An agent-based control mechanism for WFQ in IP networks

This paper presents a new packet scheduling scheme called agent-based WFQ to control and maintain QoS parameters in virtual private networks (VPNs) within the confines of adaptive networks. Future networks are expected to be open heterogeneous environments consisting of more than one network operator. In this adaptive environment, agents act on behalf of users or third-party operators to obtain the best service for their clients and maintain those services through the modification of the scheduling scheme in routers and switches spanning the VPN. In agent-based WFQ, an agent on the router monitors the accumulated queuing delay for each service. In order to control and to keep the end-to-end delay within the bounds, the weights for services are adjusted dynamically by agents on the routers spanning the VPN. If there is an increase or decrease in queuing delay of a service, an agent on a downstream router informs the upstream routers to adjust the weights of their queues. This keeps the end-to-end delay of services within the specified bounds and offers better QoS compared to VPNs using static WFQ. This paper also describes the algorithm for agent-based WFQ, and presents simulation results. (C) 2003 Elsevier Science Ltd. All rights reserved.

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.

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.

A Soft Sensor for Viscosity Control of Polymer Extrusion

Viscosity represents a key indicator of product quality in polymer extrusion but has traditionally been difficult to measure in-process in real-time. An innovative, yet simple, solution to this problem is proposed by a Prediction-Feedback observer mechanism. A `Prediction' model based on the operating conditions generates an open-loop estimate of the melt viscosity; this estimate is used as an input to a second, `Feedback' model to predict the pressure of the system. The pressure value is compared to the actual measured melt pressure and the error used to correct the viscosity estimate. The Prediction model captures the relationship between the operating conditions and the resulting melt viscosity and as such describes the specific material behavior. The Feedback model on the other hand describes the fundamental physical relationship between viscosity and extruder pressure and is a function of the machine geometry. The resulting system yields viscosity estimates within 1% error, shows excellent disturbance rejection properties and can be directly applied to model-based control. This is of major significance to achieving higher quality and reducing waste and set-up times in the polymer extrusion industry.

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.

On velocity-based local model networks for nonlinear identification

This paper exposes the strengths and weaknesses of the recently proposed velocity-based local model (LM) network. The global dynamics of the velocity-based blended representation are directly related to the dynamics of the underlying local models, an important property in the design of local controller networks. Furthermore, the sub-models are continuous-time and linear providing continuity with established linear theory and methods. This is not true for the conventional LM framework, where the global dynamics are only weakly related to the affine sub-models. In this paper, a velocity-based multiple model network is identified for a highly nonlinear dynamical system. The results show excellent dynamical modelling performances, highlighting the value of the velocity-based approach for the design and analysis of LM based control. Three important practical issues are also addressed. These relate to the blending of the velocity-based local models, the use of normalised Gaussian basis functions and the requirement of an input derivative.

Design and Implementation of a Measurement-Based Policy-Driven Resource Management Framework For Converged Networks

This paper presents the design and implementation of a measurement-based QoS and resource management framework, CNQF (Converged Networks’ QoS Management Framework). CNQF is designed to provide unified, scalable QoS control and resource management through the use of a policy-based network
management paradigm. It achieves this via distributed functional entities that are deployed to co-ordinate the resources of the transport network through centralized policy-driven decisions supported by measurement-based control architecture. We present the CNQF architecture, implementation of the
prototype and validation of various inbuilt QoS control mechanisms using real traffic flows on a Linux-based experimental test bed.

Towards optical polarization control of laser-driven proton acceleration in foils undergoing relativistic transparency

Control of the collective response of plasma particles to intense laser light is intrinsic to relativistic optics, the development of compact laser-driven particle and radiation sources, as well as investigations of some laboratory astrophysics phenomena. We recently demonstrated that a relativistic plasma aperture produced in an ultra-thin foil at the focus of intense laser radiation can induce diffraction, enabling polarization-based control of the collective motion of plasma electrons. Here we show that under these conditions the electron dynamics are mapped into the beam of protons accelerated via strong charge-separation-induced electrostatic fields. It is demonstrated experimentally and numerically via 3D particle-in-cell simulations that the degree of ellipticity of the laser polarization strongly influences the spatial-intensity distribution of the beam of multi-MeV protons. The influence on both sheath-accelerated and radiation pressure-accelerated protons is investigated. This approach opens up a potential new route to control laser-driven ion sources.

Getting to the root of neuronal signalling in plant-parasitic nematodes using RNA interference

A variety of genes expressed in preparasitic second-stage juveniles (J2) of plant-parasitic nematodes appear to be vulnerable to RNA interference (RNAi) in vitro by coupling double-stranded (ds)RNA soaking with the artificial stimulation of pharyngeal pumping. Also, there is mounting evidence that the in planta generation of nematode-specific double-stranded RNAs (dsRNAs) has real utility in the control of these pests. Although neuronally-expressed genes in Caenorhabditis elegans are commonly refractory to RNAi, we have discovered that neuronally-expressed genes in plant-parasitic nematodes are highly susceptible to RNAi and that silencing can be induced by simple soaking procedures without the need for pharyngeal stimulation. Since most front-line anthelmintics that are used for the control of nematode parasites of animals and humans act to disrupt neuromuscular coordination, we argue that intercellular signalling processes associated with neurons have much appeal as targets for transgenic plant-based control strategies for plant-parasitic nematodes. FMRFamide-like peptides (FLPs) are a large family of neuropeptides which are intimately associated with neuromuscular regulation, and our studies on flp gene function in plant-parasitic nematodes have revealed that their expression is central to coordinated locomotory activities. We propose that the high level of conservation in nervous systems across nematodes coupled with the RNAi-susceptibility of neuronally-expressed genes in plant-parasitic nematodes provides a valuable research tool which could be used to interrogate neuronal signalling processes in nematodes.

Comparisons between different polychemotherapy regimens for early breast cancer: meta-analyses of long-term outcome among 100,000 women in 123 randomised trials

Background Moderate di?erences in e?cacy between adjuvant chemotherapy regimens for breast cancer are plausible, and could a? ect treatment choices. We sought any such di?erences.

Methods We undertook individual-patient-data meta-analyses of the randomised trials comparing: any taxane-plusanthracycline-based regimen versus the same, or more, non-taxane chemotherapy (n=44 000); one anthracyclinebased regimen versus another (n=7000) or versus cyclo phosphamide, methotrexate, and ?uorouracil (CMF; n=18 000); and polychemotherapy versus no chemotherapy (n=32 000). The scheduled dosages of these three drugs and of the anthracyclines doxorubicin (A) and epirubicin (E) were used to de? ne standard CMF, standard 4AC, and CAF and CEF. Log-rank breast cancer mortality rate ratios (RRs) are reported.

Findings In trials adding four separate cycles of a taxane to a ?xed anthracycline-based control regimen, extending treatment duration, breast cancer mortality was reduced (RR 0·86, SE 0·04, two-sided signi?cance [2p]=0·0005). In trials with four such extra cycles of a taxane counterbalanced in controls by extra cycles of other cytotoxic drugs, roughly doubling non-taxane dosage, there was no signi?cant di?erence (RR 0·94, SE 0·06, 2p=0·33). Trials with CMF-treated controls showed that standard 4AC and standard CMF were equivalent (RR 0·98, SE 0·05, 2p=0·67), but that anthracycline-based regimens with substantially higher cumulative dosage than standard 4AC (eg, CAF or CEF) were superior to standard CMF (RR 0·78, SE 0·06, 2p=0·0004). Trials versus no chemotherapy also suggested greater mortality reductions with CAF (RR 0·64, SE 0·09, 2p<0·0001) than with standard 4AC (RR 0·78, SE 0·09, 2p=0·01) or
standard CMF (RR 0·76, SE 0·05, 2p<0·0001). In all meta-analyses involving taxane-based or anthracycline-based regimens, proportional risk reductions were little a? ected by age, nodal status, tumour diameter or di?erentiation (moderate or poor; few were well di?erentiated), oestrogen receptor status, or tamoxifen use. Hence, largely independently of age (up to at least 70 years) or the tumour characteristics currently available to us for the patients selected to be in these trials, some taxane-plus-anthracycline-based or higher-cumulative-dosage anthracycline-based regimens (not requiring stem cells) reduced breast cancer mortality by, on average, about one-third. 10-year overall mortality di?erences paralleled breast cancer mortality di?erences, despite taxane, anthracycline, and other toxicities.

Interpretation 10-year gains from a one-third breast cancer mortality reduction depend on absolute risks without chemotherapy (which, for oestrogen-receptor-positive disease, are the risks remaining with appropriate endocrine therapy). Low absolute risk implies low absolute bene?t, but information was lacking about tumour gene expression markers or quantitative immunohistochemistry that might help to predict risk, chemosensitivity, or both.

Neuropeptides in Helminths: Occurrence and Distribution

Nematode neuropeptide systems comprise an exceptionally complex array of similar to 250 peptidic signaling molecules that operate within a structurally simple nervous system of similar to 300 neurons. A relatively complete picture of the neuropeptide complement is available for Caenorhabditis elegans, with 30 flp, 38 ins and 43 nlp genes having been documented; accumulating evidence indicates similar complexity in parasitic nematodes from clades I, III, IV and V. In contrast, the picture for parasitic platyhelminths is less clear, with the limited peptide sequence data available providing concrete evidence for only FMRFamide-like peptide (FLP) and neuropeptide F (NPF) signaling systems, each of which only comprises one or two peptides. With the completion of the Schmidtea meditteranea and Schistosoma mansoni genome projects and expressed sequence tag datasets for other flatworm parasites becoming available, the time is ripe for a detailed reanalysis of neuropeptide signaling in flatworms. Although the actual neuropeptides provide limited obvious value as targets for chemotherapeutic-based control strategies, they do highlight the signaling systems present in these helminths and provide tools for the discovery of more amenable targets such as neuropeptide receptors or neuropeptide processing enzymes. Also, they offer opportunities to evaluate the potential of their associated signaling pathways as targets through RNA interference (RNAi)-based, target validation strategies. Currently, within both helminth phyla, the flp signaling systems appear to merit further investigation as they are intrinsically linked with motor function, a proven target for successful anti-parasitics; it is clear that some nematode NLPs also play a role in motor function and could have similar appeal. At this time, it is unclear if flatworm NPF and nematode INS peptides operate in pathways that have utility for parasite control. Clearly, RNAi-based validation could be a starting point for scoring potential target pathways within neuropeptide signaling for parasiticide discovery programs. Also, recent successes in the application of in planta-based RNAi control strategies for plant parasitic nematodes reveal a strategy whereby neuropeptide encoding genes could become targets for parasite control. The possibility of developing these approaches for the control of animal and human parasites is intriguing, but will require significant advances in the delivery of RNAi-triggers.

Tacrolimus is not associated with gingival overgrowth in renal transplant patients

BACKGROUND: Cyclosporin A is used extensively to prevent the rejection of allogenic renal transplants. However, it is associated with a variety of undesirable side effects including gingival overgrowth. Tacrolimus (FK506), has been marketed as an effective alternative immunosuppressant to cyclosporin A and recent subjective reports suggest patients taking it complain infrequently of gingival problems. This clinical investigation was undertaken to confirm whether or not tacrolimus adversely affected the gingival health of renal transplant recipients.

METHODS: Renal transplant patients (RTPs) under the care of the Renal Transplantation Service at the Manchester Royal Infirmary, who had received a renal allograft at least 18 months earlier, were recruited for this study. All but one of the RTPs had been taking tacrolimus since transplantation. The other had commenced tacrolimus therapy two months after receiving her allograft. A hospital based control group was recruited from non transplanted individuals attending the Turner Dental School, Manchester. Each patient underwent a detailed dental assessment and had dental impressions taken. The extent of gingival overgrowth was determined from plaster models.

RESULTS: 25 renal transplant recipients and 26 control patients were included in the study. None of the individuals in either the tacrolimus or control groups had clinically significant overgrowth. The patients in the tacrolimus group with the highest overgrowth scores were those also taking calcium antagonists as treatment for hypertension.

CONCLUSION: This study demonstrates that tacrolimus has no adverse effects on the gingival tissues and thus has potential as an alternative immunosuppressant for individuals susceptible to developing cyclosporin A-induced gingival overgrowth.