The Limnology of Three Limestone Rock Quarries in East-Central Nebraska and Western Iowa

Rock-quarry lakes provide a unique environment. The aim of this study was to obtain baseline limnological data on quarries, one in Iowa and two in Nebraska, which have not been previously investigated. The results show the general limnological trends of the quarries\u27 productivity. The mean oxygen, nutrient, pH, and phytoplankton-biomass values indicate the quarries are oligotrophic; however, one quarry has a profound depletion of oxygen in the summer and a large seasonal variation in alkalinity. A higher nitrogen concentration as well as more littoral plants suggests it to have more eutrophic potential than the other two quarries. Metal-ion analysis shows that the Ashland quarry had high levels of aluminum, and the North quarry had a moderate level of lead. The Logan quarry showed great concentrations of many elements, including lithium and uranium, which could account for its high specific conductivity. Further investigations should be carried out to provide a more detailed picture of these quarries

Climate justice and energy : applying international principles to UK residential energy policy

There are ethical, legal and strategic/pragmatic reasons why it is important to ensure a just approach to climate change mitigation, both internationally and within nations. Ethically, low income countries or groups can be considered to suffer an injustice if they contribute least to climate change while still suffering from its effects, and yet also have little influence in international decision making around mitigation and adaptation responses (Preston et al, 2014). Legally, equity is embedded in the ‘common and differentiated responsibility’ principles of the United Nations Framework Convention on Climate Change and in the provisions of the Kyoto Protocol (e.g. see Soltau, 2008). In the European context, the Aarhus Convention lays out rights to access to information, public participation in decision-making and access to justice in environmental matters.2 Pragmatically, people are more likely to accept climate change mitigation and adaptation policies if they reflect a fair balance of responsibility, capability, and need (Gross, 2007; Aylett, 2010), and wider participation and fair process can help with management of conflict and help to build consensus (Aylett 2010). Buell and Mayne (2011) also argue that just approaches to climate change actions have strategic and practical advantages because they can help ensure political support, mobilising hidden assets and generating wider socio-economic benefits than approaches based solely on narrow economic or financial criteria at lower financial cost. As recent public debate over fuel bills in the UK shows, there are strong public concerns about the fairness of energy policy, particularly where it affects energy prices, which in turn influence policy desig

Automating Vehicles by Deep Reinforcement Learning using Task Separation with Hill Climbing

Within the context of autonomous driving a model-based reinforcement learning algorithm is proposed for the design of neural network-parameterized controllers. Classical model-based control methods, which include sampling- and lattice-based algorithms and model predictive control, suffer from the trade-off between model complexity and computational burden required for the online solution of expensive optimization or search problems at every short sampling time. To circumvent this trade-off, a 2-step procedure is motivated: first learning of a controller during offline training based on an arbitrarily complicated mathematical system model, before online fast feedforward evaluation of the trained controller. The contribution of this paper is the proposition of a simple gradient-free and model-based algorithm for deep reinforcement learning using task separation with hill climbing (TSHC). In particular, (i) simultaneous training on separate deterministic tasks with the purpose of encoding many motion primitives in a neural network, and (ii) the employment of maximally sparse rewards in combination with virtual velocity constraints (VVCs) in setpoint proximity are advocated.Comment: 10 pages, 6 figures, 1 tabl

Assessment of Grass Production and Efficiency of Utilisation on Three Northern Ireland Dairy Farms

Recent research has shown that grazed grass can be an expensive forage for milk production, particularly if herbage production is low or utilisation is inefficient. There is very limited data on the level of herbage grown and utilised on commercial farms. The objective of this project was to quantify grass production and efficiency of utilisation on farm to substantiate the potential of grazed grass for profitable milk production

Temporal Correlations and Persistence in the Kinetic Ising Model: the Role of Temperature

We study the statistical properties of the sum $S_t=\int_{0}^{t}dt' \sigma_{t'}$, that is the difference of time spent positive or negative by the spin $\sigma_{t}$, located at a given site of a $D$-dimensional Ising model evolving under Glauber dynamics from a random initial configuration. We investigate the distribution of $S_{t}$ and the first-passage statistics (persistence) of this quantity. We discuss successively the three regimes of high temperature ($T>T_{c}$), criticality ($T=T_c$), and low temperature ($T<T_{c}$). We discuss in particular the question of the temperature dependence of the persistence exponent $\theta$, as well as that of the spectrum of exponents $\theta(x)$, in the low temperature phase. The probability that the temporal mean $S_t/t$ was always larger than the equilibrium magnetization is found to decay as $t^{-\theta-\frac12}$. This yields a numerical determination of the persistence exponent $\theta$ in the whole low temperature phase, in two dimensions, and above the roughening transition, in the low-temperature phase of the three-dimensional Ising model.Comment: 21 pages, 11 PostScript figures included (1 color figure

Geometric quantum computation using fictitious spin- 1/2 subspaces of strongly dipolar coupled nuclear spins

Geometric phases have been used in NMR, to implement controlled phase shift gates for quantum information processing, only in weakly coupled systems in which the individual spins can be identified as qubits. In this work, we implement controlled phase shift gates in strongly coupled systems, by using non-adiabatic geometric phases, obtained by evolving the magnetization of fictitious spin-1/2 subspaces, over a closed loop on the Bloch sphere. The dynamical phase accumulated during the evolution of the subspaces, is refocused by a spin echo pulse sequence and by setting the delay of transition selective pulses such that the evolution under the homonuclear coupling makes a complete $2\pi$ rotation. A detailed theoretical explanation of non-adiabatic geometric phases in NMR is given, by using single transition operators. Controlled phase shift gates, two qubit Deutsch-Jozsa algorithm and parity algorithm in a qubit-qutrit system have been implemented in various strongly dipolar coupled systems obtained by orienting the molecules in liquid crystal media.Comment: 37 pages, 17 figure

Whither discrete time model predictive control?

This note proposes an efficient computational procedure for the continuous time, input constrained, infinite horizon, linear quadratic regulator problem (CLQR). To ensure satisfaction of the constraints, the input is approximated as a piecewise linear function on a finite time discretization. The solution of this approximate problem is a standard quadratic program. A novel lower bound on the infinite dimensional CLQR problem is developed, and the discretization is adaptively refined until a user supplied error tolerance on the CLQR cost is achieved. The offline storage of the required quadrature matrices at several levels of discretization tailors the method for online use as required in model predictive control (MPC). The performance of the proposed algorithm is then compared with the standard discrete time MPC algorithms. The proposed method is shown to be significantly more efficient than standard discrete time MPC that uses a sample time short enough to generate a cost close to the CLQR solution