Using spatially distributed parameters and multi-response objective functions to solve parameterization of complex applications of semi-distributed hydrological models

Application of semi-distributed hydrological models to large, heterogeneous watersheds deals with several problems. On one hand, the spatial and temporal variability in catchment features should be adequately represented in the model parameterization, while maintaining the model complexity in an acceptable level to take advantage of state-of-the-art calibration techniques. On the other hand, model complexity enhances uncertainty in adjusted model parameter values, therefore increasing uncertainty in the water routing across the watershed. This is critical for water quality applications, where not only streamflow, but also a reliable estimation of the surface versus subsurface contributions to the runoff is needed. In this study, we show how a regularized inversion procedure combined with a multiobjective function calibration strategy successfully solves the parameterization of a complex application of a water quality-oriented hydrological model. The final value of several optimized parameters showed significant and consistentdifferences across geological and landscape features. Although the number of optimized parameters was significantly increased by the spatial and temporal discretization of adjustable parameters, the uncertainty in water routing results remained at reasonable values. In addition, a stepwise numerical analysis showed that the effects on calibration performance due to inclusion of different data types in the objective function could be inextricably linked. Thus caution should be taken when adding or removing data from an aggregated objective function.

R functions for quantifying nonindependence in standard dyadic and SRM designs

Interdependence is the main feature of dyadic relationships and, in recent years, various statistical procedures have been proposed for quantifying and testing this social attribute in different dyadic designs. The purpose of this paper is to develop several functions for this kind of statistical tests in an R package, known as nonindependence, for use by applied social researchers. A Graphical User Interface (GUI) is also developed to facilitate the use of the functions included in this package. Examples drawn from psychological research and simulated data are used to illustrate how the software works.

Measurement of the specific heat and determination of the thermodynamic functions of relaxed amorphous silicon

The specific heat, cp, of two amorphous silicon (a-Si) samples has been measured by differential scanning calorimetry in the 100–900K temperature range. When the hydrogen content is reduced by thermal annealing, cp approaches the value of crystalline Si (c-Si). Within experimental accuracy, we conclude that cp of relaxed pure a-Si coincides with that of c-Si. This result is used to determine the enthalpy, entropy, and Gibbs free energy of defect-free relaxed a-Si. Finally, the contribution of structural defects on these quantities is calculated and the melting point of several states of a-Si is predicted

Emerging functions of myelin associated proteins during development neuronal plasticity and and neurpdegeneration.

Adult mammalian central nervous system (CNS) axons have a limited regrowth capacity following injury. Myelin-associated inhibitors (MAIs) limit axonal outgrowth and their blockage improves the regeneration of damaged fiber tracts. Three of these proteins, Nogo-A, MAG and OMgp, share two common neuronal receptors: NgR1, together with its co-receptors (p75(NTR), TROY and Lingo-1), and the recently described paired immunoglobulin-like receptor B (PirB). These proteins impair neuronal regeneration by limiting axonal sprouting. Some of the elements involved in the myelin inhibitory pathways may still be unknown, but the discovery that blocking both PirB and NgR1 activities leads to near-complete release from myelin inhibition, sheds light on one of the most competitive and intense fields of neuroregeneration study during in recent decades. In parallel with the identification and characterization of the roles and functions of these inhibitory molecules in axonal regeneration, data gathered in the field strongly suggest that most of these proteins have roles other than axonal growth inhibition. The discovery of a new group of interacting partners for myelin-associated receptors and ligands, as well as functional studies within or outside the CNS environment, highlights the potential new physiological roles for these proteins in processes such as development, neuronal homeostasis, plasticity and neurodegeneration.

Traces of functions in Fock spaces on lattices of critical density

Following a scheme of Levin we describe the values that functions in Fock spaces take on lattices of critical density in terms of both the size of the values and a cancelation condition that involves discrete versions of the Cauchy and Beurling-Ahlfors transforms.

Uniform estimates in the Poincare-Aronszajn theorem on the separation of singularities of analytic functions

We study the possibility of splitting any bounded analytic function $f$ with singularities in a closed set $E\cup F$ as a sum of two bounded analytic functions with singularities in $E$ and $F$ respectively. We obtain some results under geometric restrictions on the sets $E$ and $F$ and we provide some examples showing the sharpness of the positive results.

Hardy’s inequalities for monotone functions on partly ordered measure spaces

We characterize the weighted Hardy inequalities for monotone functions in Rn +. In dimension n = 1, this recovers the standard theory of Bp weights. For n > 1, the result was previously only known for the case p = 1. In fact, our main theorem is proved in the more general setting of partly ordered measure spaces.

Effects of coastal submarine canyons on tsunami propagation and impact

We analyse the variations produced on tsunami propagation and impact over a straight coastline because of the presence of a submarine canyon incised in the continental margin. For ease of calculation we assume that the shoreline and the shelf edge are parallel and that the incident wave approaches them normally. A total of 512 synthetic scenarios have been computed by combining the bathymetry of a continental margin incised by a parameterised single canyon and the incident tsunami waves. The margin bathymetry, the canyon and the tsunami waves have been generated using mathematical functions (e.g. Gaussian). Canyon parameters analysed are: (i) incision length into the continental shelf, which for a constant shelf width relates directly to the distance from the canyon head to the coast, (ii) canyon width, and (iii) canyon orientation with respect to the shoreline. Tsunami wave parameters considered are period and sign. The COMCOT tsunami model from Cornell University was applied to propagate the waves across the synthetic bathymetric surfaces. Five simulations of tsunami propagation over a non-canyoned margin were also performed for reference. The analysis of the results reveals a strong variation of tsunami arrival times and amplitudes reaching the coastline when a tsunami wave travels over a submarine canyon, with changing maximum height location and alongshore extension. In general, the presence of a submarine canyon lowers the arrival time to the shoreline but prevents wave build-up just over the canyon axis. This leads to a decrease in tsunami amplitude at the coastal stretch located just shoreward of the canyon head, which results in a lower run-up in comparison with a non-canyoned margin. Contrarily, an increased wave build-up occurs on both sides of the canyon head, generating two coastal stretches with an enhanced run-up. These aggravated or reduced tsunami effects are modified with (i) proximity of the canyon tip to the coast, amplifying the wave height, (ii) canyon width, enlarging the areas with lower and higher maximum height wave along the coastline, and (iii) canyon obliquity with respect to the shoreline and shelf edge, increasing wave height shoreward of the leeward flank of the canyon. Moreover, the presence of a submarine canyon near the coast produces a variation of wave energy along the shore, eventually resulting in edge waves shoreward of the canyon head. Edge waves subsequently spread out alongshore reaching significant amplitudes especially when coupling with tsunami secondary waves occurs. Model results have been groundtruthed using the actual bathymetry of Blanes Canyon area in the North Catalan margin. This paper underlines the effects of the presence, morphology and orientation of submarine canyons as a determining factor on tsunami propagation and impact, which could prevail over other effects deriving from coastal configuration.

Endogenous growth with capital in R&D production functions

[eng] In this paper we claim that capital is as important in the production of ideas as in the production of final goods. Hence, we introduce capital in the production of knowledge and discuss the associated problems arising from the public good nature of knowledge. We show that although population growth can affect economic growth, it is not necessary for growth to arise. We derive both the social planner and the decentralized economy growth rates and show the optimal subsidy that decentralizes it. We also show numerically that the effects of population growth on the market growth rate, the optimal growth rate and the optimal subsidy are small. Besides, we find that physical capital is more important for the production of knowledge than for the production of goods.

Endogenous growth with capital in R&D production functions

[eng] In this paper we claim that capital is as important in the production of ideas as in the production of final goods. Hence, we introduce capital in the production of knowledge and discuss the associated problems arising from the public good nature of knowledge. We show that although population growth can affect economic growth, it is not necessary for growth to arise. We derive both the social planner and the decentralized economy growth rates and show the optimal subsidy that decentralizes it. We also show numerically that the effects of population growth on the market growth rate, the optimal growth rate and the optimal subsidy are small. Besides, we find that physical capital is more important for the production of knowledge than for the production of goods.

Characterization of Reward Functions in Networks with Costs

In this paper we study network structures in which the possibilities for cooperation are restricted and can not be described by a cooperative game. The benefits of a group of players depend on how these players are internally connected. One way to represent this type of situations is the so-called reward function, which represents the profits obtainable by the total coalition if links can be used to coordinate agents' actions. The starting point of this paper is the work of Vilaseca et al. where they characterized the reward function. We concentrate on those situations where there exist costs for establishing communication links. Given a reward function and a costs function, our aim is to analyze under what conditions it is possible to associate a cooperative game to it. We characterize the reward function in networks structures with costs for establishing links by means of two conditions, component permanence and component additivity. Finally, an economic application is developed to illustrate the main theoretical result.

Bandlimited Lipschitz functions

We study the space of bandlimited Lipschitz functions in one variable. In particular we provide a geometrical description of interpolating and sampling sequences for this space. We also give a description of the trace of such functions to sequences of critical density in terms of a cancellation condition.

Estimation of age- and stage-specific Catalan breast cancer survival functions using US and Catalan survival data

Background: During the last part of the 1990s the chance of surviving breast cancer increased. Changes in survival functions reflect a mixture of effects. Both, the introduction of adjuvant treatments and early screening with mammography played a role in the decline in mortality. Evaluating the contribution of these interventions using mathematical models requires survival functions before and after their introduction. Furthermore, required survival functions may be different by age groups and are related to disease stage at diagnosis. Sometimes detailed information is not available, as was the case for the region of Catalonia (Spain). Then one may derive the functions using information from other geographical areas. This work presents the methodology used to estimate age- and stage-specific Catalan breast cancer survival functions from scarce Catalan survival data by adapting the age- and stage-specific US functions. Methods: Cubic splines were used to smooth data and obtain continuous hazard rate functions. After, we fitted a Poisson model to derive hazard ratios. The model included time as a covariate. Then the hazard ratios were applied to US survival functions detailed by age and stage to obtain Catalan estimations. Results: We started estimating the hazard ratios for Catalonia versus the USA before and after the introduction of screening. The hazard ratios were then multiplied by the age- and stage-specific breast cancer hazard rates from the USA to obtain the Catalan hazard rates. We also compared breast cancer survival in Catalonia and the USA in two time periods, before cancer control interventions (USA 1975–79, Catalonia 1980–89) and after (USA and Catalonia 1990–2001). Survival in Catalonia in the 1980–89 period was worse than in the USA during 1975–79, but the differences disappeared in 1990–2001. Conclusion: Our results suggest that access to better treatments and quality of care contributed to large improvements in survival in Catalonia. On the other hand, we obtained detailed breast cancer survival functions that will be used for modeling the effect of screening and adjuvant treatments in Catalonia.

Affinity distribution functions in multicomponent heterogeneous adsorption. Analytical inversion of isotherms to obtain affinity spectra

An analytical approach for the interpretation of multicomponent heterogeneous adsorption or complexation isotherms in terms of multidimensional affinity spectra is presented. Fourier transform, applied to analyze the corresponding integral equation, leads to an inversion formula which allows the computation of the multicomponent affinity spectrum underlying a given competitive isotherm. Although a different mathematical methodology is used, this procedure can be seen as the extension to multicomponent systems of the classical Sips’s work devoted to monocomponent systems. Furthermore, a methodology which yields analytical expressions for the main statistical properties (mean free energies of binding and covariance matrix) of multidimensional affinity spectra is reported. Thus, the level of binding correlation between the different components can be quantified. It has to be highlighted that the reported methodology does not require the knowledge of the affinity spectrum to calculate the means, variances, and covariance of the binding energies of the different components. Nonideal competitive consistent adsorption isotherm, widely used in metal/proton competitive complexation to environmental macromolecules, and Frumkin competitive isotherms are selected to illustrate the application of the reported results. Explicit analytical expressions for the affinity spectrum as well as for the matrix correlation are obtained for the NICCA case. © 2004 American Institute of Physics.

Generating highly balanced sudoku problems as hard problems

Sudoku problems are some of the most known and enjoyed pastimes, with a never diminishing popularity, but, for the last few years those problems have gone from an entertainment to an interesting research area, a twofold interesting area, in fact. On the one side Sudoku problems, being a variant of Gerechte Designs and Latin Squares, are being actively used for experimental design, as in [8, 44, 39, 9]. On the other hand, Sudoku problems, as simple as they seem, are really hard structured combinatorial search problems, and thanks to their characteristics and behavior, they can be used as benchmark problems for refining and testing solving algorithms and approaches. Also, thanks to their high inner structure, their study can contribute more than studies of random problems to our goal of solving real-world problems and applications and understanding problem characteristics that make them hard to solve. In this work we use two techniques for solving and modeling Sudoku problems, namely, Constraint Satisfaction Problem (CSP) and Satisfiability Problem (SAT) approaches. To this effect we define the Generalized Sudoku Problem (GSP), where regions can be of rectangular shape, problems can be of any order, and solution existence is not guaranteed. With respect to the worst-case complexity, we prove that GSP with block regions of m rows and n columns with m = n is NP-complete. For studying the empirical hardness of GSP, we define a series of instance generators, that differ in the balancing level they guarantee between the constraints of the problem, by finely controlling how the holes are distributed in the cells of the GSP. Experimentally, we show that the more balanced are the constraints, the higher the complexity of solving the GSP instances, and that GSP is harder than the Quasigroup Completion Problem (QCP), a problem generalized by GSP. Finally, we provide a study of the correlation between backbone variables – variables with the same value in all the solutions of an instance– and hardness of GSP.