Endogenous fisheries management in a stochastic model: Why do fishery agencies use TAC

The aim of this paper is to explain under which circumstances using TACs as instrument to manage a fishery along with fishing periods may be interesting from a regulatory point of view. In order to do this, the deterministic analysis of Homans and Wilen (1997)and Anderson (2000) is extended to a stochastic scenario where the resource cannot be measured accurately. The resulting endogenous stochastic model is numerically solved for finding the optimal control rules in the Iberian sardine stock. Three relevant conclusions can be highligted from simulations. First, the higher the uncertainty about the state of the stock is, the lower the probability of closing the fishery is. Second, the use of TACs as management instrument in fisheries already regulated with fishing periods leads to: i) An increase of the optimal season length and harvests, especially for medium and high number of licences, ii) An improvement of the biological and economic variables when the size of the fleet is large; and iii) Eliminate the extinction risk for the resource. And third, the regulator would rather select the number of licences and do not restrict the season length.

Starting Nozzle Flow Simulation Using K-G Two-Equation Turbulence Model

The starting process of two-dimensional nozzle flows has been simulated with Euler, laminar and k - g two-equation turbulence Navier-Stokes equations. The flow solver is based on a combination of LUSGS subiteration implicit method and five spatial discretized schemes, which are Roe, HLLE, MHLLE upwind schemes and AUSM+, AUSMPW schemes. In the paper, special attention is for the flow differences of the nozzle starting process obtained from different governing equations and different schemes. Two nozzle flows, previously investigated experimentally and numerically by other researchers, are chosen as our examples. The calculated results indicate the carbuncle phenomenon and unphysical oscillations appear more or less near a wall or behind strong shock wave except using HLLE scheme, and these unphysical phenomena become more seriously with the increase of Mach number. Comparing the turbulence calculation, inviscid solution cannot simulate the wall flow separation and the laminar solution shows some different flow characteristics in the regions of flow separation and near wall.

Generation of 17-TW 23-fs pulses with a two-stage Ti : Sapphire amplifier at repetition rate 10 Hz

We have developed a two-stage Ti:sapphire amplifier system which can produce 17-TW/23-fs pulses at a repetition rate 10 MHz. A birefringent plate is used in the regenerative amplifier to alleviate gain narrowing, while an all-reflective cylindrical-mirror-based pulse stretcher and an acousto-optic programmable dispersive filter (AOPDF) are used to compensate for the higher order dispersion of the system.

Some experiments on solving multistage stochastic mixed 0-1 programs with time stochastic dominance constraints

In this work we extend to the multistage case two recent risk averse measures for two-stage stochastic programs based on first- and second-order stochastic dominance constraints induced by mixed-integer linear recourse. Additionally, we consider Time Stochastic Dominance (TSD) along a given horizon. Given the dimensions of medium-sized problems augmented by the new variables and constraints required by those risk measures, it is unrealistic to solve the problem up to optimality by plain use of MIP solvers in a reasonable computing time, at least. Instead of it, decomposition algorithms of some type should be used. We present an extension of our Branch-and-Fix Coordination algorithm, so named BFC-TSD, where a special treatment is given to cross scenario group constraints that link variables from different scenario groups. A broad computational experience is presented by comparing the risk neutral approach and the tested risk averse strategies. The performance of the new version of the BFC algorithm versus the plain use of a state-of-the-artMIP solver is also reported.

A stochastic model of temporal variations in monthly temperature, precipitation, snowfall, and resulting snowpack

We report a Monte Carlo representation of the long-term inter-annual variability of monthly snowfall on a detailed (1 km) grid of points throughout the southwest. An extension of the local climate model of the southwestern United States (Stamm and Craig 1992) provides spatially based estimates of mean and variance of monthly temperature and precipitation. The mean is the expected value from a canonical regression using independent variables that represent controls on climate in this area, including orography. Variance is computed as the standard error of the prediction and provides site-specific measures of (1) natural sources of variation and (2) errors due to limitations of the data and poor distribution of climate stations. Simulation of monthly temperature and precipitation over a sequence of years is achieved by drawing from a bivariate normal distribution. The conditional expectation of precipitation. given temperature in each month, is the basis of a numerical integration of the normal probability distribution of log precipitation below a threshold temperature (3°C) to determine snowfall as a percent of total precipitation. Snowfall predictions are tested at stations for which long-term records are available. At Donner Memorial State Park (elevation 1811 meters) a 34-year simulation - matching the length of instrumental record - is within 15 percent of observed for mean annual snowfall. We also compute resulting snowpack using a variation of the model of Martinec et al. (1983). This allows additional tests by examining spatial patterns of predicted snowfall and snowpack and their hydrologic implications.

A Stochastic Model for Electron Multiplication Charge-Coupled Devices - From Theory to Practice

Electron multiplication charge-coupled devices (EMCCD) are widely used for photon counting experiments and measurements of low intensity light sources, and are extensively employed in biological fluorescence imaging applications. These devices have a complex statistical behaviour that is often not fully considered in the analysis of EMCCD data. Robust and optimal analysis of EMCCD images requires an understanding of their noise properties, in particular to exploit fully the advantages of Bayesian and maximum-likelihood analysis techniques, whose value is increasingly recognised in biological imaging for obtaining robust quantitative measurements from challenging data. To improve our own EMCCD analysis and as an effort to aid that of the wider bioimaging community, we present, explain and discuss a detailed physical model for EMCCD noise properties, giving a likelihood function for image counts in each pixel for a given incident intensity, and we explain how to measure the parameters for this model from various calibration images. © 2013 Hirsch et al.

Visualising a stochastic model of California Water Resources Using Sankey Diagrams

This paper describes a novel approach to the analysis of supply and demand of water in California. A stochastic model is developed to assess the future supply of and demand for water resources in California. The results are presented in the form of a Sankey diagram where present and stochastically-varying future fluxes of water in California and its sub-regions are traced from source to services by mapping the various transformations of water from when it is first made available for use, through its treatment, recycling and reuse, to its eventual loss in a variety of sinks. This helps to highlight the connections of water with energy and land resources, including the amount of energy used to pump and treat water, the amount of water used for energy production, and the land resources that create a water demand to produce crops for food. By mapping water in this way, policy-makers can more easily understand the competing uses of water, through the identification of the services it delivers (e.g. sanitation, food production, landscaping), the potential opportunities for improving themanagement of the resource and the connections with other resources which are often overlooked in a traditional sector-based management strategy. This paper focuses on a Sankey diagram for water, but the ultimate aim is the visualisation of linked resource futures through inter-connected Sankey diagrams for energy, land and water, tracking changes from the basic resources for all three, their transformations, and the final services they provide.

Interplay between the Dzyaloshinskii-Moriya anisotropic antisymmetric interaction and the SWAP operation in a two-qubit Heisenberg model

The SWAP operation in a two-qubit Heisenberg model in the presence of Dzyaloshinskii-Moriya (DM) anisotropic antisymmetric interaction is investigated. 1t is shown that the SWAP operation can be implemented for some kinds of DM coupling and the influence of DM couplings is divided into different cases. The conditions of the DM coupling under which the SWAP operation is feasible are established. (C) 2007 Elsevier B.V. All rights reserved.

achieving on-time delivery: a two-stage probabilistic scheduling strategy for software projects

Chinese Academy of Sciences (ISCAS)