Industrial agglomerations and wage gradients: the Spanish economy in the interwar period

This paper gives new evidence on the relationship between integration and industrial agglomeration in the presence of scale economies, by testing directly one of the predictions that can be derived from Krugman (1991), that is, the existence of regional nominal wage gradients and its transformation following changes in trade regimes. Our case study analyzes the effects of the substitution of an open economy by a closed economy regime, exactly the opposite process studied by Hanson (1996, 1997). In Spain, during the interwar period, protectionist policies would have favored the loss of centrality of the coastal location (Barcelona) and the relative rise of central locations (such as Madrid). Our results indicate the existence of a wage gradient centered in Barcelona during the interwar period (1914-1930) and its weakening after 1925.

Comparison of estimation methods of soil strength in five soils

In agriculture, the soil strength is used to describe the susceptibility to deformation by pressure caused by agricultural machine. The purpose of this study was to compare different methods for estimating the inherent soil strength and to identify their suitability for the evaluation of load support capacity, compaction susceptibility and root growth. The physical, chemical, mineralogical and intrinsic strength properties of seven soil samples, collected from five sampling pits at different locations in Brazil, were measured. Four clay (CS) and three sandy clay loam (SCL) soils were used. The clay soils were collected on a farm in Santo Ângelo, RS (28 º 16 ' 16 '' S; 54 º 13 ' 11 '' W 290 m); A and B horizons at the Universidade Federal de Lavras, Lavras, MG (21 º 13 ' 47 '' S; 44 º 58 ' 6'' W; 918 m) and on the farm Sygenta, in Uberlandia, MG (18 º 58 ' 37 '' S; 48 º 12 ' 05 '' W 866 m). The sandy clay loam soils were collected in Aracruz, ES (19 º 47 ' 10 '' S; 40 º 16 ' 29 '' W 81 m), and on the farm Xavier, Lavras, MG (21 º 13 ' 24 '' S; 45 º 05 ' 00 '' W; 844 m). Soil strength was estimated based on measurements of: (a) a pneumatic consolidometer, (b) manual pocket (non-rotating) penetrometer; and (c) automatic (rotating) penetrometer. The results of soil strength properties were similar by the three methods. The soil structure had a significant influence on soil strength. Results of measurements with both the manual pocket and the electric penetrometer were similar, emphasizing the influence of soil texture. The data showed that, to enhance the reliability of predictions of preconsolidation pressure by penetrometers, it is better to separate the soils into the different classes, rather than analyze them jointly. It can be concluded that the consolidometer method, although expensive, is the best when evaluations of load support capacity and compaction susceptibility of soil samples are desired.

Micro-Raman study of stress distribution in local isolation structures and correlation with transmission electron microscopy

Stress in local isolation structures is studied by micro‐Raman spectroscopy. The results are correlated with predictions of an analytical model for the stress distribution and with cross‐sectional transmission electron microscopy observations. The measurements are performed on structures on which the Si3N4 oxidation mask is still present. The influence of the pitch of the periodic local isolation pattern, consisting of parallel lines, the thickness of the mask, and the length of the bird"s beak on the stress distribution are studied. It is found that compressive stress is present in the Si substrate under the center of the oxidation mask lines, with a magnitude dependent on the width of the lines. Large tensile stress is concentrated under the bird"s beak and is found to increase with decreasing length of the bird"s beak and with increasing thickness of the Si3N4 film.

Semiclassical theory of shot noise in ballistic n+in+ semiconductor structures: relevance of Pauli and long range Coulomb interactions

We work out a semiclassical theory of shot noise in ballistic n+-i-n+ semiconductor structures aiming at studying two fundamental physical correlations coming from Pauli exclusion principle and long-range Coulomb interaction. The theory provides a unifying scheme which, in addition to the current-voltage characteristics, describes the suppression of shot noise due to Pauli and Coulomb correlations in the whole range of system parameters and applied bias. The whole scenario is summarized by a phase diagram in the plane of two dimensionless variables related to the sample length and contact chemical potential. Here different regions of physical interest can be identified where only Coulomb or only Pauli correlations are active, or where both are present with different relevance. The predictions of the theory are proven to be fully corroborated by Monte Carlo simulations.

Shot noise anomalies in elastic nondegenerate diffusive conductors

We present a theoretical investigation of shot-noise properties in nondegenerate elastic diffusive conductors. Both Monte Carlo simulations and analytical approaches are used. Two interesting phenomena are found: (i) the display of enhanced shot noise for given energy dependences of the scattering time, and (ii) the recovery of full shot noise for asymptotic high applied bias. The first phenomenon is associated with the onset of negative differential conductivity in energy space that drives the system towards a dynamical electrical instability in excellent agreement with analytical predictions. The enhancement is found to be strongly amplified when the dimensionality in momentum space is lowered from three to two dimensions. The second phenomenon is due to the suppression of the effects of long-range Coulomb correlations that takes place when the transit time becomes the shortest time scale in the system, and is common to both elastic and inelastic nondegenerate diffusive conductors. These phenomena shed different light in the understanding of the anomalous behavior of shot noise in mesoscopic conductors, which is a signature of correlations among different current pulses.

The UniProt-GO Annotation database in 2011.

The GO annotation dataset provided by the UniProt Consortium (GOA: http://www.ebi.ac.uk/GOA) is a comprehensive set of evidenced-based associations between terms from the Gene Ontology resource and UniProtKB proteins. Currently supplying over 100 million annotations to 11 million proteins in more than 360,000 taxa, this resource has increased 2-fold over the last 2 years and has benefited from a wealth of checks to improve annotation correctness and consistency as well as now supplying a greater information content enabled by GO Consortium annotation format developments. Detailed, manual GO annotations obtained from the curation of peer-reviewed papers are directly contributed by all UniProt curators and supplemented with manual and electronic annotations from 36 model organism and domain-focused scientific resources. The inclusion of high-quality, automatic annotation predictions ensures the UniProt GO annotation dataset supplies functional information to a wide range of proteins, including those from poorly characterized, non-model organism species. UniProt GO annotations are freely available in a range of formats accessible by both file downloads and web-based views. In addition, the introduction of a new, normalized file format in 2010 has made for easier handling of the complete UniProt-GOA data set.

Plant species richness and environmental heterogeneity in a mountain landscape: effects of variability and spatial configuration

The loss of biodiversity has become a matter of urgent concern and a better understanding of local drivers is crucial for conservation. Although environmental heterogeneity is recognized as an important determinant of biodiversity, this has rarely been tested using field data at management scale. We propose and provide evidence for the simple hypothesis that local species diversity is related to spatial environmental heterogeneity. Species partition the environment into habitats. Biodiversity is therefore expected to be influenced by two aspects of spatial heterogeneity: 1) the variability of environmental conditions, which will affect the number of types of habitat, and 2) the spatial configuration of habitats, which will affect the rates of ecological processes, such as dispersal or competition. Earlier, simulation experiments predicted that both aspects of heterogeneity will influence plant species richness at a particular site. For the first time, these predictions were tested for plant communities using field data, which we collected in a wooded pasture in the Swiss Jura mountains using a four-level hierarchical sampling design. Richness generally increased with increasing environmental variability and "roughness" (i.e. decreasing spatial aggregation). Effects occurred at all scales, but the nature of the effect changed with scale, suggesting a change in the underlying mechanisms, which will need to be taken into account if scaling up to larger landscapes. Although we found significant effects of environmental heterogeneity, other factors such as history could also be important determinants. If a relationship between environmental heterogeneity and species richness can be shown to be general, recently available high-resolution environmental data can be used to complement the assessment of patterns of local richness and improve the prediction of the effects of land use change based on mean site conditions or land use history.

Simulations in evolution. II. Relative fitness and the propagation of mutants.

In Neo-Darwinism, variation and natural selection are the two evolutionary mechanisms which propel biological evolution. Our previous article presented a histogram model [1] consisting in populations of individuals whose number changed under the influence of variation and/or fitness, the total population remaining constant. Individuals are classified into bins, and the content of each bin is calculated generation after generation by an Excel spreadsheet. Here, we apply the histogram model to a stable population with fitness F(1)=1.00 in which one or two fitter mutants emerge. In a first scenario, a single mutant emerged in the population whose fitness was greater than 1.00. The simulations ended when the original population was reduced to a single individual. The histogram model was validated by excellent agreement between its predictions and those of a classical continuous function (Eqn. 1) which predicts the number of generations needed for a favorable mutation to spread throughout a population. But in contrast to Eqn. 1, our histogram model is adaptable to more complex scenarios, as demonstrated here. In the second and third scenarios, the original population was present at time zero together with two mutants which differed from the original population by two higher and distinct fitness values. In the fourth scenario, the large original population was present at time zero together with one fitter mutant. After a number of generations, when the mutant offspring had multiplied, a second mutant was introduced whose fitness was even greater. The histogram model also allows Shannon entropy (SE) to be monitored continuously as the information content of the total population decreases or increases. The results of these simulations illustrate, in a graphically didactic manner, the influence of natural selection, operating through relative fitness, in the emergence and dominance of a fitter mutant.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

Industrial agglomerations and wage gradients: the Spanish economy in the interwar period

This paper gives new evidence on the relationship between integration and industrial agglomeration in the presence of scale economies, by testing directly one of the predictions that can be derived from Krugman (1991), that is, the existence of regional nominal wage gradients and its transformation following changes in trade regimes. Our case study analyzes the effects of the substitution of an open economy by a closed economy regime, exactly the opposite process studied by Hanson (1996, 1997). In Spain, during the interwar period, protectionist policies would have favored the loss of centrality of the coastal location (Barcelona) and the relative rise of central locations (such as Madrid). Our results indicate the existence of a wage gradient centered in Barcelona during the interwar period (1914-1930) and its weakening after 1925.

Auction theory, sequential local service privatization, and the effects of geographical scale economies on effective competition

A sequential weakly efficient two-auction game with entry costs, interdependence between objects, two potential bidders and IPV assumption is presented here in order to give some theoretical predictions on the effects of geographical scale economies on local service privatization performance. It is shown that the first object seller takes profit of this interdependence. The interdependence externality rises effective competition for the first object, expressed as the probability of having more than one final bidder. Besides, if there is more than one final bidder in the first auction, seller extracts the entire bidder¿s expected future surplus differential between having won the first auction and having lost. Consequences for second object seller are less clear, reflecting the contradictory nature of the two main effects of object interdependence. On the one hand, first auction winner becomes ¿stronger¿, so that expected payments rise in a competitive environment. On the other hand, first auction loser becomes relatively ¿weaker¿, hence (probably) reducing effective competition for the second object. Additionally, some contributions to static auction theory with entry cost and asymmetric bidders are presented in the appendix

Example-based support vector machine for drug concentration analysis

Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. In this paper, we focus on the prediction of drug concentrations using Support Vector Machines (S VM) and the analysis of the influence of each feature to the prediction results. Our study shows that SVM-based approaches achieve similar prediction results compared with pharmacokinetic model. The two proposed example-based SVM methods demonstrate that the individual features help to increase the accuracy in the predictions of drug concentration with a reduced library of training data.

EGASP: the human ENCODE Genome Annotation Assessment Project.

BACKGROUND: We present the results of EGASP, a community experiment to assess the state-of-the-art in genome annotation within the ENCODE regions, which span 1% of the human genome sequence. The experiment had two major goals: the assessment of the accuracy of computational methods to predict protein coding genes; and the overall assessment of the completeness of the current human genome annotations as represented in the ENCODE regions. For the computational prediction assessment, eighteen groups contributed gene predictions. We evaluated these submissions against each other based on a 'reference set' of annotations generated as part of the GENCODE project. These annotations were not available to the prediction groups prior to the submission deadline, so that their predictions were blind and an external advisory committee could perform a fair assessment. RESULTS: The best methods had at least one gene transcript correctly predicted for close to 70% of the annotated genes. Nevertheless, the multiple transcript accuracy, taking into account alternative splicing, reached only approximately 40% to 50% accuracy. At the coding nucleotide level, the best programs reached an accuracy of 90% in both sensitivity and specificity. Programs relying on mRNA and protein sequences were the most accurate in reproducing the manually curated annotations. Experimental validation shows that only a very small percentage (3.2%) of the selected 221 computationally predicted exons outside of the existing annotation could be verified. CONCLUSION: This is the first such experiment in human DNA, and we have followed the standards established in a similar experiment, GASP1, in Drosophila melanogaster. We believe the results presented here contribute to the value of ongoing large-scale annotation projects and should guide further experimental methods when being scaled up to the entire human genome sequence.

Diffusionless first-order phase transitions in systems with frozen configurational degrees of freedom

We consider systems that can be described in terms of two kinds of degree of freedom. The corresponding ordering modes may, under certain conditions, be coupled to each other. We may thus assume that the primary ordering mode gives rise to a diffusionless first-order phase transition. The change of its thermodynamic properties as a function of the secondary-ordering-mode state is then analyzed. Two specific examples are discussed. First, we study a three-state Potts model in a binary system. Using mean-field techniques, we obtain the phase diagram and different properties of the system as a function of the distribution of atoms on the different lattice sites. In the second case, the properties of a displacive structural phase transition of martensitic type in a binary alloy are studied as a function of atomic order. Because of the directional character of the martensitic-transition mechanism, we find only a very weak dependence of the entropy on atomic order. Experimental results are found to be in quite good agreement with theoretical predictions.

Thermal nucleation and cavitation in 3He and 4He

Density functionals that reproduce the helium liquid-gas interface as a function of temperature have been used, within an improved homogeneous nucleation approach, to investigate thermal nucleation and cavitation in both helium isotopes. The results are compared with available experimental data on cavitation in 3He and 4He. Predictions are made for cavitation in 3He at negative pressures and for nucleation in both isotopes.