Classifying seabed sediment type using simulated tidal-induced bed shear stress

An ability to estimate the large-scale spatial variability of seabed sediment type in the absence of extensive observational data is valuable for many applications. In some physical (e.g., morphodynamic) models, knowledge of seabed sediment type is important for inputting spatially-varying bed roughness, and in biological studies, an ability to estimate the distribution of seabed sediment benefits habitat mapping (e.g., scallop dredging). Although shelf sea sediment motion is complex, driven by a combination of tidal currents, waves, and wind-driven currents, in many tidally energetic seas, such as the Irish Sea, long-term seabed sediment transport is dominated by tidal currents. We compare observations of seabed sediment grain size from 242 Irish Sea seabed samples with simulated tidal-induced bed shear stress from a three-dimensional tidal model (ROMS) to quantitatively define the relationship between observed grain size and simulated bed shear stress. With focus on the median grain size of well-sorted seabed sediment samples, we present predictive maps of the distribution of seabed sediment classes in the Irish Sea, ranging from mud to gravel. When compared with the distribution of well-sorted sediment classifications (mud, sand and gravel) from the British Geological Survey digital seabed sediment map of Irish Sea sediments (DigSBS250), this �grain size tidal current proxy� (GSTCP) correctly estimates the observed seabed sediment classification in over 73% of the area

Influence of L-carnitine on litter characteristics from gilts harvested at day 40, 55, and 70 of gestation

Swine research, 2005 is known as Swine day, 2005A total of 59 gilts were used to determine the effects of supplemental L-carnitine on reproductive performance. Experimental treatments were arranged in a 2 × 3 factorial with main effects of L-carnitine (0 or 50 ppm) and day of gestation (40, 55, or 70). All gilts received a constant feed allowance of 3.86 lb/day and a top-dress containing either 0 or 88 mg of L-carnitine, starting on the first day of breeding and continuing until the day of harvest. Total litter size, total litter weight, and crown-to-rump length of fetuses were not different (P>0.10) between treatments at any gestation length. By d 70 of gestation, average fetus weight was heavier (P = 0.06) for fetuses from gilts fed L-carnitine, compared with fetuses from gilts fed the control diet. In addition, at d 70, fetal insulin-like growth factor- II (IGF-II) concentrations were lower (P = 0.09) for fetuses from gilts fed L-carnitine than for fetuses from gilts fed the control diet. Feeding L-carnitine may have decreased fetal IGF-II, therefore increasing cell proliferation and delaying cell differentiation. These results show that providing supplemental Lcarnitine to gestating gilts has beneficial effects on average fetal weight, possibly observed because of its ability to reduce fetal IGF-II concentrations

A parametrization for the growth index of linear matter perturbations

We propose a parametrization for the growth index of the linear matter perturbations, $\gamma(z)=\gamma_0+\frac{z}{1+z}\gamma_1$. The growth factor of the perturbations parameterized as $\Omega_m^{\gamma}$ is analyzed for both the $w$CDM model and the DGP model with our proposed form for $\gamma$. We find that $\gamma_1$ is negative for the $w$CDM model but is positive for the DGP model. Thus it provides another signature to discriminate them. We demonstrate that $\Omega_m^{\gamma}$ with $\gamma$ taking our proposed form approximates the growth factor very well both at low and high redshfits for both kinds of models. In fact, the error is below 0.03% for the $\Lambda$CDM model and 0.18% for the DGP model for all redshifts when $\Omega_{m0}=0.27$. Therefore, our parametrization may be robustly used to constrain the growth index of different models with the observational data which include points for redshifts ranging from 0.15 to 3.8, thus providing discriminative signatures for different models.Comment: 14 pages, 6 figures; Added reference

Convergence in relationships between leaf traits, spectra and age across diverse canopy environments and two contrasting tropical forests

• Leaf age structures the phenology and development of plants, as well as the evolution of leaf traits over life histories. However, a general method for efficiently estimating leaf age across forests and canopy environments is lacking. • Here, we explored the potential for a statistical model, previously developed for Peruvian sunlit leaves, to consistently predict leaf ages from leaf reflectance spectra across two contrasting forests in Peru and Brazil and across diverse canopy environments. • The model performed well for independent Brazilian sunlit and shade canopy leaves (R2 = 0.75–0.78), suggesting that canopy leaves (and their associated spectra) follow constrained developmental trajectories even in contrasting forests. The model did not perform as well for mid-canopy and understory leaves (R2 = 0.27–0.29), because leaves in different environments have distinct traits and trait developmental trajectories. When we accounted for distinct environment–trait linkages – either by explicitly including traits and environments in the model, or, even better, by re-parameterizing the spectra-only model to implicitly capture distinct trait-trajectories in different environments – we achieved a more general model that well-predicted leaf age across forests and environments (R2 = 0.79). • Fundamental rules, linked to leaf environments, constrain the development of leaf traits and allow for general prediction of leaf age from spectra across species, sites and canopy environments

Landscape-scale drivers of glacial ecosystem change in the montane forests of the eastern Andean flank, Ecuador

Understanding the impact of landscape-scale disturbance events during the last glacial period is vital in accu- rately reconstructing the ecosystem dynamics of montane environments. Here, a sedimentary succession from the tropical montane cloud forest of the eastern Andean flank of Ecuador provides evidence of the role of non- climate drivers of vegetation change (volcanic events, fire regime and herbivory) during the late-Pleistocene. Multiproxy analysis (pollen, non-pollen palynomorphs, charcoal, geochemistry and carbon content) of the se- diments, radiocarbon dated to ca. 45–42 ka, provide a snap shot of the depositional environment, vegetation community and non-climate drivers of ecosystem dynamics. The geomorphology of the Vinillos study area, along with the organic‐carbon content, and aquatic remains suggest deposition took place near a valley floor in a swamp or shallow water environment. The pollen assemblage initially composed primarily of herbaceous types (Poaceae-Asteraceae-Solanaceae) is replaced by assemblages characterised by Andean forest taxa, (first Melastomataceae-Weinmannia-Ilex, and later, Alnus-Hedyosmum-Myrica). The pollen assemblages have no modern analogues in the tropical montane cloud forest of Ecuador. High micro-charcoal and rare macro-charcoal abundances co-occur with volcanic tephra deposits suggesting transportation from extra-local regions and that volcanic eruptions were an important source of ignition in the wider glacial landscape. The presence of the coprophilous fungi Sporormiella reveals the occurrence of herbivores in the glacial montane forest landscape. Pollen analysis indicates a stable regional vegetation community, with changes in vegetation population co- varying with large volcanic tephra deposits suggesting that the structure of glacial vegetation at Vinillos was driven by volcanic activity

GONADOTROPHIN RESPONSES TO GnRH PULSES IN HYPOGONADOTROPHIC HYPOGONADISM: LH RESPONSIVENESS IS MAINTAINED IN THE PRESENCE OF LUTEAL PHASE CONCENTRATIONS OF OESTROGEN AND PROGESTERONE

LH pulse secretion changes during the menstrual cycle from a rapid regular pattern in the follicular phase to a slower and irregular pattern in the luteal phase. To determine whether the irregular LH pulse pattern in the luteal phase reflects altered GnRH secretion or altered pituitary responsiveness to GnRH, we gave low dose GnRH pulses (25 ng/kg i.v.) every 2 h or every hour for 10 or 12 d to three women with isolated GnRH deficiency. After 4 d of GnRH alone, oestradiol (E 2 ) was given and after 6 d progesterone (P) was added to mimic the hormonal milieu of the luteal phase. LH and FSH were measured every 4 h throughout and also every 20 min for 6 or 12 h, before and after GnRH alone (day 0 and day 4), after E 2 (day 6), and after E 2 + P (day 10 and day 12). Both GnRH pulse frequencies resulted in a rapid increase in plasma FSH to peaks on day 4 (every 2 h) and day 2 and 3 (every hour). FSH concentrations then declined as plasma E 2 rose to 50–80 pg/ml reflecting the selective inhibitory effect of E 2 on FSH release. Plasma LH was also increased after the hourly GnRH injections and this regimen was associated with a more rapid rise in E 2 reflecting follicular maturation. In contrast to the differences in mean hormone concentrations, administration of GnRH at both frequencies resulted in sustained one-on-one responsiveness of LH that was maintained in the presence of both oestrogen and progesterone at mid-luteal phase concentrations. We conclude that the slow frequency of LH pulses observed during the luteal phase reflects decreased GnRH pulse frequency rather than impaired pituitary responsiveness to GnRH.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74947/1/j.1365-2265.1987.tb00786.x.pd

The growth factor of matter perturbations in an f(R) gravity

The growth of matter perturbations in the $f(R)$ model proposed by Starobinsky is studied in this paper. Three different parametric forms of the growth index are considered respectively and constraints on the model are obtained at both the $1\sigma$ and $2\sigma$ confidence levels, by using the current observational data for the growth factor. It is found, for all the three parametric forms of the growth index examined, that the Starobinsky model is consistent with the observations only at the $2\sigma$ confidence level.Comment: 15 pages, 5 figure

On the origin and evolution of the material in 67P/Churyumov-Gerasimenko

International audiencePrimitive objects like comets hold important information on the material that formed our solar system. Several comets have been visited by spacecraft and many more have been observed through Earth- and space-based telescopes. Still our understanding remains limited. Molecular abundances in comets have been shown to be similar to interstellar ices and thus indicate that common processes and conditions were involved in their formation. The samples returned by the Stardust mission to comet Wild 2 showed that the bulk refractory material was processed by high temperatures in the vicinity of the early sun. The recent Rosetta mission acquired a wealth of new data on the composition of comet 67P/Churyumov-Gerasimenko (hereafter 67P/C-G) and complemented earlier observations of other comets. The isotopic, elemental, and molecular abundances of the volatile, semi-volatile, and refractory phases brought many new insights into the origin and processing of the incorporated material. The emerging picture after Rosetta is that at least part of the volatile material was formed before the solar system and that cometary nuclei agglomerated over a wide range of heliocentric distances, different from where they are found today. Deviations from bulk solar system abundances indicate that the material was not fully homogenized at the location of comet formation, despite the radial mixing implied by the Stardust results. Post-formation evolution of the material might play an important role, which further complicates the picture. This paper discusses these major findings of the Rosetta mission with respect to the origin of the material and puts them in the context of what we know from other comets and solar system objects

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors