Evidence of a critical time in constrained Kinetic Ising models

We study the relaxational dynamics of the one-spin facilitated Ising model introduced by Fredrickson and Andersen. We show the existence of a critical time which separates an initial regime in which the relaxation is exponentially fast and aging is absent from a regime in which relaxation becomes slow and aging effects are present. The presence of this fast exponential process and its associated critical time is in agreement with some recent experimental results on fragile glasses.

Diffusion Spectrum Imaging after stroke shows structural changes in the contra-lateral motor network correlating with functional recovery

There is growing interest in understanding the role of the non-injured contra-lateral hemisphere in stroke recovery. In the experimental field, histological evidence has been reported that structural changes occur in the contra-lateral connectivity and circuits during stroke recovery. In humans, some recent imaging studies indicated that contra-lateral sub-cortical pathways and functional and structural cortical networks are remodeling, after stroke. Structural changes in the contra-lateral networks, however, have never been correlated to clinical recovery in patients. To determine the importance of the contra-lateral structural changes in post-stroke recovery, we selected a population of patients with motor deficits after stroke affecting the motor cortex and/or sub-cortical motor white matter. We explored i) the presence of Generalized Fractional Anisotropy (GFA) changes indicating structural alterations in the motor network of patientsâeuro? contra-lateral hemisphere as well as their longitudinal evolution ii) the correlation of GFA changes with patientsâeuro? clinical scores, stroke size and demographics data iii) and a predictive model.

Geology of the NW Indian Himalaya

This review paper deals with the geology of the NW Indian Himalaya situated in the states of Jammu and Kashmir, Himachal Pradesh and Garhwal. The models and mechanisms discussed, concerning the tectonic and metamorphic history of the Himalayan range, are based on a new compilation of a geological map and cross sections, as well as on paleomagnetic, stratigraphic, petrologic, structural, metamorphic, thermobarometric and radiometric data. The protolith of the Himalayan range, the North Indian flexural passive margin of the Neo-Tethys ocean, consists of a Lower Proterozoic basement, intruded by 1.8-1.9 Ga bimodal magmatites, overlain by a horizontally stratified sequence of Upper Proterozoic to Paleocene sediments, intruded by 470-500 Ma old Ordovician mainly peraluminous s-type granites, Carboniferous tholeiitic to alkaline basalts and intruded and overlain by Permian tholeiitic continental flood basalts. No elements of the Archaen crystalline basement of the South Indian shield have been identified in the Himalayan range. Deformation of the Himalayan accretionary wedge resulted from the continental collision of India and Asia beginning some 65-55 Ma ago, after the NE-directed underthrusting of the Neo-Tethys oceanic crust below Asia and the formation of the Andean-type 103-50 (-41) Ma old Ladakh batholith to the north of the Indus Suture. Cylindrical in geometry, the Himalayan range consists, from NE to SW, from older to younger tectonic elements, of the following zones: 1) The 25 km wide Ladakh batholith and the Asian mantle wedge form the backstop of the growing Himalayan accretionary wedge. 2) The Indus Suture zone is composed of obducted slices of the oceanic crust, island arcs, like the Dras arc, overlain by Late Cretaceous fore arc basin sediments and the mainly Paleocene to Early Eocene and Miocene epi-sutural intra-continental Indus molasse. 3) The Late Paleocene to Eocene North Himalayan nappe stack, up to 40 km thick prior to erosion, consists of Upper Proterozoic to Paleocene rocks, with the eclogitic and coesite bearing Tso Morari gneiss nappe at its base. It includes a branch of the Central Himalayan detachment, the 22-18 Ma old Zanskar Shear zone that is intruded and dated by the 22 Ma Gumburanjun leucogranite; it reactivates the frontal thrusts of the SW-verging North Himalayan nappes. 4) The late Eocene-Miocene SW-directed High Himalayan or ``Crystalline'' nappe comprises Upper Proterozoic to Mesozoic sediments and Ordovician granites, identical to those of the North Himalayan nappes. The Main Central thrust at its base was created in a zone of Eocene to Early Oligocene anatexis by ductile detachment of the subducted Indian crust, below the pre-existing 25-35 km thick NE-directed Shikar Beh and SW-directed North Himalayan nappe stacks. 5) The late Miocene Lesser Himalayan thrust with the Main Boundary Thrust at its base consists of early Proterozoic to Cambrian rocks intruded by 1.8-1.9 Ga bimodal magmatites. The Subhimalaya is a thrust wedge of Himalayan fore deep basin sediments, composed of the Early Eocene marine Subathu marls and sandstones as well as the up to 8'000 m-thick Miocene to recent Ganga molasse, a coarsening upwards sequence of shales, sandstones and conglomerates. The active frontal thrust is covered by the sediments of the Indus-Ganga plains.

The hourglass and the early conservation models--co-existing patterns of developmental constraints in vertebrates.

Developmental constraints have been postulated to limit the space of feasible phenotypes and thus shape animal evolution. These constraints have been suggested to be the strongest during either early or mid-embryogenesis, which corresponds to the early conservation model or the hourglass model, respectively. Conflicting results have been reported, but in recent studies of animal transcriptomes the hourglass model has been favored. Studies usually report descriptive statistics calculated for all genes over all developmental time points. This introduces dependencies between the sets of compared genes and may lead to biased results. Here we overcome this problem using an alternative modular analysis. We used the Iterative Signature Algorithm to identify distinct modules of genes co-expressed specifically in consecutive stages of zebrafish development. We then performed a detailed comparison of several gene properties between modules, allowing for a less biased and more powerful analysis. Notably, our analysis corroborated the hourglass pattern at the regulatory level, with sequences of regulatory regions being most conserved for genes expressed in mid-development but not at the level of gene sequence, age, or expression, in contrast to some previous studies. The early conservation model was supported with gene duplication and birth that were the most rare for genes expressed in early development. Finally, for all gene properties, we observed the least conservation for genes expressed in late development or adult, consistent with both models. Overall, with the modular approach, we showed that different levels of molecular evolution follow different patterns of developmental constraints. Thus both models are valid, but with respect to different genomic features.

Magnetic resonance imaging of Huntington's disease: preparing for clinical trials.

The known genetic mutation causing Huntington's disease (HD) makes this disease an important model to study links between gene and brain function. An autosomal dominant family history and the availability of a sensitive and specific genetic test allow pre-clinical diagnosis many years before the onset of any typical clinical signs. This review summarizes recent magnetic resonance imaging (MRI)-based findings in HD with a focus on the requirements if imaging is to be used in treatment trials. Despite its monogenetic cause, HD presents with a range of clinical manifestations, not explained by variation in the number of CAG repeats in the affected population. Neuroimaging studies have revealed a complex pattern of structural and functional changes affecting widespread cortical and subcortical regions far beyond the confines of the striatal degeneration that characterizes this disorder. Besides striatal dysfunction, functional imaging studies have reported a variable pattern of increased and decreased activation in cortical regions in both pre-clinical and clinically manifest HD-gene mutation carriers. Beyond regional brain activation changes, evidence from functional and diffusion-weighted MRI further suggests disrupted connectivity between corticocortical and corticostriatal areas. However, substantial inconsistencies with respect to structural and functional changes have been reported in a number of studies. Possible explanations include methodological factors and differences in study samples. There may also be biological explanations but these are poorly characterized and understood at present. Additional insights into this phenotypic variability derived from study of mouse models are presented to explore this phenomenon.

Improving plant functional groups for dynamic models of biodiversity: at the crossroads between functional and community ecology

The pace of on-going climate change calls for reliable plant biodiversity scenarios. Traditional dynamic vegetation models use plant functional types that are summarized to such an extent that they become meaningless for biodiversity scenarios. Hybrid dynamic vegetation models of intermediate complexity (hybrid-DVMs) have recently been developed to address this issue. These models, at the crossroads between phenomenological and process-based models, are able to involve an intermediate number of well-chosen plant functional groups (PFGs). The challenge is to build meaningful PFGs that are representative of plant biodiversity, and consistent with the parameters and processes of hybrid-DVMs. Here, we propose and test a framework based on few selected traits to define a limited number of PFGs, which are both representative of the diversity (functional and taxonomic) of the flora in the Ecrins National Park, and adapted to hybrid-DVMs. This new classification scheme, together with recent advances in vegetation modeling, constitutes a step forward for mechanistic biodiversity modeling.

Detection, analysis and monitoring of slope movements by high-resolution digital elevation models

Summary Detection, analysis and monitoring of slope movements by high-resolution digital elevation modelsSlope movements, such as rockfalls, rockslides, shallow landslides or debris flows, are frequent in many mountainous areas. These natural hazards endanger the inhabitants and infrastructures making it necessary to assess the hazard and risk caused by these phenomena. This PhD thesis explores various approaches using digital elevation models (DEMs) - and particularly high-resolution DEMs created by aerial or terrestrial laser scanning (TLS) - that contribute to the assessment of slope movement hazard at regional and local scales.The regional detection of areas prone to rockfalls and large rockslides uses different morphologic criteria or geometric instability factors derived from DEMs, i.e. the steepness of the slope, the presence of discontinuities, which enable a sliding mechanism, and the denudation potential. The combination of these factors leads to a map of susceptibility to rockfall initiation that is in good agreement with field studies as shown with the example of the Little Mill Campground area (Utah, USA). Another case study in the Illgraben catchment in the Swiss Alps highlighted the link between areas with a high denudation potential and actual rockfall areas.Techniques for a detailed analysis and characterization of slope movements based on high-resolution DEMs have been developed for specific, localized sites, i.e. ancient slide scars, present active instabilities or potential slope instabilities. The analysis of the site's characteristics mainly focuses on rock slopes and includes structural analyses (orientation of discontinuities); estimation of spacing, persistence and roughness of discontinuities; failure mechanisms based on the structural setting; and volume calculations. For the volume estimation a new 3D approach was tested to reconstruct the topography before a landslide or to construct the basal failure surface of an active or potential instability. The rockslides at Åknes, Tafjord and Rundefjellet in western Norway were principally used as study sites to develop and test the different techniques.The monitoring of slope instabilities investigated in this PhD thesis is essentially based on multitemporal (or sequential) high-resolution DEMs, in particular sequential point clouds acquired by TLS. The changes in the topography due to slope movements can be detected and quantified by sequential TLS datasets, notably by shortest distance comparisons revealing the 3D slope movements over the entire region of interest. A detailed analysis of rock slope movements is based on the affine transformation between an initial and a final state of the rock mass and its decomposition into translational and rotational movements. Monitoring using TLS was very successful on the fast-moving Eiger rockslide in the Swiss Alps, but also on the active rockslides of Åknes and Nordnesfjellet (northern Norway). One of the main achievements on the Eiger and Aknes rockslides is to combine the site's morphology and structural setting with the measured slope movements to produce coherent instability models. Both case studies also highlighted a strong control of the structures in the rock mass on the sliding directions. TLS was also used to monitor slope movements in soils, such as landslides in sensitive clays in Québec (Canada), shallow landslides on river banks (Sorge River, Switzerland) and a debris flow channel (Illgraben).The PhD thesis underlines the broad uses of high-resolution DEMs and especially of TLS in the detection, analysis and monitoring of slope movements. Future studies should explore in more depth the different techniques and approaches developed and used in this PhD, improve them and better integrate the findings in current hazard assessment practices and in slope stability models.Résumé Détection, analyse et surveillance de mouvements de versant à l'aide de modèles numériques de terrain de haute résolutionDes mouvements de versant, tels que des chutes de blocs, glissements de terrain ou laves torrentielles, sont fréquents dans des régions montagneuses et mettent en danger les habitants et les infrastructures ce qui rend nécessaire d'évaluer le danger et le risque causé par ces phénomènes naturels. Ce travail de thèse explore diverses approches qui utilisent des modèles numériques de terrain (MNT) et surtout des MNT de haute résolution créés par scanner laser terrestre (SLT) ou aérien - et qui contribuent à l'évaluation du danger de mouvements de versant à l'échelle régionale et locale.La détection régionale de zones propices aux chutes de blocs ou aux éboulements utilise plusieurs critères morphologiques dérivés d'un MNT, tels que la pente, la présence de discontinuités qui permettent un mécanisme de glissement ou le potentiel de dénudation. La combinaison de ces facteurs d'instabilité mène vers une carte de susceptibilité aux chutes de blocs qui est en accord avec des travaux de terrain comme démontré avec l'exemple du Little Mill Campground (Utah, États-Unis). Un autre cas d'étude - l'Illgraben dans les Alpes valaisannes - a mis en évidence le lien entre les zones à fort potentiel de dénudation et les sources effectives de chutes de blocs et d'éboulements.Des techniques pour l'analyse et la caractérisation détaillée de mouvements de versant basées sur des MNT de haute résolution ont été développées pour des sites spécifiques et localisés, comme par exemple des cicatrices d'anciens éboulements et des instabilités actives ou potentielles. Cette analyse se focalise principalement sur des pentes rocheuses et comprend l'analyse structurale (orientation des discontinuités); l'estimation de l'espacement, la persistance et la rugosité des discontinuités; l'établissement des mécanismes de rupture; et le calcul de volumes. Pour cela une nouvelle approche a été testée en rétablissant la topographie antérieure au glissement ou en construisant la surface de rupture d'instabilités actuelles ou potentielles. Les glissements rocheux d'Åknes, Tafjord et Rundefjellet en Norvège ont été surtout utilisés comme cas d'étude pour développer et tester les diverses approches. La surveillance d'instabilités de versant effectuée dans cette thèse de doctorat est essentiellement basée sur des MNT de haute résolution multi-temporels (ou séquentiels), en particulier des nuages de points séquentiels acquis par SLT. Les changements topographiques dus aux mouvements de versant peuvent être détectés et quantifiés sur l'ensemble d'un glissement, notamment par comparaisons des distances les plus courtes entre deux nuages de points. L'analyse détaillée des mouvements est basée sur la transformation affine entre la position initiale et finale d'un bloc et sa décomposition en mouvements translationnels et rotationnels. La surveillance par SLT a démontré son potentiel avec l'effondrement d'un pan de l'Eiger dans les Alpes suisses, mais aussi aux glissements rocheux d'Aknes et Nordnesfjellet en Norvège. Une des principales avancées à l'Eiger et à Aknes est la création de modèles d'instabilité cohérents en combinant la morphologie et l'agencement structural des sites avec les mesures de déplacements. Ces deux cas d'étude ont aussi démontré le fort contrôle des structures existantes dans le massif rocheux sur les directions de glissement. Le SLT a également été utilisé pour surveiller des glissements dans des terrains meubles comme dans les argiles sensibles au Québec (Canada), sur les berges de la rivière Sorge en Suisse et dans le chenal à laves torrentielles de l'Illgraben.Cette thèse de doctorat souligne le vaste champ d'applications des MNT de haute résolution et particulièrement du SLT dans la détection, l'analyse et la surveillance des mouvements de versant. Des études futures devraient explorer plus en profondeur les différentes techniques et approches développées, les améliorer et mieux les intégrer dans des pratiques actuelles d'analyse de danger et surtout dans la modélisation de stabilité des versants.

Advanced geostatistical and machine-learning models for spatial data analysis of radioactively contaminated regions

Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Traditional approaches for mapping the spatial concentration of radionuclides employ various regression-based models, which usually provide a single-value prediction realization accompanied (in some cases) by estimation error. Such approaches do not provide the capability for rigorous uncertainty quantification or probabilistic mapping. Machine learning is a recent and fast-developing approach based on learning patterns and information from data. Artificial neural networks for prediction mapping have been especially powerful in combination with spatial statistics. A data-driven approach provides the opportunity to integrate additional relevant information about spatial phenomena into a prediction model for more accurate spatial estimates and associated uncertainty. Machine-learning algorithms can also be used for a wider spectrum of problems than before: classification, probability density estimation, and so forth. Stochastic simulations are used to model spatial variability and uncertainty. Unlike regression models, they provide multiple realizations of a particular spatial pattern that allow uncertainty and risk quantification. This paper reviews the most recent methods of spatial data analysis, prediction, and risk mapping, based on machine learning and stochastic simulations in comparison with more traditional regression models. The radioactive fallout from the Chernobyl Nuclear Power Plant accident is used to illustrate the application of the models for prediction and classification problems. This fallout is a unique case study that provides the challenging task of analyzing huge amounts of data ('hard' direct measurements, as well as supplementary information and expert estimates) and solving particular decision-oriented problems.

Case studies and mathematical models of ecological speciation. 1. Cichlids in a crater lake.

A recent study of a pair of sympatric species of cichlids in Lake Apoyo in Nicaragua is viewed as providing probably one of the most convincing examples of sympatric speciation to date. Here, we describe and study a stochastic, individual-based, explicit genetic model tailored for this cichlid system. Our results show that relatively rapid (<20,000 generations) colonization of a new ecological niche and (sympatric or parapatric) speciation via local adaptation and divergence in habitat and mating preferences are theoretically plausible if: (i) the number of loci underlying the traits controlling local adaptation, and habitat and mating preferences is small; (ii) the strength of selection for local adaptation is intermediate; (iii) the carrying capacity of the population is intermediate; and (iv) the effects of the loci influencing nonrandom mating are strong. We discuss patterns and timescales of ecological speciation identified by our model, and we highlight important parameters and features that need to be studied empirically to provide information that can be used to improve the biological realism and power of mathematical models of ecological speciation.

Chemical sensing in Drosophila.

Chemical sensing begins when peripheral receptor proteins recognise specific environmental stimuli and translate them into spatial and temporal patterns of sensory neuron activity. The chemosensory system of the fruit fly, Drosophila melanogaster, has become a dominant model to understand this process, through its accessibility to a powerful combination of molecular, genetic and electrophysiological analysis. Recent results have revealed many surprises in the biology of peripheral chemosensation in Drosophila, including novel structural and signalling properties of the insect odorant receptors (ORs), combinatorial mechanisms of chemical recognition by the gustatory receptors (GRs), and the implication of Transient Receptor Potential (TRP) ion channels as a novel class of chemosensory receptors.

Very high-resolution environmental predictors in species distribution models: moving beyond topography?

Recent advances in remote sensing technologies have facilitated the generation of very high resolution (VHR) environmental data. Exploratory studies suggested that, if used in species distribution models (SDMs), these data should enable modelling species' micro-habitats and allow improving predictions for fine-scale biodiversity management. In the present study, we tested the influence, in SDMs, of predictors derived from a VHR digital elevation model (DEM) by comparing the predictive power of models for 239 plant species and their assemblages fitted at six different resolutions in the Swiss Alps. We also tested whether changes of the model quality for a species is related to its functional and ecological characteristics. Refining the resolution only contributed to slight improvement of the models for more than half of the examined species, with the best results obtained at 5 m, but no significant improvement was observed, on average, across all species. Contrary to our expectations, we could not consistently correlate the changes in model performance with species characteristics such as vegetation height. Temperature, the most important variable in the SDMs across the different resolutions, did not contribute any substantial improvement. Our results suggest that improving resolution of topographic data only is not sufficient to improve SDM predictions - and therefore local management - compared to previously used resolutions (here 25 and 100 m). More effort should be dedicated now to conduct finer-scale in-situ environmental measurements (e.g. for temperature, moisture, snow) to obtain improved environmental measurements for fine-scale species mapping and management.

Effects of Heat Straightening Structural Steel, MLR-91-3, 1992

Heat straightening of steel beams on bridges struck by over height trucks has become common practice in recent years in Iowa. A study of the effects of this heat straightening on the steel beams thus straightened is needed. Appropriate samples for mechanical and metallurgical tests were cut from the same rolled beam from the end which was heated and the end which was not heated and the test results were compared. The test results showed beyond doubt that the steel was being heated beyond the permitted temperature and that the impact properties are being drastically reduced by the current method of heat straightening.

Dynamic models of viral replication and latency.

PURPOSE OF REVIEW: HIV targets primary CD4(+) T cells. The virus depends on the physiological state of its target cells for efficient replication, and, in turn, viral infection perturbs the cellular state significantly. Identifying the virus-host interactions that drive these dynamic changes is important for a better understanding of viral pathogenesis and persistence. The present review focuses on experimental and computational approaches to study the dynamics of viral replication and latency. RECENT FINDINGS: It was recently shown that only a fraction of the inducible latently infected reservoirs are successfully induced upon stimulation in ex-vivo models while additional rounds of stimulation make allowance for reactivation of more latently infected cells. This highlights the potential role of treatment duration and timing as important factors for successful reactivation of latently infected cells. The dynamics of HIV productive infection and latency have been investigated using transcriptome and proteome data. The cellular activation state has shown to be a major determinant of viral reactivation success. Mathematical models of latency have been used to explore the dynamics of the latent viral reservoir decay. SUMMARY: Timing is an important component of biological interactions. Temporal analyses covering aspects of viral life cycle are essential for gathering a comprehensive picture of HIV interaction with the host cell and untangling the complexity of latency. Understanding the dynamic changes tipping the balance between success and failure of HIV particle production might be key to eradicate the viral reservoir.

Structural investigations into the interaction of hemoglobin and part structures with bacterial endotoxins.

An understanding of details of the interaction mechanisms of bacterial endotoxins (lipopolysaccharide, LPS) with the oxygen transport protein hemoglobin is still lacking, despite its high biological relevance. Here, a biophysical investigation into the endotoxin:hemoglobin interaction is presented which comprises the use of various rough mutant LPS as well as free lipid A; in addition to the complete hemoglobin molecule from fetal sheep extract, also the partial structure alpha-chain and the heme-free sample are studied. The investigations comprise the determination of the gel-to-liquid crystalline phase behaviour of the acyl chains of LPS, the ultrastructure (type of aggregate structure and morphology) of the endotoxins, and the incorporation of the hemoglobins into artificial immune cell membranes and into LPS. Our data suggest a model for the interaction between Hb and LPS in which hemoglobins do not react strongly with the hydrophilic or with the hydrophobic moiety of LPS, but with the complete endotoxin aggregate. Hb is able to incorporate into LPS with the longitudinal direction parallel to the lipid A double-layer. Although this does not lead to a strong disturbance of the LPS acyl chain packing, the change of the curvature leads to a slightly conical molecular shape with a change of the three-dimensional arrangement from unilamellar into cubic LPS aggregates. Our previous results show that cubic LPS structures exhibit strong endotoxic activity. The property of Hb on the physical state of LPS described here may explain the observation of an increase in LPS-mediating endotoxicity due to the action of Hb.

Inferring recent migration rates from individual genotypes.

We present a novel and straightforward method for estimating recent migration rates between discrete populations using multilocus genotype data. The approach builds upon a two-step sampling design, where individual genotypes are sampled before and after dispersal. We develop a model that estimates all pairwise backwards migration rates (m(ij), the probability that an individual sampled in population i is a migrant from population j) between a set of populations. The method is validated with simulated data and compared with the methods of BayesAss and Structure. First, we use data for an island model and then we consider more realistic data simulations for a metapopulation of the greater white-toothed shrew (Crocidura russula). We show that the precision and bias of estimates primarily depend upon the proportion of individuals sampled in each population. Weak sampling designs may particularly affect the quality of the coverage provided by 95% highest posterior density intervals. We further show that it is relatively insensitive to the number of loci sampled and the overall strength of genetic structure. The method can easily be extended and makes fewer assumptions about the underlying demographic and genetic processes than currently available methods. It allows backwards migration rates to be estimated across a wide range of realistic conditions.