Study of orientation effect on nanoscale polarization in BaTiO3 thin films using piezoresponse force microscopy

We have investigated the effect of texture on in-plane (IPP) and out- of plane (OPP) polarizations of pulsed-laser-deposited BaTiO3 thin films grown on Pt and La0.5Sr0.5CoO3 (LSCO) buffered Pt electrodes. The OPP and IPP polarizations were observed by piezoresponse force microscopy (PFM) for three-dimensional polarization analyses in conjunction with conventional diffraction methods using x-ray diffraction and reflection high energy electron diffraction measurements. BaTiO3 films grown on Pt electrodes exhibited highly (101) preferred orientation with higher IPP component whereas BaTiO3 film grown on LSCO/Pt electrodes showed (001) and (101) orientations with higher OPP component. Measured effective d(33) values of BaTiO3 films deposited on Pt and LSCO/ Pt electrodes were 14.3 and 54.0 pm/ V, respectively. Local piezoelectric strain loops obtained by OPP and IPP-PFM showed that piezoelectric properties were strongly related to film orientation

Prediction of biopore- and matrix-dominated flow from X-ray CT-derived macropore network characteristics

Peer reviewedPublisher PD

Efficient algorithms for reconstructing gene content by co-evolution

<p>Abstract</p> <p>Background</p> <p>In a previous study we demonstrated that co-evolutionary information can be utilized for improving the accuracy of ancestral gene content reconstruction. To this end, we defined a new computational problem, the Ancestral Co-Evolutionary (ACE) problem, and developed algorithms for solving it.</p> <p>Results</p> <p>In the current paper we generalize our previous study in various ways. First, we describe new efficient computational approaches for solving the ACE problem. The new approaches are based on reductions to classical methods such as linear programming relaxation, quadratic programming, and min-cut. Second, we report new computational hardness results related to the ACE, including practical cases where it can be solved in polynomial time.</p> <p>Third, we generalize the ACE problem and demonstrate how our approach can be used for inferring parts of the genomes of <it>non-ancestral</it> organisms. To this end, we describe a heuristic for finding the portion of the genome ('dominant set’) that can be used to reconstruct the rest of the genome with the lowest error rate. This heuristic utilizes both evolutionary information and co-evolutionary information.</p> <p>We implemented these algorithms on a large input of the ACE problem (95 unicellular organisms, 4,873 protein families, and 10, 576 of co-evolutionary relations), demonstrating that some of these algorithms can outperform the algorithm used in our previous study. In addition, we show that based on our approach a ’dominant set’ cab be used reconstruct a major fraction of a genome (up to 79%) with relatively low error-rate (<it>e.g.</it> 0.11). We find that the ’dominant set’ tends to include metabolic and regulatory genes, with high evolutionary rate, and low protein abundance and number of protein-protein interactions.</p> <p>Conclusions</p> <p>The <it>ACE</it> problem can be efficiently extended for inferring the genomes of organisms that exist today. In addition, it may be solved in polynomial time in many practical cases. Metabolic and regulatory genes were found to be the most important groups of genes necessary for reconstructing gene content of an organism based on other related genomes.</p

Pedagogical Aspects of Applied Software Packages and Computer Technologies Use in Student's Education

Special software development is necessary for successful realization of teachers and students activity. There are two directions of such software development: first is for training process organization and second is for software use in education. General ASP purpose are universal software products intended for user functional tasks operation and it is also widely used in educational process

Macropore flow at the field scale: predictive performance of empirical models and X-ray CT analyzed macropore characteristics

Predictions of macropore flow is important for maintaining both soil and water quality as it governs key related soil processes e.g. soil erosion and subsurface transport of pollutants. However, macropore flow currently cannot be reliably predicted at the field scale because of inherently large spatial variability. The aim of this study was to perform field scale characterization of macropore flow and investigate the predictive performance of (1) current empirical models for both water and air flow, and (2) X-ray CT derived macropore network characteristics. For this purpose, 65 cylindrical soil columns (6 cm diameter and 3.5 cm height) were extracted from the topsoil (5 to 8.5 cm depth) in a 15 m × 15 m grid from an agricultural loamy field located in Silstrup, Denmark. All soil columns were scanned with an industrial CT scanner (129 μm resolution) and later used for measurements of saturated water permeability, air permeability and gas diffusivity at -30 and -100 cm matric potentials. Distribution maps for both water and air permeabilities and gas diffusivity reflected no spatial correlation irrespective of the soil texture and organic matter maps. Empirical predictive models for both water and air permeabilities showed poor performance as they were not able to realistically capture macropore flow because of poor correlations with soil texture and bulk density. The tested empirical model predicted well gas diffusivity at -100 cm matric potential, but relatively failed at -30 cm matric potential particularly for samples with biopore flow. Image segmentation output of the four employed methods was nearly the same, and matched well with measured air-filled porosity at -30 cm matric potential. Many of the CT derived macropore network characteristics were strongly interrelated. Most of the macropore network characteristics were also strongly correlated with saturated water permeability, air permeability, and gas diffusivity. The correlations between macropore network characteristics and macropore flow parameters were further improved on dividing soil samples into samples with biopore and matrix flow. Observed strong correlations between macropore network characteristics and macropore flow highlighted the need of further research on numerical simulations of macropore flow based on X-ray CT images. This could pave the way for the digital soil physics laboratory in the future

The Gathering Storm: Infectious Diseases and Human Rights in Burma

Documents how decades of repressive rule, civil war, and poor governance in Burma have contributed to the spread of HIV/AIDS, tuberculosis, malaria, and other infectious diseases

Discovering local patterns of co - evolution: computational aspects and biological examples

<p>Abstract</p> <p>Background</p> <p>Co-evolution is the process in which two (or more) sets of orthologs exhibit a similar or correlative pattern of evolution. Co-evolution is a powerful way to learn about the functional interdependencies between sets of genes and cellular functions and to predict physical interactions. More generally, it can be used for answering fundamental questions about the evolution of biological systems.</p> <p>Orthologs that exhibit a strong signal of co-evolution in a certain part of the evolutionary tree may show a mild signal of co-evolution in other branches of the tree. The major reasons for this phenomenon are noise in the biological input, genes that gain or lose functions, and the fact that some measures of co-evolution relate to rare events such as positive selection. Previous publications in the field dealt with the problem of finding sets of genes that co-evolved along an entire underlying phylogenetic tree, without considering the fact that often co-evolution is local.</p> <p>Results</p> <p>In this work, we describe a new set of biological problems that are related to finding patterns of <it>local </it>co-evolution. We discuss their computational complexity and design algorithms for solving them. These algorithms outperform other bi-clustering methods as they are designed specifically for solving the set of problems mentioned above.</p> <p>We use our approach to trace the co-evolution of fungal, eukaryotic, and mammalian genes at high resolution across the different parts of the corresponding phylogenetic trees. Specifically, we discover regions in the fungi tree that are enriched with positive evolution. We show that metabolic genes exhibit a remarkable level of co-evolution and different patterns of co-evolution in various biological datasets.</p> <p>In addition, we find that protein complexes that are related to gene expression exhibit non-homogenous levels of co-evolution across different parts of the <it>fungi </it>evolutionary line. In the case of mammalian evolution, signaling pathways that are related to <it>neurotransmission </it>exhibit a relatively higher level of co-evolution along the <it>primate </it>subtree.</p> <p>Conclusions</p> <p>We show that finding local patterns of co-evolution is a computationally challenging task and we offer novel algorithms that allow us to solve this problem, thus opening a new approach for analyzing the evolution of biological systems.</p

Chemomechanics of ionically conductive ceramics for electrical energy conversion and storage

Functional materials for energy conversion and storage exhibit strong coupling between electrochemistry and mechanics. For example, ceramics developed as electrodes for both solid oxide fuel cells and batteries exhibit cyclic volumetric expansion upon reversible ion transport. Such chemomechanical coupling is typically far from thermodynamic equilibrium, and thus is challenging to quantify experimentally and computationally. In situ measurements and atomistic simulations are under rapid development to explore how this coupling can be used to potentially improve both device performance and durability. Here, we review the commonalities of coupling between electrochemical and mechanical states in fuel cell and battery materials, illustrating with specific cases the progress in materials processing, in situ characterization, and computational modeling and simulation. We also highlight outstanding questions and opportunities in these applications – both to better understand the limiting mechanisms within the materials and to significantly advance the durability and predictability of device performance required for renewable energy conversion and storage.United States. Dept. of Energy (Basic Energy Sciences Division of Materials Sciences and Engineering, grant DE-SC0002633)United States. Dept. of Energy (Office of Science, Graduate Fellowship Program (DOE SCGF))United States. American Recovery and Reinvestment Act of 2009 (ORISE-ORAU, contract no. DE-AC05-06OR23100))United States. Dept. of Energy. Division of Materials Sciences and Engineering (MIT/DMSE Salapatas Fellowship)United States. Air Force Office of Scientific Research (Presidential Early Career Award in Science and Engineering (PECASE)

Quantitative principles of cis-translational control by general mRNA sequence features in eukaryotes.

BackgroundGeneral translational cis-elements are present in the mRNAs of all genes and affect the recruitment, assembly, and progress of preinitiation complexes and the ribosome under many physiological states. These elements include mRNA folding, upstream open reading frames, specific nucleotides flanking the initiating AUG codon, protein coding sequence length, and codon usage. The quantitative contributions of these sequence features and how and why they coordinate to control translation rates are not well understood.ResultsHere, we show that these sequence features specify 42-81% of the variance in translation rates in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, Mus musculus, and Homo sapiens. We establish that control by RNA secondary structure is chiefly mediated by highly folded 25-60 nucleotide segments within mRNA 5' regions, that changes in tri-nucleotide frequencies between highly and poorly translated 5' regions are correlated between all species, and that control by distinct biochemical processes is extensively correlated as is regulation by a single process acting in different parts of the same mRNA.ConclusionsOur work shows that general features control a much larger fraction of the variance in translation rates than previously realized. We provide a more detailed and accurate understanding of the aspects of RNA structure that directs translation in diverse eukaryotes. In addition, we note that the strongly correlated regulation between and within cis-control features will cause more even densities of translational complexes along each mRNA and therefore more efficient use of the translation machinery by the cell