Vaccinia virus DNA replication: two hundred base pairs of telomeric sequence confer optimal replication efficiency on minichromosome templates.

Vaccinia virus is a complex DNA virus that exhibits significant genetic and physical autonomy from the host cell. Most if not all of the functions involved in replication and transcription of the 192-kb genome are virally encoded. Although significant progress has been made in identifying trans-acting factors involved in DNA synthesis, the mechanism of genome replication has remained poorly understood. The genome is a linear duplex with covalently closed hairpin termini, and it has been presumed that sequences and/or structures within these termini are important for the initiation of genome replication. In this report we describe the construction of minichromosomes containing a central plasmid insert flanked by hairpin termini derived from the viral genome and their use as replication templates. When replication of these minichromosomes was compared with a control substrate containing synthetic hairpin termini, specificity for viral telomeres was apparent. Inclusion of > or = 200 bp from the viral telomere was sufficient to confer optimal replication efficiency, whereas 65-bp telomeres were not effective. Chimeric 200-bp telomeres containing the 65-bp terminal element and 135 bp of ectopic sequence also failed to confer efficient replication, providing additional evidence that telomere function is sequence-specific. Replication of these exogenous templates was dependent upon the viral replication machinery, was temporally coincident with viral replication, and generated covalently closed minichromosome products. These data provide compelling evidence for specificity in template recognition and utilization in vaccinia virus-infected cells.

A Community Analysis of the Implementation for Household Curbside Recycling Programs: A Diversionary Method to Control Municipal Solid Waste

The Municipality of Anchorage (MOA) is required to better manage, operate and control municipal solid waste (MSW) after the Anchorage Assembly instituted a Zero Waste Policy. Two household curbside recycling programs (CRPs), pay-as-you-throw (PAYT) and single-stream, were compared and evaluated to determine an optimal municipal solid waste diversion method for households within the MOA. The analyses find: (1) a CRP must be designed from comprehensive analysis, models and data correlation that combine demographic and psychographic variables; and (2) CRPs can be easily adjusted towards community-specific goals using technology, such as Geographic Information System (GIS) and Radio Frequency Identification (RFID). Combining resources of policy-makers, businesses, and other viable actors are necessary components to produce a sustainable, economically viable curbside recycling program.

Optimal Design of a Hybrid Membrane System Combining Reverse and Forward Osmosis for Seawater Desalination

In this work we study Forward Osmosis (FO) as an emerging desalination technology, and its capability to replace totally or partially Reverse Osmosis (RO) in order to reduce the great amount of energy required in the current desalination plants. For this purpose, we propose a superstructure that includes both membrane based desalination technologies, allowing the selection of only one of the technologies or a combination of both of them seeking for the optimal configuration of the network. The optimization problem is solved for a seawater desalination plant with a given fresh water production. The results obtained show that the optimal solution combines both desalination technologies to reduce not only the energy consumption but also the total cost of the desalination process in comparison with the same plant but operating only with RO.

Practicality of time-optimal two-qubit Hamiltonian simulation

What is the time-optimal way of using a set of control Hamiltonians to obtain a desired interaction? Vidal, Hammerer, and Cirac [Phys. Rev. Lett. 88, 237902 (2002)] have obtained a set of powerful results characterizing the time-optimal simulation of a two-qubit quantum gate using a fixed interaction Hamiltonian and fast local control over the individual qubits. How practically useful are these results? We prove that there are two-qubit Hamiltonians such that time-optimal simulation requires infinitely many steps of evolution, each infinitesimally small, and thus is physically impractical. A procedure is given to determine which two-qubit Hamiltonians have this property, and we show that almost all Hamiltonians do. Finally, we determine some bounds on the penalty that must be paid in the simulation time if the number of steps is fixed at a finite number, and show that the cost in simulation time is not too great.

Optimally distributed actuator placement and control for a slewing single-link flexible manipulator

A method is proposed for determining the optimal placement and controller design for multiple distributed actuators to reduce the vibrations of flexible structures. In particular, application of piezoceramic patches to a horizontally-slewing single-link flexible manipulator modeled using the assumed modes method is investigated. The optimization method uses simulated annealing and allows placement of any number of distributed actuators of unequal length, although piezoceramics of fixed equal lengths are used in the example. It also designs an linear-quadratic-regulator controller as part of the optimization procedure. The measures of performance used in the investigation to determine optimality are the total mass of the system and the time integral of the absolute value of the hub and tip position error. This study also varies the relative weightings for each of these performance measures to observe the effects on the controller designs and piezoceramic patch positions in the optimized solutions.

Optimal strategies in political elections

In the Majoritarian Parliamentary System, the government has a constitutional right to call an early election. This right provides the government a control to achieve its objective to remain in power for as long as possible. We model the early election problem mathematically using opinion polls data as a stochastic process to proxy the government's probability of re-election. These data measure the difference in popularity between the government and the opposition. We fit a mean reverting Stochastic Differential Equation to describe the behaviour of the process and consider the possibility for the government to use other control tools, which are termed 'boosts' to induce shocks to the opinion polls by making timely policy announcements or economic actions. These actions improve the government's popularity and have some impact upon the early-election exercise boundary. © Austral. Mathematical Soc. 2005.

Properties of the stochastic Gross-Pitaevskii equation: finite temperature Ehrenfest relations and the optimal plane wave representation

We present Ehrenfest relations for the high temperature stochastic Gross-Pitaevskii equation description of a trapped Bose gas, including the effect of growth noise and the energy cutoff. A condition for neglecting the cutoff terms in the Ehrenfest relations is found which is more stringent than the usual validity condition of the truncated Wigner or classical field method-that all modes are highly occupied. The condition requires a small overlap of the nonlinear interaction term with the lowest energy single particle state of the noncondensate band, and gives a means to constrain dynamical artefacts arising from the energy cutoff in numerical simulations. We apply the formalism to two simple test problems: (i) simulation of the Kohn mode oscillation for a trapped Bose gas at zero temperature, and (ii) computing the equilibrium properties of a finite temperature Bose gas within the classical field method. The examples indicate ways to control the effects of the cutoff, and that there is an optimal choice of plane wave basis for a given cutoff energy. This basis gives the best reproduction of the single particle spectrum, the condensate fraction and the position and momentum densities.

Control of culture environment for improved polyethylenimine-mediated transient production of recombinant monoclonal antibodies by CHO cells

In this study we describe optimization of polyethylenimine (PEI)-mediated transient production of recombinant protein by CHO cells by facile manipulation of a chemically defined culture environment to limit accumulation of nonproductive cell biomass, increase the duration of recombinant protein production from transfected plasmid DNA, and increase cell-specific production. The optimal conditions for transient transfection of suspension-adapted CHO cells using branched, 25 kDa PEI as a gene delivery vehicle were experimentally determined by production of secreted alkaline phosphatase reporter in static cultures and recombinant IgG(4) monoclonal antibody (Mab) production in agitated shake flask cultures to be a DNA concentration of 1.25 mu g 10(6) cells(-1) mL(-1) at a PEI nitrogen: DNA phosphate ratio of 20:1. These conditions represented the optimal compromise between PEI cytotoxicity and product yield with most efficient recombinant DNA utilization. Separately, both addition of recombinant insulin-like growth factor (LR3-IGF) and a reduction in culture temperature to 32 degrees C were found to increase product titer 2- and 3-fold, respectively. However, mild hypothermia and LR3-IGF acted synergistically to increase product titer 11-fold. Although increased product titer in the presence of LR3-IGF alone was solely a consequence of increased culture duration, a reduction in culture temperature post-transfection increased both the integral of viable cell concentration (IVC) and cell-specific Mab production rate. For cultures maintained at 32 degrees C in the presence of LR3-IGF, IVC and qMab were increased 4- and 2.5-fold, respectively. To further increase product yield from transfected DNA, the duration of transgene expression in cell populations maintained at 32 C in the presence of LR3-IGF was doubled by periodic resuspension of transfected cells in fresh media, leading to a 3-fold increase in accumulated Mab titer from similar to 13 to similar to 39 mg L-1. Under these conditions, Mab glycosylation at Asn297 remained essentially constant and similar to that of the same Mab produced by stably transfected GS-CHO cells. From these data we suggest that the efficiency of transient production processes (protein output per rDNA input) can be significantly improved using a combination of mild hypothermia and growth factor(s) to yield an extended activated hypothermic synthesis.

Control of structured populations by harvest

It has long been recognized that demographic structure within a population can significantly affect the likely outcomes of harvest. Many studies have focussed on equilibrium dynamics and maximization of the value of the harvest taken. However, in some cases the management objective is to maintain the population at a abundance that is significantly below the carrying capacity. Achieving such an objective by harvest can be complicated by the presence of significant structure (age or stage) in the target population. in such cases, optimal harvest strategies must account for differences among age- or stage-classes of individuals in their relative contribution to the demography of the population. In addition, structured populations are also characterized by transient non-linear dynamics following perturbation, such that even under an equilibrium harvest, the population may exhibit significant momentum, increasing or decreasing before cessation of growth. Using simple linear time-invariant models, we show that if harvest levels are set dynamically (e.g., annually) then transient effects can be as or more important than equilibrium outcomes. We show that appropriate harvest rates can be complicated by uncertainty about the demographic structure of the population, or limited control over the structure of the harvest taken. (c) 2006 Elsevier B.V. All rights reserved.

Probability distribution modelling to improve stability in nonlinear MIMO control

We consider the direct adaptive inverse control of nonlinear multivariable systems with different delays between every input-output pair. In direct adaptive inverse control, the inverse mapping is learned from examples of input-output pairs. This makes the obtained controller sub optimal, since the network may have to learn the response of the plant over a larger operational range than necessary. Moreover, in certain applications, the control problem can be redundant, implying that the inverse problem is ill posed. In this paper we propose a new algorithm which allows estimating and exploiting uncertainty in nonlinear multivariable control systems. This approach allows us to model strongly non-Gaussian distribution of control signals as well as processes with hysteresis. The proposed algorithm circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider.

A methodology for analysis and control of discrete event dynamic systems

The rapid developments in computer technology have resulted in a widespread use of discrete event dynamic systems (DEDSs). This type of system is complex because it exhibits properties such as concurrency, conflict and non-determinism. It is therefore important to model and analyse such systems before implementation to ensure safe, deadlock free and optimal operation. This thesis investigates current modelling techniques and describes Petri net theory in more detail. It reviews top down, bottom up and hybrid Petri net synthesis techniques that are used to model large systems and introduces on object oriented methodology to enable modelling of larger and more complex systems. Designs obtained by this methodology are modular, easy to understand and allow re-use of designs. Control is the next logical step in the design process. This thesis reviews recent developments in control DEDSs and investigates the use of Petri nets in the design of supervisory controllers. The scheduling of exclusive use of resources is investigated and an efficient Petri net based scheduling algorithm is designed and a re-configurable controller is proposed. To enable the analysis and control of large and complex DEDSs, an object oriented C++ software tool kit was developed and used to implement a Petri net analysis tool, Petri net scheduling and control algorithms. Finally, the methodology was applied to two industrial DEDSs: a prototype can sorting machine developed by Eurotherm Controls Ltd., and a semiconductor testing plant belonging to SGS Thomson Microelectronics Ltd.

The factors affecting the optimal performance of eddy-current machines

This thesis presents an examination of the factors which influence the performance of eddy-current machines and the way in which they affect optimality of those machines. After a brief introduction to the types of eddy-current machine considered, the applications to which these machines are put are examined. A list of parameters by which to assess their performance is obtained by considering the machine as part of a system. in this way an idea of what constitutes an optimal machine is obtained. The third chapter then identifies the factors which affects the performance and makes a quantitative evaluation of the effect. Here the various alternative configurations and components are compared with regard to their influence on the mechanical, electromagnetic, and thermal performance criteria of the machine. Chapter four contains a brief review of the methods of controlling eddy-current machines by electronic methods using thyristors or transistors as the final control element. Where necessary, the results of previous workers in the field of electrical machines have been extended or adapted to increase the usefulness of this thesis.

Fully probabilistic control for stochastic nonlinear control systems with input dependent noise

Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibler divergence between the actual joint probability density function (pdf) of the closed loop control system, and an ideal joint pdf is presented emphasising how the uncertainty can be systematically incorporated in the absence of reliable systems models. To achieve this objective all probabilistic models of the system are estimated from process data using mixture density networks (MDNs) where all the parameters of the estimated pdfs are taken to be state and control input dependent. Based on this dependency of the density parameters on the input values, explicit formulations to the construction of optimal generalised probabilistic controllers are obtained through the techniques of dynamic programming and adaptive critic methods. Using the proposed generalised probabilistic controller, the conditional joint pdfs can be made to follow the ideal ones. A simulation example is used to demonstrate the implementation of the algorithm and encouraging results are obtained.

Fully probabilistic control design in an adaptive critic framework

Optimal stochastic controller pushes the closed-loop behavior as close as possible to the desired one. The fully probabilistic design (FPD) uses probabilistic description of the desired closed loop and minimizes Kullback-Leibler divergence of the closed-loop description to the desired one. Practical exploitation of the fully probabilistic design control theory continues to be hindered by the computational complexities involved in numerically solving the associated stochastic dynamic programming problem. In particular very hard multivariate integration and an approximate interpolation of the involved multivariate functions. This paper proposes a new fully probabilistic contro algorithm that uses the adaptive critic methods to circumvent the need for explicitly evaluating the optimal value function, thereby dramatically reducing computational requirements. This is a main contribution of this short paper.