Hypercube is one of the most popular interconnection networks. In this paper, we prove that for ngreater than or equal to6, an n-dimensional cube with a set F of at most (4n-10) failing processors has a component of size greater than or equal to2"-\F-3. This result demonstrates the superiority of hypercube in terms of the fault tolerance.

On the maximal connected component of a hypercube with faulty vertices III

Hypercube is one of the most popular topologies for connecting processors in multicomputer systems. In this paper we address the maximum order of a connected component in a faulty cube. The results established include several known conclusions as special cases. We conclude that the hypercube structure is resilient as it includes a large connected component in the presence of large number of faulty vertices.

Largest connected component of a star graph with faulty vertices

In order to make a full evaluation of an interconnection network, it is essential to estimate the minimum size of a largest connected component of this network provided the faulty vertices in the network may break its connectedness. Star graphs are recognized as promising candidates for interconnection networks. This article addresses the size of a largest connected component of a faulty star graph. We prove that, in an n-star graph (n >= 3) with up to 2n-4 faulty vertices, all fault-free vertices but at most two form a connected component. Moreover, all fault-free vertices but exactly two form a connected component if and only if the set of all faulty vertices is equal to the neighbourhood of a pair of fault-free adjacent vertices. These results show that star graphs exhibit excellent fault-tolerant abilities in the sense that there exists a large functional network in a faulty star graph.

Component processes of early reading, spelling, and narrative writing skills in Turkish: a longitudinal study

The study examined: (a) the role of phonological, grammatical, and rapid automatized naming (RAN) skills in reading and spelling development; and (b) the component processes of early narrative writing skills. Fifty-seven Turkish-speaking children were followed from Grade 1 to Grade 2. RAN was the most powerful longitudinal predictor of reading speed and its effect was evident even when previous reading skills were taken into account. Broadly, the phonological and grammatical skills made reliable contributions to spelling performance but their effects were completely mediated by previous spelling skills. Different aspects of the narrative writing skills were related to different processing skills. While handwriting speed predicted writing fluency, spelling accuracy predicted spelling error rate. Vocabulary and working memory were the only reliable longitudinal predictors of the quality of composition content. The overall model, however, failed to explain any reliable variance in the structural quality of the compositions

Linking the coevolutionary and population dynamics of host-parasitoid interactions

The interplay between coevolutionary and population or community dynamics is currently the focus of much empirical and theoretical consideration. Here, we develop a simulation model to study the coevolutionary and population dynamics of a hypothetical host-parasitoid interaction. In the model, host resistance and parasitoid virulence are allowed to coevolve. We investigate how trade-offs associated with these traits modify the system's coevolutionary and population dynamics. The most important influence on these dynamics comes from the incorporation of density-dependent costs of resistance ability. We find three main outcomes. First, if the costs of resistance are high, then one or both of the players go extinct. Second, when the costs of resistance are intermediate to low, cycling population and coevolutionary dynamics are found, with slower evolutionary changes observed when the costs of virulence are also low. Third, when the costs associated with resistance and virulence are both high, the hosts trade-off resistance against fecundity and invest little in resistance. However, the parasitoids continue to invest in virulence, leading to stable host and parasitoid population sizes. These results support the hypothesis that costs associated with resistance and virulence will maintain the heritable variation in these traits found in natural populations and that the nature of these trade-offs will greatly influence the population dynamics of the interacting species.

Linking carbon and sulphur cycling during simulated drought cycles in peat from six sites across the UK

Water table draw-down is thought to increase peat decomposition and, therefore, DOC release. However, several studies have shown lower DOC concentrations during droughts relative to ‘normal’ periods with high water table. We carried out controlled incubation experiments at 10°C on 10x10 cm peat soil cores collected from six UK sites across a sulphur deposition gradient. Our aim was to quantify the balance between microbial consumption and chemical precipitation of DOC due to episodic acidification driven by sulphur redox reactions by comparing changes in soil water chemistry to microbial activity (i.e. soil respiration and trace gas fluxes). During dry periods, all sites showed a concurrent increase in SO4 and soil respiration and a decline in DOC. However, the magnitude of change in both DOC and SO4 varied considerably between sites according to historical sulphur deposition loads and the variation in acid/base chemistry.

Isolation and characterisation of EfeM, a periplasmic component of the putative EfeUOBM iron transporter of Pseudomonas syringae pv. syringae

The EfeM protein is a component of the putative EfeUOBM iron-transporter of Pseudomonas syringae pathovar syringae and is thought to act as a periplasmic, ferrous-iron binding protein. It contains a signal peptide of 34 amino acid residues and a C-terminal 'Peptidase_M75' domain of 251 residues. The C-terminal domain contains a highly conserved 'HXXE' motif thought to act as part of a divalent cation-binding site. In this work, the gene (efeM or 'Psyr_3370') encoding EfeM was cloned and over-expressed in Escherichia coli, and the mature protein was purified from the periplasm. Mass spectrometry confirmed the identity of the protein (M(W) 27,772Da). Circular dichroism spectroscopy of EfeM indicated a mainly alpha-helical structure, consistent with bioinformatic predictions. Purified EfeM was crystallised by hanging-drop vapor diffusion to give needle-shaped crystals that diffracted to a resolution of 1.6A. This is the first molecular study of a peptidase M75 domain with a presumed iron transport role.

Chemical ageing and transformation of diffusivity in semi-solid multi-component organic aerosol particles

Recent experimental evidence underlines the importance of reduced diffusivity in amorphous semi-solid or glassy atmospheric aerosols. This paper investigates the impact of diffusivity on the ageing of multi-component reactive organic particles representative of atmospheric cooking aerosols. We apply and extend the recently developed KM-SUB model in a study of a 12-component mixture containing oleic and palmitoleic acids. We demonstrate that changes in the diffusivity may explain the evolution of chemical loss rates in ageing semi-solid particles, and we resolve surface and bulk processes under transient reaction conditions considering diffusivities altered by oligomerisation. This new model treatment allows prediction of the ageing of mixed organic multi-component aerosols over atmospherically relevant time scales and conditions. We illustrate the impact of changing diffusivity on the chemical half-life of reactive components in semisolid particles, and we demonstrate how solidification and crust formation at the particle surface can affect the chemical transformation of organic aerosols.

Photochemical cross-linking of plastically compressed collagen gel produces an optimal scaffold for corneal tissue engineering

The experiments were designed to use photochemically cross-linked plastically compressed collagen (PCPCC) gel to support corneal epithelial cells. A plastically compressed collagen (PCC) scaffold was photo cross-linked by UVA in the presence of riboflavin to form a biomaterial with optimal mechanical properties. The breaking force, rheology, surgical suture strength, transparency, ultrastructure, and cell-based biocompatibility were compared between PCPCC and PCC gels. The breaking force increased proportionally with an increased concentration of riboflavin. The stress required to reach breaking point of the PCPCC scaffolds was over two times higher compared to the stress necessary to break PCC scaffolds in the presence of 0.1% riboflavin. Rheology results indicated that the structural properties of PCC remain unaltered after UVA cross-linking. The PCC gels were more easily broken than PCPCC gels when sutured on to bovine corneas. The optical density values of PCPCC and PCC showed no significant differences (p > 0.05). SEM analyses showed that the collagen fibres within the PCPCC gels were similar in morphology to PCC gels. No difference in cell-based biocompatibility was seen between the PCPCC and PCC scaffolds in terms of their ability to support the ex vivo expansion of corneal epithelial cells or their subsequent differentiation evidenced by similar levels of cytokeratin 14. In conclusion, PCPCC scaffold is an optimal biomaterial for use in therapeutic tissue engineering of the cornea.

The underlying return generating factors for REIT returns: an application of independent component analysis

Multi-factor approaches to analysis of real estate returns have, since the pioneering work of Chan, Hendershott and Sanders (1990), emphasised a macro-variables approach in preference to the latent factor approach that formed the original basis of the arbitrage pricing theory. With increasing use of high frequency data and trading strategies and with a growing emphasis on the risks of extreme events, the macro-variable procedure has some deficiencies. This paper explores a third way, with the use of an alternative to the standard principal components approach – independent components analysis (ICA). ICA seeks higher moment independence and maximises in relation to a chosen risk parameter. We apply an ICA based on kurtosis maximisation to weekly US REIT data using a kurtosis maximising algorithm. The results show that ICA is successful in capturing the kurtosis characteristics of REIT returns, offering possibilities for the development of risk management strategies that are sensitive to extreme events and tail distributions.