Limitations of instantaneous water quality sampling in surface-water catchments: Comparison with near-continuous phosphorus time-series data.

The validity of load estimates from intermittent, instantaneous grab sampling is dependent on adequate spatial coverage by monitoring networks and a sampling frequency that re?ects the variability in the system under study. Catchments with a ?ashy hydrology due to surface runoff pose a particular challenge as intense short duration rainfall events may account for a signi?cant portion of the total diffuse transfer of pollution from soil to water in any hydrological year. This can also be exacerbated by the presence of strong background pollution signals from point sources during low flows. In this paper, a range of sampling methodologies and load estimation techniques are applied to phosphorus data from such a surface water dominated river system, instrumented at three sub-catchments (ranging from 3 to 5 km2 in area) with near-continuous monitoring stations. Systematic and Monte Carlo approaches were applied to simulate grab sampling using multiple strategies and to calculate an estimated load, Le based on established load estimation methods. Comparison with the actual load, Lt, revealed signi?cant average underestimation, of up to 60%, and high variability for all feasible sampling approaches. Further analysis of the time series provides an insight into these observations; revealing peak frequencies and power-law scaling in the distributions of P concentration, discharge and load associated with surface runoff and background transfers. Results indicate that only near-continuous monitoring that re?ects the rapid temporal changes in these river systems is adequate for comparative monitoring and evaluation purposes. While the implications of this analysis may be more tenable to small scale ?ashy systems, this represents an appropriate scale in terms of evaluating catchment mitigation strategies such as agri-environmental policies for managing diffuse P transfers in complex landscapes.

Evaluation of cement stresses in finite element analyses of cemented orthopaedic implants

Stress analysis of the cement fixation of orthopaedic implants to bone is frequently? carried out using finite element analysis. However, the stress distribution in the cement laver is usually intricate, and it is difficult to report it in a way that facilitates comparison of implants for pre-clinical testing. To study this problem, and make recommendations for stress reporting, a finite element analysis of a hip prosthesis implanted into a synthetic composite femur is developed. Three cases are analyzed: a fully bonded implant, a debonded implant, and a debonded implant where the cement is removed distal to the stein tip. In addition to peak stresses, and contour and vector plots, a stressed volume and probability-of-failure analysis is reported. It is predicted that the peak stress is highest for the debonded stem, and that removal of the distal cement more than halves this peak stress. This would suggest that omission of the distal cement is good for polished prostheses (as practiced for the Exeter design). However; if the percentage of cement stressed above a certain threshold (say 3 MPa) is considered, then the removal of distal cement is shown to be disadvantageous because a higher volume of cement is stressed to above the threshold. Vector plots clearly demonstrate the different load transfer for bonded and debonded prostheses: A bonded stein generates maximum tensile stresses in the longitudinal direction, whereas a debonded stem generates most tensile stresses in the hoop direction, except near the tip where tensile longitudinal stresses occur due to subsidence of the stein. Removal of the cement distal to the tip allows greater subsidence but alleviates these large stresses at the tip, albeit at the expense of increased hoop stresses throughout the mantle. It is concluded that a thorough analysis of cemented implants should not report peak stress, which can be misleading, but rather stressed volume, and that vector plots should be reported if a precise analysis of the load transfer mechanism is required.

Computer simulating a trial of a load-bearing implant: example of an intramedullary prosthesis

Computational modelling is becoming ever more important for obtaining regulatory approval for new medical devices. An accepted approach is to infer performance in a population from an analysis conducted for an idealised or ‘average’ patient; we present here a method for predicting the performance of an orthopaedic implant when released into a population—effectively simulating a clinical trial. Specifically we hypothesise that an analysis based on a method for predicting the performance in a population will lead to different conclusions than an analysis based on an idealised or ‘average’ patient. To test this hypothesis we use a finite element model of an intramedullary implant in a bone whose size and remodelling activity is different for each individual in the population. We compare the performance of a low Young’s modulus implant (View the MathML source) to one with a higher Young’s modulus (200 GPa). Cyclic loading is applied and failure is assumed when the migration of the implant relative to the bone exceeds a threshold magnitude. The analysis for an idealised of ‘average’ patient predicts that the lower modulus device survives longer whereas the analysis simulating a clinical trial predicts no statistically-significant tendency (p=0.77) for the low modulus device to perform better. It is concluded that population-based simulations of implant performance–simulating a clinical trial–present a very valuable opportunity for more realistic computational pre-clinical testing of medical devices.

Sedative load of medications prescribed for older people with dementia in care homes

The objective of this study was to determine the sedative load and use of sedative and psychotropic medications among older people with dementia living in (residential) care homes.

Electric vehicles and displaced gaseous emission

Electric vehicles (EV) do not emit tailpipe exhaust fumes in the same manner as internal combustion engine vehicles. Optimal benefits can only be achieved, if EVS are deployed effectively, so that the tailpipe emissions are not substituted by additional emissions in the electricity sector. This paper examines the potential contributions that Plug in Hybrid Electric Vehicles can make in reducing carbon dioxide. The paper presents the results of the generation expansion model for Northern Ireland and the Republic of Ireland built using the dynamic programming based long term generation expansion planning tool called the Wien Automatic System Planning IV tool. The model optimizes power dispatch using hourly electricity demand curves for each year up to 2020, while incorporating generator characteristics and certain operational requirements such as energy not served and loss of load probability while satisfying constraints on environmental emissions, fuel availability and generator operational and maintenance costs. In order to simulate the effect of PHEV, two distinct charging scenarios are applied based on a peak tariff and an off peak tariff. The importance and influence of the charging regime on the amount of energy used and gaseous emissions displaced is determined and discussed.

Scaling in the time-dependent failure of a fiber bundle with local load sharing

We study the scaling behaviors of a time-dependent fiber-bundle model with local load sharing. Upon approaching the complete failure of the bundle, the breaking rate of fibers diverges according to r(t)proportional to(T-f-t)(-xi) where T-f is the lifetime of the bundle and xi approximate to 1.0 is a universal scaling exponent. The average lifetime of the bundle [T-f] scales with the system size as N-delta, where delta depends on the distribution of individual fiber as well as the breakdown rule. [S1063-651X(99)13902-3].

Failure of fiber bundles with local load sharing

We develop a recursion-relation approach for calculating the failure probabilities of a fiber bundle with local load sharing. This recursion relation is exact, so it provides a way to test the validity of the various approximate methods. Applying the exact calculation to uniform and Weibull threshold distributions, we find that the most probable failure load coincides with the average strength as the size of the system N --> infinity.

BURST-SIZE DISTRIBUTION IN FIBER-BUNDLES WITH LOCAL LOAD-SHARING

A critical load x(c) is introduced into the fiber-bundle model with local load-sharing. The critical load is defined as the average load per fiber that causes the final complete failure. It is shown that x(c) --> 0 when the size of the system N --> infinity. A power law for the burst-size distribution, D(DELTA) is-proportional-to DELTA(-xi) is approximately correct. The exponent xi is not universal, since it depends on the strength distribution as well as the size of the system.

Intelligent demand response electric water heating to integrate wind power in Ireland

Dwindling fossil fuel resources and pressures to reduce greenhouse gas (GHG) emissions will result in a more diverse range of generation portfolios for future electricity systems. Irrespective of the portfolio mix the overarching requirement for all electricity suppliers and system operators is that supply instantaneously meets demand and that robust operating standards are maintained to ensure a consistent supply of high quality electricity to end-users. Therefore all electricity market participants will ultimately need to use a variety of tools to balance the power system. Thus the role of demand side management (DSM) with energy storage will be paramount to integrate future diverse generation portfolios. Electric water heating (EWH) has been studied previously, particularly at the domestic level to provide load control, peak shave and to benefit end-users financially with lower bills, particularly in vertically integrated monopolies. In this paper, a continuous Direct Load Control (DLC) EWH algorithm is applied in a liberalized market environment using actual historical electricity system and market data to examine the potential energy savings, cost reductions and electricity system operational improvements.