Semi-supervised remote sensing image classification with cluster kernels

A semisupervised support vector machine is presented for the classification of remote sensing images. The method exploits the wealth of unlabeled samples for regularizing the training kernel representation locally by means of cluster kernels. The method learns a suitable kernel directly from the image and thus avoids assuming a priori signal relations by using a predefined kernel structure. Good results are obtained in image classification examples when few labeled samples are available. The method scales almost linearly with the number of unlabeled samples and provides out-of-sample predictions.

Molecular Proxies for Climate Maladaptation in a Long-Lived Tree (Pinus pinaster Aiton, Pinaceae).

Understanding adaptive genetic responses to climate change is a main challenge for preserving biological diversity. Successful predictive models for climate-driven range shifts of species depend on the integration of information on adaptation, including that derived from genomic studies. Long-lived forest trees can experience substantial environmental change across generations, which results in a much more prominent adaptation lag than in annual species. Here, we show that candidate-gene SNPs (single nucleotide polymorphisms) can be used as predictors of maladaptation to climate in maritime pine (Pinus pinaster Aiton), an outcrossing long-lived keystone tree. A set of 18 SNPs potentially associated with climate, 5 of them involving amino acid-changing variants, were retained after performing logistic regression, latent factor mixed models, and Bayesian analyses of SNP-climate correlations. These relationships identified temperature as an important adaptive driver in maritime pine and highlighted that selective forces are operating differentially in geographically discrete gene pools. The frequency of the locally advantageous alleles at these selected loci was strongly correlated with survival in a common garden under extreme (hot and dry) climate conditions, which suggests that candidate-gene SNPs can be used to forecast the likely destiny of natural forest ecosystems under climate change scenarios. Differential levels of forest decline are anticipated for distinct maritime pine gene pools. Geographically defined molecular proxies for climate adaptation will thus critically enhance the predictive power of range-shift models and help establish mitigation measures for long-lived keystone forest trees in the face of impending climate change.

Spatial variability of soil chemical properties after coffee tree removal

Assessing the spatial variability of soil chemical properties has become an important aspect of soil management strategies with a view to higher crop yields with minimal environmental degradation. This study was carried out at the Centro Experimental of the Instituto Agronomico, in Campinas, São Paulo, Brazil. The aim was to characterize the spatial variability of chemical properties of a Rhodic Hapludox on a recently bulldozer-cleaned area after over 30 years of coffee cultivation. Soil samples were collected in a 20 x 20 m grid with 36 sampling points across a 1 ha area in the layers 0.0-0.2 and 0.2-0.4 m to measure the following chemical properties: pH, organic matter, K+, P, Ca2+, Mg2+, potential acidity, NH4-N, and NO3-N. Descriptive statistics were applied to assess the central tendency and dispersion moments. Geostatistical methods were applied to evaluate and to model the spatial variability of variables by calculating semivariograms and kriging interpolation. Spatial dependence patterns defined by spherical model adjusted semivariograms were made for all cited soil properties. Moderate to strong degrees of spatial dependence were found between 31 and 60 m. It was still possible to map soil spatial variability properties in the layers 0-20 cm and 20-40 cm after plant removal with bulldozers.

Genetic differentiation for size at first reproduction through male versus female functions in the widespread Mediterranean tree Pinus pinaster.

BACKGROUND AND AIMS: The study of local adaptation in plant reproductive traits has received substantial attention in short-lived species, but studies conducted on forest trees are scarce. This lack of research on long-lived species represents an important gap in our knowledge, because inferences about selection on the reproduction and life history of short-lived species cannot necessarily be extrapolated to trees. This study considers whether the size for first reproduction is locally adapted across a broad geographical range of the Mediterranean conifer species Pinus pinaster. In particular, the study investigates whether this monoecious species varies genetically among populations in terms of whether individuals start to reproduce through their male function, their female function or both sexual functions simultaneously. Whether differences among populations could be attributed to local adaptation across a climatic gradient is then considered. METHODS: Male and female reproduction and growth were measured during early stages of sexual maturity of a P. pinaster common garden comprising 23 populations sampled across the species range. Generalized linear mixed models were used to assess genetic variability of early reproductive life-history traits. Environmental correlations with reproductive life-history traits were tested after controlling for neutral genetic structure provided by 12 nuclear simple sequence repeat markers. KEY RESULTS: Trees tended to reproduce first through their male function, at a size (height) that varied little among source populations. The transition to female reproduction was slower, showed higher levels of variability and was negatively correlated with vegetative growth traits. Several female reproductive traits were correlated with a gradient of growth conditions, even after accounting for neutral genetic structure, with populations from more unfavourable sites tending to commence female reproduction at a lower individual size. CONCLUSIONS: The study represents the first report of genetic variability among populations for differences in the threshold size for first reproduction between male and female sexual functions in a tree species. The relatively uniform size at which individuals begin reproducing through their male function probably represents the fact that pollen dispersal is also relatively invariant among sites. However, the genetic variability in the timing of female reproduction probably reflects environment-dependent costs of cone production. The results also suggest that early sex allocation in this species might evolve under constraints that do not apply to other conifers.

Resting-state temporal synchronization networks emerge from connectivity topology and heterogeneity.

Spatial patterns of coherent activity across different brain areas have been identified during the resting-state fluctuations of the brain. However, recent studies indicate that resting-state activity is not stationary, but shows complex temporal dynamics. We were interested in the spatiotemporal dynamics of the phase interactions among resting-state fMRI BOLD signals from human subjects. We found that the global phase synchrony of the BOLD signals evolves on a characteristic ultra-slow (<0.01Hz) time scale, and that its temporal variations reflect the transient formation and dissolution of multiple communities of synchronized brain regions. Synchronized communities reoccurred intermittently in time and across scanning sessions. We found that the synchronization communities relate to previously defined functional networks known to be engaged in sensory-motor or cognitive function, called resting-state networks (RSNs), including the default mode network, the somato-motor network, the visual network, the auditory network, the cognitive control networks, the self-referential network, and combinations of these and other RSNs. We studied the mechanism originating the observed spatiotemporal synchronization dynamics by using a network model of phase oscillators connected through the brain's anatomical connectivity estimated using diffusion imaging human data. The model consistently approximates the temporal and spatial synchronization patterns of the empirical data, and reveals that multiple clusters that transiently synchronize and desynchronize emerge from the complex topology of anatomical connections, provided that oscillators are heterogeneous.

First-generation linkage map for the European tree frog (Hyla arborea) with utility in congeneric species.

BACKGROUND: Western Palearctic tree frogs (Hyla arborea group) represent a strong potential for evolutionary and conservation genetic research, so far underexploited due to limited molecular resources. New microsatellite markers have recently been developed for Hyla arborea, with high cross-species utility across the entire circum-Mediterranean radiation. Here we conduct sibship analyses to map available markers for use in future population genetic applications. FINDINGS: We characterized eight linkage groups, including one sex-linked, all showing drastically reduced recombination in males compared to females, as previously documented in this species. Mapping of the new 15 markers to the ~200 My diverged Xenopus tropicalis genome suggests a generally conserved synteny with only one confirmed major chromosome rearrangement. CONCLUSIONS: The new microsatellites are representative of several chromosomes of H. arborea that are likely to be conserved across closely-related species. Our linkage map provides an important resource for genetic research in European Hylids, notably for studies of speciation, genome evolution and conservation.

Growth of seedlings of pigeon pea (Cajanus cajan (l.) millsp), wand riverhemp (Sesbania virgata (cav.) pers.), and lead tree (Leucaena leucocephala (lam.) de wit) in an arsenic-contaminated soil

Phytoremediation strategies utilize plants to decontaminate or immobilize soil pollutants. Among soil pollutants, metalloid As is considered a primary concern as a toxic element to organisms. Arsenic concentrations in the soil result from anthropogenic activities such as: the use of pesticides (herbicides and fungicides); some fertilizers; Au, Pb, Cu and Ni mining; Fe and steel production; coal combustion; and as a bi-product during natural gas extraction. This study evaluated the potential of pigeon pea (Cajanus cajan), wand riverhemp (Sesbania virgata), and lead tree (Leucaena leucocephala) as phytoremediators of soils polluted by As. Soil samples were placed in plastic pots, incubated with different As doses (0; 50; 100 and 200 mg dm-3) and then sown with seeds of the three species. Thirty (pigeon pea) and 90 days after sowing, the plants were evaluated for height, collar diameter and dry matter of young, intermediate and basal leaves, stems and roots. Arsenic concentration was determined in different aged leaves, stems and roots to establish the translocation index (TI) between the plant root system and aerial plant components and the bioconcentration factors (BF). The evaluated species showed distinct characteristics regarding As tolerance, since the lead tree and wand riverhemp were significantly more tolerant than pigeon pea. The high As levels found in wand riverhemp roots suggest the existence of an efficient accumulation and compartmentalization mechanism in order to reduce As translocation to shoot tissues. Pigeon pea is a sensitive species and could serve as a potential bioindicator plant, whereas the other two species have potential for phytoremediation programs in As polluted areas. However, further studies are needed with longer exposure times in actual field conditions to reach definite conclusions on relative phytoremediation potentials.

Networks of people in specialty production: family firms in the iron and steel Wire industries in Spain (1870-2000)

Capital intensive industries in specialized niches of production have constituted solid ground for family firms in Spain , as evidenced by the experience of the iron and steel wire industries between 1870 and 2000. The embeddedness of these firms in their local and regional environments have allowed the creation of networks that, together with favourable institutional conditions, significantly explain the dominance of family entrepreneurship in iron and steel wire manufacturing in Spain, until the end of the 20 th century. Dominance of family firms at the regional level has not been not an obstacle for innovation in wire manufacturing in Spain, which has taken place even when institutional conditions blocked innovation and traditional networking. Therefore, economic theories about the difficulties dynastic family firms may have to perform appropriately in science-based industries must be questioned

Synchronizability of EEG-Based Functional Networks in Early Alzheimer's Disease.

Recently graph theory and complex networks have been widely used as a mean to model functionality of the brain. Among different neuroimaging techniques available for constructing the brain functional networks, electroencephalography (EEG) with its high temporal resolution is a useful instrument of the analysis of functional interdependencies between different brain regions. Alzheimer's disease (AD) is a neurodegenerative disease, which leads to substantial cognitive decline, and eventually, dementia in aged people. To achieve a deeper insight into the behavior of functional cerebral networks in AD, here we study their synchronizability in 17 newly diagnosed AD patients compared to 17 healthy control subjects at no-task, eyes-closed condition. The cross-correlation of artifact-free EEGs was used to construct brain functional networks. The extracted networks were then tested for their synchronization properties by calculating the eigenratio of the Laplacian matrix of the connection graph, i.e., the largest eigenvalue divided by the second smallest one. In AD patients, we found an increase in the eigenratio, i.e., a decrease in the synchronizability of brain networks across delta, alpha, beta, and gamma EEG frequencies within the wide range of network costs. The finding indicates the destruction of functional brain networks in early AD.

Testing Spatial Autocorrelation in Weighted Networks : the Modes Permutation Test

In a weighted spatial network, as specified by an exchange matrix, the variances of the spatial values are inversely proportional to the size of the regions. Spatial values are no more exchangeable under independence, thus weakening the rationale for ordinary permutation and bootstrap tests of spatial autocorrelation. We propose an alternative permutation test for spatial autocorrelation, based upon exchangeable spatial modes, constructed as linear orthogonal combinations of spatial values. The coefficients obtain as eigenvectors of the standardised exchange matrix appearing in spectral clustering, and generalise to the weighted case the concept of spatial filtering for connectivity matrices. Also, two proposals aimed at transforming an acessibility matrix into a exchange matrix with with a priori fixed margins are presented. Two examples (inter-regional migratory flows and binary adjacency networks) illustrate the formalism, rooted in the theory of spectral decomposition for reversible Markov chains.

Generalizing sample tree information with semiparametric and parametric models

Summary

Validation of network communicability metrics for the analysis of brain structural networks.

Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

Predicting the growth response to thinning for Scots pine stands using individual-tree growth models

Summary