Real estate ownership and the demand for cars in Denmark: - A pseudo-panel analysis

This paper examines how real estate ownership, increasing real estate values and the falling interest rates affect car demand. It uses data from the Danish Transport Diary Survey together with data from Statistics Denmark to estimate a simple partial adjustment model for car availability in Danish households. We find that car availability differs among households owning real estate and households not owning real estate. Furthermore we show that both households groups have increased their demand for cars due to the falling interest rate

Real estate ownership and the demand for cars in Denmark: - A pseudo-panel analysis

This paper examines how real estate ownership, increasing real estate values and the falling interest rates affect car demand. It uses data from the Danish Transport Diary Survey together with data from Statistics Denmark to estimate a simple partial adjustment model for car availability in Danish households. We find that car availability differs among households owning real estate and households not owning real estate. Furthermore we show that both households groups have increased their demand for cars due to the falling interest rate

Lessons from data-driven stabilization of industrial enzymes

The use of high through-put screening methods has the power to generate vast amounts of information on the link between protein structure and function. With the advancements in affordability and throughput of these technologies, it is increasingly possible to perform data-driven development of enzymes for biotechnological applications. Nowhere is this effort more linked to classical structure-based energy calculation models and our understanding of proteins than when we engineer the stability of proteins. It is now possible to obtain residue-specific information on the effect of all possible single amino acid substitutions on the stability of a protein, thus directly providing statistics and possible answers to some classical ideas on the energy distribution in protein structures. In the present talk, I will discuss the results from recent protein stability engineering projects in relation to long-standing hypotheses in protein engineering, and attempt to provide an outlook for the use of structure-based energy calculation methods in protein engineering

Optimal taxation and congestion externalities in a model of household time allocation

When wanting to solve the externality problem in the transport sector the tax system is an available instrument and the optimal tax system has been analyzed extensively. Unfortunately many of the approaches fail to take account of the insights pointed out in Becker (1965) that the allocation of household time is important for the characterization of household behavior. Since transports main characteristic is that it consumes time this insight should be applied to the transport sector. Recent papers have analyzed the optimal tax system in this setup (Kleven (2004), Nielsen and Pilegaard (2004)) in situations with and without atmospheric externalities. It was shown that the inclusion of household time changes the formulas for optimal taxation and these changes has direct policy implications. If the Becker setup is to be applied to the transport sector an analysis of the optimal tax system in the presence of congestion externalities is needed. This lack of insight is the focus of the present paper. The purpose here is to implement congestion type externalities in a Becker-like setup which explicitly models the use of household time. The paper demonstrates the strength of the Becker approach since existing tax results emerge as special cases in the present setup. The formulas derived for the optimal tax is a valuable guidance when designing the tax system in the transport sector

Taxation, Time Allocation and Externalities

Using the approach introduced in Becker (1965) this paper derives rules for optimal taxation in the presence of externalities. The same was done in Kleven (2004) in the case where externalities were excluded resulting in the inverse factor share rule for optimal taxation. This rule states that fast cars should carry a lower tax rate than slow cars because of time savings. Including externalities modifies the result and gives a simple extension to the tax formulae. The results emphasize that taxation of externalities and revenue-generating taxation of goods should not be looked on separately

Numerical Simulations of Intermittent Transport in Scrape-Off Layer Plasmas

Two-dimensional fluid simulations of interchange turbulence for geometry and parameters relevant for the scrape-off layer of confined plasmas are presented. We observe bursty ejection of particles and heat from the bulk plasma in the form of blobs. These structures propagate far into the scrape-off layer where they are lost due to transport along open magnetic field lines. From single-point recordings it is shown that the blobs have asymmetric conditional wave forms and lead to positively skewed and flat probability distribution functions. The radial propagation velocity may reach one tenth of the sound speed. These results are in excellent agreement with recent experimental measurements.Comment: 8 pages, 7 figure

Intermittent transport in edge plasmas

The properties of low-frequency convective fluctuations and transport are investigated for the boundary region of magnetized plasmas. We employ a two-dimensional fluid model for the evolution of the global plasma quantities in a geometry and with parameters relevant to the scrape-off layer of confined toroidal plasmas. Strongly intermittent plasma transport is regulated by self-consistently generated sheared poloidal flows and is mediated by bursty ejection of particles and heat from the bulk plasma in the form of blobs. Coarse grained probe signals reveal a highly skewed and flat distribution on short time scales, but tends towards a normal distribution at large time scales. Conditionally averaged signals are in perfect agreement with experimental measurements.Comment: 12th International Congress on Plasma Physics, 25-29 October 2004, Nice (France

pKD: re-designing protein pK(a) values

The pK(a) values in proteins govern the pH-dependence of protein stability and enzymatic activity. A large number of mutagenesis experiments have been carried out in the last three decades to re-engineer the pH-activity and pH-stability profile of enzymes and proteins. We have developed the pKD webserver (), which predicts sets of point mutations that will change the pK(a) values of a set of target residues in a given direction, thus allowing for targeted re-design of the pH-dependent characteristics of proteins. The server provides the user with an interactive experience for re-designing pK(a) values by pre-calculating ΔpK(a) values from all feasible point mutations. Design solutions are found in less than 10 min for a typical design job for a medium-sized protein. Mutant ΔpK(a) values calculated by the pKD web server are in close agreement with those produced by comparing results from full-fledged pK(a) calculation methods

Improved method for predicting linear B-cell epitopes

BACKGROUND: B-cell epitopes are the sites of molecules that are recognized by antibodies of the immune system. Knowledge of B-cell epitopes may be used in the design of vaccines and diagnostics tests. It is therefore of interest to develop improved methods for predicting B-cell epitopes. In this paper, we describe an improved method for predicting linear B-cell epitopes. RESULTS: In order to do this, three data sets of linear B-cell epitope annotated proteins were constructed. A data set was collected from the literature, another data set was extracted from the AntiJen database and a data sets of epitopes in the proteins of HIV was collected from the Los Alamos HIV database. An unbiased validation of the methods was made by testing on data sets on which they were neither trained nor optimized on. We have measured the performance in a non-parametric way by constructing ROC-curves. CONCLUSION: The best single method for predicting linear B-cell epitopes is the hidden Markov model. Combining the hidden Markov model with one of the best propensity scale methods, we obtained the BepiPred method. When tested on the validation data set this method performs significantly better than any of the other methods tested. The server and data sets are publicly available at