Assessment of emotional reactivity produced by exposure to virtual environments in patients with eating disorders

The aim of this study was to assess the usefulness of virtual environments representing situations that are emotionally significant to subjects with eating disorders (ED). These environments may be applied with both evaluative and therapeutic aims and in simulation procedures to carry out a range of experimental studies. This paper is part of a wider research project analyzing the influence of the situation to which subjects are exposed on their performance on body image estimation tasks. Thirty female patients with eating disorders were exposed to six virtual environments: a living-room (neutral situation), a kitchen with highcalorie food, a kitchen with low-calorie food, a restaurant with high-calorie food, a restaurant with low-calorie food, and a swimming-pool. After exposure to each environment the STAI-S (a measurement of state anxiety) and the CDB (a measurement of depression) were administered to all subjects. The results show that virtual reality instruments are particularly useful for simulating everyday situations that may provoke emotional reactions such as anxiety and depression, in patients with ED. Virtual environments in which subjects are obliged to ingest high-calorie food provoke the highest levels of state anxiety and depression.

Predictive analysis and mapping of indoor radon concentrations in Switzerland

It is estimated that around 230 people die each year due to radon (222Rn) exposure in Switzerland. 222Rn occurs mainly in closed environments like buildings and originates primarily from the subjacent ground. Therefore it depends strongly on geology and shows substantial regional variations. Correct identification of these regional variations would lead to substantial reduction of 222Rn exposure of the population based on appropriate construction of new and mitigation of already existing buildings. Prediction of indoor 222Rn concentrations (IRC) and identification of 222Rn prone areas is however difficult since IRC depend on a variety of different variables like building characteristics, meteorology, geology and anthropogenic factors. The present work aims at the development of predictive models and the understanding of IRC in Switzerland, taking into account a maximum of information in order to minimize the prediction uncertainty. The predictive maps will be used as a decision-support tool for 222Rn risk management. The construction of these models is based on different data-driven statistical methods, in combination with geographical information systems (GIS). In a first phase we performed univariate analysis of IRC for different variables, namely the detector type, building category, foundation, year of construction, the average outdoor temperature during measurement, altitude and lithology. All variables showed significant associations to IRC. Buildings constructed after 1900 showed significantly lower IRC compared to earlier constructions. We observed a further drop of IRC after 1970. In addition to that, we found an association of IRC with altitude. With regard to lithology, we observed the lowest IRC in sedimentary rocks (excluding carbonates) and sediments and the highest IRC in the Jura carbonates and igneous rock. The IRC data was systematically analyzed for potential bias due to spatially unbalanced sampling of measurements. In order to facilitate the modeling and the interpretation of the influence of geology on IRC, we developed an algorithm based on k-medoids clustering which permits to define coherent geological classes in terms of IRC. We performed a soil gas 222Rn concentration (SRC) measurement campaign in order to determine the predictive power of SRC with respect to IRC. We found that the use of SRC is limited for IRC prediction. The second part of the project was dedicated to predictive mapping of IRC using models which take into account the multidimensionality of the process of 222Rn entry into buildings. We used kernel regression and ensemble regression tree for this purpose. We could explain up to 33% of the variance of the log transformed IRC all over Switzerland. This is a good performance compared to former attempts of IRC modeling in Switzerland. As predictor variables we considered geographical coordinates, altitude, outdoor temperature, building type, foundation, year of construction and detector type. Ensemble regression trees like random forests allow to determine the role of each IRC predictor in a multidimensional setting. We found spatial information like geology, altitude and coordinates to have stronger influences on IRC than building related variables like foundation type, building type and year of construction. Based on kernel estimation we developed an approach to determine the local probability of IRC to exceed 300 Bq/m3. In addition to that we developed a confidence index in order to provide an estimate of uncertainty of the map. All methods allow an easy creation of tailor-made maps for different building characteristics. Our work is an essential step towards a 222Rn risk assessment which accounts at the same time for different architectural situations as well as geological and geographical conditions. For the communication of 222Rn hazard to the population we recommend to make use of the probability map based on kernel estimation. The communication of 222Rn hazard could for example be implemented via a web interface where the users specify the characteristics and coordinates of their home in order to obtain the probability to be above a given IRC with a corresponding index of confidence. Taking into account the health effects of 222Rn, our results have the potential to substantially improve the estimation of the effective dose from 222Rn delivered to the Swiss population.

Melanin-based colorations signal strategies to cope with poor and rich environments

One hypothesis for the maintenance of genetic variation states that alternative genotypes are adapted to different environmental conditions (i.e., genotype-by-environment interaction GxE) that vary in space and time. Although GxE has been demonstrated for morphological traits, little evidence has been given whether these GxE are associated with traits used as signal in mate choice. In three wild bird species, we investigated whether the degree of melanin-based coloration, a heritable trait, covaries with nestling growth rate in rich and poor environments. Variation in the degree of reddish-brown phaeomelanism is pronounced in the barn owl (Tyto alba) and tawny owl (Strix aluco), and variation in black eumelanism in the barn owl and Alpine swift (Apus melba). Melanin-based coloration has been shown to be a criterion in mate choice in the barn owl. We cross-fostered hatchlings to test whether nestlings sired by parents displaying melanin-based colorations to different extent exhibit alternative growth trajectories when raised by foster parents in poor (experimentally enlarged broods) and rich (experimentally reduced broods) environments. With respect to phaeomelanism, barn owl and tawny owl offspring sired by redder parents grew more rapidly in body mass only in experimentally reduced broods. With respect to eumelanism, Alpine swift offspring of darker fathers grew their wings more rapidly only in experimentally enlarged broods, a difference that was not detected in reduced broods. These interactions between parental melanism and offspring growth rate indicate that individuals display substantial plasticity in response to the rearing environment which is associated with the degree of melanism: at least with respect to nestling growth, phaeomelanic and eumelanic individuals are best adapted to rich and poor environments, respectively. It now remains to be investigated why eumelanism and phaeomelanism have a different signaling function and what the lifelong consequences of these melanism-dependent allocation strategies are. This is important to fully appraise the role played by environmental heterogeneity in maintaining variation in the degree of melanin-based coloration.

Fate of Hydrophilic Nanoparticles in Biological Environments

The nanoparticles developed are based on chitosan, a biocompatible and biodegradable polysaccharide. The chitosan nanoparticles are formed in an entirely water-based process by electrostatic interactions with other biocompatible molecules. As a prerequisite to understand the fate of such nanoparticles in cells, comprehensive characterization and stability studies serve to identify quantitatively the impact of the raw material characteristics and preparation conditions on the nanoparticle characteristics. Methods included H-1 NMR spectroscopy, dilution viscometry, particle size analysis and electron microscopy. Cytotoxicity and cell uptake experiments on RAW 264.7 murine macrophages and p23 murine endothelial cells were performed to investigate the correlation with nanoparticle characteristics and effect of surface decoration with alginate. Cytotoxicity was assessed by the MTT survival test; cell uptake was monitored by fluorescent microscopy using labeled polymers.

A non-linear VAD for noisy environments

This paper deals with non-linear transformations for improving the performance of an entropy-based voice activity detector (VAD). The idea to use a non-linear transformation has already been applied in the field of speech linear prediction, or linear predictive coding (LPC), based on source separation techniques, where a score function is added to classical equations in order to take into account the true distribution of the signal. We explore the possibility of estimating the entropy of frames after calculating its score function, instead of using original frames. We observe that if the signal is clean, the estimated entropy is essentially the same; if the signal is noisy, however, the frames transformed using the score function may give entropy that is different in voiced frames as compared to nonvoiced ones. Experimental evidence is given to show that this fact enables voice activity detection under high noise, where the simple entropy method fails.

Modelling ecological niches with support vector machines

1. The ecological niche is a fundamental biological concept. Modelling species' niches is central to numerous ecological applications, including predicting species invasions, identifying reservoirs for disease, nature reserve design and forecasting the effects of anthropogenic and natural climate change on species' ranges. 2. A computational analogue of Hutchinson's ecological niche concept (the multidimensional hyperspace of species' environmental requirements) is the support of the distribution of environments in which the species persist. Recently developed machine-learning algorithms can estimate the support of such high-dimensional distributions. We show how support vector machines can be used to map ecological niches using only observations of species presence to train distribution models for 106 species of woody plants and trees in a montane environment using up to nine environmental covariates. 3. We compared the accuracy of three methods that differ in their approaches to reducing model complexity. We tested models with independent observations of both species presence and species absence. We found that the simplest procedure, which uses all available variables and no pre-processing to reduce correlation, was best overall. Ecological niche models based on support vector machines are theoretically superior to models that rely on simulating pseudo-absence data and are comparable in empirical tests. 4. Synthesis and applications. Accurate species distribution models are crucial for effective environmental planning, management and conservation, and for unravelling the role of the environment in human health and welfare. Models based on distribution estimation rather than classification overcome theoretical and practical obstacles that pervade species distribution modelling. In particular, ecological niche models based on machine-learning algorithms for estimating the support of a statistical distribution provide a promising new approach to identifying species' potential distributions and to project changes in these distributions as a result of climate change, land use and landscape alteration.

Quantitative comparison between simulations of seismic wave propagation in heterogeneous poro-elastic media and equivalent visco-elastic solids for marine-type environments

There is increasing evidence to suggest that the presence of mesoscopic heterogeneities constitutes an important seismic attenuation mechanism in porous rocks. As a consequence, centimetre-scale perturbations of the rock physical properties should be taken into account for seismic modelling whenever detailed and accurate responses of specific target structures are desired, which is, however, computationally prohibitive. A convenient way to circumvent this problem is to use an upscaling procedure to replace each of the heterogeneous porous media composing the geological model by corresponding equivalent visco-elastic solids and to solve the visco-elastic equations of motion for the inferred equivalent model. While the overall qualitative validity of this procedure is well established, there are as of yet no quantitative analyses regarding the equivalence of the seismograms resulting from the original poro-elastic and the corresponding upscaled visco-elastic models. To address this issue, we compare poro-elastic and visco-elastic solutions for a range of marine-type models of increasing complexity. We found that despite the identical dispersion and attenuation behaviour of the heterogeneous poro-elastic and the equivalent visco-elastic media, the seismograms may differ substantially due to diverging boundary conditions, where there exist additional options for the poro-elastic case. In particular, we observe that at the fluid/porous-solid interface, the poro- and visco-elastic seismograms agree for closed-pore boundary conditions, but differ significantly for open-pore boundary conditions. This is an important result which has potentially far-reaching implications for wave-equation-based algorithms in exploration geophysics involving fluid/porous-solid interfaces, such as, for example, wavefield decomposition.

Spatial learning by rats across visually disconnected environments

Two spatial tasks were designed to test specific properties of spatial representation in rats. In the first task, rats were trained to locate an escape hole at a fixed position in a visually homogeneous arena. This arena was connected with a periphery where a full view of the room environment existed. Therefore, rats were dependent on their memory trace of the previous position in the periphery to discriminate a position within the central region. Under these experimental conditions, the test animals showed a significant discrimination of the training position without a specific local view. In the second task, rats were trained in a radial maze consisting of tunnels that were transparent at their distal ends only. Because the central part of the maze was non-transparent, rats had to plan and execute appropriate trajectories without specific visual feedback from the environment. This situation was intended to encourage the reliance on prospective memory of the non-visited arms in selecting the following move. Our results show that acquisition performance was only slightly decreased compared to that shown in a completely transparent maze and considerably higher than in a translucent maze or in darkness. These two series of experiments indicate (1) that rats can learn about the relative position of different places with no common visual panorama, and (2) that they are able to plan and execute a sequence of visits to several places without direct visual feed-back about their relative position.

Ain't no mountain high enough: plant invasions reaching new elevations

Most studies of invasive species have been in highly modified, lowland environments, with comparatively little attention directed to less disturbed, high-elevation environments. However, increasing evidence indicates that plant invasions do occur in these environments, which often have high conservation value and provide important ecosystem services. Over a thousand non-native species have become established in natural areas at high elevations worldwide, and although many of these are not invasive, some may pose a considerable threat to native mountain ecosystems. Here, we discuss four main drivers that shape plant invasions into high-elevation habitats: (1) the (pre-)adaptation of non-native species to abiotic conditions, (2) natural and anthropogenic disturbances, (3) biotic resistance of the established communities, and (4) propagule pressure. We propose a comprehensive research agenda for tackling the problem of plant invasions into mountain ecosystems, including documentation of mountain invasion patterns at multiple scales, experimental studies, and an assessment of the impacts of non-native species in these systems. The threat posed to high-elevation biodiversity by invasive plant species is likely to increase because of globalization and climate change. However, the higher mountains harbor ecosystems where invasion by non-native species has scarcely begun, and where science and management have the opportunity to respond in time.

Climatic and anthropogenic influence on the stable isotope record from bulk carbonates and ostracodes in Lake Neuchatel, Switzerland, during the last two millennia

Lake Neuchatel is a medium sized, hard-water lake, lacking varved sediments, situated in the western Swiss Lowlands at the foot of the Jura Mountains. Stable isotope data (delta(18)O and delta(13)C) from both bulk carbonate and ostracode calcite in an 81 cm long, radiocarbon-dated sediment core represent the last 1500 years of Lake Neuchatel's environmental history. Comparison between this isotopic and other palaeolimnologic data (mineralogical, geochemical, palynological, etc.) helps to differentiate between anthropogenic and natural factors most recently affecting the lake. An increase in lacustrine productivity (450-650AD ca), inferred from the positive trend in delta(13)C values of bulk carbonate, is related to medieval forest clearances and the associated nutrient budget changes. A negative trend in both the bulk carbonate and ostracode calcite delta(18)O values between approximately 1300 and 1500AD, is tentatively interpreted as due to a cooling in mean air temperature at the transition from the Medieval Warm Period to the Little Ice Age. Negative trends in bulk carbonate delta(18)O and delta(13)C values through the uppermost sediments, which have no equivalent in ostracode calcite isotopic values, are concomitant with the recent onset of eutrophication in the lake. Isotopic disequilibrium during calcite precipitation, probably due to kinetic factors in periods of high productivity is postulated as the mechanism to explain the associated negative isotopic trends, although the effect of a shift of the calcite precipitation towards the warmer months cannot be excluded.

QTL mapping for protein content in soybean cultivated in two tropical environments

The objectives of this study were to detect quantitative trait loci (QTL) for protein content in soybean grown in two distinct tropical environments and to build a genetic map for protein content. One hundred eighteen soybean recombinant inbred lines (RIL), obtained from a cross between cultivars BARC 8 and Garimpo, were used. The RIL were cultivated in two distinct Brazilian tropical environments: Cascavel county, in Paraná, and Viçosa county, in Minas Gerais (24º57'S, 53º27'W and 20º45'S, 42º52'W, respectively). Sixty-six SSR primer pairs and 65 RAPD primers were polymorphic and segregated at a 1:1 proportion. Thirty poorly saturated linkage groups were obtained, with 90 markers and 41 nonlinked markers. For the lines cultivated in Cascavel, three QTL were mapped in C2, E and N linkage groups, which explained 14.37, 10.31 and 7.34% of the phenotypic variation of protein content, respectively. For the lines cultivated in Viçosa, two QTL were mapped in linkage groups G and #1, which explained 9.51 and 7.34% of the phenotypic variation of protein content. Based on the mean of the two environments, two QTL were identified: one in the linkage group E (9.90%) and other in the group L (7.11%). In order for future studies to consistently detect QTL effects of different environments, genotypes with greater stability should be used.

Structure of Poduromorpha (Collembola) communities in "restinga" environments in Brazil

The objectives of this work were to evaluate the richness and diversity of the Poduromorpha fauna in two biotopes in Restinga de Maricá, RJ, Brazil, to identify the characteristic species of each biotope and to determine the relationships between the community structure and the abiotic environmental parameters. Representatives of the Poduromorpha (Collembola) order were studied under an ecological viewpoint in halophyte-psammophyte vegetation and foredune zone in preserved areas of Restinga de Maricá, a sand dune environment in the state of Rio de Janeiro, Brazil. The foredune zone showed the highest diversity, richness and equitability of springtail species. Differences in the fundamental, accessory and accidental species in each environment were encountered. Paraxenylla piloua was found to be an indicator species of the halophyte-psammophyte vegetation, while Friesea reducta, Pseudachorutes difficilis and Xenylla maritima were indicators of the foredune zone. The canonical correspondence analysis indicated pH, organic matter content and soil humidity as the most important factors influencing the spatiotemporal distribution of the species.

The earthworm fauna of regenerating forests and anthropogenic habitats in the coastal region of Paraná

The aim of this study was to evaluate abundance, biomass and diversity of earthworms in the southern coast region of the Mata Atlântica biodiversity hotspot. A total of 51 study sites in pastures, banana monocultures, mixed agroforestry systems, secondary forests in succession and old-growth forests near the coast of Paraná, Brazil, were evaluated. Each site was sampled once. Species richness of the earthworms was generally low and varied little between sites. At all sites except for one, the peregrine species Pontoscolex corethrurus (Glossoscolecidae) strongly dominated. Three other peregrine species, Amynthas corticis, Amynthas gracilis (Megascolecidae) and Ocnerodrilus occidentalis (Ocnerodrilidae), were frequent in moist sites. No autochthonous species were found. Abundance and biomass of earthworms varied strongly within and between sites (0-338 individuals m-2, 0-96 g m-2 fresh weight). Pastures had significantly lower abundance than all other sites. The forest sites had similar earthworm abundance and biomass, with a tendency to be higher in younger succession stages. The coastal plain region has been strongly altered by human activities. Reasons for the lack of any autochthonous species and the dominance of one peregrine species require further investigation.