471 research outputs found
Topographic and electronic contrast of the graphene moir\'e on Ir(111) probed by scanning tunneling microscopy and non-contact atomic force microscopy
Epitaxial graphene grown on transition metal surfaces typically exhibits a
moir\'e pattern due to the lattice mismatch between graphene and the underlying
metal surface. We use both scanning tunneling microscopy (STM) and atomic force
microscopy (AFM) experiments to probe the electronic and topographic contrast
of the graphene moir\'e on the Ir(111) surface. While STM topography is
influenced by the local density of states close to the Fermi energy and the
local tunneling barrier height, AFM is capable of yielding the 'true' surface
topography once the background force arising from the van der Waals (vdW)
interaction between the tip and the substrate is taken into account. We observe
a moir\'e corrugation of 3510 pm, where the graphene-Ir(111) distance is
the smallest in the areas where the graphene honeycomb is atop the underlying
iridium atoms and larger on the fcc or hcp threefold hollow sites.Comment: revised versio
Differential Expression Of Gap Junction mRNAs And Proteins In The Developing Murine Kidney And In Experimentally Induced Nephric Mesenchymes
The expression of three gap junction (GJ) proteins, alpha-1 (Cx43), beta-1 (Cx32), and beta-2 (Cx26), and their transcripts were examined during the ontogeny of the mouse and rat kidney. These proteins were expressed in two non-overlapping patterns. The alpha-1 GJ protein was first observed in mesenchymal cells in the 12-day mouse kidney. By day 14 and thereafter, the ai protein was detected in the transient S-shaped bodies, but not in the podocytes of the maturing glomeruli. After birth the antigen was retained in a small subset of secretory tubules.The beta-1 and beta-2 GJ proteins were similar in their developmental patterns. They were first detected in a small subset of secretory tubules in the subcortical zone of day 17 embryos. These tubules were identified by immunohistochemical markers to be proximal. At birth, practically all proximal tubules expressed the two antigens.This analysis of GJ proteins was consistent with the results of S1 nuclease protection assays showing that, while the alpha-1 mRNA appeared early during kidney development and declined around birth, the two beta mRNAs appeared later and became intensified during the last days of intrauterine development.In experimentally induced metanephric mesenchymes, a transient expression of the alpha-1 GJ protein was seen during the segregation of the tubular anlagen. beta-1 and beta-2 GJ proteins were not detected in such induced mesenchymes cultivated up to 7 days.These observations provide evidence for the cell-specific utilization of different GJ genes during different stages of kidney organogenesis. The alpha-1 gene is activated during the early segregation of the secretory tubule and might contribute to its compartmentalization, while the beta-1 and beta-2 gene products are not detected until advanced stages of development. The latter gene products might be correlated with the physiological activity of the proximal tubules in vivo, as they are not expressed in experimentally induced tubules detectable with markers for proximal tubules
Constraints on the three-fluid model of curvaton decay
A three fluid system describing the decay of the curvaton is studied by
numerical and analytical means. We place constraints on the allowed interaction
strengths between the fluids and initial curvaton density by requiring that the
curvaton decays before nucleosynthesis while nucleosynthesis, radiation-matter
equality and decoupling occur at correct temperatures. We find that with a
continuous, time-independent interaction, a small initial curvaton density is
naturally preferred along with a low reheating temperature. Allowing for a
time-dependent interaction, this constraint can be relaxed. In both cases, a
purely adiabatic final state can be generated, but not without fine-tuning.
Unlike in the two fluid system, the time-dependent interactions are found to
have a small effect on the curvature perturbation itself due to the different
nature of the system. The presence of non-gaussianity in the model is
discussed.Comment: 9 pages, 10 figure
PyCOOL - a Cosmological Object-Oriented Lattice code written in Python
There are a number of different phenomena in the early universe that have to
be studied numerically with lattice simulations. This paper presents a graphics
processing unit (GPU) accelerated Python program called PyCOOL that solves the
evolution of scalar fields in a lattice with very precise symplectic
integrators. The program has been written with the intention to hit a sweet
spot of speed, accuracy and user friendliness. This has been achieved by using
the Python language with the PyCUDA interface to make a program that is easy to
adapt to different scalar field models. In this paper we derive the symplectic
dynamics that govern the evolution of the system and then present the
implementation of the program in Python and PyCUDA. The functionality of the
program is tested in a chaotic inflation preheating model, a single field
oscillon case and in a supersymmetric curvaton model which leads to Q-ball
production. We have also compared the performance of a consumer graphics card
to a professional Tesla compute card in these simulations. We find that the
program is not only accurate but also very fast. To further increase the
usefulness of the program we have equipped it with numerous post-processing
functions that provide useful information about the cosmological model. These
include various spectra and statistics of the fields. The program can be
additionally used to calculate the generated curvature perturbation. The
program is publicly available under GNU General Public License at
https://github.com/jtksai/PyCOOL . Some additional information can be found
from http://www.physics.utu.fi/tiedostot/theory/particlecosmology/pycool/ .Comment: 23 pages, 12 figures; some typos correcte
Long-term prognosis of haemangioblastoma of the CNS: Impact of von Hippel-Lindau disease
Peer reviewe
Sensitivity of barley varieties to weather in Finland
Global climate change is predicted to shift seasonal temperature and precipitation patterns. An increasing frequency of extreme weather events such as heat waves and prolonged droughts is predicted, but there are high levels of uncertainty about the nature of local changes. Crop adaptation will be important in reducing potential damage to agriculture. Crop diversity may enhance resilience to climate variability and changes that are difficult to predict. Therefore, there has to be sufficient diversity within the set of available cultivars in response to weather parameters critical for yield formation. To determine the scale of such âweather response diversityâ within barley (Hordeum vulgare L.), an important crop in northern conditions, the yield responses of a wide range of modern and historical varieties were analysed according to a well-defined set of critical agro-meteorological variables. The Finnish long-term dataset of MTT Official Variety Trials was used together with historical weather records of the Finnish Meteorological Institute. The foci of the analysis were firstly to describe the general response of barley to different weather conditions and secondly to reveal the diversity among varieties in the sensitivity to each weather variable. It was established that barley yields were frequently reduced by drought or excessive rain early in the season, by high temperatures at around heading, and by accelerated temperature sum accumulation rates during periods 2 weeks before heading and between heading and yellow ripeness. Low temperatures early in the season increased yields, but frost during the first 4 weeks after sowing had no effect. After canopy establishment, higher precipitation on average resulted in higher yields. In a cultivar-specific analysis, it was found that there were differences in responses to all but three of the studied climatic variables: waterlogging and drought early in the season and temperature sum accumulation rate before heading. The results suggest that low temperatures early in the season, delayed sowing, rain 3â7 weeks after sowing, a temperature change 3â4 weeks after sowing, a high temperature sum accumulation rate from heading to yellow ripeness and high temperatures (â©Ÿ25°C) at around heading could mostly be addressed by exploiting the traits found in the range of varieties included in the present study. However, new technology and novel genetic material are needed to enable crops to withstand periods of excessive rain or drought early in the season and to enhance performance under increased temperature sum accumulation rates prior to heading
Comprehensive feature selection for classifying the treatment outcome of high-intensity ultrasound therapy in uterine fibroids
The study aim was to utilise multiple feature selection methods in order to select the most important parameters from clinical patient data for high-intensity focused ultrasound (HIFU) treatment outcome classification in uterine fibroids. The study was retrospective using patient data from 66 HIFU treatments with 89 uterine fibroids. A total of 39 features were extracted from the patient data and 14 different filter-based feature selection methods were used to select the most informative features. The selected features were then used in a support vector classification (SVC) model to evaluate the performance of these parameters in predicting HIFU therapy outcome. The therapy outcome was defined as non-perfused volume (NPV) ratio in three classes: 80%. The ten most highly ranked features in order were: fibroid diameter, subcutaneous fat thickness, fibroid volume, fibroid distance, Funaki type I, fundus location, gravidity, Funaki type III, submucosal fibroid type and urinary symptoms. The maximum F1-micro classification score was 0.63 using the top ten features from Mutual Information Maximisation (MIM) and Joint Mutual Information (JMI) feature selection methods. Classification performance of HIFU therapy outcome prediction in uterine fibroids is highly dependent on the chosen feature set which should be determined prior using different classifiers
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