Measles virus and classical Hodgkin lymphoma: no evidence for a direct association.

A proportion of Hodgkin lymphoma (HL) cases are causally associated with the Epstein-Barr virus (EBV) but the aetiology of the remaining cases remains obscure. Over the last 3 decades several studies have found an association between HL and measles virus (MV) including a recent cohort study describing the detection of MV antigens in Hodgkin and Reed-Sternberg cells, the tumour cells in HL. In the present study we looked at the relationship between history of MV infection and risk of developing HL in a population-based, case/control study of HL. In addition we used immunohistochemistry and RT-PCR to look for direct evidence of MV in HL biopsies. There was no significant difference in the proportion of cases reporting previous measles compared to controls in the entire data set or when young adults were considered separately. Using a robust immunohistochemical assay for MV infection, we failed to find evidence of MV in biopsies from 97 cases of HL and RT-PCR studies similarly gave negative results. This study therefore provides no evidence that MV is directly involved in the development of HL. However, when age at first reported MV infection was investigated, significant differences emerged with children infected before school-age having higher risk, especially of EBV-ve HL, when compared with children infected at older ages; the interpretation of these latter results is unclear.

Robustness of Damping Control Implemented by Energy Storage Systems Installed in Power Systems

An energy storage system (ESS) installed in a power system can effectively damp power system oscillations through controlling exchange of either active or reactive power between the ESS and power system. This paper investigates the robustness of damping control implemented by the ESS to the variations of power system operating conditions. It proposes a new analytical method based on the well-known equal-area criterion and small-signal stability analysis. By using the proposed method, it is concluded in the paper that damping control implemented by the ESS through controlling its active power exchange with the power system is robust to the changes of power system operating conditions. While if the ESS damping control is realized by controlling its reactive power exchange with the power system, effectiveness of damping control changes with variations of power system operating condition. In the paper, an example power system installed with a battery ESS (BESS) is presented. Simulation results confirm the analytical conclusions made in the paper about the robustness of ESS damping control. Laboratory experiment of a physical power system installed with a 35kJ/7kW SMES (Superconducting Magnetic Energy Storage) was carried out to evaluate theoretical study. Results are given in the paper, which demonstrate that effectiveness of SMES damping control realized through regulating active power is robust to changes of load conditions of the physical power system.

Allocating transmission loss to loads and generators through complex power flow tracing

This paper presents a new method for complex power flow tracing that can be used for allocating the transmission loss to loads or generators. Two algorithms for upstream tracing (UST) and downstream tracing (DST) of the complex power are introduced. UST algorithm traces the complex power extracted by loads back to source nodes and assigns a fraction of the complex power flow through each line to each load. DST algorithm traces the output of the generators down to the sink nodes determining the contributions of each generator to the complex power flow and losses through each line. While doing so, active- and reactive-power flows as well as complex losses are considered simultaneously, not separately as most of the available methods do. Transmission losses are taken into consideration during power flow tracing. Unbundling line losses are carried out using an equation, which has a physical basis, and considers the coupling between active- and reactive-power flows as well as the cross effects of active and reactive powers on active and reactive losses. The tracing algorithms introduced can be considered direct to a good extent, as there is no need for exhaustive search to determine the flow paths as these are determined in a systematic way during the course of tracing. Results of application of the proposed method are also presented.

Neural modelling, control and optimisation of an industrial grinding process

This paper describes the development of neural model-based control strategies for the optimisation of an industrial aluminium substrate disk grinding process. The grindstone removal rate varies considerably over a stone life and is a highly nonlinear function of process variables. Using historical grindstone performance data, a NARX-based neural network model is developed. This model is then used to implement a direct inverse controller and an internal model controller based on the process settings and previous removal rates. Preliminary plant investigations show that thickness defects can be reduced by 50% or more, compared to other schemes employed. (c) 2004 Elsevier Ltd. All rights reserved.

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.

Glycemic index, glycemic load, and risk of digestive tract neoplasms: a systematic review and meta-analysis

Background: Habitual consumption of diets with a high glycemic index (GI) and a high glycemic load (GL) may influence cancer risk via hyperinsulinemia and the insulin-like growth factor axis.
Objective: The objective was to conduct a systematic review to assess the association between GI, GL, and risk of digestive tract cancers.
Design: Medline and Embase were searched for relevant publications from inception to July 2008. When possible, adjusted results from a comparison of cancer risk of the highest compared with the lowest category of GI and GL intake were combined by using random-effects meta-analyses.
Results: Cohort and case-control studies that examined the risk between GI or GL intake and colorectal cancer (n = 12) and adenomas (n = 2), pancreatic cancer (n = 6), gastric cancer (n = 2), and squamous-cell esophageal carcinoma (n = 1) were retrieved. Most case-control studies observed positive associations between GI and GL intake and these cancers. However, pooled cohort study results showed no associations between colorectal cancer risk and GI intake [relative risk (RR): 1.04; 95% CI: 0.92, 1.12; n = 7 studies] or GL intake (RR: 1.06; 95% CI: 0.95, 1.17; n = 8 studies). Furthermore, no significant associations were observed in meta-analyses of cohort study results of colorectal cancer subsites and GI and GL intake. Similarly, no significant associations emerged between pancreatic cancer risk and GI intake (RR: 0.99; 95% CI: 0.83, 1.19; n = 5 studies) or GL intake (RR: 1.01; 95% CI: 0.86, 1.19; n = 6 studies) in combined cohort studies.
Conclusions: The findings from our meta-analyses indicate that GI and GL intakes are not associated with risk of colorectal or pancreatic cancers. There were insufficient data available regarding other digestive tract cancers to make any conclusions about GI or GL intake and risk.

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.

Pathways to state-selective control of vibrational wavepackets in the deuterium molecular ion

The capability of intense ultrashort laser pulses to initiate, control and image vibrational wavepacket dynamics in the deuterium molecular ion has been simulated with a view to inform and direct future femtosecond pump-control-probe experiments. The intense-field coherent control of the vibrational superposition has been studied as a function of pulse intensity and delay time, to provide an indication of key constraints for experimental studies. For selected cases of the control mechanism, probing of the subsequent vibrational wavepacket dynamics has been simulated via the photodissociation (PD) channel. Such PD probing is shown to elucidate the modified wavepacket dynamics where the position of the quantum revival is sensitive to the control process. Through Fourier transform analysis the PD yield is also shown to provide a characterisation of the vibrational distribution. It has been shown that a simple 'critical R cut-off' approximation can be used to reproduce the effect of a probe pulse interaction, providing a convenient and efficient alternative to intensive computer simulations of the PD mechanism in the deuterium molecular ion.

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.

Neural network based control for synchronous generators

In this paper, a Radial Basis Function neural network based AVR is proposed. A control strategy which generates local linear models from a global neural model on-line is used to derive controller feedback gains based on the Generalised Minimum Variance technique. Testing is carried out on a micromachine system which enables evaluation of practical implementation of the scheme. Constraints imposed by gathering training data, computational load, and memory requirements for the training algorithm are addressed.

The Yin and Yang of vitamin D receptor (VDR) signaling in neoplastic progression: Operational networks and tissue-specific growth control

Substantive evidence implicates vitamin D receptor (VDR) or its natural ligand 1a,25-(OH)2 D3 in modulation of tumor growth. However, both human and animal studies indicate tissue-specificity of effect. Epidemiological studies show both inverse and direct relationships between serum 25(OH)D levels and common solid cancers. VDR ablation affects carcinogen-induced tumorigenesis in a tissue-specific manner in model systems. Better understanding of the tissue-specificity of vitamin D-dependent molecular networks may provide insight into selective growth control by the seco-steroid, 1a,25-(OH)2 D3. This commentary considers complex factors that may influence the cell- or tissue-specificity of 1a,25-(OH)2 D3/VDR growth effects, including local synthesis, metabolism and transport of vitamin D and its metabolites, vitamin D receptor (VDR) expression and ligand-interactions, 1a,25-(OH)2 D3 genomic and non-genomic actions, Ca2+ flux, kinase activation, VDR interactions with activating and inhibitory vitamin D responsive elements (VDREs) within target gene promoters, VDR coregulator recruitment and differential effects on key downstream growth regulatory genes. We highlight some differences of VDR growth control relevant to colonic, esophageal, prostate, pancreatic and other cancers and assess the potential for development of selective prevention or treatment strategies.

Retinal pericytes control expression of nitric oxide synthase and endothelin-1 in microvascular endothelial cells

Pericytes are known to communicate with endothelial cells by direct contact and by releasing cytokines such as TGF-beta. There is also strong evidence that pericytes act as regulators of endothelial cell proliferation and differentiation. We have investigated the effect of pericyte-conditioned medium (PCM) on proliferation of human microvascular endothelial cells in vitro, together with the expression of the vasoregulatory molecules, constitutive and inducible nitric oxide synthases (ecNOS and iNOS), and endothelin-1 (ET-1). Expression was measured at the mRNA level using semiquantitative RT-PCR for all three genes and at the protein level for ecNOS and iNOS using Western blotting. Growth curves for HMECs showed that PCM inhibits proliferation, eventually leading to cell death. Exposure to PCM repressed iNOS mRNA expression fivefold after 6 h. A similar, though delayed, reduction in protein levels was observed. ecNOS mRNA was slightly induced at 6 h, though there was no significant change in ecNOS protein. By contrast, ET-1 mRNA was induced 2.3-fold after 6 h exposure to PCM. We conclude that pericytes release a soluble factor or factors that are potent inhibitors of endothelial cell growth and promote vasoconstriction by up-regulating endothelin-1 and down-regulating iNOS. (C) 2000 Academic Press.

Replication of EPHA1 and CD33 associations with late-onset Alzheimer’s disease: a multi-centre case-control study

A recently published genome-wide association study (GWAS) of late-onset Alzheimer's disease (LOAD) revealed genome-wide significant association of variants in or near MS4A4A, CD2AP, EPHA1 and CD33. Meta-analyses of this and a previously published GWAS revealed significant association at ABCA7 and MS4A, independent evidence for association of CD2AP, CD33 and EPHA1 and an opposing yet significant association of a variant near ARID5B. In this study, we genotyped five variants (in or near CD2AP, EPHA1, ARID5B, and CD33) in a large (2,634 LOAD, 4,201 controls), independent dataset comprising six case-control series from the USA and Europe. We performed meta-analyses of the association of these variants with LOAD and tested for association using logistic regression adjusted by age-at-diagnosis, gender, and APOE e4 dosage.

Working Memory and Postural Control: Adult Age Differences in Potential for Improvement, Task Priority, and Dual Tasking

We investigate dynamic posture control and working memory (NBack) retest practice in young and older adults, focusing on older adults' potential for improvement in the component tasks but more importantly in dual-task performance. Participants performed the 2 tasks in 11 sessions under single- and dual-task conditions. Posture improvement was observed with retest practice for both groups. Increase in cognitive load after initial practice led to greater dual-task costs in both tasks in older adults and higher costs in memory in young adults. With continued practice, costs were reduced by both groups; however, the 2 groups focused improvement on different tasks: Older adults focused on posture but young adults on cognition. These results emphasize older adults' potential for improvement in dual-task performance and their flexibility to utilize the practice gains in posture to optimize cognitive performance.