Recent Breakthroughs on Angle-of-Arrival Estimation for Millimeter-Wave High-Speed Railway Communication

© 2019 IEEE. With significantly improved efficiency, largescale hybrid antenna arrays with tens to hundreds of antennas have great potential to support millimeter-wave (mmWave) communication for high-speed railway (HSR) applications. The significant beamforming gains rely on fast and accurate estimation of the angle-of-arrival (AoA), but this can be impeded by the high train speed, the cost/energy oriented design of arrays, and the severe attenuation of mmWave signals. This article reviews these challenges, and discusses the limitations of existing AoA estimation techniques under hybrid antenna array settings. The article further reveals a few recent theoretical breakthroughs that can potentially enable fast and reliable estimation, even based on severely attenuated signals. Under a speed setting of 500 km/h, a performance study is carried out to confirm the significant improvements of estimation accuracy and subsequent beamforming gains as the results of the breakthroughs

Distribution and significance of interstitial fibrosis and stroma-infiltrating B cells in tongue squamous cell carcinoma

published_or_final_versio

Angle-Resolved Photoemission Spectroscopy of Tetragonal CuO: Evidence for Intralayer Coupling Between Cupratelike Sublattices

We investigate by angle-resolved photoemission the electronic structure of in situ grown tetragonal CuO, a synthetic quasi-two-dimensional edge-sharing cuprate. We show that, in spite of the very different nature of the copper oxide layers, with twice as many Cu in the CuO layers of tetragonal CuO as compared to the CuO2 layers of the high-T-c cuprates, the low-energy electronic excitations are surprisingly similar, with a Zhang-Rice singlet dispersing on weakly coupled cupratelike sublattices. This system should thus be considered as a member of the high-T-c cuprate family, with, however, interesting differences due to the intralayer coupling between the cupratelike sublattices.open1199sciescopu

Molecular evolution of psbA gene in ferns: unraveling selective pressure and co-evolutionary

Background: The photosynthetic oxygen-evolving photo system II (PS II) produces almost the entire oxygen in the atmosphere. This unique biochemical system comprises a functional core complex that is encoded by psbA and other genes. Unraveling the evolutionary dynamics of this gene is of particular interest owing to its direct role in oxygen production. psbA underwent gene duplication in leptosporangiates, in which both copies have been preserved since. Because gene duplication is often followed by the non-fictionalization of one of the copies and its subsequent erosion, preservation of both psbA copies pinpoint functional or regulatory specialization events. The aim of this study was to investigate the molecular evolution of psbA among fern lineages. Results: We sequenced psbA, which encodes D1 protein in the core complex of PSII, in 20 species representing 8 orders of extant ferns; then we searched for selection and convolution signatures in psbA across the 11 fern orders. Collectively, our results indicate that: (1) selective constraints among D1 protein relaxed after the duplication in 4 leptosporangiate orders; (2) a handful positively selected codons were detected within species of single copy psbA, but none in duplicated ones; (3) a few sites among D1 protein were involved in co-evolution process which may intimate significant functional/structural communications between them. Conclusions: The strong competition between ferns and angiosperms for light may have been the main cause for a continuous fixation of adaptive amino acid changes in psbA, in particular after its duplication. Alternatively, a single psbA copy may have undergone bursts of adaptive changes at the molecular level to overcome angiosperms competition. The strong signature of positive Darwinian selection in a major part of D1 protein is testament to this. At the same time, species own two psbA copies hardly have positive selection signals among the D1 protein coding sequences. In this study, eleven co-evolving sites have been detected via different molecules, which may be more important than others.We thank Dr. Yefu Wang at State Key Laboratory of Virology, College of Life Sciences, Wuhan University, China, for the guidance for wording, and we also thank Bo Wang and Dr. Lei Gao at the Wuhan Botanical Garden, Chinese Academy of Sciences, China, for the experimental assistance. We thank Dr. Jianqiang Li at the Wuhan Botanical Garden, Chinese Academy of Sciences, China, for the advices on species sampling. We appreciate two anonymous reviewers and other editors for their helpful suggestions. The present work was financially supported by the National Nature Science Foundation of China (No. 30970290, 31070594), and by the Knowledge Innovation Program of the Chinese Academy of Sciences (No. KSCX2-EW-J-20, KSCX2-YW-Z-0940). Dr. Mario A. Fares was supported by Spanish Ministerio de Ciencia e Inovacion (No. BFU2009-12022) and Research Frontiers Program (No. 10/RFP/GEN2685) from Science Foundation Ireland.Sen, L.; Fares Riaño, MA.; Su, Y.; Wang, T. (2012). Molecular evolution of psbA gene in ferns: unraveling selective pressure and co-evolutionary. BMC Evolutionary Biology. 12(145):1-13. https://doi.org/10.1186/1471-2148-12-145S11312145Hohmann-Marriott, M. F., & Blankenship, R. E. (2011). Evolution of Photosynthesis. Annual Review of Plant Biology, 62(1), 515-548. doi:10.1146/annurev-arplant-042110-103811Minai, L., Wostrikoff, K., Wollman, F.-A., & Choquet, Y. (2005). Chloroplast Biogenesis of Photosystem II Cores Involves a Series of Assembly-Controlled Steps That Regulate Translation. The Plant Cell, 18(1), 159-175. doi:10.1105/tpc.105.037705Guskov, A., Kern, J., Gabdulkhakov, A., Broser, M., Zouni, A., & Saenger, W. (2009). Cyanobacterial photosystem II at 2.9-Å resolution and the role of quinones, lipids, channels and chloride. Nature Structural & Molecular Biology, 16(3), 334-342. doi:10.1038/nsmb.1559Stein, D. B., Conant, D. S., Ahearn, M. E., Jordan, E. T., Kirch, S. A., Hasebe, M., … Thomson, J. A. (1992). Structural rearrangements of the chloroplast genome provide an important phylogenetic link in ferns. Proceedings of the National Academy of Sciences, 89(5), 1856-1860. doi:10.1073/pnas.89.5.1856Gao, L., Yi, X., Yang, Y.-X., Su, Y.-J., & Wang, T. (2009). Complete chloroplast genome sequence of a tree fern Alsophila spinulosa: insights into evolutionary changes in fern chloroplast genomes. BMC Evolutionary Biology, 9(1), 130. doi:10.1186/1471-2148-9-130Wolf, P. G. (2003). Complete Nucleotide Sequence of the Chloroplast Genome from a Leptosporangiate Fern, Adiantum capillus-veneris L. DNA Research, 10(2), 59-65. doi:10.1093/dnares/10.2.59Wolf, P. G., Roper, J. M., & Duffy, A. M. (2010). The evolution of chloroplast genome structure in ferns. Genome, 53(9), 731-738. doi:10.1139/g10-061Lynch, M. (2000). The Evolutionary Fate and Consequences of Duplicate Genes. Science, 290(5494), 1151-1155. doi:10.1126/science.290.5494.1151Tautz, D., & Domazet-Lošo, T. (2011). The evolutionary origin of orphan genes. Nature Reviews Genetics, 12(10), 692-702. doi:10.1038/nrg3053Gravemann, S., Schnipper, N., Meyer, H., Vaya, A., Nowaczyk, M. J. M., Rajab, A., … Hoffmann, K. (2010). Dosage effect of zero to three functional LBR-genes in vivo and in vitro. Nucleus, 1(2), 179-189. doi:10.4161/nucl.1.2.11113Colbourne, J. K., Pfrender, M. E., Gilbert, D., Thomas, W. K., Tucker, A., Oakley, T. H., … Basu, M. K. (2011). The Ecoresponsive Genome of Daphnia pulex. Science, 331(6017), 555-561. doi:10.1126/science.1197761Crisp, M. D., & Cook, L. G. (2011). Cenozoic extinctions account for the low diversity of extant gymnosperms compared with angiosperms. New Phytologist, 192(4), 997-1009. doi:10.1111/j.1469-8137.2011.03862.xSchuettpelz, E., & Pryer, K. M. (2009). Evidence for a Cenozoic radiation of ferns in an angiosperm-dominated canopy. Proceedings of the National Academy of Sciences, 106(27), 11200-11205. doi:10.1073/pnas.0811136106Wang, G.-Z., & Lercher, M. J. (2011). The Effects of Network Neighbours on Protein Evolution. PLoS ONE, 6(4), e18288. doi:10.1371/journal.pone.0018288Liang, Z., Xu, M., Teng, M., Niu, L., & Wu, J. (2010). Coevolution is a short-distance force at the protein interaction level and correlates with the modular organization of protein networks. FEBS Letters, 584(19), 4237-4240. doi:10.1016/j.febslet.2010.09.014Lovell, S. C., & Robertson, D. L. (2010). An Integrated View of Molecular Coevolution in Protein-Protein Interactions. Molecular Biology and Evolution, 27(11), 2567-2575. doi:10.1093/molbev/msq144Poon, A., & Chao, L. (2005). The Rate of Compensatory Mutation in the DNA Bacteriophage φX174. Genetics, 170(3), 989-999. doi:10.1534/genetics.104.039438Mateo, R., & Mateu, M. G. (2006). Deterministic, Compensatory Mutational Events in the Capsid of Foot-and-Mouth Disease Virus in Response to the Introduction of Mutations Found in Viruses from Persistent Infections. Journal of Virology, 81(4), 1879-1887. doi:10.1128/jvi.01899-06Davis, B. H., Poon, A. F. Y., & Whitlock, M. C. (2009). Compensatory mutations are repeatable and clustered within proteins. Proceedings of the Royal Society B: Biological Sciences, 276(1663), 1823-1827. doi:10.1098/rspb.2008.1846Sen, L., Fares, M. A., Liang, B., Gao, L., Wang, B., Wang, T., & Su, Y.-J. (2011). Molecular evolution of rbcL in three gymnosperm families: identifying adaptive and coevolutionary patterns. Biology Direct, 6(1), 29. doi:10.1186/1745-6150-6-29Lehtonen, S. (2011). Towards Resolving the Complete Fern Tree of Life. PLoS ONE, 6(10), e24851. doi:10.1371/journal.pone.0024851Drummond, A. J., & Rambaut, A. (2007). BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evolutionary Biology, 7(1), 214. doi:10.1186/1471-2148-7-214Fazekas, A. J., Kuzmina, M. L., Newmaster, S. G., & Hollingsworth, P. M. (2012). DNA Barcoding Methods for Land Plants. Methods in Molecular Biology™, 223-252. doi:10.1007/978-1-61779-591-6_11Chase, M. W., Salamin, N., Wilkinson, M., Dunwell, J. M., Kesanakurthi, R. P., Haidar, N., & Savolainen, V. (2005). Land plants and DNA barcodes: short-term and long-term goals. Philosophical Transactions of the Royal Society B: Biological Sciences, 360(1462), 1889-1895. doi:10.1098/rstb.2005.1720Yang, Z. (2007). PAML 4: Phylogenetic Analysis by Maximum Likelihood. Molecular Biology and Evolution, 24(8), 1586-1591. doi:10.1093/molbev/msm088Stern, A., Doron-Faigenboim, A., Erez, E., Martz, E., Bacharach, E., & Pupko, T. (2007). Selecton 2007: advanced models for detecting positive and purifying selection using a Bayesian inference approach. Nucleic Acids Research, 35(Web Server), W506-W511. doi:10.1093/nar/gkm382Delport, W., Poon, A. F. Y., Frost, S. D. W., & Kosakovsky Pond, S. L. (2010). Datamonkey 2010: a suite of phylogenetic analysis tools for evolutionary biology. Bioinformatics, 26(19), 2455-2457. doi:10.1093/bioinformatics/btq429Pond, S. L. K., & Frost, S. D. W. (2005). Datamonkey: rapid detection of selective pressure on individual sites of codon alignments. Bioinformatics, 21(10), 2531-2533. doi:10.1093/bioinformatics/bti320Fares, M. A., & McNally, D. (2006). CAPS: coevolution analysis using protein sequences. Bioinformatics, 22(22), 2821-2822. doi:10.1093/bioinformatics/btl493Gouveia-Oliveira, R., Roque, F. S., Wernersson, R., Sicheritz-Ponten, T., Sackett, P. W., Molgaard, A., & Pedersen, A. G. (2009). InterMap3D: predicting and visualizing co-evolving protein residues. Bioinformatics, 25(15), 1963-1965. doi:10.1093/bioinformatics/btp335Fazekas, A. J., Burgess, K. S., Kesanakurti, P. R., Graham, S. W., Newmaster, S. G., Husband, B. C., … Barrett, S. C. H. (2008). Multiple Multilocus DNA Barcodes from the Plastid Genome Discriminate Plant Species Equally Well. PLoS ONE, 3(7), e2802. doi:10.1371/journal.pone.0002802Kress, W. J., & Erickson, D. L. (2007). A Two-Locus Global DNA Barcode for Land Plants: The Coding rbcL Gene Complements the Non-Coding trnH-psbA Spacer Region. PLoS ONE, 2(6), e508. doi:10.1371/journal.pone.0000508Karol, K. G., Arumuganathan, K., Boore, J. L., Duffy, A. M., Everett, K. D., Hall, J. D., … Wolf, P. G. (2010). Complete plastome sequences of Equisetum arvense and Isoetes flaccida: implications for phylogeny and plastid genome evolution of early land plant lineages. BMC Evolutionary Biology, 10(1), 321. doi:10.1186/1471-2148-10-321Brown, C. J., Todd, K. M., & Rosenzweig, R. F. (1998). Multiple duplications of yeast hexose transport genes in response to selection in a glucose-limited environment. Molecular Biology and Evolution, 15(8), 931-942. doi:10.1093/oxfordjournals.molbev.a026009Bekaert, M., & Conant, G. C. (2010). Copy Number Alterations among Mammalian Enzymes Cluster in the Metabolic Network. Molecular Biology and Evolution, 28(2), 1111-1121. doi:10.1093/molbev/msq296Müh, F., Renger, T., & Zouni, A. (2008). Crystal structure of cyanobacterial photosystem II at 3.0 Å resolution: A closer look at the antenna system and the small membrane-intrinsic subunits. Plant Physiology and Biochemistry, 46(3), 238-264. doi:10.1016/j.plaphy.2008.01.003Guskov, A., Gabdulkhakov, A., Broser, M., Glöckner, C., Hellmich, J., Kern, J., … Zouni, A. (2010). Recent Progress in the Crystallographic Studies of Photosystem II. ChemPhysChem, 11(6), 1160-1171. doi:10.1002/cphc.200900901Lee, B.-C., Park, K., & Kim, D. (2008). Analysis of the residue-residue coevolution network and the functionally important residues in proteins. Proteins: Structure, Function, and Bioinformatics, 72(3), 863-872. doi:10.1002/prot.21972Wyman, S. K., Jansen, R. K., & Boore, J. L. (2004). Automatic annotation of organellar genomes with DOGMA. Bioinformatics, 20(17), 3252-3255. doi:10.1093/bioinformatics/bth352Posada, D. (2008). jModelTest: Phylogenetic Model Averaging. Molecular Biology and Evolution, 25(7), 1253-1256. doi:10.1093/molbev/msn083Phipps, C. J., Taylor, T. N., Taylor, E. L., Cúneo, N. R., Boucher, L. D., & Yao, X. (1998). OSMUNDA (OSMUNDACEAE) FROM THE TRIASSIC OF Antarctica: an example of evolutionary stasis. American Journal of Botany, 85(6), 888-895. doi:10.2307/2446424Anisimova, M., Bielawski, J. P., & Yang, Z. (2001). Accuracy and Power of the Likelihood Ratio Test in Detecting Adaptive Molecular Evolution. Molecular Biology and Evolution, 18(8), 1585-1592. doi:10.1093/oxfordjournals.molbev.a003945Suzuki, Y., & Gojobori, T. (1999). A method for detecting positive selection at single amino acid sites. Molecular Biology and Evolution, 16(10), 1315-1328. doi:10.1093/oxfordjournals.molbev.a026042Kosakovsky Pond, S. L., & Frost, S. D. W. (2005). Not So Different After All: A Comparison of Methods for Detecting Amino Acid Sites Under Selection. Molecular Biology and Evolution, 22(5), 1208-1222. doi:10.1093/molbev/msi105Caporaso, J. G., Smit, S., Easton, B. C., Hunter, L., Huttley, G. A., & Knight, R. (2008). Detecting coevolution without phylogenetic trees? Tree-ignorant metrics of coevolution perform as well as tree-aware metrics. BMC Evolutionary Biology, 8(1), 327. doi:10.1186/1471-2148-8-327Li, W.-H. (1993). Unbiased estimation of the rates of synonymous and nonsynonymous substitution. Journal of Molecular Evolution, 36(1), 96-99. doi:10.1007/bf02407308Poon, A. F. Y., Lewis, F. I., Frost, S. D. W., & Kosakovsky Pond, S. L. (2008). Spidermonkey: rapid detection of co-evolving sites using Bayesian graphical models. Bioinformatics, 24(17), 1949-1950. doi:10.1093/bioinformatics/btn313Tillier, E. R. M., & Lui, T. W. H. (2003). Using multiple interdependency to separate functional from phylogenetic correlations in protein alignments. Bioinformatics, 19(6), 750-755. doi:10.1093/bioinformatics/btg072Gouveia-Oliveira, R., & Pedersen, A. G. (2007). Finding coevolving amino acid residues using row and column weighting of mutual information and multi-dimensional amino acid representation. Algorithms for Molecular Biology, 2(1). doi:10.1186/1748-7188-2-12Martin, L. C., Gloor, G. B., Dunn, S. D., & Wahl, L. M. (2005). Using information theory to search for co-evolving residues in proteins. Bioinformatics, 21(22), 4116-4124. doi:10.1093/bioinformatics/bti671Makarova, K. S., Wolf, Y. I., van der Oost, J., & Koonin, E. V. (2009). Prokaryotic homologs of Argonaute proteins are predicted to function as key components of a novel system of defense against mobile genetic elements. Biology Direct, 4(1), 29. doi:10.1186/1745-6150-4-2

Methyl 8-hydroxy-(S)-3-methyl-1-oxoisochromane-5-carboxylate (5-methoxycarbonylmellein)

The title compound, C12H12O5, exists as two independent, relatively planar molecules in the asymmetric unit; these differ in the orientation of the ester group

7,8-dihydroxy-3-methyl-10-oxo-1H,10H-pyrano[4,3-b]chromene-9-carboxylic acid

The structure of the title compound, anhydrofulvic acid, C14H10O7, a yellow acidic metabolite isolated from Paecilomyces sp. was determined by X-ray analysis. The chromone ring system is essentially planar, with the carboxylic acid group coplanar with the ring

Effect of Prestrain on Hydrogen-Induced Delayed Cracking for Medium Mn Steels

Medium Mn steels are a class of the new-generation ultra-high-strength materials used in automotives. However, despite excellent ductility, they may suffer from delayed cracking and thus cause serious concerns. In this study, several medium Mn steels were tested with different prestrain and hydrogen charging conditions. The interaction and synergistic effects of prestrain and hydrogen content on hydrogen-induced delayed cracking behavior are investigated. The threshold stress of hydrogen-induced cracking (HIC) decreased during dynamic hydrogen charging under a constant load. In the process of dynamic hydrogen charging, for M7B and M10B steels, the normalized stress intensity factor σ/σb and the corresponding threshold stress σHIC decreased sharply as prestrain increased. This is because the volume fraction of retained austenite decreased with an increase in prestrain. Similarly, σHIC was reduced and the critical hydrogen content dropped drastically with increasing prestrain. For M7C, the influence of prestrain on threshold stress and hydrogen concentration was less than that of M7B. This is because the different treatment processes leads to a different stability of the retained austenite. By observing the SEM fractographs, the fracture surface of medium Mn steels showed different fracture characteristics, such as dimple fractures and intergranular and transgranular modes

8-Hydroxy-(S)-3-methyl-1-oxoisochromane-5-carboxylic acid(5-carboxymellein)

The molecules of the title compound, C11H10O5, are linked by a hydrogen bond involving the acid H and the carbonyl O atom of the dihydroisocoumarin unit into a linear chain running along the b axis of the monoclinic unit cell

7-methoxy-4,6-dimethyl-3H-isobenzofuran-1-one

The title compound, C11H12O3, exists as a nearly planar molecule, the dihedral angle between the five- and six-membered rings being 1.9 (2)degrees