Electrical stimulation for trunk control in paraplegia:A feasibility study

Paraplegic subjects lack trunk stability due to the loss of voluntary muscle control.This leads to a restriction of the volume of bi-manual workspace available,and hence has a detrimental impact on activities of daily living. Electrical Stimulation of paralysed muscles can be used to stabilize the trunk, but has never been applied in closed loop for this purpose. This paper describes the development of two closed loop controllers(PID and LQR),and their experimental evaluation on a human subject. Advantages and disadvantages of the two are discussed,considering a potential use of this technology during daily activities.

A mesoscopic modelling approach to anaesthetic action on brain electrical activity

Relating the measurable, large scale, effects of anaesthetic agents to their molecular and cellular targets of action is necessary to better understand the principles by which they affect behavior, as well as enabling the design and evaluation of more effective agents and the better clinical monitoring of existing and future drugs. Volatile and intravenous general anaesthetic agents (GAs) are now known to exert their effects on a variety of protein targets, the most important of which seem to be the neuronal ion channels. It is hence unlikely that anaesthetic effect is the result of a unitary mechanism at the single cell level. However, by altering the behavior of ion channels GAs are believed to change the overall dynamics of distributed networks of neurons. This disruption of regular network activity can be hypothesized to cause the hypnotic and analgesic effects of GAs and may well present more stereotypical characteristics than its underlying microscopic causes. Nevertheless, there have been surprisingly few theories that have attempted to integrate, in a quantitative manner, the empirically well documented alterations in neuronal ion channel behavior with the corresponding macroscopic effects. Here we outline one such approach, and show that a range of well documented effects of anaesthetics on the electroencephalogram (EEG) may be putatively accounted for. In particular we parameterize, on the basis of detailed empirical data, the effects of halogenated volatile ethers (a clinically widely used class of general anaesthetic agent). The resulting model is able to provisionally account for a range of anaesthetically induced EEG phenomena that include EEG slowing, biphasic changes in EEG power, and the dose dependent appearance of anomalous ictal activity, as well as providing a basis for novel approaches to monitoring brain function in both health and disease.

A new error measure for forecasts of household-level, high resolution electrical energy consumption

As low carbon technologies become more pervasive, distribution network operators are looking to support the expected changes in the demands on the low voltage networks through the smarter control of storage devices. Accurate forecasts of demand at the single household-level, or of small aggregations of households, can improve the peak demand reduction brought about through such devices by helping to plan the appropriate charging and discharging cycles. However, before such methods can be developed, validation measures are required which can assess the accuracy and usefulness of forecasts of volatile and noisy household-level demand. In this paper we introduce a new forecast verification error measure that reduces the so called “double penalty” effect, incurred by forecasts whose features are displaced in space or time, compared to traditional point-wise metrics, such as Mean Absolute Error and p-norms in general. The measure that we propose is based on finding a restricted permutation of the original forecast that minimises the point wise error, according to a given metric. We illustrate the advantages of our error measure using half-hourly domestic household electrical energy usage data recorded by smart meters and discuss the effect of the permutation restriction.

Rheological and electrical properties of NaY zeolite electrorheological fluid

The relations between the rheological and electrical properties of NaY zeolite electrorheological fluid and its solid phase are studied. It is found that then exist complex relations between its electrical and theological properties. The temperature spectra of dielectric properties of the fluid under high AC electric field are strongly field strength dependent. The relation between the DC conductivity of the fluid and the exciting electric field is experimentally presented as log sigma =A+BE1/2, when A is a strong function, but B, a very weak function of temperature. The shear stress of the fluid under a fixed electric field and temperature decreases with shear rate. A relaxation time for the adsorbed charges is estimated to be about 0.3 to 6.6 s in the temperature range from 280 to 380 K. The relaxation time qualitatively corresponds to the shear rate at which the shear stress begins to drop. The time dependent leaking current of the ER fluids under DC electric field is also measured. The conductivity increase is mainly caused by the structure evolution of particles. The experimental results can he explained with the calculations of Davis (J. Appl. Phys. 81(1997) pp.1985-1991) and Martin (J. Chem. Phys. 110(1999) pp.4854-4866). It is predicted that the NaY zeolite ER fluid strength would get degraded slowly.

Long term individual load forecast under different electrical vehicles uptake scenarios

More and more households are purchasing electric vehicles (EVs), and this will continue as we move towards a low carbon future. There are various projections as to the rate of EV uptake, but all predict an increase over the next ten years. Charging these EVs will produce one of the biggest loads on the low voltage network. To manage the network, we must not only take into account the number of EVs taken up, but where on the network they are charging, and at what time. To simulate the impact on the network from high, medium and low EV uptake (as outlined by the UK government), we present an agent-based model. We initialise the model to assign an EV to a household based on either random distribution or social influences - that is, a neighbour of an EV owner is more likely to also purchase an EV. Additionally, we examine the effect of peak behaviour on the network when charging is at day-time, night-time, or a mix of both. The model is implemented on a neighbourhood in south-east England using smart meter data (half hourly electricity readings) and real life charging patterns from an EV trial. Our results indicate that social influence can increase the peak demand on a local level (street or feeder), meaning that medium EV uptake can create higher peak demand than currently expected.

Compositional control of the electrical transport properties in the new series of thiospinels Ga1-xGexV4S8-delta (0 <=x<=1)

A new series of non-stoichiometric sulfides Ga1−xGexV4S8−δ (0≤x≤1; δ≤0.23) has been synthesized at high temperatures by heating stoichiometric mixtures of the elements in sealed quartz tubes. The samples have been characterized by powder X-ray diffraction, SQUID magnetometry and electrical transport-property measurements. Structural analysis reveals that a solid solution is formed throughout this composition range, whilst thermogravimetric data reveal sulfur deficiency of up to 2.9% in the quaternary phases. Magnetic measurements suggest that the ferromagnetic behavior of the end-member phase GaV4S8 is retained at x≤0.7; samples in this composition range showing a marked increase in magnetization at low temperatures. By contrast Ga0.25Ge0.75V4S8−δ appears to undergo antiferromagnetic ordering at ca. 15 K. All materials with x≠1 are n-type semiconductors whose resistivity falls by almost six orders of magnitude with decreasing Ga content, whilst the end-member phase GeV4S8−δ is a p-type semiconductor. The results demonstrate that the physical properties are determined principally by the degree of electron filling of narrow-band states arising from intracluster V–V interactions.

Structure and electrical transport properties of the ordered skutterudites MGe1.5S1.5 (M = Co, Rh, Ir)

High-resolution powder neutron diffraction data collected for the skutterudites MGe1.5S1.5 (M=Co, Rh, Ir) reveal that these materials adopt an ordered skutterudite structure (space group R3¯), in which the anions are ordered in layers perpendicular to the [111] direction. In this ordered structure, the anions form two-crystallographically distinct four-membered rings, with stoichiometry Ge2S2, in which the Ge and S atoms are trans to each other. The transport properties of these materials, which are p-type semiconductors, are discussed in the light of the structural results. The effect of iron substitution in CoGe1.5S1.5 has been investigated. While doping of CoGe1.5S1.5 has a marked effect on both the electrical resistivity and the Seebeck coefficient, these ternary skutterudites exhibit significantly higher electrical resistivities than their binary counterparts.

Time-lapse geophysical investigations over known archaeological features using electrical resistivity imaging and earth resistance

Electrical methods of geophysical survey are known to produce results that are hard to predict at different times of the year, and under differing weather conditions. This is a problem which can lead to misinterpretation of archaeological features under investigation. The dynamic relationship between a ‘natural’ soil matrix and an archaeological feature is a complex one, which greatly affects the success of the feature’s detection when using active electrical methods of geophysical survey. This study has monitored the gradual variation of measured resistivity over a selection of study areas. By targeting difficult to find, and often ‘missing’ electrical anomalies of known archaeological features, this study has increased the understanding of both the detection and interpretation capabilities of such geophysical surveys. A 16 month time-lapse study over 4 archaeological features has taken place to investigate the aforementioned detection problem across different soils and environments. In addition to the commonly used Twin-Probe earth resistance survey, electrical resistivity imaging (ERI) and quadrature electro-magnetic induction (EMI) were also utilised to explore the problem. Statistical analyses have provided a novel interpretation, which has yielded new insights into how the detection of archaeological features is influenced by the relationship between the target feature and the surrounding ‘natural’ soils. The study has highlighted both the complexity and previous misconceptions around the predictability of the electrical methods. The analysis has confirmed that each site provides an individual and nuanced situation, the variation clearly relating to the composition of the soils (particularly pore size) and the local weather history. The wide range of reasons behind survey success at each specific study site has been revealed. The outcomes have shown that a simplistic model of seasonality is not universally applicable to the electrical detection of archaeological features. This has led to the development of a method for quantifying survey success, enabling a deeper understanding of the unique way in which each site is affected by the interaction of local environmental and geological conditions.