Linear and nonlinear terrain deformation maps from a reduced set of interferometric SAR images

In this paper, an advanced technique for the generation of deformation maps using synthetic aperture radar (SAR) data is presented. The algorithm estimates the linear and nonlinear components of the displacement, the error of the digital elevation model (DEM) used to cancel the topographic terms, and the atmospheric artifacts from a reduced set of low spatial resolution interferograms. The pixel candidates are selected from those presenting a good coherence level in the whole set of interferograms and the resulting nonuniform mesh tessellated with the Delauney triangulation to establish connections among them. The linear component of movement and DEM error are estimated adjusting a linear model to the data only on the connections. Later on, this information, once unwrapped to retrieve the absolute values, is used to calculate the nonlinear component of movement and atmospheric artifacts with alternate filtering techniques in both the temporal and spatial domains. The method presents high flexibility with respect to the required number of images and the baselines length. However, better results are obtained with large datasets of short baseline interferograms. The technique has been tested with European Remote Sensing SAR data from an area of Catalonia (Spain) and validated with on-field precise leveling measurements.

Image-Based Coral Reef Classification and Thematic Mapping

This paper presents a novel image classification scheme for benthic coral reef images that can be applied to both single image and composite mosaic datasets. The proposed method can be configured to the characteristics (e.g., the size of the dataset, number of classes, resolution of the samples, color information availability, class types, etc.) of individual datasets. The proposed method uses completed local binary pattern (CLBP), grey level co-occurrence matrix (GLCM), Gabor filter response, and opponent angle and hue channel color histograms as feature descriptors. For classification, either k-nearest neighbor (KNN), neural network (NN), support vector machine (SVM) or probability density weighted mean distance (PDWMD) is used. The combination of features and classifiers that attains the best results is presented together with the guidelines for selection. The accuracy and efficiency of our proposed method are compared with other state-of-the-art techniques using three benthic and three texture datasets. The proposed method achieves the highest overall classification accuracy of any of the tested methods and has moderate execution time. Finally, the proposed classification scheme is applied to a large-scale image mosaic of the Red Sea to create a completely classified thematic map of the reef benthos

Complexation to macromolecules with a large number of sites

This paper presents an approach based on the saddle-point approximation to study the equilibrium interactions between small molecules and macromolecules with a large number of sites. For this case, the application of the Darwin–Fowler method results in very simple expressions for the stoichiometric equilibrium constants and their corresponding free energies in terms of integrals of the binding curve plus a correction term which depends on the first derivatives of the binding curve in the points corresponding to an integer value of the mean occupation number. These expressions are simplified when the number of sites tends to infinity, providing an interpretation of the binding curve in terms of the stoichiometric stability constants. The formalism presented is applied to some simple complexation models, obtaining good values for the free energies involved. When heterogeneous complexation is assumed, simple expressions are obtained to relate the macroscopic description of the binding, given by the stoichiomeric constants, with the microscopic description in terms of the intrinsic stability constants or the affinity spectrum. © 1999 American Institute of Physics.

Large N QCD from rotating branes

We study large N SU(N) Yang-Mills theory in three and four dimensions using a one-parameter family of supergravity models which originate from non-extremal rotating D-branes. We show explicitly that varying this angular momentum parameter decouples the Kaluza-Klein modes associated with the compact D-brane coordinate, while the mass ratios for ordinary glueballs are quite stable against this variation, and are in good agreement with the latest lattice results. We also compute the topological susceptibility and the gluon condensate as a function of the "angular momentum" parameter.

Large Magnetoresistance in Fe/MgO/FeCo(001) Epitaxial Tunnel-Junctions on GaAs(001).

We present tunneling experiments on Fe~001!/MgO~20 Å!/FeCo~001! single-crystal epitaxial junctions of high quality grown by sputtering and laser ablation. Tunnel magnetoresistance measurements give 60% at 30 K, to be compared with 13% obtained recently on ~001!-oriented Fe/amorphous-Al2O3 /FeCo tunnel junctions. This difference demonstrates that the spin polarization of tunneling electrons is not directly related to the density of states of the free metal surface Fe~001! in this case but depends on the actual electronic structure of the entire electrode/barrier system.

Fluid dynamical prediction of changed v1-flow at energies available at the CERN Large Hadron Collider

Substantial collective flow is observed in collisions between lead nuclei at Large Hadron Collider (LHC) as evidenced by the azimuthal correlations in the transverse momentum distributions of the produced particles. Our calculations indicate that the global v1-flow, which at RHIC peaked at negative rapidities (named third flow component or antiflow), now at LHC is going to turn toward forward rapidities (to the same side and direction as the projectile residue). Potentially this can provide a sensitive barometer to estimate the pressure and transport properties of the quark-gluon plasma. Our calculations also take into account the initial state center-of-mass rapidity fluctuations, and demonstrate that these are crucial for v1 simulations. In order to better study the transverse momentum flow dependence we suggest a new"symmetrized" vS1(pt) function, and we also propose a new method to disentangle global v1 flow from the contribution generated by the random fluctuations in the initial state. This will enhance the possibilities of studying the collective Global v1 flow both at the STAR Beam Energy Scan program and at LHC.

CERKL Knockdown Causes Retinal Degeneration in Zebrafish

The human CERKL gene is responsible for common and severe forms of retinal dystrophies. Despite intense in vitro studies at the molecular and cellular level and in vivo analyses of the retina of murine knockout models, CERKL function remains unknown. In this study, we aimed to approach the developmental and functional features of cerkl in Danio rerio within an Evo-Devo framework. We show that gene expression increases from early developmental stages until the formation of the retina in the optic cup. Unlike the high mRNA-CERKL isoform multiplicity shown in mammals, the moderate transcriptional complexity in fish facilitates phenotypic studies derived from gene silencing. Moreover, of relevance to pathogenicity, teleost CERKL shares the two main human protein isoforms. Morpholino injection has been used to generate a cerkl knockdown zebrafish model. The morphant phenotype results in abnormal eye development with lamination defects, failure to develop photoreceptor outer segments, increased apoptosis of retinal cells and small eyes. Our data support that zebrafish Cerkl does not interfere with proliferation and neural differentiation during early developmental stages but is relevant for survival and protection of the retinal tissue. Overall, we propose that this zebrafish model is a powerful tool to unveil CERKL contribution to human retinal degeneration

A Feedfordward Adaptive Controller to Reduce the Imaging Time of Large-Sized Biological Samples with a SPM-Based Multiprobe Station

The time required to image large samples is an important limiting factor in SPM-based systems. In multiprobe setups, especially when working with biological samples, this drawback can make impossible to conduct certain experiments. In this work, we present a feedfordward controller based on bang-bang and adaptive controls. The controls are based in the difference between the maximum speeds that can be used for imaging depending on the flatness of the sample zone. Topographic images of Escherichia coli bacteria samples were acquired using the implemented controllers. Results show that to go faster in the flat zones, rather than using a constant scanning speed for the whole image, speeds up the imaging process of large samples by up to a 4x factor.

Monitoring spatial and temporal dynamics of bird communities in Mediterranean landscapes affected by largewildfires = Seguimiento de la dinámica espacial y temporal de comunidades de aves en paisajes mediterráneos afectados por grandes fuegos

We presented a bird-monitoring database inMediterranean landscapes (Catalonia, NE Spain) affected by wildfires and we evaluated: 1) the spatial and temporal variability in the bird community composition and 2) the influence of pre-fire habitat configuration in the composition of bird communities. The DINDIS database results fromthemonitoring of bird communities occupying all areas affected by large wildfires in Catalonia since 2000.We used bird surveys conducted from 2006 to 2009 and performed a principal components analysis to describe two main gradients of variation in the composition of bird communities, which were used as descriptors of bird communities in subsequent analyses. We then analysed the relationships of these community descriptors with bioclimatic regions within Catalonia, time since fire and pre-fire vegetation (forest or shrubland).We have conducted 1,918 bird surveys in 567 transects distributed in 56 burnt areas. Eight out of the twenty most common detected species have an unfavourable conservation status, most of them being associated to open-habitats. Both bird communities’ descriptors had a strong regional component and were related to pre-fire vegetation, and to a lesser extent to the time since fire.We came to the conclusion that the responses of bird communities to wildfires are heterogeneous, complex and context dependent. Large-scale monitoring datasets, such as DINDIS, might allow identifying factors acting at different spatial and temporal scales that affect the dynamics of species and communities, giving additional information on the causes under general trends observed using other monitoring systems

Purinergic receptors in ocular inflammation

Inflammation is a complex process that implies the interaction between cells and molecular mediators, which, when not properly 'tuned,' can lead to disease. When inflammation affects the eye, it can produce severe disorders affecting the superficial and internal parts of the visual organ. The nucleoside adenosine and nucleotides including adenine mononucleotides like ADP and ATP and dinucleotides such as P(1),P(4)-diadenosine tetraphosphate (Ap4A), and P(1),P(5)-diadenosine pentaphosphate (Ap5A) are present in different ocular locations and therefore they may contribute/modulate inflammatory processes. Adenosine receptors, in particular A2A adenosine receptors, present anti-inflammatory action in acute and chronic retinal inflammation. Regarding the A3 receptor, selective agonists like N(6)-(3-iodobenzyl)-5'-N-methylcarboxamidoadenosine (CF101) have been used for the treatment of inflammatory ophthalmic diseases such as dry eye and uveoretinitis. Sideways, diverse stimuli (sensory stimulation, large intraocular pressure increases) can produce a release of ATP from ocular sensory innervation or after injury to ocular tissues. Then, ATP will activate purinergic P2 receptors present in sensory nerve endings, the iris, the ciliary body, or other tissues surrounding the anterior chamber of the eye to produce uveitis/endophthalmitis. In summary, adenosine and nucleotides can activate receptors in ocular structures susceptible to suffer from inflammatory processes. This involvement suggests the possible use of purinergic agonists and antagonists as therapeutic targets for ocular inflammation.

Factors explaining urban transport systems in large European cities: A cross-sectional approach

The paper analyses the link between human capital and regional economic growth in the European Union. Using different indicat The importance of effective and efficient mobility in large cities is becoming essential for planners and citizens due to its impact in terms of social, economic and geographic development. The aim of this research is to determine factors explaining urban transport systems by estimating aggregate supply and demand equations for 45 large European cities. Supply and Demand equations are separately and jointly determined using OLS and SUR estimation models. On one hand, our findings suggest the importance of economic variables on the supply of public transport. On the other, we highlight the role of those factors influencing the generalized cost of transport as main drivers of demand for public transit. Additionally, regional variables are introduced to capture institutional heterogeneity in this service, and we find that regional patterns are powerful explanatory determinants of urban transportation systems in Europe.

Visual SLAM for 3D large-scale seabed acquisition employing underwater vehicles

This paper presents a novel technique to align partial 3D reconstructions of the seabed acquired by a stereo camera mounted on an autonomous underwater vehicle. Vehicle localization and seabed mapping is performed simultaneously by means of an Extended Kalman Filter. Passive landmarks are detected on the images and characterized considering 2D and 3D features. Landmarks are re-observed while the robot is navigating and data association becomes easier but robust. Once the survey is completed, vehicle trajectory is smoothed by a Rauch-Tung-Striebel filter obtaining an even better alignment of the 3D views and yet a large-scale acquisition of the seabed

Local map update for large scale SLAM

A technique for simultaneous localisation and mapping (SLAM) for large scale scenarios is presented. This solution is based on the use of independent submaps of a limited size to map large areas. In addition, a global stochastic map, containing the links between adjacent submaps, is built. The information in both levels is corrected every time a loop is closed: local maps are updated with the information from overlapping maps, and the global stochastic map is optimised by means of constrained minimisation

Investigating the impact of small versus large firms on economic performance of countries and industries

Following earlier work by Audretsch et al. (2002), we assume that an optimal size-class structure exists, in terms of achieving maximal economic growth rates. Such an optimal structure is likely to exist as economies need a balance between the core competences of large firms (such as exploitation of economies of scale) and those of smaller firms (such as flexibility and exploration of new ideas). Accordingly, changes in size-class structure (i.e., changes in the relative shares in economic activity accounted for by micro, small, medium-sized and large firms) may affect macro-economic growth. Using a unique data base of the EU-27 countries for the period 2002-2008 for five broad sectors of economic activity and four size-classes, we find empirical support which suggests that, on average for these countries over this period, the share of micro and large firms may have been ‘above optimum’ (particularly in lower income EU countries) whereas the share of medium-sized firms may have been ‘below optimum’ (particularly in higher income EU countries). This evidence suggests that the transition from a ‘managed’ to an ‘entrepreneurial’ economy (Audretsch and Thurik, 2001) has not been completed yet in all countries of the EU-27. Keywords: small firms, large firms, size-classes, macro-economic performance

Do innovation and human capital explain the productivity gap between small and large firms?

Empirical evidence is compelling that large firms are more productive than small firms. The hypothesis in this paper is that the productivity differences between small and large firms are associated with two of the main determinants of a firm’s performance: the human and technological capital that firms incorporate. We suggest that the contribution of these factors in explaining the productivity-size gap might not only be due to the fact that large firms make a more extensive use of them, but also because large firms obtain higher returns from their investment in human and technological capital. The evidence we obtain for a comprehensive sample of Spanish manufacturing firms (1990-2002) supports this hypothesis, which has important implications for the effectiveness of policies designed to improve productivity in SMEs by stimulating innovation and the use of more skilled workers.