Coherent quantum LQG control

Based on a recently developed notion of physical realizability for quantum linear stochastic systems, we formulate a quantum LQG optimal control problem for quantum linear stochastic systems where the controller itself may also be a quantum system and the plant output signal can be fully quantum. Such a control scheme is often referred to in the quantum control literature as "coherent feedback control.'' It distinguishes the present work from previous works on the quantum LQG problem where measurement is performed on the plant and the measurement signals are used as input to a fully classical controller with no quantum degrees of freedom. The difference in our formulation is the presence of additional non-linear and linear constraints on the coefficients of the sought after controller, rendering the problem as a type of constrained controller design problem. Due to the presence of these constraints our problem is inherently computationally hard and this also distinguishes it in an important way from the standard LQG problem. We propose a numerical procedure for solving this problem based on an alternating projections algorithm and, as initial demonstration of the feasibility of this approach, we provide fully quantum controller design examples in which numerical solutions to the problem were successfully obtained. For comparison, we also consider the case of classical linear controllers that use direct or indirect measurements, and show that there exists a fully quantum linear controller which offers an improvement in performance over the classical ones.Comment: 25 pages, 1 figure, revised and corrected version (mainly to Section 8). To be published in Automatica, Journal of IFAC, 200

Effects of Local and Landscape Factors on Population Dynamics of a Cotton Pest

BACKGROUND: Many polyphagous pests sequentially use crops and uncultivated habitats in landscapes dominated by annual crops. As these habitats may contribute in increasing or decreasing pest density in fields of a specific crop, understanding the scale and temporal variability of source and sink effects is critical for managing landscapes to enhance pest control. METHODOLOGY/PRINCIPAL FINDINGS: We evaluated how local and landscape characteristics affect population density of the western tarnished plant bug, Lygus hesperus (Knight), in cotton fields of the San Joaquin Valley in California. During two periods covering the main window of cotton vulnerability to Lygus attack over three years, we examined the associations between abundance of six common Lygus crops, uncultivated habitats and Lygus population density in these cotton fields. We also investigated impacts of insecticide applications in cotton fields and cotton flowering date. Consistent associations observed across periods and years involved abundances of cotton and uncultivated habitats that were negatively associated with Lygus density, and abundance of seed alfalfa and cotton flowering date that were positively associated with Lygus density. Safflower and forage alfalfa had variable effects, possibly reflecting among-year variation in crop management practices, and tomato, sugar beet and insecticide applications were rarely associated with Lygus density. Using data from the first two years, a multiple regression model including the four consistent factors successfully predicted Lygus density across cotton fields in the last year of the study. CONCLUSIONS/SIGNIFICANCE: Our results show that the approach developed here is appropriate to characterize and test the source and sink effects of various habitats on pest dynamics and improve the design of landscape-level pest management strategies

Effect of variable transmission rate on the dynamics of HIV in sub-Saharan Africa

<p>Abstract</p> <p>Background</p> <p>The cause of the high HIV prevalence in sub-Saharan Africa is incompletely understood, with heterosexual penile-vaginal transmission proposed as the main mechanism. Heterosexual HIV transmission has been estimated to have a very low probability; but effects of cofactors that vary in space and time may substantially alter this pattern.</p> <p>Methods</p> <p>To test the effect of individual variation in the HIV infectiousness generated by co-infection, we developed and analyzed a mathematical sexual network model that simulates the behavioral components of a population from Malawi, as well as the dynamics of HIV and the co-infection effect caused by other infectious diseases, including herpes simplex virus type-2, gonorrhea, syphilis and malaria.</p> <p>Results</p> <p>The analysis shows that without the amplification effect caused by co-infection, no epidemic is generated, and HIV prevalence decreases to extinction. But the model indicates that an epidemic can be generated by the amplification effect on HIV transmission caused by co-infection.</p> <p>Conclusion</p> <p>The simulated sexual network demonstrated that a single value for HIV infectivity fails to describe the dynamics of the epidemic. Regardless of the low probability of heterosexual transmission per sexual contact, the inclusion of individual variation generated by transient but repeated increases in HIV viral load associated with co-infections may provide a biological basis for the accelerated spread of HIV in sub-Saharan Africa. Moreover, our work raises the possibility that the natural history of HIV in sub-Saharan Africa cannot be fully understood if individual variation in infectiousness is neglected.</p

To what extent has Sustainable Intensification in England been achieved?

Agricultural intensification has significantly increased yields and fed growing populations across the planet, but has also led to considerable environmental degradation. In response an alternative process of ‘Sustainable Intensification’ (SI), whereby food production increases while environmental impacts are reduced, has been advocated as necessary, if not sufficient, for delivering food and environmental security. However, the extent to which SI has begun, the main drivers of SI, and the degree to which degradation is simply ‘offshored’ are uncertain. In this study we assess agroecosystem services in England and two contrasting sub-regions, majority-arable Eastern England and majority-pastoral South-Western England, since 1950 by analysing ecosystem service metrics and developing a simple system dynamics model. We find that rapid agricultural intensification drove significant environmental degradation in England in the early 1980s, but that most ecosystem services except farmland biodiversity began to recover after 2000, primarily due to reduced livestock and fertiliser usage decoupling from high yields. This partially follows the trajectory of an Environmental Kuznets Curve, with yields and GDP growth decoupling from environmental degradation above ~£17,000 per capita per annum. Together, these trends suggest that SI has begun in England. However, the lack of recovery in farmland biodiversity, and the reduction in UK food self-sufficiency resulting in some agricultural impacts being ‘offshored’, represent major negative trade-offs. Maintaining yields and restoring biodiversity while also addressing climate change, offshored degradation, and post-Brexit subsidy changes will require significant further SI in the future