Runaway Greenhouse Effect in a Semigray Radiative-Convective Model

The effects of the nongray absorption (i.e., atmospheric opacity varying with wavelength) on the possible upper bound of the outgoing longwave radiation (OLR) emitted by a planetary atmosphere have been examined. This analysis is based on the semigray approach, which appears to be a reasonable compromise between the complexity of nongray models and the simplicity of the gray assumption (i.e., atmospheric absorption independent of wavelength). Atmospheric gases in semigray atmospheres make use of constant absorption coefficients in finite-width spectral bands. Here, such a semigray absorption is introduced in a one-dimensional (1D) radiative– convective model with a stratosphere in radiative equilibrium and a troposphere fully saturated with water vapor, which is the semigray gas. A single atmospheric window in the infrared spectrum has been assumed. In contrast to the single absolute limit of OLR found in gray atmospheres, semigray ones may also show a relative limit. This means that both finite and infinite runaway effects may arise in some semigray cases. Of particular importance is the finding of an entirely new branch of stable steady states that does not appear in gray atmospheres. This new multiple equilibrium is a consequence of the nongray absorption only. It is suspected that this new set of stable solutions has not been previously revealed in analyses of radiative–convective models since it does not appear for an atmosphere with nongray parameters similar to those for the earth’s current state

Analytical investigation of the atmospheric radiation limits in semigray atmospheres in radiative equilibrium

We model the wavelength-dependent absorption of atmospheric gases by assuming constant mass absorption coefficients in finite-width spectral bands. Such a semigray atmosphere is analytically solved by a discrete ordinate method. The general solution is analyzed for a water vapor saturated atmosphere that also contains a carbon dioxide-like absorbing gas in the infrared. A multiple stable equilibrium with a relative upper limit in the outgoing long-wave radiation is found. Differing from previous radiative–convective models, we find that the amount of carbon dioxide strongly modifies the value of this relative upper limit. This result is also obtained in a gray (i.e., equal absorption of radiation at all infrared wavelengths) water vapor saturated atmosphere. The destabilizing effect of carbon dioxide implies that massive carbon dioxide atmospheres are more likely to reach a runaway greenhouse state than thin carbon dioxide ones

Endogeneizing know-how flows through the nature of R&D investments

In this paper we carefully link knowledge flows to and from a firms innovation process with this firms investment decisions. Three types of investments are considered: investments in applied research, investments in basic research, and investments in intellectual property protection. Only when basic research is performed, can the firm effectively access incoming knowledge flows and these incoming spillovers serve to increase the efficiency of own applied research.. The firm can at the same time influence outgoing knowledge flows, improving appropriability of its innovations, by investing in protection. Our results indicate that firms with small budgets for innovation will not invest in basic research. This occurs in the short run, when the budget for know-how creation is restricted, or in the long-run, when market opportunities are low, when legal protection is not very important, or, when the pool of accessible and relevant external know-how is limited. The ratio! of basic to applied research is non-decreasing in the size of the pool of accessible external know-how, the size and opportunity of the market, and, the effectiveness of intellectual property rights protection. This indicates the existence of economies of scale in basic research due to external market related factors. Empirical evidence from a sample of innovative manufacturing firms in Belgium confirms the economies of scale in basic research as a consequence of the firms capacity to access external knowledge flows and to protect intellectual property, as well as the complementarity between legal and strategic investments.

Generalized property R and the Schoenflies Conjecture

There is a relation between the generalized Property R Conjecture and the Schoenflies Conjecture that suggests a new line of attack on the latter. The new approach gives a quick proof of the genus 2 Schoenflies Conjecture and suffices to prove the genus 3 case, even in the absence of new progress on the generalized Property R Conjecture.

Firm strategies in R&D: cooperation and participation in R&D programs

This paper presents empirical evidence on firms’ decisions to cooperate in R&D and the extent to which government sponsored R&D programs increase cooperation. Using a sample of firms from the Spanish innovation survey we jointly estimate the determinants of firm participation in R&D programs and of choice of cooperation partners. We find that (i) firms participating in national and European programs have different profiles, suggesting program complementarity; (ii) private-private and publicprivate cooperation are associated on average with firms with different characteristics, and (iii) national R&D programs seem to have a positive effect on all types of cooperation, but especially on public-private partnerships.

Who participates in R&D subsidy programs? The case of spanish manufacturing firms.

Empirical evidence on the effectiveness of R&D subsidies to firms has produced mixed results so far. One possible explanation is that firms and project selection rules may be quite heterogeneous both across agencies and across industries, leading to different outcomes in terms of the induced additional private effort. Here we focus on the participation stage. Using a sample of Spanish firms, we test for differences across agencies and industries. Our results suggest that firms in the same industry face different hurdles to participate in different agencies’ programs, that participation patterns may reflect a combination of agency goals, and that patterns differ across high-tech and low-tech industries.

A compositional data analysis package for R providing multiple approaches

”compositions” is a new R-package for the analysis of compositional and positive data.It contains four classes corresponding to the four different types of compositional andpositive geometry (including the Aitchison geometry). It provides means for computation,plotting and high-level multivariate statistical analysis in all four geometries.These geometries are treated in an fully analogous way, based on the principle of workingin coordinates, and the object-oriented programming paradigm of R. In this way,called functions automatically select the most appropriate type of analysis as a functionof the geometry. The graphical capabilities include ternary diagrams and tetrahedrons,various compositional plots (boxplots, barplots, piecharts) and extensive graphical toolsfor principal components. Afterwards, ortion and proportion lines, straight lines andellipses in all geometries can be added to plots. The package is accompanied by ahands-on-introduction, documentation for every function, demos of the graphical capabilitiesand plenty of usage examples. It allows direct and parallel computation inall four vector spaces and provides the beginner with a copy-and-paste style of dataanalysis, while letting advanced users keep the functionality and customizability theydemand of R, as well as all necessary tools to add own analysis routines. A completeexample is included in the appendix

News from compositions, the R package

The R-package “compositions”is a tool for advanced compositional analysis. Its basicfunctionality has seen some conceptual improvement, containing now some facilitiesto work with and represent ilr bases built from balances, and an elaborated subsys-tem for dealing with several kinds of irregular data: (rounded or structural) zeroes,incomplete observations and outliers. The general approach to these irregularities isbased on subcompositions: for an irregular datum, one can distinguish a “regular” sub-composition (where all parts are actually observed and the datum behaves typically)and a “problematic” subcomposition (with those unobserved, zero or rounded parts, orelse where the datum shows an erratic or atypical behaviour). Systematic classificationschemes are proposed for both outliers and missing values (including zeros) focusing onthe nature of irregularities in the datum subcomposition(s).To compute statistics with values missing at random and structural zeros, a projectionapproach is implemented: a given datum contributes to the estimation of the desiredparameters only on the subcompositon where it was observed. For data sets withvalues below the detection limit, two different approaches are provided: the well-knownimputation technique, and also the projection approach.To compute statistics in the presence of outliers, robust statistics are adapted to thecharacteristics of compositional data, based on the minimum covariance determinantapproach. The outlier classification is based on four different models of outlier occur-rence and Monte-Carlo-based tests for their characterization. Furthermore the packageprovides special plots helping to understand the nature of outliers in the dataset.Keywords: coda-dendrogram, lost values, MAR, missing data, MCD estimator,robustness, rounded zeros

Computation of multiple correspondence analysis, with code in R

The generalization of simple correspondence analysis, for two categorical variables, to multiple correspondence analysis where they may be three or more variables, is not straighforward, both from a mathematical and computational point of view. In this paper we detail the exact computational steps involved in performing a multiple correspondence analysis, including the special aspects of adjusting the principal inertias to correct the percentages of inertia, supplementary points and subset analysis. Furthermore, we give the algorithm for joint correspondence analysis where the cross-tabulations of all unique pairs of variables are analysed jointly. The code in the R language for every step of the computations is given, as well as the results of each computation.

R&D in the pharmaceutical industry: A world of small innovations

It is commonly argued that in recent years pharmaceutical companies have directed theirR&D towards small improvements of existing compounds instead of more risky drastic innovations. In this paper we show that the proliferation of these small innovations is likely to be linked to the lack of market sensitivity of a part of the demand to changes in prices. Compared to their social contribution, small innovations are relatively more profitable than large ones because they are targeted to the smaller but more inelastic part of the demand. We also study the effect of regulatory instruments such as price ceilings, copayments and reference prices and extend the analysis to competition in research.

A Geometric Characterization of Interpolation in $\hat{\E}^\prime(\R)$

We give a geometric description of the interpolating varieties for the algebra of Fourier transforms of distributions (or Beurling ultradistributions) with compact support on the real line.