Change in defense mechanisms and coping over the course of short-term dynamic psychotherapy for adjustment disorder.

Short-term dynamic psychotherapy (STDP) has rarely been investigated with regard to its underlying mechanisms of change, even if psychoanalytic theory informs us about several potential putative mechanisms of change in patients. Change in overall defensive functioning is one. In this study, we explored the role of overall defensive functioning, by comparing it on the process level with the neighbouring concept of overall coping functioning. A total of N=32 patients, mainly presenting adjustment disorder, were included in the study. The patients underwent STDP up to 40 sessions; three sessions per psychotherapy were transcribed and analyzed by using two observer-rating scales: Defense Mechanism Rating Scales (Perry, 1990) and Coping Action Patterns (Perry, Drapeau, Dunkley, & Blake, 2005). Hierarchical linear modeling was applied to model the change over the course of therapy and relate it to outcome. Results suggest that STDP has an effect on the target variable of overall defensive functioning, which was absent for overall coping functioning. Links with outcome confirm the importance of the effect. These results are discussed from methodological and clinical viewpoints.

Reaction-diffusion wave fronts: Multigeneration biological species under climate change

A generalization of reaction-diffusion models to multigeneration biological species is presented. It is based on more complex random walks than those in previous approaches. The new model is developed analytically up to infinite order. Our predictions for the speed agree to experimental data for several butterfly species better than existing models. The predicted dependence for the speed on the number of generations per year allows us to explain the change in speed observed for a specific invasion

Kernel-based methods for change detection in remote sensing images

Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.

Proteomic analysis of mononuclear cells of patients with minimal-change nephrotic syndrome of childhood.

Background/Aims. Recently, peripheral blood mononuclear cell transcriptome analysis has identified genes that are upregulated in relapsing minimal-change nephrotic syndrome (MCNS). In order to investigate protein expression in peripheral blood mononuclear cells (PBMC) from relapsing MCNS patients, we performed proteomic comparisons of PBMC from patients with MCNS in relapse and controls. METHODS: PBMC from a total of 20 patients were analysed. PBMC were taken from five patients with relapsing MCNS, four in remission, five patients with other glomerular diseases and six controls. Two dimensional electrophoresis was performed and proteome patterns were compared. RESULTS: Automatic heuristic clustering analysis allowed us to pool correctly the gels from the MCNS patients in the relapse and in the control groups. Using hierarchical population matching, nine spots were found to be increased in PBMC from MCNS patients in relapse. Four spots were identified by mass spectrometry. Three of the four proteins identified (L-plastin, alpha-tropomyosin and annexin III) were cytoskeletal-associated proteins. Using western blot and immunochemistry, L-plastin and alpha-tropomyosin 3 concentrations were found to be enhanced in PBMC from MCNS patients in relapse. Conclusions. These data indicate that a specific proteomic profile characterizes PBMC from MCNS patients in relapse. Proteins involved in PBMC cytoskeletal rearrangement are increased in relapsing MCNS. We hypothesize that T-cell cytoskeletal rearrangement may play a role in the pathogenesis of MCNS by altering the expression of cell surface receptors and by modifying the interaction of these cells with glomerular cells.

An Analysis of black-box optimization problems in reinsurance: evolutionary-based approaches

Black-box optimization problems (BBOP) are de ned as those optimization problems in which the objective function does not have an algebraic expression, but it is the output of a system (usually a computer program). This paper is focussed on BBOPs that arise in the eld of insurance, and more speci cally in reinsurance problems. In this area, the complexity of the models and assumptions considered to de ne the reinsurance rules and conditions produces hard black-box optimization problems, that must be solved in order to obtain the optimal output of the reinsurance. The application of traditional optimization approaches is not possible in BBOP, so new computational paradigms must be applied to solve these problems. In this paper we show the performance of two evolutionary-based techniques (Evolutionary Programming and Particle Swarm Optimization). We provide an analysis in three BBOP in reinsurance, where the evolutionary-based approaches exhibit an excellent behaviour, nding the optimal solution within a fraction of the computational cost used by inspection or enumeration methods.

Fishery-induced selection on an Alpine whitefish: quantifying genetic and environmental effects on individual growth rate

Size-selective fishing, environmental changes and reproductive strategies are expected to affect life-history traits such as the individual growth rate. The relative contribution of these factors is not clear, particularly whether size-selective fishing can have a substantial impact on the genetics and hence on the evolution of individual growth rates in wild populations. We analysed a 25-year monitoring survey of an isolated population of the Alpine whitefish Coregonus palaea. We determined the selection differentials on growth rate, the actual change of growth rate over time and indicators of reproductive strategies that may potentially change over time. The selection differential can be reliably estimated in our study population because almost all the fish are harvested within their first years of life, i.e. few fish escape fishing mortality. We found a marked decline in average adult growth rate over the 25 years and a significant selection differential for adult growth, but no evidence for any linear change in reproductive strategies over time. Assuming that the heritability of growth in this whitefish corresponds to what was found in other salmonids, about a third of the observed decline in growth rate would be linked to fishery-induced evolution. Size-selective fishing seems to affect substantially the genetics of individual growth in our study population.

Change in biased thinking in a 10-session treatment for borderline personality disorder: Further evidence of the motive-oriented therapeutic relationship.

Abstract Borderline Personality Disorder (BPD) is characterized by both maladaptive thinking and problematic schemas. Kramer and colleagues (2011) showed that using the motive-oriented therapeutic relationship (MOTR), based on the individualized understanding of the patient according to Plan Analysis (Caspar, 2007), can improve treatment outcomes for BPD. The present process-outcome pilot study aimed to examine the effects of the motive-oriented therapeutic relationship on the cognitive biases of patients with BPD. Change in biased cognitions in N=10 patients who were subject to MOTR was compared to that of N=10 patients who received psychiatric-psychodynamic treatment (Gunderson & Links, 2008). Results show a greater decrease in over-generalizations in patients who received MOTR, compared to the patients who received the psychiatric-psychodynamic treatment. These changes were related to outcome in various ways. These findings underline the importance of an individualized case formulation method in bringing about therapeutic change.

C-H···O H-bonded complexes: how does basis set superposition error change their potential-energy surfaces?

Geometries, vibrational frequencies, and interaction energies of the CNH⋯O3 and HCCH⋯O3 complexes are calculated in a counterpoise-corrected (CP-corrected) potential-energy surface (PES) that corrects for the basis set superposition error (BSSE). Ab initio calculations are performed at the Hartree-Fock (HF) and second-order Møller-Plesset (MP2) levels, using the 6-31G(d,p) and D95++(d,p) basis sets. Interaction energies are presented including corrections for zero-point vibrational energy (ZPVE) and thermal correction to enthalpy at 298 K. The CP-corrected and conventional PES are compared; the unconnected PES obtained using the larger basis set including diffuse functions exhibits a double well shape, whereas use of the 6-31G(d,p) basis set leads to a flat single-well profile. The CP-corrected PES has always a multiple-well shape. In particular, it is shown that the CP-corrected PES using the smaller basis set is qualitatively analogous to that obtained with the larger basis sets, so the CP method becomes useful to correctly describe large systems, where the use of small basis sets may be necessary

How does basis set superposition error change the potential surfaces for hydrogen-bonded dimers?

We describe a simple method to automate the geometric optimization of molecular orbital calculations of supermolecules on potential surfaces that are corrected for basis set superposition error using the counterpoise (CP) method. This method is applied to the H-bonding complexes HF/HCN, HF/H2O, and HCCH/H2O using the 6-31G(d,p) and D95 + + (d,p) basis sets at both the Hartree-Fock and second-order Møller-Plesset levels. We report the interaction energies, geometries, and vibrational frequencies of these complexes on the CP-optimized surfaces; and compare them with similar values calculated using traditional methods, including the (more traditional) single point CP correction. Upon optimization on the CP-corrected surface, the interaction energies become more negative (before vibrational corrections) and the H-bonding stretching vibrations decrease in all cases. The extent of the effects vary from extremely small to quite large depending on the complex and the calculational method. The relative magnitudes of the vibrational corrections cannot be predicted from the H-bond stretching frequencies alone

Multisensor change detection with nonlinear canonical correlation

The analysis of multi-modal and multi-sensor images is nowadays of paramount importance for Earth Observation (EO) applications. There exist a variety of methods that aim at fusing the different sources of information to obtain a compact representation of such datasets. However, for change detection existing methods are often unable to deal with heterogeneous image sources and very few consider possible nonlinearities in the data. Additionally, the availability of labeled information is very limited in change detection applications. For these reasons, we present the use of a semi-supervised kernel-based feature extraction technique. It incorporates a manifold regularization accounting for the geometric distribution and jointly addressing the small sample problem. An exhaustive example using Landsat 5 data illustrates the potential of the method for multi-sensor change detection.

Evolutionary patterns of MHC class II B in owls and their implications for the understanding of avian MHC evolution

Owing to its special mode of evolution and central role in the adaptive immune system, the major histocompatibility complex (MHC) has become the focus of diverse disciplines such as immunology, evolutionary ecology, and molecular evolution. MHC evolution has been studied extensively in diverse vertebrate lineages over the last few decades, and it has been suggested that birds differ from the established mammalian norm. Mammalian MHC genes evolve independently, and duplication history (i.e., orthology) can usually be traced back within lineages. In birds, this has been observed in only 3 pairs of closely related species. Here we report strong evidence for the persistence of orthology of MHC genes throughout an entire avian order. Phylogenetic reconstructions of MHC class II B genes in 14 species of owls trace back orthology over tens of thousands of years in exon 3. Moreover, exon 2 sequences from several species show closer relationships than sequences within species, resembling transspecies evolution typically observed in mammals. Thus, although previous studies suggested that long-term evolutionary dynamics of the avian MHC was characterized by high rates of concerted evolution, resulting in rapid masking of orthology, our results question the generality of this conclusion. The owl MHC thus opens new perspectives for a more comprehensive understanding of avian MHC evolution.

21st century climate change: where has all the geomorphology gone?

This Commentary draws together recently published work relating to the relationship between climate change and geomorphology to address the surprising observation that geomorphic work seems to have had little impact upon the work of the Intergovernmental Panel for Climate Change. However, recent papers show that methodological innovation has allowed geomorphological reconstruction over timescales highly relevant to late 20th century and 21st century climate change. In turn, these and other developments are allowing links to be made between climatic variability and geomorphology, to begin to predict geomorphic futures and also to appreciate the role that geomorphic processes play in the flux of carbon and the carbon cycle.

Biodiversity and global change in Mediterranean benthic communities: perspectives over large spatial and long temporal scales

Many terrestrial and marine systems are experiencing accelerating decline due to the effects of global change. This situation has raised concern about the consequences of biodiversity losses for ecosystem function, ecosystem service provision, and human well-being. Coastal marine habitats are a main focus of attention because they harbour a high biological diversity, are among the most productive systems of the world and present high anthropogenic interaction levels. The accelerating degradation of many terrestrial and marine systems highlights the urgent need to evaluate the consequence of biodiversity loss. Because marine biodiversity is a dynamic entity and this study was interested global change impacts, this study focused on benthic biodiversity trends over large spatial and long temporal scales. The main aim of this project was to investigate the current extent of biodiversity of the high diverse benthic coralligenous community in the Mediterranean Sea, detect its changes, and predict its future changes over broad spatial and long temporal scales. These marine communities are characterized by structural species with low growth rates and long life spans; therefore they are considered particularly sensitive to disturbances. For this purpose, this project analyzed permanent photographic plots over time at four locations in the NW Mediterranean Sea. The spatial scale of this study provided information on the level of species similarity between these locations, thus offering a solid background on the amount of large scale variability in coralligenous communities; whereas the temporal scale was fundamental to determine the natural variability in order to discriminate between changes observed due to natural factors and those related to the impact of disturbances (e.g. mass mortality events related to positive thermal temperatures, extreme catastrophic events). This study directly addressed the challenging task of analyzing quantitative biodiversity data of these high diverse marine benthic communities. Overall, the scientific knowledge gained with this research project will improve our understanding in the function of marine ecosystems and their trajectories related to global change.

Modeling the biophysical impacts of global change in mountain biosphere reserves

Mountains and mountain societies provide a wide range of goods and services to humanity, but they are particularly sensitive to the effects of global environmental change. Thus, the definition of appropriate management regimes that maintain the multiple functions of mountain regions in a time of greatly changing climatic, economic, and societal drivers constitutes a significant challenge. Management decisions must be based on a sound understanding of the future dynamics of these systems. The present article reviews the elements required for an integrated effort to project the impacts of global change on mountain regions, and recommends tools that can be used at 3 scientific levels (essential, improved, and optimum). The proposed strategy is evaluated with respect to UNESCO's network of Mountain Biosphere Reserves (MBRs), with the intention of implementing it in other mountain regions as well. First, methods for generating scenarios of key drivers of global change are reviewed, including land use/land cover and climate change. This is followed by a brief review of the models available for projecting the impacts of these scenarios on (1) cryospheric systems, (2) ecosystem structure and diversity, and (3) ecosystem functions such as carbon and water relations. Finally, the cross-cutting role of remote sensing techniques is evaluated with respect to both monitoring and modeling efforts. We conclude that a broad range of techniques is available for both scenario generation and impact assessments, many of which can be implemented without much capacity building across many or even most MBRs. However, to foster implementation of the proposed strategy, further efforts are required to establish partnerships between scientists and resource managers in mountain areas.

The evolutionary history of the CD209 (DC-SIGN) family in humans and non-human primates

The CD209 gene family that encodes C-type lectins in primates includes CD209 (DC-SIGN), CD209L (L-SIGN) and CD209L2. Understanding the evolution of these genes can help understand the duplication events generating this family, the process leading to the repeated neck region and identify protein domains under selective pressure. We compiled sequences from 14 primates representing 40 million years of evolution and from three non-primate mammal species. Phylogenetic analyses used Bayesian inference, and nucleotide substitutional patterns were assessed by codon-based maximum likelihood. Analyses suggest that CD209 genes emerged from a first duplication event in the common ancestor of anthropoids, yielding CD209L2 and an ancestral CD209 gene, which, in turn, duplicated in the common Old World primate ancestor, giving rise to CD209L and CD209. K(A)/K(S) values averaged over the entire tree were 0.43 (CD209), 0.52 (CD209L) and 0.35 (CD209L2), consistent with overall signatures of purifying selection. We also assessed the Toll-like receptor (TLR) gene family, which shares with CD209 genes a common profile of evolutionary constraint. The general feature of purifying selection of CD209 genes, despite an apparent redundancy (gene absence and gene loss), may reflect the need to faithfully recognize a multiplicity of pathogen motifs, commensals and a number of self-antigens