ECONOMIC IMPACTS OF DRYLAND SALINITY FOR GRAINS INDUSTRIES

This paper explores some possible economic impacts of worsening salinity severity and extent in the grains industry across Australia. It also looks at the potential to increase agricultural profits through remediation. The analysis is based on a spatial model of agricultural profits and salinity related crop/pasture yield losses. It is estimated that grains industry farming profits across Australia would rise by an upper limit $138 million per year were salinity costlessly removed from the landscape. It is also estimated that the present value of grains industry profit losses from worsening salinity extent and severity over the next 20 years is$237 million. These amounts can be considered against the costs of repair.Crop Production/Industries, Environmental Economics and Policy,

Evergreen Leasing of Aquaculture Sites

Government policy on siting of aquaculture must balance the objective of providing a long planning horizon for the industry against a broader social interest of adapting lease terms to new environmental information. Evergreen leases are proposed to balance these objectives. Under an evergreen lease, the lease renewal occurs not at the end of the lease, but rather at midterm. For example, a 20-year lease might be renewed at year five or year 10. The mid-term renewal process avoids end-point biases and also creates incentives for the two parties to successfully bargain a renewal. Evergreen leases are an appropriate institution when two parties want a long-term relationship but recognize that terms of the relationship must evolve to reflect new information.aquaculture, evergreen leases, Resource /Energy Economics and Policy, Q22,

Designing water abstraction regimes for an ever-changing and ever-varying future

Most of the world's water entitlement and allocation regimes evolved during periods of abundance and, hence, are not well suited to the management of water scarcity. Development of the institutional arrangements necessary to manage changing demands and supplies is in its infancy. Design criteria for the development of a set of institutional arrangements for the robust management of scarce water resources is offered and then used to develop a generic framework for the allocation and use of water. Variations to account for differences in ground, regulated and unregulated water resources are offered. The question of how best to sequence reform of existing water entitlement and allocation regimes is also addressed. The result is a recommendation for the use of water sharing plans to determine how much water may be used at any point in time and an unbundled suite of arrangements that enable efficient but separated management of long term and short term considerations and, also, the control of externalities. System-wide adjustment is facilitated through the periodic revision of water sharing plans. Individual adjustment to changing circumstances is facilitated through trade in entitlements and allocations. Before the introduction of institutional arrangements that encourage adjustment through trade it is recommended that the abstraction regime used be converted into one that accounts for return flows and allocates water according to shareholder entitlement. Seniority, beneficial-use criteria and opportunities to third parties to prevent adjustment according to pre-specified rules should be repealed. Well-designed regimes can be extended to include dam-capacity shares and allow the use of market-based instruments in delivery of water-quality objectives. Pooling can be used to lower the costs of risk management.Engineering and Applied Science

Towards a Principled Representation of Discourse Plans

We argue that discourse plans must capture the intended causal and decompositional relations between communicative actions. We present a planning algorithm, DPOCL, that builds plan structures that properly capture these relations, and show how these structures are used to solve the problems that plagued previous discourse planners, and allow a system to participate effectively and flexibly in an ongoing dialogue.Comment: requires cogsci94.sty, psfig.st

Community Property—Deferred Compensation: Disposition of Military Retired Pay upon Dissolution of Marriage—Payne v. Payne, 82 Wn. 2d 573, 512 P.2d 736 (1973)

Petitioner-wife and respondent-husband were married a year after he entered the military service, and divorced in Washington a year before he became eligible to retire. In a property distribution provision of its divorce decree, the trial court awarded the wife $65 per month of the$360 per month military retired pay which the husband expected to receive incident to his prospective retirement from the United States Air Force. The court of appeals, reversing, held that such an interest could not be distributed as property under a divorce decree. The Washington Supreme Court, however, reinstated the decree of the trial court, holding that an interest in military retired pay and the anticipated future benefits therefrom are distributable as property in a divorce proceeding. Payne v. Payne, 82 Wn. 2d 573, 512 P.2d 736 (1973)

Impulse oscillometry identifies peripheral airway dysfunction in children with adenosine deaminase deficiency.

Adenosine deaminase-deficient severe combined immunodeficiency (ADA-SCID) is characterized by impaired T-, B- and NK-cell function. Affected children, in addition to early onset of infections, manifest non-immunologic symptoms including pulmonary dysfunction likely attributable to elevated systemic adenosine levels. Lung disease assessment has primarily employed repetitive radiography and effort-dependent functional studies. Through impulse oscillometry (IOS), which is effort-independent, we prospectively obtained objective measures of lung dysfunction in 10 children with ADA-SCID. These results support the use of IOS in the identification and monitoring of lung function abnormalities in children with primary immunodeficiencies

Deep learning delay coordinate dynamics for chaotic attractors from partial observable data

A common problem in time series analysis is to predict dynamics with only scalar or partial observations of the underlying dynamical system. For data on a smooth compact manifold, Takens theorem proves a time delayed embedding of the partial state is diffeomorphic to the attractor, although for chaotic and highly nonlinear systems learning these delay coordinate mappings is challenging. We utilize deep artificial neural networks (ANNs) to learn discrete discrete time maps and continuous time flows of the partial state. Given training data for the full state, we also learn a reconstruction map. Thus, predictions of a time series can be made from the current state and several previous observations with embedding parameters determined from time series analysis. The state space for time evolution is of comparable dimension to reduced order manifold models. These are advantages over recurrent neural network models, which require a high dimensional internal state or additional memory terms and hyperparameters. We demonstrate the capacity of deep ANNs to predict chaotic behavior from a scalar observation on a manifold of dimension three via the Lorenz system. We also consider multivariate observations on the Kuramoto-Sivashinsky equation, where the observation dimension required for accurately reproducing dynamics increases with the manifold dimension via the spatial extent of the system