Origin, evolution and dynamic context of a Neoglacial lateral-frontal moraine at Austre Lovénbreen, Svalbard

Moraines marking the Neoglacial limits in Svalbard are commonly ice cored. Investigating the nature of this relict ice is important because it can aid our understanding of former glacier dynamics. This paper examines the composition of the lateral–frontal moraine associated with the Neoglacial limit at Austre Lovénbreen and assesses the likely geomorphological evolution. The moraine was investigated using ground-penetrating radar (GPR), with context being provided by structural mapping of the glacier based on an oblique aerial image from 1936 and vertical aerial imagery from 2003. Multiple up-glacier dipping reflectors and syncline structures are found in the GPR surveys. The reflectors are most clearly defined in lateral positions, where the moraine is substantially composed of ice. The frontal area of the moraine is dominantly composed of debris. The core of the lateral part of the moraine is likely to consist of stacked sequences of basal ice that have been deformed by strong longitudinal compression. The long term preservation potential of the ice-dominated lateral moraine is negligible, whereas the preservation of the debris-dominated frontal moraine is high. A glacier surface bulge, identified on the 1936 aerial imagery, provides evidence that Austre Lovénbreen has previously displayed surge activity, although it is highly unlikely to do so in the near future in its current state. This research shows the value of relict buried ice that is preserved in landforms to aiding our understanding of former glacier characteristics

Evolution of high-Arctic glacial landforms during deglaciation

Glacial landsystems in the high-Arctic have been reported to undergo geomorphological transformation during deglaciation. This research evaluates moraine evolution over a decadal timescale at Midtre Lovénbreen, Svalbard. This work is of interest because glacial landforms developed in Svalbard have been used as an analogue for landforms developed during Pleistocene mid-latitude glaciation. Ground penetrating radar was used to investigate the subsurface characteristics of moraines. To determine surface change, a LiDAR topographic data set (obtained 2003) and a UAV-derived (obtained 2014) digital surface model processed using structure-from-motion (SfM) are also compared. Evaluation of these data sets together enables subsurface character and landform response to climatic amelioration to be linked. Ground penetrating radar evidence shows that the moraine substrate at Midtre Lovénbreen includes ice-rich (radar velocities of 0.17 m ns−1) and debris-rich (radar velocities of 0.1–0.13 m ns−1) zones. The ice-rich zones are demonstrated to exhibit relatively high rates of surface change (mean thresholded rate of −4.39 m over the 11-year observation period). However, the debris-rich zones show a relatively low rate of surface change (mean thresholded rate of −0.98 m over the 11-year observation period), and the morphology of the debris-rich landforms appear stable over the observation period. A complex response of proglacial landforms to climatic warming is shown to occur within and between glacier forelands as indicated by spatially variable surface lowering rates. Landform response is controlled by the ice-debris balance of the moraine substrate, along with the topographic context (such as the influence of meltwater). Site-specific characteristics such as surface debris thickness and glaciofluvial drainage are, therefore, argued to be a highly important control on surface evolution in ice-cored terrain, resulting in a diverse response of high-Arctic glacial landsystems to climatic amelioration. These results highlight that care is needed when assessing the long-term preservation potential of contemporary landforms at high-Arctic glaciers. A better understanding of ice-cored terrain facilitates the development of appropriate age and climatic interpretations that can be obtained from palaeo ice-marginal landsystems

Multiple scattering in random mechanical systems and diffusion approximation

This paper is concerned with stochastic processes that model multiple (or iterated) scattering in classical mechanical systems of billiard type, defined below. From a given (deterministic) system of billiard type, a random process with transition probabilities operator P is introduced by assuming that some of the dynamical variables are random with prescribed probability distributions. Of particular interest are systems with weak scattering, which are associated to parametric families of operators P_h, depending on a geometric or mechanical parameter h, that approaches the identity as h goes to 0. It is shown that (P_h -I)/h converges for small h to a second order elliptic differential operator L on compactly supported functions and that the Markov chain process associated to P_h converges to a diffusion with infinitesimal generator L. Both P_h and L are selfadjoint (densely) defined on the space L2(H,{\eta}) of square-integrable functions over the (lower) half-space H in R^m, where {\eta} is a stationary measure. This measure's density is either (post-collision) Maxwell-Boltzmann distribution or Knudsen cosine law, and the random processes with infinitesimal generator L respectively correspond to what we call MB diffusion and (generalized) Legendre diffusion. Concrete examples of simple mechanical systems are given and illustrated by numerically simulating the random processes.Comment: 34 pages, 13 figure

Self-organization of (001) cubic crystal surfaces

Self-organization on crystal surface is studied as a two dimensional spinodal decomposition in presence of a surface stress. The elastic Green function is calculated for a $(001)$ cubic crystal surface taking into account the crystal anisotropy. Numerical calculations show that the phase separation is driven by the interplay between domain boundary energy and long range elastic interactions. At late stage of the phase separation process, a steady state appears with different nanometric patterns according to the surface coverage and the crystal elastic constants

Population-based studies of myocardial hypertrophy: high resolution cardiovascular magnetic resonance atlases improve statistical power

BACKGROUND: Cardiac phenotypes, such as left ventricular (LV) mass, demonstrate high heritability although most genes associated with these complex traits remain unidentified. Genome-wide association studies (GWAS) have relied on conventional 2D cardiovascular magnetic resonance (CMR) as the gold-standard for phenotyping. However this technique is insensitive to the regional variations in wall thickness which are often associated with left ventricular hypertrophy and require large cohorts to reach significance. Here we test whether automated cardiac phenotyping using high spatial resolution CMR atlases can achieve improved precision for mapping wall thickness in healthy populations and whether smaller sample sizes are required compared to conventional methods. METHODS: LV short-axis cine images were acquired in 138 healthy volunteers using standard 2D imaging and 3D high spatial resolution CMR. A multi-atlas technique was used to segment and co-register each image. The agreement between methods for end-diastolic volume and mass was made using Bland-Altman analysis in 20 subjects. The 3D and 2D segmentations of the LV were compared to manual labeling by the proportion of concordant voxels (Dice coefficient) and the distances separating corresponding points. Parametric and nonparametric data were analysed with paired t-tests and Wilcoxon signed-rank test respectively. Voxelwise power calculations used the interstudy variances of wall thickness. RESULTS: The 3D volumetric measurements showed no bias compared to 2D imaging. The segmented 3D images were more accurate than 2D images for defining the epicardium (Dice: 0.95 vs 0.93, P < 0.001; mean error 1.3 mm vs 2.2 mm, P < 0.001) and endocardium (Dice 0.95 vs 0.93, P < 0.001; mean error 1.1 mm vs 2.0 mm, P < 0.001). The 3D technique resulted in significant differences in wall thickness assessment at the base, septum and apex of the LV compared to 2D (P < 0.001). Fewer subjects were required for 3D imaging to detect a 1 mm difference in wall thickness (72 vs 56, P < 0.001). CONCLUSIONS: High spatial resolution CMR with automated phenotyping provides greater power for mapping wall thickness than conventional 2D imaging and enables a reduction in the sample size required for studies of environmental and genetic determinants of LV wall thickness

Processing Bi-Pb-Sr-Ca-Cu-O superconductors from amorphous state

The bismuth based high T sub c superconductors can be processed via an amorphous Bi-Pb-Sr-Ca-Cu oxide. The amorphous oxides were prepared by melting the constituent powders in an alumina crucible at 1200 C in air followed by pouring the liquid onto an aluminum plate, and rapidly pressing with a second plate. In the amorphous state, no crystalline phase was identified in the powder x ray diffraction pattern of the quenched materials. After heat treatment at high temperature the amorphous materials crystallized into a glass ceramic containing a large fraction of the Bi2Sr2Ca2Cu3O(x) phase T sub c = 110 K. The processing method, crystallization, and results of dc electrical resistivity and ac magnetic susceptibility measurements are discussed

Phase Transformations in the High-Tc Superconducting Compounds, Ba_2RCu_3O_(7–δ) (R = Nd, Sm, Gd, Y, Ho, and Er)

The phase transformation between the orthorhombic and tetragonal structures of six high-Tc superconductors, Ba2RCu3O7−δ, where R = Nd, Sm, Gd, Y, Ho, and Er, and δ = 0 to 1, has been investigated using techniques of x-ray diffraction, differential thermal analysis/thermogravimetric analysis (DTA/TGA) and electron diffraction. The transformation from the oxygen-rich orthorhombic phase to the oxygen-deficient tetragonal phase involves two orthorhombic phases. A superlattice cell caused by oxygen ordering, with a′ = 2a, was observed for materials with smaller ionic radius (Y, Ho, and Er). For the larger lanthanide samples (Nd, Sm, and Gd), the a′ = 2a type superlattice cell was not observed. The structural phase transition temperatures, oxygen stoichiometry and characteristics of the Tc plateaus appear to correlate with the ionic radius, which varies based on the number of f electrons. Lanthanide elements with a smaller ionic radius stabilize the orthorhombic phase to higher temperatures and lower oxygen content. Also, the superconducting temperature is less sensitive to the oxygen content for materials with smaller ionic radius. The trend of dependence of the phase transformation temperature on ionic radius across the lanthanide series can be explained using a quasi-chemical approximation (QCA) whereby the strain effect plays an important role on the order-disorder transition due to the effect of oxygen content on the CuO chain sites

Preconditioning of mesenchymal stromal cells with low-intensity ultrasound: influence on chondrogenesis and directed SOX9 signaling pathways

Background: Continuous low-intensity ultrasound (cLIUS) facilitates the chondrogenic differentiation of human mesenchymal stromal cells (MSCs) in the absence of exogenously added transforming growth factor-beta (TGFβ) by upregulating the expression of transcription factor SOX9, a master regulator of chondrogenesis. The present study evaluated the molecular events associated with the signaling pathways impacting SOX9 gene and protein expression under cLIUS. Methods: Human bone marrow-derived MSCs were exposed to cLIUS stimulation at 14 kPa (5 MHz, 2.5 Vpp) for 5 min. The gene and protein expression of SOX9 was evaluated. The specificity of SOX9 upregulation under cLIUS was determined by treating the MSCs with small molecule inhibitors of select signaling molecules, followed by cLIUS treatment. Signaling events regulating SOX9 expression under cLIUS were analyzed by gene expression, immunofluorescence staining, and western blotting. Results: cLIUS upregulated the gene expression of SOX9 and enhanced the nuclear localization of SOX9 protein when compared to non-cLIUS-stimulated control. cLIUS was noted to enhance the phosphorylation of the signaling molecule ERK1/2. Inhibition of MEK/ERK1/2 by PD98059 resulted in the effective abrogation of cLIUS-induced SOX9 expression, indicating that cLIUS-induced SOX9 upregulation was dependent on the phosphorylation of ERK1/2. Inhibition of integrin and TRPV4, the upstream cell-surface effectors of ERK1/2, did not inhibit the phosphorylation of ERK1/2 and therefore did not abrogate cLIUS-induced SOX9 expression, thereby suggesting the involvement of other mechanoreceptors. Consequently, the effect of cLIUS on the actin cytoskeleton, a mechanosensitive receptor regulating SOX9, was evaluated. Diffused and disrupted actin fibers observed in MSCs under cLIUS closely resembled actin disruption by treatment with cytoskeletal drug Y27632, which is known to increase the gene expression of SOX9. The upregulation of SOX9 under cLIUS was, therefore, related to cLIUS-induced actin reorganization. SOX9 upregulation induced by actin reorganization was also found to be dependent on the phosphorylation of ERK1/2. Conclusions: Collectively, preconditioning of MSCs by cLIUS resulted in the nuclear localization of SOX9, phosphorylation of ERK1/2 and disruption of actin filaments, and the expression of SOX9 was dependent on the phosphorylation of ERK1/2 under cLIUS

kLog: A Language for Logical and Relational Learning with Kernels

We introduce kLog, a novel approach to statistical relational learning. Unlike standard approaches, kLog does not represent a probability distribution directly. It is rather a language to perform kernel-based learning on expressive logical and relational representations. kLog allows users to specify learning problems declaratively. It builds on simple but powerful concepts: learning from interpretations, entity/relationship data modeling, logic programming, and deductive databases. Access by the kernel to the rich representation is mediated by a technique we call graphicalization: the relational representation is first transformed into a graph --- in particular, a grounded entity/relationship diagram. Subsequently, a choice of graph kernel defines the feature space. kLog supports mixed numerical and symbolic data, as well as background knowledge in the form of Prolog or Datalog programs as in inductive logic programming systems. The kLog framework can be applied to tackle the same range of tasks that has made statistical relational learning so popular, including classification, regression, multitask learning, and collective classification. We also report about empirical comparisons, showing that kLog can be either more accurate, or much faster at the same level of accuracy, than Tilde and Alchemy. kLog is GPLv3 licensed and is available at http://klog.dinfo.unifi.it along with tutorials