Thermopower of the Correlated Narrow Gap Semiconductor FeSi and Comparison to RuSi

Iron based narrow gap semiconductors such as FeSi, FeSb2, or FeGa3 have received a lot of attention because they exhibit a large thermopower, as well as striking similarities to heavy fermion Kondo insulators. Many proposals have been advanced, however, lacking quantitative methodologies applied to this problem, a consensus remained elusive to date. Here, we employ realistic many-body calculations to elucidate the impact of electronic correlation effects on FeSi. Our methodology accounts for all substantial anomalies observed in FeSi: the metallization, the lack of conservation of spectral weight in optical spectroscopy, and the Curie susceptibility. In particular we find a very good agreement for the anomalous thermoelectric power. Validated by this congruence with experiment, we further discuss a new physical picture of the microscopic nature of the insulator-to-metal crossover. Indeed, we find the suppression of the Seebeck coefficient to be driven by correlation induced incoherence. Finally, we compare FeSi to its iso-structural and iso-electronic homologue RuSi, and predict that partially substituted Fe(1-x)Ru(x)Si will exhibit an increased thermopower at intermediate temperatures.Comment: 14 pages. Proceedings of the Hvar 2011 Workshop on 'New materials for thermoelectric applications: theory and experiment

Academic Performance and Behavioral Patterns

Identifying the factors that influence academic performance is an essential part of educational research. Previous studies have documented the importance of personality traits, class attendance, and social network structure. Because most of these analyses were based on a single behavioral aspect and/or small sample sizes, there is currently no quantification of the interplay of these factors. Here, we study the academic performance among a cohort of 538 undergraduate students forming a single, densely connected social network. Our work is based on data collected using smartphones, which the students used as their primary phones for two years. The availability of multi-channel data from a single population allows us to directly compare the explanatory power of individual and social characteristics. We find that the most informative indicators of performance are based on social ties and that network indicators result in better model performance than individual characteristics (including both personality and class attendance). We confirm earlier findings that class attendance is the most important predictor among individual characteristics. Finally, our results suggest the presence of strong homophily and/or peer effects among university students

OrgConv: detection of gene conversion using consensus sequences and its application in plant mitochondrial and chloroplast homologs

<p>Abstract</p> <p>Background</p> <p>The ancestry of mitochondria and chloroplasts traces back to separate endosymbioses of once free-living bacteria. The highly reduced genomes of these two organelles therefore contain very distant homologs that only recently have been shown to recombine inside the mitochondrial genome. Detection of gene conversion between mitochondrial and chloroplast homologs was previously impossible due to the lack of suitable computer programs. Recently, I developed a novel method and have, for the first time, discovered recurrent gene conversion between chloroplast mitochondrial genes. The method will further our understanding of plant organellar genome evolution and help identify and remove gene regions with incongruent phylogenetic signals for several genes widely used in plant systematics. Here, I implement such a method that is available in a user friendly web interface.</p> <p>Results</p> <p><monospace>OrgConv</monospace> (<b>Org</b>anellar <b>Conv</b>ersion) is a computer package developed for detection of gene conversion between mitochondrial and chloroplast homologous genes. <monospace>OrgConv</monospace> is available in two forms; source code can be installed and run on a Linux platform and a web interface is available on multiple operating systems. The input files of the feature program are two multiple sequence alignments from different organellar compartments in FASTA format. The program compares every examined sequence against the consensus sequence of each sequence alignment rather than exhaustively examining every possible combination. Making use of consensus sequences significantly reduces the number of comparisons and therefore reduces overall computational time, which allows for analysis of very large datasets. Most importantly, with the significantly reduced number of comparisons, the statistical power remains high in the face of correction for multiple tests.</p> <p>Conclusions</p> <p>Both the source code and the web interface of <monospace>OrgConv</monospace> are available for free from the <monospace>OrgConv</monospace> website <url>http://www.indiana.edu/~orgconv</url>. Although <monospace>OrgConv</monospace> has been developed with main focus on detection of gene conversion between mitochondrial and chloroplast genes, it may also be used for detection of gene conversion between any two distinct groups of homologous sequences.</p

Evidence for the h_b(1P) meson in the decay Upsilon(3S) --> pi0 h_b(1P)

Using a sample of 122 million Upsilon(3S) events recorded with the BaBar detector at the PEP-II asymmetric-energy e+e- collider at SLAC, we search for the $h_b(1P)$ spin-singlet partner of the P-wave chi_{bJ}(1P) states in the sequential decay Upsilon(3S) --> pi0 h_b(1P), h_b(1P) --> gamma eta_b(1S). We observe an excess of events above background in the distribution of the recoil mass against the pi0 at mass 9902 +/- 4(stat.) +/- 2(syst.) MeV/c^2. The width of the observed signal is consistent with experimental resolution, and its significance is 3.1sigma, including systematic uncertainties. We obtain the value (4.3 +/- 1.1(stat.) +/- 0.9(syst.)) x 10^{-4} for the product branching fraction BF(Upsilon(3S)-->pi0 h_b) x BF(h_b-->gamma eta_b).Comment: 8 pages, 4 postscript figures, submitted to Phys. Rev. D (Rapid Communications

Whole-Gene Positive Selection, Elevated Synonymous Substitution Rates, Duplication, and Indel Evolution of the Chloroplast clpP1 Gene

Synonymous DNA substitution rates in the plant chloroplast genome are generally relatively slow and lineage dependent. Non-synonymous rates are usually even slower due to purifying selection acting on the genes. Positive selection is expected to speed up non-synonymous substitution rates, whereas synonymous rates are expected to be unaffected. Until recently, positive selection has seldom been observed in chloroplast genes, and large-scale structural rearrangements leading to gene duplications are hitherto supposed to be rare. genes experiencing negative (purifying) selection are characterized by having very conserved lengths, genes under positive selection often have large insertions of more or less repetitive amino acid sequence motifs. gene and surrounding regions, repetitive amino acid sequences, and increase in synonymous substitution rates. The present study sheds light on the controversial issue of whether negative or positive selection is to be expected after gene duplications by providing evidence for the latter alternative. The observed increase in synonymous substitution rates in some of the lineages indicates that the detection of positive selection may be obscured under such circumstances. Future studies are required to explore the functional significance of the large inserted repeated amino acid motifs, as well as the possibility that synonymous substitution rates may be affected by positive selection

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Varying constants, Gravitation and Cosmology

Fundamental constants are a cornerstone of our physical laws. Any constant varying in space and/or time would reflect the existence of an almost massless field that couples to matter. This will induce a violation of the universality of free fall. It is thus of utmost importance for our understanding of gravity and of the domain of validity of general relativity to test for their constancy. We thus detail the relations between the constants, the tests of the local position invariance and of the universality of free fall. We then review the main experimental and observational constraints that have been obtained from atomic clocks, the Oklo phenomenon, Solar system observations, meteorites dating, quasar absorption spectra, stellar physics, pulsar timing, the cosmic microwave background and big bang nucleosynthesis. At each step we describe the basics of each system, its dependence with respect to the constants, the known systematic effects and the most recent constraints that have been obtained. We then describe the main theoretical frameworks in which the low-energy constants may actually be varying and we focus on the unification mechanisms and the relations between the variation of different constants. To finish, we discuss the more speculative possibility of understanding their numerical values and the apparent fine-tuning that they confront us with.Comment: 145 pages, 10 figures, Review for Living Reviews in Relativit

The complete sequence of the Acacia ligulata chloroplast genome reveals a highly divergent clpP1 gene

Legumes are a highly diverse angiosperm family that include many agriculturally important species. To date, 21 complete chloroplast genomes have been sequenced from legume crops confined to the Papilionoideae subfamily. Here we report the first chloroplast genome from the Mimosoideae, Acacia ligulata, and compare it to the previously sequenced legume genomes. The A. ligulata chloroplast genome is 158,724 bp in size, comprising inverted repeats of 25,925 bp and single-copy regions of 88,576 bp and 18,298 bp. Acacia ligulata lacks the inversion present in many of the Papilionoideae, but is not otherwise significantly different in terms of gene and repeat content. The key feature is its highly divergent clpP1 gene, normally considered essential in chloroplast genomes. In A. ligulata, although transcribed and spliced, it probably encodes a catalytically inactive protein. This study provides a significant resource for further genetic research into Acacia and the Mimosoideae. The divergent clpP1 gene suggests that Acacia will provide an interesting source of information on the evolution and functional diversity of the chloroplast Clp protease comple

The Bryopsis hypnoides Plastid Genome: Multimeric Forms and Complete Nucleotide Sequence

BACKGROUND: Bryopsis hypnoides Lamouroux is a siphonous green alga, and its extruded protoplasm can aggregate spontaneously in seawater and develop into mature individuals. The chloroplast of B. hypnoides is the biggest organelle in the cell and shows strong autonomy. To better understand this organelle, we sequenced and analyzed the chloroplast genome of this green alga. PRINCIPAL FINDINGS: A total of 111 functional genes, including 69 potential protein-coding genes, 5 ribosomal RNA genes, and 37 tRNA genes were identified. The genome size (153,429 bp), arrangement, and inverted-repeat (IR)-lacking structure of the B. hypnoides chloroplast DNA (cpDNA) closely resembles that of Chlorella vulgaris. Furthermore, our cytogenomic investigations using pulsed-field gel electrophoresis (PFGE) and southern blotting methods showed that the B. hypnoides cpDNA had multimeric forms, including monomer, dimer, trimer, tetramer, and even higher multimers, which is similar to the higher order organization observed previously for higher plant cpDNA. The relative amounts of the four multimeric cpDNA forms were estimated to be about 1, 1/2, 1/4, and 1/8 based on molecular hybridization analysis. Phylogenetic analyses based on a concatenated alignment of chloroplast protein sequences suggested that B. hypnoides is sister to all Chlorophyceae and this placement received moderate support. CONCLUSION: All of the results suggest that the autonomy of the chloroplasts of B. hypnoides has little to do with the size and gene content of the cpDNA, and the IR-lacking structure of the chloroplasts indirectly demonstrated that the multimeric molecules might result from the random cleavage and fusion of replication intermediates instead of recombinational events

Biclustering via optimal re-ordering of data matrices in systems biology: rigorous methods and comparative studies

<p>Abstract</p> <p>Background</p> <p>The analysis of large-scale data sets via clustering techniques is utilized in a number of applications. Biclustering in particular has emerged as an important problem in the analysis of gene expression data since genes may only jointly respond over a subset of conditions. Biclustering algorithms also have important applications in sample classification where, for instance, tissue samples can be classified as cancerous or normal. Many of the methods for biclustering, and clustering algorithms in general, utilize simplified models or heuristic strategies for identifying the "best" grouping of elements according to some metric and cluster definition and thus result in suboptimal clusters.</p> <p>Results</p> <p>In this article, we present a rigorous approach to biclustering, OREO, which is based on the Optimal RE-Ordering of the rows and columns of a data matrix so as to globally minimize the dissimilarity metric. The physical permutations of the rows and columns of the data matrix can be modeled as either a network flow problem or a traveling salesman problem. Cluster boundaries in one dimension are used to partition and re-order the other dimensions of the corresponding submatrices to generate biclusters. The performance of OREO is tested on (a) metabolite concentration data, (b) an image reconstruction matrix, (c) synthetic data with implanted biclusters, and gene expression data for (d) colon cancer data, (e) breast cancer data, as well as (f) yeast segregant data to validate the ability of the proposed method and compare it to existing biclustering and clustering methods.</p> <p>Conclusion</p> <p>We demonstrate that this rigorous global optimization method for biclustering produces clusters with more insightful groupings of similar entities, such as genes or metabolites sharing common functions, than other clustering and biclustering algorithms and can reconstruct underlying fundamental patterns in the data for several distinct sets of data matrices arising in important biological applications.</p