952 resultados para Individual atomic scale


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Zooplankton samples were taken in five depth strata using a Multinet type Midi, with 50 µm nets. The samples were taken during the second leg only, three times at station 1, two times at station 2 and once at station 3. Zooplankton were identified to species / genus and life-stage, and at least 300 individuals were counted per sample. 10 individuals of each stage / species were measured and the numbers of eggs counted.

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Gas hydrate samples from various locations in the Gulf of Mexico (GOM) differ considerably in their microstructure. Distinct microstructure characteristics coincide with discrete crystallographic structures, gas compositions and calculated thermodynamic stabilities. The crystallographic structures were established by X-ray diffraction, using both conventional X-ray sources and high-energy synchrotron radiation. The microstructures were examined by cryo-stage Field-Emission Scanning Electron Microscopy (FE-SEM). Good sample preservation was warranted by the low ice fractions shown from quantitative phase analyses. Gas hydrate structure II samples from the Green Canyon in the northern GOM had methane concentrations of 70-80% and up to 30% of C2-C5 of measured hydrocarbons. Hydrocarbons in the crystallographic structure I hydrate from the Chapopote asphalt volcano in the southern GOM was comprised of more than 98% methane. Fairly different microstructures were identified for those different hydrates: Pores measuring 200-400 nm in diameter were present in structure I gas hydrate samples; no such pores but dense crystal surfaces instead were discovered in structure II gas hydrate. The stability of the hydrate samples is discussed regarding gas composition, crystallographic structure and microstructure. Electron microscopic observations showed evidence of gas hydrate and liquid oil co-occurrence on a micrometer scale. That demonstrates that oil has direct contact to gas hydrates when it diffuses through a hydrate matrix.

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1. The spatial distribution of individual plants within a population and the population’s genetic structure are determined by several factors, like dispersal, reproduction mode or biotic interactions. The role of interspecific interactions in shaping the spatial genetic structure of plant populations remains largely unknown. 2. Species with a common evolutionary history are known to interact more closely with each other than unrelated species due to the greater number of traits they share. We hypothesize that plant interactions may shape the fine genetic structure of closely related congeners. 3. We used spatial statistics (georeferenced design) and molecular techniques (ISSR markers) to understand how two closely related congeners, Thymus vulgaris (widespread species) and T. loscosii (narrow endemic) interact at the local scale. Specific cover, number of individuals of both study species and several community attributes were measured in a 10 × 10 m plot. 4. Both species showed similar levels of genetic variation, but differed in their spatial genetic structure. Thymus vulgaris showed spatial aggregation but no spatial genetic structure, while T. loscosii showed spatial genetic structure (positive genetic autocorrelation) at short distances. The spatial pattern of T. vulgaris’ cover showed significant dissociation with that of T. loscosii. The same was true between the spatial patterns of the cover of T. vulgaris and the abundance of T. loscosii and between the abundance of each species. Most importantly, we found a correlation between the genetic structure of T. loscosii and the abundance of T. vulgaris: T. loscosii plants were genetically more similar when they were surrounded by a similar number of T. vulgaris plants. 5. Synthesis. Our results reveal spatially complex genetic structures of both congeners at small spatial scales. The negative association among the spatial patterns of the two species and the genetic structure found for T. loscosii in relation to the abundance of T. vulgaris indicate that competition between the two species may account for the presence of adapted ecotypes of T. loscosii to the abundance of a competing congeneric species. This suggests that the presence and abundance of close congeners can influence the genetic spatial structure of plant species at fine scales.

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We investigated how richness and composition of vascular plant species in the understory of a mixed hardwood forest stand varied with respect to the abundance and composition of the overstory. The stand is in central Spain and represents the southernmost range of distribution of several tree and herbaceous species in Europe. Understory species were identified in 46 quadrats (0.25 m2) where variables litter depth and light availability were measured. In addition, we estimated tree density, basal area, and percent basal area by tree species within 6-m-radius areas around each plot. Species richness and composition were studied using path analysis and scale-dependent geostatistical methods, respectively. We found that the relative abundance of certain trees species in the overstory was more important than total overstory abundance in explaining understory species richness. Richness decreased as soil litter depth increased, and soil litter increased as the relative proportion of Fagus sylvatica in the overstory increased, which accounted for a negative, indirect effect of Fagus sylvatica on richness. Regarding understory species composition, we found that some species distributed preferentially below certain tree species. For example, Melica uniflora was most frequent below Fagus sylvatica and Quercus petraea while the increasing proportion of Q. pyrenaica in the overstory favored the presence of Cruciata glabra, Arenaria montana, Prunus avium, Conopodium bourgaei, Holcus mollis, Stellaria media and Galium aparine in the understory. Overall, these results emphasize the importance of individual tree species in controlling the assemblage and richness of understory species in mixed stands. We conclude that soil litter accumulation is one way through which overstory composition shapes the understory community.

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We investigated the atomic surface properties of differently prepared silicon and germanium (100) surfaces during metal-organic vapour phase epitaxy/chemical vapour deposition (MOVPE/MOCVD), in particular the impact of the MOVPE ambient, and applied reflectance anisotropy/difference spectroscopy (RAS/RDS) in our MOVPE reactor to in-situ watch and control the preparation on the atomic length scale for subsequent III-V-nucleation. The technological interest in the predominant opto-electronic properties of III-V-compounds drives the research for their heteroepitaxial integration on more abundant and cheaper standard substrates such as Si(100) or Ge(100). In these cases, a general task must be accomplished successfully, i.e. the growth of polar materials on non-polar substrates and, beyond that, very specific variations such as the individual interface formation and the atomic step structure, have to be controlled. Above all, the method of choice to grow industrial relevant high-performance device structures is MOVPE, not normally compatible with surface and interface sensitive characterization tools, which are commonly based on ultrahigh vacuum (UHV) ambients. A dedicated sample transfer system from MOVPE environment to UHV enabled us to benchmark the optical in-situ spectra with results from various surfaces science instruments without considering disruptive contaminants. X-ray photoelectron spectroscopy (XPS) provided direct observation of different terminations such as arsenic and phosphorous and verified oxide removal under various specific process parameters. Absorption lines in Fourier-transform infrared (FTIR) spectra were used to identify specific stretch modes of coupled hydrides and the polarization dependence of the anti-symmetric stretch modes distinguished different dimer orientations. Scanning tunnelling microscopy (STM) studied the atomic arrangement of dimers and steps and tip-induced H-desorption proved the saturation of dangling bonds after preparati- n. In-situ RAS was employed to display details transiently such as the presence of H on the surface at lower temperatures (T <; 800°C) and the absence of Si-H bonds at elevated annealing temperature and also surface terminations. Ge buffer growth by the use of GeH4 enables the preparation of smooth surfaces and leads to a more pronounced amplitude of the features in the spectra which indicates improvements of the surface quality.

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Canonical test cases for sloshing wave impact problems are pre-sented and discussed. In these cases the experimental setup has been simpli?ed seeking the highest feasible repeatability; a rectangular tank subjected to harmonic roll motion has been the tested con?guration. Both lateral and roof impacts have been studied, since both cases are relevant in sloshing assessment and show speci?c dynamics. An analysis of the impact pressure of the ?rst four impact events is provided in all cases. It has been found that not in all cases a Gaussian ?tting of each individual peak is feasible. The tests have been conducted with both water and oil in order to obtain high and moderate Reynolds number data; the latter may be useful as simpler test cases to assess the capabilities of CFD codes in simulating sloshing impacts. The re-peatability of impact pressure values increases dramatically when using oil. In addition, a study of the two-dimensionality of the problem using a tank con?guration that can be adjusted to 4 di?erent thicknesses has been carried out. Though the kinemat-ics of the free surface does not change signi cantly in some of the cases, the impact pressure values of the ?rst impact events changes substantially from the small to the large aspect ratios thus meaning that attention has to be paid to this issue when reference data is used for validation of 2D and 3D CFD codes.

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Inter-individual differences in cognitive performance are based on an efficient use of task-related brain resources. However, little is known yet on how these differences might be reflected on resting-state brain networks. Here we used Magnetoencephalography resting-state recordings to assess the relationship between a behavioral measurement of verbal working memory and functional connectivity as measured through Mutual Information. We studied theta (4?8 Hz), low alpha (8?10 Hz), high alpha (10?13 Hz), low beta (13?18 Hz) and high beta (18?30 Hz) frequency bands. A higher verbal working memory capacity was associated with a lower mutual information in the low alpha band, prominently among right-anterior and left-lateral sensors. The results suggest that an efficient brain organization in the domain of verbal working memory might be related to a lower resting-state functional connectivity across large-scale brain networks possibly involving right prefrontal and left perisylvian areas.

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Spatial variability of Vertisol properties is relevant for identifying those zones with physical degradation. In this sense, one has to face the problem of identifying the origin and distribution of spatial variability patterns. The objectives of the present work were (i) to quantify the spatial structure of different physical properties collected from a Vertisol, (ii) to search for potential correlations between different spatial patterns and (iii) to identify relevant components through multivariate spatial analysis. The study was conducted on a Vertisol (Typic Hapludert) dedicated to sugarcane (Saccharum officinarum L.) production during the last sixty years. We used six soil properties collected from a squared grid (225 points) (penetrometer resistance (PR), total porosity, fragmentation dimension (Df), vertical electrical conductivity (ECv), horizontal electrical conductivity (ECh) and soil water content (WC)). All the original data sets were z-transformed before geostatistical analysis. Three different types of semivariogram models were necessary for fitting individual experimental semivariograms. This suggests the different natures of spatial variability patterns. Soil water content rendered the largest nugget effect (C0 = 0.933) while soil total porosity showed the largest range of spatial correlation (A = 43.92 m). The bivariate geostatistical analysis also rendered significant cross-semivariance between different paired soil properties. However, four different semivariogram models were required in that case. This indicates an underlying co-regionalization between different soil properties, which is of interest for delineating management zones within sugarcane fields. Cross-semivariograms showed larger correlation ranges than individual, univariate, semivariograms (A ≥ 29 m). All the findings were supported by multivariate spatial analysis, which showed the influence of soil tillage operations, harvesting machinery and irrigation water distribution on the status of the investigated area.

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This paper describes the main goals and outcomes of the EU-funded Framework 7 project entitled Semantic Evaluation at Large Scale (SEALS). The growth and success of the Semantic Web is built upon a wide range of Semantic technologies from ontology engineering tools through to semantic web service discovery and semantic search. The evaluation of such technologies ? and, indeed, assessments of their mutual compatibility ? is critical for their sustained improvement and adoption. The SEALS project is creating an open and sustainable platform on which all aspects of an evaluation can be hosted and executed and has been designed to accommodate most technology types. It is envisaged that the platform will become the de facto repository of test datasets and will allow anyone to organise, execute and store the results of technology evaluations free of charge and without corporate bias. The demonstration will show how individual tools can be prepared for evaluation, uploaded to the platform, evaluated according to some criteria and the subsequent results viewed. In addition, the demonstration will show the flexibility and power of the SEALS Platform for evaluation organisers by highlighting some of the key technologies used.

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A new method to study large scale neural networks is presented in this paper. The basis is the use of Feynman- like diagrams. These diagrams allow the analysis of collective and cooperative phenomena with a similar methodology to the employed in the Many Body Problem. The proposed method is applied to a very simple structure composed by an string of neurons with interaction among them. It is shown that a new behavior appears at the end of the row. This behavior is different to the initial dynamics of a single cell. When a feedback is present, as in the case of the hippocampus, this situation becomes more complex with a whole set of new frequencies, different from the proper frequencies of the individual neurons. Application to an optical neural network is reported.

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Background Gray scale images make the bulk of data in bio-medical image analysis, and hence, the main focus of many image processing tasks lies in the processing of these monochrome images. With ever improving acquisition devices, spatial and temporal image resolution increases, and data sets become very large. Various image processing frameworks exists that make the development of new algorithms easy by using high level programming languages or visual programming. These frameworks are also accessable to researchers that have no background or little in software development because they take care of otherwise complex tasks. Specifically, the management of working memory is taken care of automatically, usually at the price of requiring more it. As a result, processing large data sets with these tools becomes increasingly difficult on work station class computers. One alternative to using these high level processing tools is the development of new algorithms in a languages like C++, that gives the developer full control over how memory is handled, but the resulting workflow for the prototyping of new algorithms is rather time intensive, and also not appropriate for a researcher with little or no knowledge in software development. Another alternative is in using command line tools that run image processing tasks, use the hard disk to store intermediate results, and provide automation by using shell scripts. Although not as convenient as, e.g. visual programming, this approach is still accessable to researchers without a background in computer science. However, only few tools exist that provide this kind of processing interface, they are usually quite task specific, and don’t provide an clear approach when one wants to shape a new command line tool from a prototype shell script. Results The proposed framework, MIA, provides a combination of command line tools, plug-ins, and libraries that make it possible to run image processing tasks interactively in a command shell and to prototype by using the according shell scripting language. Since the hard disk becomes the temporal storage memory management is usually a non-issue in the prototyping phase. By using string-based descriptions for filters, optimizers, and the likes, the transition from shell scripts to full fledged programs implemented in C++ is also made easy. In addition, its design based on atomic plug-ins and single tasks command line tools makes it easy to extend MIA, usually without the requirement to touch or recompile existing code. Conclusion In this article, we describe the general design of MIA, a general purpouse framework for gray scale image processing. We demonstrated the applicability of the software with example applications from three different research scenarios, namely motion compensation in myocardial perfusion imaging, the processing of high resolution image data that arises in virtual anthropology, and retrospective analysis of treatment outcome in orthognathic surgery. With MIA prototyping algorithms by using shell scripts that combine small, single-task command line tools is a viable alternative to the use of high level languages, an approach that is especially useful when large data sets need to be processed.

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This is the final report on reproducibility@xsede, a one-day workshop held in conjunction with XSEDE14, the annual conference of the Extreme Science and Engineering Discovery Environment (XSEDE). The workshop's discussion-oriented agenda focused on reproducibility in large-scale computational research. Two important themes capture the spirit of the workshop submissions and discussions: (1) organizational stakeholders, especially supercomputer centers, are in a unique position to promote, enable, and support reproducible research; and (2) individual researchers should conduct each experiment as though someone will replicate that experiment. Participants documented numerous issues, questions, technologies, practices, and potentially promising initiatives emerging from the discussion, but also highlighted four areas of particular interest to XSEDE: (1) documentation and training that promotes reproducible research; (2) system-level tools that provide build- and run-time information at the level of the individual job; (3) the need to model best practices in research collaborations involving XSEDE staff; and (4) continued work on gateways and related technologies. In addition, an intriguing question emerged from the day's interactions: would there be value in establishing an annual award for excellence in reproducible research? Overview

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A modification of the Paul–Straubel trap previously described by us may profitably be operated in a Paul–Straubel–Kingdon (PSK) mode during the initial loading of an individual ion into the trap. Thereby the coating of the trap ring electrode by the atomic beam directed upon it in earlier experiments is eliminated, as is the ionization of an already trapped ion. Coating created serious problems as it spot-wise changed the work function of the ring electrode, which caused large, uncontrolled dc fields in the trap center that prevented zero-point confinement. Operating the Paul–Straubel trap with a small negative bias on the ring electrode wire is all that is required to realize the PSK mode. In this mode the tiny ring trap in the center of the long, straight wire section is surrounded by a second trapping well shaped like a long, thin-walled cylindrical shell and extending to the end-caps. There, ions may be conveniently created in this well without danger of coating the ring with barium. In addition, the long second well is useful as a multi-ion reservoir.

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We have combined high-resolution atomic force microscopy (AFM) imaging and force spectroscopy to gain insight into the interaction forces between the individual protomers of the hexagonally packed intermediate (HPI) layer of Deinococcus radiodurans. After imaging the HPI layer, the AFM stylus was attached to individual protomers by enforced stylus-sample contact to allow force spectroscopy experiments. Imaging of the HPI layer after recording force-extension curves allowed adhesion forces to be correlated with structural alterations. By using this approach, individual protomers of the HPI layer were found to be removed at pulling forces of ≈300 pN. Furthermore, it was possible to sequentially unzip entire bacterial pores formed by six HPI protomers. The combination of high-resolution AFM imaging of individual proteins with the determination of their intramolecular forces is a method of studying the mechanical stability of supramolecular structures at the level of single molecules.

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The function of many of the uncharacterized open reading frames discovered by genomic sequencing can be determined at the level of expressed gene products, the proteome. However, identifying the cognate gene from minute amounts of protein has been one of the major problems in molecular biology. Using yeast as an example, we demonstrate here that mass spectrometric protein identification is a general solution to this problem given a completely sequenced genome. As a first screen, our strategy uses automated laser desorption ionization mass spectrometry of the peptide mixtures produced by in-gel tryptic digestion of a protein. Up to 90% of proteins are identified by searching sequence data bases by lists of peptide masses obtained with high accuracy. The remaining proteins are identified by partially sequencing several peptides of the unseparated mixture by nanoelectrospray tandem mass spectrometry followed by data base searching with multiple peptide sequence tags. In blind trials, the method led to unambiguous identification in all cases. In the largest individual protein identification project to date, a total of 150 gel spots—many of them at subpicomole amounts—were successfully analyzed, greatly enlarging a yeast two-dimensional gel data base. More than 32 proteins were novel and matched to previously uncharacterized open reading frames in the yeast genome. This study establishes that mass spectrometry provides the required throughput, the certainty of identification, and the general applicability to serve as the method of choice to connect genome and proteome.