Quantitative Measurement of [Na+] and [K+] in Postmortem Human Brain Tissue Indicates Disturbances in Subjects with Alzheimer's Disease and Dementia with Lewy Bodies

Alzheimer’s disease (AD) is associated with significant disturbances in the homeostasis of Na+ and K+ ions as well as reduced levels of Na+/K+ ATPase in the brain. This study used ICP-MS to accurately quantify Na+ and K+ concentrations in human postmortem brain tissue. We analyzed parietal cortex (Brodmann area 7) from 28 cognitively normal age-matched controls, 15 cases of moderate AD, 30 severe AD, and 15 dementia with Lewy bodies (DLB). Associations were investigated between [Na+] and [K+] and a number of variables including diagnosis, age, gender, Braak tangle stage, amyloid-β (Aβ) plaque load, tau load, frontal tissue pH, and APOE genotype. Brains from patients with severe AD had significantly higher (26%; p<0.001) [Na+] (mean 65.43 ± standard error 2.91 mmol/kg) than controls, but the concentration was not significantly altered in moderate AD or DLB. [Na+] correlated positively with Braak stage (r=0.45; p<0.0001), indicating association with disease severity. [K+] in tissue was 10% lower (p<0.05) in moderate AD than controls. However, [K+] in severe AD and DLB (40.97±1.31 mmol/kg) was not significantly different from controls. There was a significant positive correlation between [K+] and Aβ plaque load (r=0.46; p=0.035), and frontal tissue pH (r=0.35; p=0.008). [Na+] was not associated with [K+] across the groups, and neither ion was associated with tau load or APOE genotype. We have demonstrated disturbances of both [Na+] and [K+] in relation to the severity of AD and markers of AD pathology, although it is possible that these relate to late-stage secondary manifestations of the disease pathology.

Performance assessment of cascade control loopswith non-Gaussian disturbances using entropy information

Cascade control is one of the routinely used control strategies in industrial processes because it can dramatically improve the performance of single-loop control, reducing both the maximum deviation and the integral error of the disturbance response. Currently, many control performance assessment methods of cascade control loops are developed based on the assumption that all the disturbances are subject to Gaussian distribution. However, in the practical condition, several disturbance sources occur in the manipulated variable or the upstream exhibits nonlinear behaviors. In this paper, a general and effective index of the performance assessment of the cascade control system subjected to the unknown disturbance distribution is proposed. Like the minimum variance control (MVC) design, the output variances of the primary and the secondary loops are decomposed into a cascade-invariant and a cascade-dependent term, but the estimated ARMA model for the cascade control loop based on the minimum entropy, instead of the minimum mean squares error, is developed for non-Gaussian disturbances. Unlike the MVC index, an innovative control performance index is given based on the information theory and the minimum entropy criterion. The index is informative and in agreement with the expected control knowledge. To elucidate wide applicability and effectiveness of the minimum entropy cascade control index, a simulation problem and a cascade control case of an oil refinery are applied. The comparison with MVC based cascade control is also included.

Modelling and Prediction of NOx Emission in a Coal-Fired Power Generation Plant

In this paper NOx emissions modelling for real-time operation and control of a 200 MWe coal-fired power generation plant is studied. Three model types are compared. For the first model the fundamentals governing the NOx formation mechanisms and a system identification technique are used to develop a grey-box model. Then a linear AutoRegressive model with eXogenous inputs (ARX) model and a non-linear ARX model (NARX) are built. Operation plant data is used for modelling and validation. Model cross-validation tests show that the developed grey-box model is able to consistently produce better overall long-term prediction performance than the other two models.

Enhancing process insight in polymer extrusion by grey box modelling

Due to the complexity and inherent instability in polymer extrusion there is a need for process models which can be run on-line to optimise settings and control disturbances. First-principle models demand computationally intensive solution, while ‘black box’ models lack generalisation ability and physical process insight. This work examines a novel ‘grey box’ modelling technique which incorporates both prior physical knowledge and empirical data in generating intuitive models of the process. The models can be related to the underlying physical mechanisms in the extruder and have been shown to capture unpredictable effects of the operating conditions on process instability. Furthermore, model parameters can be related to material properties available from laboratory analysis and as such, lend themselves to re-tuning for different materials without extensive remodelling work.

Synchronous Islanded Operation of a Diesel Generator

The amount of distributed generation connected to the distribution network is increasing. To use this resource more effectively, splitting of the distribution network, or islanding the system, for prevention of power outages is being considered by some utilities. In this paper an islanding method that avoids out-ofsynchronism re-closure is proposed. The island is kept in synchronism with the rest of the utility while it is not electrically connected. This is referred to as synchronous islanded operation. A phase difference control algorithm, developed by the authors, was tested in a single set scenario on a 50-kVA diesel generator using two different governors. These are the “standard product” variable gain governor of the diesel generator and a governor developed by the authors, which utilizes supplementary inputs in addition to engine speed. The results show that phase difference can be controlled within acceptable limits, both in steady state and after load disturbances are applied. The advantages of employing supplementary governor inputs are fully evaluated.

The influence of compliant surfaces on bypass transition', Experiments in Fluids

The objective of the work was to investigate the effect of compliant surfaces on the receptivity and bypass transition of a boundary layer. Hot wire measurements in the pre-transitional and transitional boundary layers on nine different compliant and one rigid surface with identical geometries were made. The experiments were conducted in air and the compliant surfaces were manufactured from gelatine covered by a 10 lm protective PVC film. The laminar boundary layer profiles and growth rate results were the same for all the surfaces. However, the receptivity of the laminar boundary layer to freestream disturbances increased close to the leading edge of each compliant surface. Further downstream the majority of the compliant surfaces were successful in reducing the receptivity to a value below that for the rigid surface. The transition onset position on the compliant surfaces ranged from 3% downstream to 20% upstream of the rigid surface position. It was concluded that compliant surfaces with optimum properties can reduce receptivity and delay transition.

Quaternary pollen analysis: recent progress in palaeoecology and palaeoclimatology

During the last decade Quaternary pollen analysis has developed towards improved pollen-taxonomical precision, automated pollen identification and more rigorous definition of pollen assemblage zones. There have been significant efforts to model the spatial representation of pollen records in lake sediments which is important for more precise interpretation of the pollen records in terms of past vegetation patterns. We review the difficulties in matching modelled post-glacial plant migration patterns with pollen-based palaeorecords and discuss the potential of DNA analysis of pollen to investigate the ancestry and past migration pathways of the plants. In population ecology there has been an acceleration of the widely advocated conceptual advance of pollen-analytical research from vaguely defined ‘environmental reconstructions’ towards investigating more precisely defined ecological problems aligned with the current ecological theories. Examples of such research have included an increasing number of investigations about the ecological impacts of past disturbances, often integrating pollen records with other palaeoecological data. Such an approach has also been applied to incorporate a time perspective to the questions of ecosystem restoration, nature conservation and forest management. New lines of research are the use of pollen analysis to study long-term patterns of vegetation diversity, such as the role of glacial-age vegetation fragmentation as a cause of Amazonian rain forest diversity, and to investigate links between pollen richness and past plant diversity. Palaeoclimatological use of pollen records has become more quantitative and has included more precise and rigorous testing of pollen-climate calibration models with modern climate data. These tests show the approximate nature of the models and warn against a too straightforward climatic interpretation of the small-scale variation in reconstructions. Pollenbased climate reconstructions over the Late Glacial–early Holocene boundary have indicated that pollen-stratigraphical changes have been rapid with no evidence for response lags. This does not rule out the possibility of migrational disequilibrium, however, as the rapid changes may be mostly due to nonmigrational responses of existing vegetation. It is therefore difficult to assess whether the amplitude of reconstructed climate change reflects real climate change. Other outstanding problems remain the obscure relationship of pollen production and climate, the role of human impact and other nonclimatic factors, and nonanalogue situations.

Dynamics of North Patagonian rainforests from fine-resolution pollen, charcoal and tree-ring analysis, Chonos Archipelago, Southern Chile

Fine-resolution palaeoecological and dendrochronological methods were used to investigate the impacts of climate change, and natural and anthropogenic disturbances on vegetation in the North Patagonian rainforest of southern Chile at decadal to century timescales during the late Holocene. A lake sediment mud–water interface core was collected from the northern Chonos Archipelago and analysed for pollen and charcoal. Dendrochronological analysis of tree cores collected from stands of Pilgerodendron uviferum close to the lake site was incorporated into the study. The combined analysis showed that the present mosaic of vegetation types in this region is a function of environmental changes across a range of timescales: millennial climate change, more recent natural and anthropogenic disturbances, and possibly short-term climatic variations. Of particular interest is the spatiotemporal distribution of Pilgerodendron uviferum dieback/burning in the Chonos Archipelago region.

A hierarchical physical model-based approach to predictive control of a thermal power plant for efficient plant-wide disturbance rejection

Extending the work presented in Prasad et al. (IEEE Proceedings on Control Theory and Applications, 147, 523-37, 2000), this paper reports a hierarchical nonlinear physical model-based control strategy to account for the problems arising due to complex dynamics of drum level and governor valve, and demonstrates its effectiveness in plant-wide disturbance handling. The strategy incorporates a two-level control structure consisting of lower-level conventional PI regulators and a higher-level nonlinear physical model predictive controller (NPMPC) for mainly set-point manoeuvring. The lower-level PI loops help stabilise the unstable drum-boiler dynamics and allow faster governor valve action for power and grid-frequency regulation. The higher-level NPMPC provides an optimal load demand (or set-point) transition by effective handling of plant-wide interactions and system disturbances. The strategy has been tested in a simulation of a 200-MW oil-fired power plant at Ballylumford in Northern Ireland. A novel approach is devized to test the disturbance rejection capability in severe operating conditions. Low frequency disturbances were created by making random changes in radiation heat flow on the boiler-side, while condenser vacuum was fluctuating in a random fashion on the turbine side. In order to simulate high-frequency disturbances, pulse-type load disturbances were made to strike at instants which are not an integral multiple of the NPMPC sampling period. Impressive results have been obtained during both types of system disturbances and extremely high rates of load changes, right across the operating range, These results compared favourably with those from a conventional state-space generalized predictive control (GPC) method designed under similar conditions.

Multiple Input Governor Control for a Diesel Generating Set

The paper presents a multiple input single output fuzzy logic governor algorithm that can be used to improve the transient response of a diesel generating set, when supplying an islanded load. The proposed governor uses the traditional speed input in addition to voltage and power factor to modify the fuelling requirements during various load disturbances. The use of fuzzy logic control allows the use of PID type structures that can provide variable gain strategies to account for non-linearities in the system. Fuzzy logic also provides a means of processing other input information by linguistic reasoning and a logical control output to aid the governor action during transient disturbance. The test results were obtained using a 50 kVA naturally aspirated diesel generator testing facility. Both real and reactive load tests were conducted. The complex load test results demonstrate that, by using additional inputs to the governor algorithm, enhanced generator transient speed recovery response can be obtained.

A framework for assessing the vulnerability of food systems to future shocks

Modem society depends on complex agro-ecological and trading systems to provide food for urban residents, yet there are few tools available to assess whether these systems are vulnerable to future disturbances. We propose a preliminary framework to assess the vulnerability of food systems to future shocks based on landscape ecology's 'Panarchy Framework'. According to Panarchy, ecosystem vulnerability is determined by three generic characteristics: (1) the wealth available in the system, (2) how connected the system is, and (3) how much diversity exists in the system. In this framework, wealthy, non-diverse, tightly connected systems are highly vulnerable. The wealth of food systems can be measured using the approach pioneered by development economists to assess how poverty affects food security. Diversity can be measured using the tools investors use to measure the diversity of investment portfolios to assess financial risk. The connectivity of a system can be evaluated with the tools chemists use to assess the pathways chemicals use to flow through the environment. This approach can lead to better tools for creating policy designed to reduce vulnerability, and can help urban or regional planners identify where food systems are vulnerable to shocks and disturbances that may occur in the future. (c) 2005 Elsevier Ltd. All rights reserved.

Plant-wide predictive control for a thermal power plant based on a physical plant model

A constrained non-linear, physical model-based, predictive control (NPMPC) strategy is developed for improved plant-wide control of a thermal power plant. The strategy makes use of successive linearisation and recursive state estimation using extended Kalman filtering to obtain a linear state-space model. The linear model and a quadratic programming routine are used to design a constrained long-range predictive controller One special feature is the careful selection of a specific set of plant model parameters for online estimation, to account for time-varying system characteristics resulting from major system disturbances and ageing. These parameters act as nonstationary stochastic states and help to provide sufficient degrees-of-freedom to obtain unbiased estimates of controlled outputs. A 14th order non-linear plant model, simulating the dominant characteristics of a 200 MW oil-fired pou er plant has been used to test the NPMPC algorithm. The control strategy gives impressive simulation results, during large system disturbances and extremely high rate of load changes, right across the operating range. These results compare favourably to those obtained with the state-space GPC method designed under similar conditions.

A time-domain approach to the analysis and modeling of on-body propagation characteristics using synchronized measurements at 2.45 GHz

Modeling of on-body propagation channels is of paramount importance to those wishing to evaluate radio channel performance for wearable devices in body area networks (BANs). Difficulties in modeling arise due to the highly variable channel conditions related to changes in the user's state and local environment. This study characterizes these influences by using time-series analysis to examine and model signal characteristics for on-body radio channels in user stationary and mobile scenarios in four different locations: anechoic chamber, open office area, hallway, and outdoor environment. Autocorrelation and cross-correlation functions are reported and shown to be dependent on body state and surroundings. Autoregressive (AR) transfer functions are used to perform time-series analysis and develop models for fading in various on-body links. Due to the non-Gaussian nature of the logarithmically transformed observed signal envelope in the majority of mobile user states, a simple method for reproducing the failing based on lognormal and Nakagami statistics is proposed. The validity of the AR models is evaluated using hypothesis testing, which is based on the Ljung-Box statistic, and the estimated distributional parameters of the simulator output compared with those from experimental results.