Influence of the menstrual cycle on the sweating response measured by direct calorimetry in women exposed to warm environmental conditions.

The whole body sweating response was measured at rest in eight women during the follicular (F) and the luteal (L) phases of the menstrual cycle. Subjects were exposed for 30-min to neutral (N) environmental conditions [ambient temperature (Ta) 28 degrees C] and then for 90-min to warm (W) environmental conditions (Ta, 35 degrees C) in a direct calorimeter. At the end of the N exposure, tympanic temperature (Tty) was 0.18 (SEM 0.06) degrees C higher in the L than in the F phase (P less than 0.05), whereas mean skin temperature (Tsk) was unchanged. During W exposure, the time to the onset of sweating as well as the concomitant increase in body heat content were similar in both phases. At the onset of sweating, the tympanic threshold temperature (Tty,thresh) was higher in the L phase [37.18 (SEM 0.08) degrees C] than in the F phase [36.95 (SEM 0.07) degrees C; P less than 0.01]. The magnitude of the shift in Tty,thresh [0.23 (SEM 0.07) degrees C] was similar to the L-F difference in Tty observed at the end of the N exposure. The mean skin threshold temperature was not statistically different between the two phases. The slope of the relationship between sweating rate and Tty was similar in F and L. It was concluded that the internal set point temperature of resting women exposed to warm environmental conditions shifted to a higher value during the L phase compared to the F phase of the menstrual cycle; and that the magnitude of the shift corresponded to the difference in internal temperature observed in neutral environmental conditions between the two phases.

Social Cognition is not Reducible to Theory of Mind. When Children use Deontic Rules to Predict Others' Behaviors

The objective of this paper is to discuss whether children have a capacity for deonticreasoning that is irreducible to mentalizing. The results of two experiments point tothe existence of such non-mentalistic understanding and prediction of the behaviourof others. In Study 1, young children (3- and 4-year-olds) were told different versionsof classic false-belief tasks, some of which were modified by the introduction of a ruleor a regularity. When the task (a standard change of location task) included a rule, theperformance of 3-year-olds, who fail traditional false-belief tasks, significantly improved.In Study 2, 3-year-olds proved to be able to infer a rule from a social situation and touse it in order to predict the behaviour of a character involved in a modified versionof the false-belief task. These studies suggest that rules play a central role in the socialcognition of young children and that deontic reasoning might not necessarily involvemind reading.

Ontogeny and covariation in the Toarcian genus Osperleioceras (Ammonoidea)

Starting from embryonic (protoconch-ammonitella) and early juvenile shells, which are indistinguishable at the species level, growth curves of Osperleioceras from the Reynesi Subzone (Upper Toarcian) of the Causses Basin (Aveyron, France) show a continuous radiating range of correlated variation in dimensional and ornamental characters, such as involution, whorl compression, rib strength and rib density. This covariation pattern can be observed among single-horizon assemblages, as well as during individual ontogenetic development. The existence of a continuous intergradational series of shells, ranging from stout coarsely ribbed to smooth suboxycone morphologies, rules out functional or ecological selectivity to explain this non-random variability pattern. The complex interdependence of shape and sculpture can be simulated by a model in which sculpture intensity depends on mantle curvature [GUEX, 1999]. The expression of covariation in subadult specimens since the base of Upper Toarcian reveals a rise in variability, concomitant with a size decrease, both contemporaneous with environmental instability. It developed in successive bursts from a fairly long low variability period spanning the whole Middle Toarcian.

Genome-wide transposon insertion scanning of environmental survival functions in the polycyclic aromatic hydrocarbon degrading bacterium Sphingomonas wittichii RW1.

Sphingomonas wittichii RW1 is a dibenzofuran and dibenzodioxin-degrading bacterium with potentially interesting properties for bioaugmentation of contaminated sites. In order to understand the capacity of the microorganism to survive in the environment we used a genome-wide transposon scanning approach. RW1 transposon libraries were generated with around 22 000 independent insertions. Libraries were grown for an average of 50 generations (five successive passages in batch liquid medium) with salicylate as sole carbon and energy source in presence or absence of salt stress at -1.5 MPa. Alternatively, libraries were grown in sand with salicylate, at 50% water holding capacity, for 4 and 10 days (equivalent to 7 generations). Library DNA was recovered from the different growth conditions and scanned by ultrahigh throughput sequencing for the positions and numbers of inserted transposed kanamycin resistance gene. No transposon reads were recovered in 579 genes (10% of all annotated genes in the RW1 genome) in any of the libraries, suggesting those to be essential for survival under the used conditions. Libraries recovered from sand differed strongly from those incubated in liquid batch medium. In particular, important functions for survival of cells in sand at the short term concerned nutrient scavenging, energy metabolism and motility. In contrast to this, fatty acid metabolism and oxidative stress response were essential for longer term survival of cells in sand. Comparison to transcriptome data suggested important functions in sand for flagellar movement, pili synthesis, trehalose and polysaccharide synthesis and putative cell surface antigen proteins. Interestingly, a variety of genes were also identified, interruption of which cause significant increase in fitness during growth on salicylate. One of these was an Lrp family transcription regulator and mutants in this gene covered more than 90% of the total library after 50 generations of growth on salicylate. Our results demonstrate the power of genome-wide transposon scanning approaches for analysis of complex traits.

Plant species richness and environmental heterogeneity in a mountain landscape: effects of variability and spatial configuration

The loss of biodiversity has become a matter of urgent concern and a better understanding of local drivers is crucial for conservation. Although environmental heterogeneity is recognized as an important determinant of biodiversity, this has rarely been tested using field data at management scale. We propose and provide evidence for the simple hypothesis that local species diversity is related to spatial environmental heterogeneity. Species partition the environment into habitats. Biodiversity is therefore expected to be influenced by two aspects of spatial heterogeneity: 1) the variability of environmental conditions, which will affect the number of types of habitat, and 2) the spatial configuration of habitats, which will affect the rates of ecological processes, such as dispersal or competition. Earlier, simulation experiments predicted that both aspects of heterogeneity will influence plant species richness at a particular site. For the first time, these predictions were tested for plant communities using field data, which we collected in a wooded pasture in the Swiss Jura mountains using a four-level hierarchical sampling design. Richness generally increased with increasing environmental variability and "roughness" (i.e. decreasing spatial aggregation). Effects occurred at all scales, but the nature of the effect changed with scale, suggesting a change in the underlying mechanisms, which will need to be taken into account if scaling up to larger landscapes. Although we found significant effects of environmental heterogeneity, other factors such as history could also be important determinants. If a relationship between environmental heterogeneity and species richness can be shown to be general, recently available high-resolution environmental data can be used to complement the assessment of patterns of local richness and improve the prediction of the effects of land use change based on mean site conditions or land use history.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

When information can save lives: the duty to warn relatives about sudden cardiac death and environmental risks.

In certain cases of sudden death, forensic experts may discover during an investigation or autopsy that family members of the deceased are also at risk of harm-from genetic disease, for instance. But do they have a duty to warn them? Looking at similar duties of physicians and researchers to warn third parties of risk suggests they do.

Environmental sex reversal, Trojan sex genes, and sex ratio adjustment: conditions and population consequences.

Abstract The great diversity of sex determination mechanisms in animals and plants ranges from genetic sex determination (GSD, e.g. mammals, birds, and most dioecious plants) to environmental sex determination (ESD, e.g. many reptiles) and includes a mixture of both, for example when an individual's genetically determined sex is environmentally reversed during ontogeny (ESR, environmental sex reversal, e.g. many fish and amphibia). ESD and ESR can lead to widely varying and unstable population sex ratios. Populations exposed to conditions such as endocrine-active substances or temperature shifts may decline over time due to skewed sex ratios, a scenario that may become increasingly relevant with greater anthropogenic interference on watercourses. Continuous exposure of populations to factors causing ESR could lead to the extinction of genetic sex factors and may render a population dependent on the environmental factors that induce the sex change. However, ESR also presents opportunities for population management, especially if the Y or W chromosome is not, or not severely, degenerated. This seems to be the case in many amphibians and fish. Population growth or decline in such species can potentially be controlled through the introduction of so-called Trojan sex genes carriers, individuals that possess sex chromosomes or genes opposite from what their phenotype predicts. Here, we review the conditions for ESR, its prevalence in natural populations, the resulting physiological and reproductive consequences, and how these may become instrumental for population management.

Major environmental change and bonebed genesis prior to the Triassic-Jurassic mass extinction

We present new geochemical and sedimentological data from marginal marine strata of Penarth Bay, south Wales (UK) to elucidate the origin of widespread but enigmatic concentrations of vertebrate hard parts (bonebeds) in marine successions of Rhaetian age (late Triassic). Sedimentological evidence shows that the phosphatic constituents of the bonebeds were subjected to intense phosphatization in shallow current-dominated settings and subsequently reworked and transported basinward by storms. Interbedded organic-rich strata deposited under quiescent and poorly oxygenated conditions record enhanced phosphorus regeneration from sedimentary organic matter into the water column and probably provided the main source of phosphate required for heavy bonebed clast phosphatization. The stratigraphically limited interval showing evidence for oxygen depletion and accelerated P-cycling coincides with a negative 4% organic carbon isotope excursion, which possibly reflects supra-regional changes in carbon cycling and clearly predates the 'initial isotope excursion' characterizing many Triassic-Jurassic boundary strata. our data indicate that Rhaetian bonebeds are the lithological signature of profound, climatically driven changes in carbon cycling and redox conditions and support the idea of a multi-pulsed environmental crisis at the end of the Triassic, possibly linked to successive episodes of igneous activity in the central Atlantic Magmatic Province.

Automatic Mapping and Classification of Spatial Environmental Data

The paper deals with the development and application of the generic methodology for automatic processing (mapping and classification) of environmental data. General Regression Neural Network (GRNN) is considered in detail and is proposed as an efficient tool to solve the problem of spatial data mapping (regression). The Probabilistic Neural Network (PNN) is considered as an automatic tool for spatial classifications. The automatic tuning of isotropic and anisotropic GRNN/PNN models using cross-validation procedure is presented. Results are compared with the k-Nearest-Neighbours (k-NN) interpolation algorithm using independent validation data set. Real case studies are based on decision-oriented mapping and classification of radioactively contaminated territories.

Processes models, environmental analyses, and cognitive architectures: Quo vadis quantum probability theory? (Commentary on Pothos and Busemeyer)

A lot of research in cognition and decision making suffers from a lack of formalism. The quantum probability program could help to improve this situation, but we wonder whether it would provide even more added value if its presumed focus on outcome models were complemented by process models that are, ideally, informed by ecological analyses and integrated into cognitive architectures.

Auditory perceptual decision-making based on semantic categorization of environmental sounds.

Discriminating complex sounds relies on multiple stages of differential brain activity. The specific roles of these stages and their links to perception were the focus of the present study. We presented 250ms duration sounds of living and man-made objects while recording 160-channel electroencephalography (EEG). Subjects categorized each sound as that of a living, man-made or unknown item. We tested whether/when the brain discriminates between sound categories even when not transpiring behaviorally. We applied a single-trial classifier that identified voltage topographies and latencies at which brain responses are most discriminative. For sounds that the subjects could not categorize, we could successfully decode the semantic category based on differences in voltage topographies during the 116-174ms post-stimulus period. Sounds that were correctly categorized as that of a living or man-made item by the same subjects exhibited two periods of differences in voltage topographies at the single-trial level. Subjects exhibited differential activity before the sound ended (starting at 112ms) and on a separate period at ~270ms post-stimulus onset. Because each of these periods could be used to reliably decode semantic categories, we interpreted the first as being related to an implicit tuning for sound representations and the second as being linked to perceptual decision-making processes. Collectively, our results show that the brain discriminates environmental sounds during early stages and independently of behavioral proficiency and that explicit sound categorization requires a subsequent processing stage.