Development of Transportation Infrastructure in the Context of Economic Growth

Developed road infrastructure is an essential factor facilitating and accelerating economic growth, which will in turn enable the addition of more roads. At the same time, the marginal benet of adding roads to a large stock of existing capacity might be diminishing. It is thus evident that the co-evolution of economic output and road infrastructure is rather intricate and deserves special attention. The model developed in this paper therefore investigates the interdependency between a country's economic growth and the development of transportation infrastructure in this country. To this end, a co-evolutionary perspective is developed, where the mutual inuence of the rate of economic growth and the capacity of transportation infrastructure are explicitly taken into account. This approach enables us to set up an optimal control problem, where the optimal investment rate is determined considering the co-evolutionary dynamics of GDP growth and capacity expansion. This model forms a comprehensive framework for understanding the underlying dynamics and the patterns of economic growth in relation to transport infrastructure. We nd an analytical solution for the innite horizon problem, where the control turns out to be a constant. The steady state is shown to depend crucially on the rate of physical decay of roads, which we think can be interpreted as an index of quality, and the speed of adjustment, at which the economy moves along a trajectory. Testing the model for the data of two countries, France and Finland, illustrates the usefulness of such an approach to real world problems and possibly policy recommendation, where the model would have to be adapted to the peculiarities of each country or region to make precise statements

The Relationship Between the Number of Shots and the Quality of Gamma Knife Radiosurgeries

Radiosurgery is a non-invasive alternative to brain surgery that uses a single focused application of high radiation to destroy intracerebral target tissues. A Gamma Knife delivers such treatments by using 201 cylindrically collimated cobalt-60 sources that are arranged in a hemispherical pattern and aimed to a common focal point. The accumulation of radiation at the focal point, called a \shot due to the spherical nature of the dose distribution, is used to ablate (or destroy) target tissue in the brain. If the target is small and spherical, it is easily treated by choosing one of four available collimators (4, 8, 14, or 18 mm). For large, irregular targets, multiple shots are typically required to treat the entire lesion, and the process of determining the optimal arrangement and number of shots is complex. In this research, fast simulated annealing and a novel objective function are used to investigate the relationship between the number of shots and the quality of the resulting treatment. Sets of 5, 10, 25, 50, and an unrestricted number of shots are studied for an arteriovenous malformation (AVM). As the shot limit increases the following improvements in plan quality are observed: the conformity of the prescription isodose line increases, the lesion dose becomes more homogeneous, and an increase use of smaller collimators to deposit dose. Large improvements in plan quality are realized by increasing the number of shots from 5 to 50, and to achieve a similar magnitude of improvement past 50 requires an increase over 1500 shots for the complex lesion investigated. This observation suggests that it is clinically valuable to improve the Gamma Knife\u27s delivery capabilities so that 50 shot treatments are possible

What are the mechanics of quantum cognition?

Pothos & Busemeyer (P&B) argue that quantum probability (QP) provides a descriptive model of behavior and can also provide a rational analysis of a task. We discuss QP models using Marr's levels of analysis, arguing that they make most sense as algorithmic level theories. We also highlight the importance of having clear interpretations for basic mechanisms such as interference.Daniel Joseph Navarroa and Ian Fus

Response time distributions in partially-coherent quantum walk models for simple decision tasks

Psychological models for two-choice decision tasks typically model the probability that a particular response is made at time t via the first-passage time to an absorbing boundary for some stochastic process. In contrast to the most commonly used models which use classical random walks for the underlying process, a recent paper by Busemeyer, Wang, and Townsend (2006) proposed that quantum walks may provide an interesting alternative. In this paper, we extend this work by introducing a class of partially-coherent quantum walk models that can be applied to human two-choice tasks. The models trace out a path from quantum to classical models, preserving some of the desirable features of both. We discuss the properties of these models, and the implications for modeling simple decisions.Ian G. Fuss and Daniel J. Navarr

Forest-based bioenergy in the Eurasian context

This study analyses the Russian forest biomass-based bioenergy sector. It is shown that presently - although given abundant resources - the share of heat and electricity from biomass is very minor. With the help of 2 IIASA models, future green-field bioenergy plants are identified in a geographically explicit way. Results indicate that by only using 3.3% of the total wood removals, twice as much heat and electricity than presently available from biomass could be generated. Furthermore, there is a multitude of additional co-benefits quantified for the socio-economic sector such as green jobs linked to bioenergy

Negative Emissions and Interactions with other Mitigation Options: A Bottom-up Methodology for Indonesia

BECCS (here the combination of forest-based bioenergy with carbon capture and storage) is seen as a promising tool to deliver the large quantities of negative emissions needed to comply with ambitious climate stabilization targets. However, a land-based mitigation option such as large-scale bioenergy production (without CCS) might interfere with other land-based mitigation options popular for their large co-benefits such as reduced emissions from deforestation and degradation (REDD+). We develop a systems approach to identify and quantify possible trade-offs between REDD+ and BECCS with the help of remote sensing and engineering modeling and apply this for illustration to Indonesia. First results indicate that prioritizing REDD+ does imply that there the BECCS potential remains limited. Further research is needed to take into account opportunities where the two options could be deployed synergistically, capitalizing on co-benefits. BECCS and REDD+ must be evaluated from a portfolio perspective, as estimating their potentials independently will not take such opportunities into account