Cadmium distribution in soils covering Jurassic oolitic limestone with high Cd contents in the Swiss Jura

Oolitic carbonates belonging to the Hauptrogenstein Formation of Bajocian (Middle Jurassic) age have been shown to be anomalously enriched in cadmium (Cd) throughout the Jura Mountains. Soils associated with this type of rock substratum may be naturally polluted with regards to Cd. At Schleifenberg (Canton Basel Land, Switzerland) the Hauptrogenstein Formation is almost entirely exposed along a trail on its SW flank. Cadmium concentrations were systematically measured throughout this formation and Cd enrichments in rocks are shown to occur to a maximum content of 4.9 mg kg(-1). We investigated associated soils, which cover the entire outcrop, and show that they have been formed through the weathering of the underlying bedrock and through the uptake of colluvial limestone fragments from the same and older formations. Cadmium contents in the soils reach a maximum value of 2.0 mg kg(-1), thereby exceeding the official Swiss indicative guideline value for soils fixed at 0.8 mg.kg(-1). Mineralogical analyses on the soils and associated bedrock suggest that no allochthonous component related to aeolian transport is present. Sequential extractions applied to selected soil samples show that about half of the Cd resides in the carbonate fraction coming from the fractured parent-rock, while the Cd released from the weathered carbonates is associated either with organic matter (over 10%) or with Fe and Mn-oxihydroxides (approximately 30%). No exchangeable Cd phase was found and this, together with the buffer capacity of this calcareous soil, suggests that the amount of mobile Cd is quite negligible in this soil, which also greatly reduces the amount of bioavailable

Comparison of plantar pressure distribution in adolescent runners at low vs. high running velocity.

This study aimed to compare foot plantar pressure distribution while jogging and running in highly trained adolescent runners. Eleven participants performed two constant-velocity running trials either at jogging (11.2 ± 0.9 km/h) or running (17.8 ± 1.4 km/h) pace on a treadmill. Contact area (CA in cm(2)), maximum force (F(max) in N), peak pressure (PP in kPa), contact time (CT in ms), and relative load (force time integral in each individual region divided by the force time integral for the total plantar foot surface, in %) were measured in nine regions of the right foot using an in-shoe plantar pressure device. Under the whole foot, CA, F(max) and PP were lower in jogging than in running (-1.2% [p<0.05], -12.3% [p<0.001] and -15.1% [p<0.01] respectively) whereas CT was higher (+20.1%; p<0.001). Interestingly, we found an increase in relative load under the medial and central forefoot regions while jogging (+6.7% and +3.7%, respectively; [p<0.05]), while the relative load under the lesser toes (-8.4%; p<0.05) was reduced. In order to prevent overloading of the metatarsals in adolescent runners, excessive mileage at jogging pace should be avoided.

Suitability, success and sinks: how do predictions of nesting distributions relate to fitness parameters in high arctic waders?

AimAlthough habitat suitability maps derived from species distribution models (SDMs) are often assumed to highlight locations that can sustain healthy populations over time, the relationship between suitability scores and fitness parameters has rarely been tested thoroughly. LocationZackenberg Valley, north-east Greenland. MethodsUsing 14years of data (1997-2010) representing three wader species (dunlin Calidris alpina, sanderling Calidris alba and ruddy turnstone Arenaria interpres), we tested the relationships between modelled suitability and fitness parameters at nesting locations. ResultsAmong the three species examined, only the ruddy turnstone exhibited significant relationships between suitability and nest success, but over time rather than space. During years with extensive snow cover in the landscape, the nesting sites of ruddy turnstone occurred in different habitats than were typically used across years. Moreover, in years with extensive snow cover, the ruddy turnstone initiated nests later and suffered from higher egg predation rates. Main conclusionOur results suggest that SDMs derived from species occurrences that include years of low reproductive success may over-estimate the potential suitable habitat in the landscape. Whenever possible, variation in reproductive success should be considered when building models to inform species' response to environmental change. species' response to environmental change.

Cell size distribution in a random tessellation of space governed by the Kolmogorov-Johnson-Mehl-Avrami model: Grain size distribution in crystallization

The space subdivision in cells resulting from a process of random nucleation and growth is a subject of interest in many scientific fields. In this paper, we deduce the expected value and variance of these distributions while assuming that the space subdivision process is in accordance with the premises of the Kolmogorov-Johnson-Mehl-Avrami model. We have not imposed restrictions on the time dependency of nucleation and growth rates. We have also developed an approximate analytical cell size probability density function. Finally, we have applied our approach to the distributions resulting from solid phase crystallization under isochronal heating conditions

Discourse Type Clustering using POS n-gram Profiles and High-Dimensional Embeddings

Abstract: To cluster textual sequence types (discourse types/modes) in French texts, K-means algorithm with high-dimensional embeddings and fuzzy clustering algorithm were applied on clauses whose POS (part-ofspeech) n-gram profiles were previously extracted. Uni-, bi- and trigrams were used on four 19th century French short stories by Maupassant. For high-dimensional embeddings, power transformations on the chi-squared distances between clauses were explored. Preliminary results show that highdimensional embeddings improve the quality of clustering, contrasting the use of bi and trigrams whose performance is disappointing, possibly because of feature space sparsity.

High-intensity running and plantar-flexor fatigability and plantar-pressure distribution in adolescent runners.

CONTEXT: Fatigue-induced alterations in foot mechanics may lead to structural overload and injury. OBJECTIVES: To investigate how a high-intensity running exercise to exhaustion modifies ankle plantar-flexor and dorsiflexor strength and fatigability, as well as plantar-pressure distribution in adolescent runners. DESIGN: Controlled laboratory study. SETTING: Academy research laboratory. PATIENTS OR OTHER PARTICIPANTS: Eleven male adolescent distance runners (age = 16.9 ± 2.0 years, height = 170.6 ± 10.9 cm, mass = 54.6 ± 8.6 kg) were tested. INTERVENTION(S): All participants performed an exhausting run on a treadmill. An isokinetic plantar-flexor and dorsiflexor maximal-strength test and a fatigue test were performed before and after the exhausting run. Plantar-pressure distribution was assessed at the beginning and end of the exhausting run. MAIN OUTCOME MEASURE(S): We recorded plantar-flexor and dorsiflexor peak torques and calculated the fatigue index. Plantar-pressure measurements were recorded 1 minute after the start of the run and before exhaustion. Plantar variables (ie, mean area, contact time, mean pressure, relative load) were determined for 9 selected regions. RESULTS: Isokinetic peak torques were similar before and after the run in both muscle groups, whereas the fatigue index increased in plantar flexion (28.1%; P = .01) but not in dorsiflexion. For the whole foot, mean pressure decreased from 1 minute to the end (-3.4%; P = .003); however, mean area (9.5%; P = .005) and relative load (7.2%; P = .009) increased under the medial midfoot, and contact time increased under the central forefoot (8.3%; P = .01) and the lesser toes (8.9%; P = .008). CONCLUSIONS: Fatigue resistance in the plantar flexors declined after a high-intensity running bout performed by adolescent male distance runners. This phenomenon was associated with increased loading under the medial arch in the fatigued state but without any excessive pronation.

Second differential of the entropy as a criterion for the stability in low-dimensional climate models

The second differential of the entropy is used for analysing the stability of a thermodynamic climatic model. A delay time for the heat flux is introduced whereby it becomes an independent variable. Two different expressions for the second differential of the entropy are used: one follows classical irreversible thermodynamics theory; the second is related to the introduction of response time and is due to the extended irreversible thermodynamics theory. the second differential of the classical entropy leads to unstable solutions for high values of delay times. the extended expression always implies stable states for an ice-free earth. When the ice-albedo feedback is included, a discontinuous distribution of stable states is found for high response times. Following the thermodynamic analysis of the model, the maximum rates of entropy production at the steady state are obtained. A latitudinally isothermal earth produces the extremum in global entropy production. the material contribution to entropy production (by which we mean the production of entropy by material transport of heat) is a maximum when the latitudinal distribution of temperatures becomes less homogeneous than present values

Comparison of plantar pressure distribution in adolescent runners at low vs. high running velocity

This study aimed to compare foot plantar pressure distribution while jogging and running in highly trained adolescent runners. Eleven participants performed two constant-velocity running trials either at jogging (11.2 ± 0.9 km/h) or running (17.8 ± 1.4 km/h) pace on a treadmill. Contact area (CA in cm(2)), maximum force (F(max) in N), peak pressure (PP in kPa), contact time (CT in ms), and relative load (force time integral in each individual region divided by the force time integral for the total plantar foot surface, in %) were measured in nine regions of the right foot using an in-shoe plantar pressure device. Under the whole foot, CA, F(max) and PP were lower in jogging than in running (-1.2% [p<0.05], -12.3% [p<0.001] and -15.1% [p<0.01] respectively) whereas CT was higher (+20.1%; p<0.001). Interestingly, we found an increase in relative load under the medial and central forefoot regions while jogging (+6.7% and +3.7%, respectively; [p<0.05]), while the relative load under the lesser toes (-8.4%; p<0.05) was reduced. In order to prevent overloading of the metatarsals in adolescent runners, excessive mileage at jogging pace should be avoided.

Adaptive MCMC methods with applications in environmental and geophysical models

This work presents new, efficient Markov chain Monte Carlo (MCMC) simulation methods for statistical analysis in various modelling applications. When using MCMC methods, the model is simulated repeatedly to explore the probability distribution describing the uncertainties in model parameters and predictions. In adaptive MCMC methods based on the Metropolis-Hastings algorithm, the proposal distribution needed by the algorithm learns from the target distribution as the simulation proceeds. Adaptive MCMC methods have been subject of intensive research lately, as they open a way for essentially easier use of the methodology. The lack of user-friendly computer programs has been a main obstacle for wider acceptance of the methods. This work provides two new adaptive MCMC methods: DRAM and AARJ. The DRAM method has been built especially to work in high dimensional and non-linear problems. The AARJ method is an extension to DRAM for model selection problems, where the mathematical formulation of the model is uncertain and we want simultaneously to fit several different models to the same observations. The methods were developed while keeping in mind the needs of modelling applications typical in environmental sciences. The development work has been pursued while working with several application projects. The applications presented in this work are: a winter time oxygen concentration model for Lake Tuusulanjärvi and adaptive control of the aerator; a nutrition model for Lake Pyhäjärvi and lake management planning; validation of the algorithms of the GOMOS ozone remote sensing instrument on board the Envisat satellite of European Space Agency and the study of the effects of aerosol model selection on the GOMOS algorithm.

Assessing the use of very high resolution data to predict species distribution in a mountain environment

Nowadays, Species Distribution Models (SDMs) are a widely used tool. Using different statistical approaches these models reconstruct the realized niche of a species using presence data and a set of variables, often topoclimatic. There utilization range is quite large from understanding single species requirements, to the creation of nature reserve based on species hotspots, or modeling of climate change impact, etc... Most of the time these models are using variables at a resolution of 50km x 50km or 1 km x 1 km. However in some cases these models are used with resolutions below the kilometer scale and thus called high resolution models (100 m x 100 m or 25 m x 25 m). Quite recently a new kind of data has emerged enabling precision up to lm x lm and thus allowing very high resolution modeling. However these new variables are very costly and need an important amount of time to be processed. This is especially the case when these variables are used in complex calculation like models projections over large areas. Moreover the importance of very high resolution data in SDMs has not been assessed yet and is not well understood. Some basic knowledge on what drive species presence-absences is still missing. Indeed, it is not clear whether in mountain areas like the Alps coarse topoclimatic gradients are driving species distributions or if fine scale temperature or topography are more important or if their importance can be neglected when balance to competition or stochasticity. In this thesis I investigated the importance of very high resolution data (2-5m) in species distribution models using either very high resolution topographic, climatic or edaphic variables over a 2000m elevation gradient in the Western Swiss Alps. I also investigated more local responses of these variables for a subset of species living in this area at two precise elvation belts. During this thesis I showed that high resolution data necessitates very good datasets (species and variables for the models) to produce satisfactory results. Indeed, in mountain areas, temperature is the most important factor driving species distribution and needs to be modeled at very fine resolution instead of being interpolated over large surface to produce satisfactory results. Despite the instinctive idea that topographic should be very important at high resolution, results are mitigated. However looking at the importance of variables over a large gradient buffers the importance of the variables. Indeed topographic factors have been shown to be highly important at the subalpine level but their importance decrease at lower elevations. Wether at the mountane level edaphic and land use factors are more important high resolution topographic data is more imporatant at the subalpine level. Finally the biggest improvement in the models happens when edaphic variables are added. Indeed, adding soil variables is of high importance and variables like pH are overpassing the usual topographic variables in SDMs in term of importance in the models. To conclude high resolution is very important in modeling but necessitate very good datasets. Only increasing the resolution of the usual topoclimatic predictors is not sufficient and the use of edaphic predictors has been highlighted as fundamental to produce significantly better models. This is of primary importance, especially if these models are used to reconstruct communities or as basis for biodiversity assessments. -- Ces dernières années, l'utilisation des modèles de distribution d'espèces (SDMs) a continuellement augmenté. Ces modèles utilisent différents outils statistiques afin de reconstruire la niche réalisée d'une espèce à l'aide de variables, notamment climatiques ou topographiques, et de données de présence récoltées sur le terrain. Leur utilisation couvre de nombreux domaines allant de l'étude de l'écologie d'une espèce à la reconstruction de communautés ou à l'impact du réchauffement climatique. La plupart du temps, ces modèles utilisent des occur-rences issues des bases de données mondiales à une résolution plutôt large (1 km ou même 50 km). Certaines bases de données permettent cependant de travailler à haute résolution, par conséquent de descendre en dessous de l'échelle du kilomètre et de travailler avec des résolutions de 100 m x 100 m ou de 25 m x 25 m. Récemment, une nouvelle génération de données à très haute résolution est apparue et permet de travailler à l'échelle du mètre. Les variables qui peuvent être générées sur la base de ces nouvelles données sont cependant très coûteuses et nécessitent un temps conséquent quant à leur traitement. En effet, tout calcul statistique complexe, comme des projections de distribution d'espèces sur de larges surfaces, demande des calculateurs puissants et beaucoup de temps. De plus, les facteurs régissant la distribution des espèces à fine échelle sont encore mal connus et l'importance de variables à haute résolution comme la microtopographie ou la température dans les modèles n'est pas certaine. D'autres facteurs comme la compétition ou la stochasticité naturelle pourraient avoir une influence toute aussi forte. C'est dans ce contexte que se situe mon travail de thèse. J'ai cherché à comprendre l'importance de la haute résolution dans les modèles de distribution d'espèces, que ce soit pour la température, la microtopographie ou les variables édaphiques le long d'un important gradient d'altitude dans les Préalpes vaudoises. J'ai également cherché à comprendre l'impact local de certaines variables potentiellement négligées en raison d'effets confondants le long du gradient altitudinal. Durant cette thèse, j'ai pu monter que les variables à haute résolution, qu'elles soient liées à la température ou à la microtopographie, ne permettent qu'une amélioration substantielle des modèles. Afin de distinguer une amélioration conséquente, il est nécessaire de travailler avec des jeux de données plus importants, tant au niveau des espèces que des variables utilisées. Par exemple, les couches climatiques habituellement interpolées doivent être remplacées par des couches de température modélisées à haute résolution sur la base de données de terrain. Le fait de travailler le long d'un gradient de température de 2000m rend naturellement la température très importante au niveau des modèles. L'importance de la microtopographie est négligeable par rapport à la topographie à une résolution de 25m. Cependant, lorsque l'on regarde à une échelle plus locale, la haute résolution est une variable extrêmement importante dans le milieu subalpin. À l'étage montagnard par contre, les variables liées aux sols et à l'utilisation du sol sont très importantes. Finalement, les modèles de distribution d'espèces ont été particulièrement améliorés par l'addition de variables édaphiques, principalement le pH, dont l'importance supplante ou égale les variables topographique lors de leur ajout aux modèles de distribution d'espèces habituels.

Change points detection in crime-related time series: an on-line fuzzy approach based on a shape space representation

The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.

Stressors and turning points in high school and dropout : a stress process, life course framework

High school dropout is commonly seen as the result of a long-term process of failure and disengagement. As useful as it is, this view has obscured the heterogeneity of pathways leading to dropout. Research suggests, for instance, that some students leave school not as a result of protracted difficulties but in response to situations that emerge late in their schooling careers, such as health problems or severe peer victimization. Conversely, others with a history of early difficulties persevere when their circumstances improve during high school. Thus, an adequate understanding of why and when students drop out requires a consideration of both long-term vulnerabilities and proximal disruptive events and contingencies. The goal of this review is to integrate long-term and immediate determinants of dropout by proposing a stress process, life course model of dropout. This model is also helpful for understanding how the determinants of dropout vary across socioeconomic conditions and geographical and historical contexts.

Bioclimatic envelope model of climate change impacts on blanket peatland distribution in Great Britain

Blanket peatlands are rain-fed mires that cover the landscape almost regardless of topography. The geographical extent of this type of peatland is highly sensitive to climate. We applied a global process-based bioclimatic envelope model, PeatStash, to predict the distribution of British blanket peatlands. The model captures the present areal extent (Kappa = 0.77) and is highly sensitive to both temperature and precipitation changes. When the model is run using the UKCIP02 climate projections for the time periods 2011–2040, 2041–2070 and 2071–2100, the geographical distribution of blanket peatlands gradually retreats towards the north and the west. In the UKCIP02 high emissions scenario for 2071–2100, the blanket peatland bioclimatic space is ~84% smaller than contemporary conditions (1961–1990); only parts of the west of Scotland remain inside this space. Increasing summer temperature is the main driver of the projected changes in areal extent. Simulations using 7 climate model outputs resulted in generally similar patterns of declining aereal extent of the bioclimatic space, although differing in degree. The results presented in this study should be viewed as a first step towards understanding the trends likely to affect the blanket peatland distribution in Great Britain. The eventual fate of existing blanket peatlands left outside their bioclimatic space remains uncertain.