Buckminsterfullerene (C60) is one of the most important carbon-based nanoparticles (CNPs). Industrial-scale production of C60 has reached the level of tons; release to the environment has been confirmed (Tremblay, 2002; Qiao et al., 2007). The present study was devoted to study of the effect of clay minerals on the migration process of C60. Molecular dynamics (MD) simulations were used to study the interaction of CNPS with clay minerals through study of the adsorption of C60 on various surfaces of kaolinite and pyrophyllite in vacuum and aqueous environments. Two kinds of surfaces, hydrophobic siloxane surfaces and hydrophilic hydroxyl surfaces, were investigated. C60 is mainly adsorbed onto the vacancy of the six-membered ring, composed of SiO4 tetrahedra or AlO6 octahedra, on clay-mineral surfaces. A single adsorption layer consisting of C60 molecules with an ordered hexagonal arrangement is presented for all surfaces in vacuum. In aqueous environments, however, the monolayer appears on the siloxane surfaces only, while a cluster of C60 molecules is formed on the hydroxyl surfaces. Free energies prove that the attachment of two C60 molecules is stronger than the adsorption of C60 onto the hydroxyl surface in water, which is the reason for unfavorable formation of C60 monolayer. On the other hand, the adsorption free energy is more negative on the hydrophobic siloxane surface, explaining the monolayer formation. The existence of water, which forms hydration layers on the surfaces of clay minerals, produces energy barriers, and reduces the adsorption affinity to some extent. Because clay minerals act as geosorbents in the environment, the present study is significant in terms of understanding the migration and fate of CNPS in nature.

We consider a premium control problem in discrete time, formulated in terms of a Markov decision process. In a simplified setting, the optimal premium rule can be derived with dynamic programming methods. However, these classical methods are not feasible in a more realistic setting due to the dimension of the state space and lack of explicit expressions for transition probabilities. We explore reinforcement learning techniques, using function approximation, to solve the premium control problem for realistic stochastic models. We illustrate the appropriateness of the approximate optimal premium rule compared with the true optimal premium rule in a simplified setting and further demonstrate that the approximate optimal premium rule outperforms benchmark rules in more realistic settings where classical approaches fail.

Catastrophe insurance markets fail to provide sufficient protections against natural catastrophes, whereas they have the capacity to absorb the losses. In this paper, we assume the catastrophic risks are dependent and extremely heavy-tailed, and insurers have limited liability to cover losses up to a certain amount. We provide a comprehensive study to show that the diversification in the catastrophe insurance markets can be transited from suboptimal to preferred by increasing the number of insurers in the market. This highlights the importance of coordination among insurers and the government intervention in encouraging insurers to participate in the catastrophe insurance market to exploit risk sharing. Simulation studies are provided to illuminate the key findings of our results.

Low and highly variable prices plague the coffee market, generating concerns that coffee farmers producing in shade systems under natural forests, as in biodiversity hotspot Oaxaca, Mexico, will abandon production and contribute to deforestation and reduced ecosystem services. Using stakeholder information, we build a setting-informed model to analyze farmers' decisions to abandon shade-grown coffee production and their reactions to policy to reduce abandonment. Exploring price premiums for bird-friendly certified coffee, payments for ecosystem services, and price floors as policies, we find that once a farmer is on the path toward abandonment, it is difficult to reverse. However, implementing policies early that are low cost to farmers – price floors and no-cost certification programs – can stem abandonment. Considering the abandonment that policy avoids per dollar spent, price floors are the most cost-effective policy, yet governments prefer certification programs that push costs onto international coffee consumers who pay the price premium.

We study a weighted comonotonic risk-sharing problem among multiple agents with distortion risk measures under heterogeneous beliefs. The explicit forms of optimal allocations are obtained, which are Pareto-optimal. A necessary and sufficient condition is given to ensure the uniqueness of the optimal allocation, and sufficient conditions are given to obtain an optimal allocation of the form of excess of loss or full insurance. The optimal allocation may satisfy individual rationality depending on the choice of the weight. When the distortion risk measure is value at risk or tail value at risk, an optimal allocation is generally of the excess-of-loss form. The numerical examples suggest that a risk is more likely to be shared among agents with heterogeneous beliefs, and the introduction of the weight enables us to prioritize some agents as part of a group sharing a risk.

We analyze the spatio-temporal dynamics of a simple model of macroeconomic geography in which demography and pollution dynamics mutually affect each other. Pollution, by reducing the carrying capacity of the natural environment – which determines the maximum amount of people a given location can effectively bear – crucially affects labor force dynamics which in turn alter the amount of resources available for abatement activities aiming to reduce pollution. Such mutual links determine the eventual sustainability of the development process in different locations and economies, and spatial interactions further complicate the picture. We show that neglecting the existence of mutual feedback between population and pollution leads to misleading conclusions about the eventual sustainability of a specific location. We also show that even neglecting the existence of spatial externalities can lead to misleading conclusions about the sustainability of different regions in the spatial economy. This suggests thus that both the nature of the population and pollution relationship and geographical factors may play a critical role in the process of sustainable development.

The growing movement of people and goods that started in the closing years of the twentieth century has increased the possibility of the accidental or intentional introduction of biohazards that can affect agricultural production in the United States. This study examines the ex ante decision between the deployment of monitoring devices (traps) versus the use of countermeasures to control Mediterranean fruit flies in Florida. To examine this tradeoff, this study outlines a mathematical model to study the effectiveness of traps and the cost of treatment. The empirical results presented in this study indicate that additional parameterization efforts are needed.

The efficiency of public education is examined using a cost indirect output distance function. Efficiency estimates are obtained using data envelopment analysis applied to data from Georgia public schools. Georgia school districts utilize educational budgets with reasonable efficiency, achieving an overall efficiency of 98% with a range of 93%–100%. If all school districts were 100% efficient, outputs could be expanded 2%. This could be achieved by increasing funding $75.46 million state-wide in total for each of the 3 years. From the consumers' (voters') point of view, this result suggests that inefficiency costs Georgia, on average, a total of $226.38 million from 1994 to 1996.

The performance of local tax offices of Norway is studied over a three-year period applying Data Envelopment Efficiency analysis and a Malmquist productivity index. The estimates are bias-corrected using a bootstrap approach recently developed for DEA models. The results show that bias correction and the construction of confidence intervals give a quite different picture without bootstrapping. A set of best practice offices is identified for future work on finding explanations for good performance. The productivity development of individual offices is classified into the four categories: productivity improving cost increase, productivity improving cost savings, productivity decreasing cost savings and productivity decreasing cost increase.

With increasingly thin margins and new technologies, it is important that farm managers know their cost of field operations on a per unit basis (e.g., acre, ton, bale). Accurate per unit costs give confidence when constructing enterprise budgets and evaluating new technologies, such as no-till. Custom rates are often used as a proxy for per unit costs; however, this research, using entropy and jackknife estimation procedures, found that custom rates understate total ownership and operating costs by approximately 25% for an average Kansas farm. Estimates from these models are then used to benchmark actual costs against expected cost.

L'article étudie les origines de la relation entre prix et quantité produite. Les travaux de trois auteurs allemands (Hermann, Rau, et Mangoldt) montrent que cette idée résulte de la réinterprétation, à l'aide d'outils algébriques et géométriques, de thèses initialement formulées par les économistes classiques dans un cadre théorique différent. Malgré leurs limites, ces premières mathématisations ont contribué à l'évolution de la théorie économique, en favorisant la transition de la pensée classique à l'affirmation de l'école néoclassique. Alors que la théorie classique fait ressortir l'hétérogénéité des phénomènes sous-jacents à la forme des fonctions de coût, les instruments mathématiques utilisés en suggèrent plutôt une interprétation en termes de symétrie et d'unité. Ces contributions préfigurent ainsi l'idée marshallienne d'une loi unique, pouvant expliquer toute forme de la courbe d'offre.