1,507 research outputs found

    Mechanical charecterization and analytical modeling of the thermo-viscoplastic behaviour AISI 304 steel under wide ranges of strain rates at room temperature

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    In this investigation, the thermo-viscoplastic behaviour of the steel AISI 304 has been examined. The experimental characterization of the material has been conducted in tension under wide ranges of strain rates.An analytical description of the macroscopic behaviour of this metal is reported. For such goal, the extended Rusinek-Klepaczko model to viscous drag effects is applied.It allows for proper description of the material behaviour within the whole range of loading conditions considered.In addition, the analytical formulation proposed gathers limited number of material constants and simple calibration procedure

    Anaerobic co-digestion of the aqueous phase from hydrothermally treated waste activated sludge with primary sewage sludge. A kinetic study

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    The mesophilic anaerobic co-digestion of the liquid fraction from hydrothermal carbonization (LFHTC) of dewatered waste activated sludge with primary sewage sludge (PSS) has been studied. Mixtures of different composition (25, 50 and 75% of LFHTC on a chemical oxygen demand (COD) basis), as well as the individual substrates, have been tested using two inocula (flocculent (FS) and granular (GS) sludges). Methane production decreased as the LFHTC/PSS ratio increased, which can be related to the presence of recalcitrant compounds in the LFHTC, such as alkenes, phenolics, and other oxygen- and nitrogen-bearing aromatics hard-to-degrade through anaerobic digestion. Methane yield reached 248 ± 11 mL CH4 STP/g CODadded with the GS inoculum and 25% LFHTC. A 74 and a 30% increase of methane production was achieved in the 25% LFHTC runs respect to the obtained in the similar experiments with 100% LFHTC, using the FS and GS inocula, respectively. In those late runs, the COD was reduced more than 86%, with a negligible concentration of total volatile fatty acids. With both inocula, total Kjeldahl nitrogen hydrolysis increased as the LFHTC to PSS mixture ratio decreased, reaching values higher than 79% at the end of the experiments. Methane yield values fitted well the first-order, Cone and Weibull kinetic models for both inocula. Significant differences in the kinetic constant values, ranging from 0.100 to 0.168 d−1 and 0.059–0.068 d−1, were found with the FS and GS inocula, respectively. The results obtained support the potential integration of HTC of dewatered waste activated sludge in wastewater treatment plantsThe authors greatly appreciate financial support from the SpanishMINECO (Project CTM2016-76564-R) and the Community of Madrid(Project P2013/MAE-2716). M.A. de la Rubia acknowledges financialsupport from the Spanish MINECO (RYC-2013-12549). The valuablecontribution of

    Valorisation of the liquid fraction from hydrothermal carbonisation of sewage sludge by anaerobic digestion

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    This is the peer reviewed version of the following article: Journal of Chemical Technology and Biotechnology 93.2 (2018): 450-456, which has been published in final form at https://doi.org/10.1002/jctb.5375. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived VersionsBACKGROUND: The mesophilic anaerobic digestion of the liquid fraction from hydrothermal carbonisation (208°C, 1 h) of dehydrated sewage sludge has been studied. Two initial inoculum concentrations (IC) (10 and 25 g COD L-1) and four inoculum to substrate ratios (ISR) (2, 1, 0.5 and 0.4 on a COD basis) have been selected to analyse their influence on the evolution of the anaerobic digestion process. RESULTS: The substrate is characterised by a high COD (95.5 g L-1) and TKN (8.7 g N L-1) values. High inoculum concentration (25 g COD L-1) and/or low ISR (≤ 0.5) inhibited methanogenesis due to the high ammonia nitrogen (1.4 g TAN L-1) and VFA (>4 g COD L-1) released. For the inhibited samples final COD removals lower than 15% and IA/TA ratios higher than 0.3 were found. The greatest methane yield (177±5 mL CH4 STP g-1 CODadded) was achieved at 25 g COD L-1 of IC and at an ISR of 2. CONCLUSION: During anaerobic digestion of the liquid fraction from the hydrothermal carbonisation of sewage sludge, the IC and ISR must be adequately selected for proper operation of the process and successful valorisation. According to the results, working at an ISR ≥ 1 is recommendedThe authors wish to express their gratitude to the UAM-Santander (Project CEAL-AL/2015-29) and Spanish MINECO (CTM2016-76564-R) for providing financial support. MA de la Rubia acknowledges financial support from the Spanish Ministry of Economy and Competitiveness (RYC-2013-12549

    Revealing patterns of local species richness along environmental gradients with a novel network tool

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    How species richness relates to environmental gradients at large extents is commonly investigated aggregating local site data to coarser grains. However, such relationships often change with the grain of analysis, potentially hiding the local signal. Here we show that a novel network technique, the “method of reflections”, could unveil the relationships between species richness and climate without such drawbacks. We introduced a new index related to potential species richness, which revealed large scale patterns by including at the local community level information about species distribution throughout the dataset (i.e., the network). The method effectively removed noise, identifying how far site richness was from potential. When applying it to study woody species richness patterns in Spain, we observed that annual precipitation and mean annual temperature explained large parts of the variance of the newly defined species richness, highlighting that, at the local scale, communities in drier and warmer areas were potentially the species richest. Our method went far beyond what geographical upscaling of the data could unfold, and the insights obtained strongly suggested that it is a powerful instrument to detect key factors underlying species richness patterns, and that it could have numerous applications in ecology and other fields

    Transcriptional diversification and functional conservation between DELLA proteins in Arabidopsis

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    [EN] Plasticity and robustness of signaling pathways partly rely on genetic redundancy, although the precise mechanism that provides functional specificity to the different redundant elements in a given process is often unknown. In Arabidopsis, functional redundancy in gibberellin signaling has been largely attributed to the presence of five members of the DELLA family of transcriptional regulators. Here, we demonstrate that two evolutionarily and functionally divergent DELLA proteins, RGL2 and RGA, can perform exchangeable functions when they are expressed under control of the reciprocal promoter. Furthermore, both DELLA proteins display equivalent abilities to interact with PIF4 and with other bHLH transcription factors with a reported role in the control of cell growth and seed germination. Therefore, we propose that functional diversification of Arabidopsis DELLA proteins has largely relied on changes in their gene expression patterns rather than on their ability to interact with different regulatory partners, model also supported by a clustering analysis of DELLA transcript profiles over a range of organs and growth conditions that revealed specific patterns of expression for each of these genes.We deeply appreciate the help of Marta Trenor and Laura Garcia-Carcel in the initial stages of this work. We also thank Tai-ping Sun (Duke University) and the Arabidpsis Biological Resource Center for seeds, Marta Boter for the pGBKT7 and pGADT7 Gateway vectors, Santiago Elena (IBMCP, CSIC-UPV) for useful comments on the manuscript, and Francois Parcy (IRTSV, CNRS-CEA) for fruitful discussions and hosting MAB. Work in the authors' laboratories is funded by grants BIO2007-60923 and BIO2005-07284 from the Spanish Ministry of Science and Innovation. J.G.B. is the recipient of a CSIC I3P Fellowship and J.A.M. is the recipient of a Fellowship from the Fundacion "la Caixa.Gallego-Bartolome, J.; Minguet, E.; Marin, JA.; Prat, S.; Blazquez Rodriguez, MA.; Alabadí Diego, D. (2010). Transcriptional diversification and functional conservation between DELLA proteins in Arabidopsis. Molecular Biology and Evolution. 27(6):1247-1256. https://doi.org/10.1093/molbev/msq0121247125627

    Effectiveness of the 23-valent polysaccharide pneumococcal vaccine against invasive pneumococcal disease in people 60 years or older

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    <p>Abstract</p> <p>Background</p> <p>The 23-valent polysaccharide pneumococcal vaccine (PPV) is currently recommended in elderly and high-risk adults. However, its efficacy in preventing pneumococcal infections remains controversial. This study assessed the clinical effectiveness of vaccination against invasive pneumococcal disease (IPD) among people over 60 years.</p> <p>Methods</p> <p>Population-based case-control study that included 88 case patients over 60 years-old with a laboratory-confirmed IPD (bacteraemic pneumonia, meningitis or sepsis) and 176 outpatient control subjects who were matched by primary care centre, age, sex and risk stratum. Adjusted odds ratios (ORs) for vaccination were calculated using conditional logistic regression, controlling for underlying conditions. Vaccine effectiveness was estimated as (1 - OR) ×100.</p> <p>Results</p> <p>Pneumococcal vaccination rate was significantly lower in cases than in control subjects (38.6% <it>vs </it>59.1%; p = 0.002). The adjusted vaccine effectiveness was 72% (OR: 0.28; 95% CI: 0.15-0.54) against all IPD and 77% (OR: 0.23; 95% CI: 0.08-0.60) against vaccine-type IPD. Vaccination was significantly effective against all IPD in both age groups: 60-79 years-old (OR 0.32; 95% CI: 0.14-0.74) and people 80 years or older (OR: 0.29; 95% CI: 0.09-0.91). Vaccination appears significantly effective as for high-risk immunocompetent subjects (OR: 0.29; 95% CI: 0.11-0.79) as well as for immunocompromised subjects (OR: 0.12; 95% CI: 0.03-0.53).</p> <p>Conclusion</p> <p>These findings confirm the effectiveness of the 23-valent PPV against IPD, and they also support the benefit of vaccination in preventing invasive infections among high-risk and older people.</p

    The role of a class III gibberellin 2-oxidase in tomato internode elongation

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    [EN] A network of environmental inputs and internal signaling controls plant growth, development and organ elongation. In particular, the growth-promoting hormone gibberellin (GA) has been shown to play a significant role in organ elongation. The use of tomato as a model organism to study elongation presents an opportunity to study the genetic control of internode-specific elongation in a eudicot species with a sympodial growth habit and substantial internodes that can and do respond to external stimuli. To investigate internode elongation, a mutant with an elongated hypocotyl and internodes but wild-type petioles was identified through a forward genetic screen. In addition to stem-specific elongation, this mutant, named tomato internode elongated -1 (tie-1) is more sensitive to the GA biosynthetic inhibitor paclobutrazol and has altered levels of intermediate and bioactive GAs compared with wild-type plants. The mutation responsible for the internode elongation phenotype was mapped to GA2oxidase 7, a class III GA 2-oxidase in the GA biosynthetic pathway, through a bulked segregant analysis and bioinformatic pipeline, and confirmed by transgenic complementation. Furthermore, bacterially expressed recombinant TIE protein was shown to have bona fide GA 2-oxidase activity. These results define a critical role for this gene in internode elongation and are significant because they further the understanding of the role of GA biosynthetic genes in organ-specific elongation.This work used the Vincent J. Coates Genomics Sequencing Laboratory at UC Berkeley, supported by NIH S10 Instrumentation Grants S10RR029668 and S10RR027303. We thank the Tomato Genetics Resource Center for providing seed of the M82 and Heinz cultivars. The material was developed by and/or obtained from the UC Davis/C M Rick Tomato Genetics Resource Center and maintained by the Department of Plant Sciences, University of California, Davis, CA 95616, USA. We thank Anthony Bolger, Alisdair Fernie and Bjorn Usadel for providing us with access to pre-publication genomic reads of the S. lycopersicum cultivar M82, and Cristina Urbez and Noel Blanco-Tourinan (IBMCP, Spain) for technical help with in vitro production of TIE1. This work was supported in part by the Elsie Taylor Stocking Memorial Fellowship awarded to ASL in 2013, by NSF grant IOS-0820854, by USDA National Institute of Food and Agriculture project CA-D-PLB-2465-H, by internal UC Davis funds, and by Spanish Ministry of Economy and Competitiveness grant BFU2016-80621-P.Lavelle, A.; Gath, N.; Devisetty, U.; Carrera Bergua, E.; Lopez Diaz, I.; Blazquez Rodriguez, MA.; Maloof, J. (2018). The role of a class III gibberellin 2-oxidase in tomato internode elongation. The Plant Journal. https://doi.org/10.1111/tpj.14145SAndrés, F., Porri, A., Torti, S., Mateos, J., Romera-Branchat, M., García-Martínez, J. L., … Coupland, G. (2014). SHORT VEGETATIVE PHASE reduces gibberellin biosynthesis at theArabidopsisshoot apex to regulate the floral transition. Proceedings of the National Academy of Sciences, 111(26), E2760-E2769. doi:10.1073/pnas.1409567111Bolger, A., Scossa, F., Bolger, M. E., Lanz, C., Maumus, F., Tohge, T., … Fernie, A. R. (2014). The genome of the stress-tolerant wild tomato species Solanum pennellii. Nature Genetics, 46(9), 1034-1038. doi:10.1038/ng.3046Bowen, M. E., Henke, K., Siegfried, K. R., Warman, M. L., & Harris, M. P. (2011). Efficient Mapping and Cloning of Mutations in Zebrafish by Low-Coverage Whole-Genome Sequencing. Genetics, 190(3), 1017-1024. doi:10.1534/genetics.111.136069Burset, M. (2000). Analysis of canonical and non-canonical splice sites in mammalian genomes. Nucleic Acids Research, 28(21), 4364-4375. doi:10.1093/nar/28.21.4364Chen, W., Yao, J., Chu, L., Yuan, Z., Li, Y., & Zhang, Y. (2015). Genetic mapping of the nulliplex-branch gene (gb_nb1) in cotton using next-generation sequencing. Theoretical and Applied Genetics, 128(3), 539-547. doi:10.1007/s00122-014-2452-2Cingolani, P., Platts, A., Wang, L. L., Coon, M., Nguyen, T., Wang, L., … Ruden, D. M. (2012). A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff. Fly, 6(2), 80-92. doi:10.4161/fly.19695Cuperus, J. T., Montgomery, T. A., Fahlgren, N., Burke, R. T., Townsend, T., Sullivan, C. M., & Carrington, J. C. (2009). Identification of MIR390a precursor processing-defective mutants in Arabidopsis by direct genome sequencing. Proceedings of the National Academy of Sciences, 107(1), 466-471. doi:10.1073/pnas.0913203107Curtis, M. D., & Grossniklaus, U. (2003). A Gateway Cloning Vector Set for High-Throughput Functional Analysis of Genes in Planta. Plant Physiology, 133(2), 462-469. doi:10.1104/pp.103.027979Devisetty, U. K., Covington, M. F., Tat, A. V., Lekkala, S., & Maloof, J. N. (2014). Polymorphism Identification and Improved Genome Annotation ofBrassica rapaThrough Deep RNA Sequencing. G3&amp;#58; Genes|Genomes|Genetics, 4(11), 2065-2078. doi:10.1534/g3.114.012526Eckardt, N. A. (2007). GA Perception and Signal Transduction: Molecular Interactions of the GA Receptor GID1 with GA and the DELLA Protein SLR1 in Rice. The Plant Cell, 19(7), 2095-2097. doi:10.1105/tpc.107.054916Ernst, H. A., Lo Leggio, L., Willemoës, M., Leonard, G., Blum, P., & Larsen, S. (2006). Structure of the Sulfolobus solfataricus α-Glucosidase: Implications for Domain Conservation and Substrate Recognition in GH31. Journal of Molecular Biology, 358(4), 1106-1124. doi:10.1016/j.jmb.2006.02.056Fillatti, J. J., Kiser, J., Rose, R., & Comai, L. (1987). Efficient Transfer of a Glyphosate Tolerance Gene into Tomato Using a Binary Agrobacterium Tumefaciens Vector. Nature Biotechnology, 5(7), 726-730. doi:10.1038/nbt0787-726Garrison , E. Marth , G. 2012 Haplotype-based variant detection from short-read sequencingHedden, P., & Graebe, J. E. (1985). Inhibition of gibberellin biosynthesis by paclobutrazol in cell-free homogenates ofCucurbita maxima endosperm andMalus pumila embryos. Journal of Plant Growth Regulation, 4(1-4), 111-122. doi:10.1007/bf02266949Kimura, S., & Sinha, N. (2008). Tomato (Solanum lycopersicum): A Model Fruit-Bearing Crop. Cold Spring Harbor Protocols, 2008(12), pdb.emo105-pdb.emo105. doi:10.1101/pdb.emo105Koenig, D., Jimenez-Gomez, J. M., Kimura, S., Fulop, D., Chitwood, D. H., Headland, L. R., … Maloof, J. N. (2013). Comparative transcriptomics reveals patterns of selection in domesticated and wild tomato. Proceedings of the National Academy of Sciences, 110(28), E2655-E2662. doi:10.1073/pnas.1309606110Li, H., & Durbin, R. (2009). Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics, 25(14), 1754-1760. doi:10.1093/bioinformatics/btp324Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., … Homer, N. (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics, 25(16), 2078-2079. doi:10.1093/bioinformatics/btp352Li, J., Sima, W., Ouyang, B., Wang, T., Ziaf, K., Luo, Z., … Ye, Z. (2012). Tomato SlDREB gene restricts leaf expansion and internode elongation by downregulating key genes for gibberellin biosynthesis. Journal of Experimental Botany, 63(18), 6407-6420. doi:10.1093/jxb/ers295Lorrain, S., & Fankhauser, C. (2012). Plant Development: Should I Stop or Should I Grow? Current Biology, 22(16), R645-R647. doi:10.1016/j.cub.2012.06.054Menda, N., Semel, Y., Peled, D., Eshed, Y., & Zamir, D. (2004). In silicoscreening of a saturated mutation library of tomato. The Plant Journal, 38(5), 861-872. doi:10.1111/j.1365-313x.2004.02088.xMichelmore, R. W., Paran, I., & Kesseli, R. V. (1991). Identification of markers linked to disease-resistance genes by bulked segregant analysis: a rapid method to detect markers in specific genomic regions by using segregating populations. Proceedings of the National Academy of Sciences, 88(21), 9828-9832. doi:10.1073/pnas.88.21.9828Pimenta Lange, M. J., Liebrandt, A., Arnold, L., Chmielewska, S.-M., Felsberger, A., Freier, E., … Lange, T. (2013). Functional characterization of gibberellin oxidases from cucumber, Cucumis sativus L. Phytochemistry, 90, 62-69. doi:10.1016/j.phytochem.2013.02.006Raskin, I., & Kende, H. (1984). Role of Gibberellin in the Growth Response of Submerged Deep Water Rice. Plant Physiology, 76(4), 947-950. doi:10.1104/pp.76.4.947Reinecke, D. M., Wickramarathna, A. D., Ozga, J. A., Kurepin, L. V., Jin, A. L., Good, A. G., & Pharis, R. P. (2013). Gibberellin 3-oxidase Gene Expression Patterns Influence Gibberellin Biosynthesis, Growth, and Development in Pea. PLANT PHYSIOLOGY, 163(2), 929-945. doi:10.1104/pp.113.225987Robinson, M. D., & Oshlack, A. (2010). A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biology, 11(3), R25. doi:10.1186/gb-2010-11-3-r25Robinson, M. D., McCarthy, D. J., & Smyth, G. K. (2009). edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics, 26(1), 139-140. doi:10.1093/bioinformatics/btp616Robinson, J. T., Thorvaldsdóttir, H., Winckler, W., Guttman, M., Lander, E. S., Getz, G., & Mesirov, J. P. (2011). Integrative genomics viewer. Nature Biotechnology, 29(1), 24-26. doi:10.1038/nbt.1754Schneeberger, K., Ossowski, S., Lanz, C., Juul, T., Petersen, A. H., Nielsen, K. L., … Andersen, S. U. (2009). SHOREmap: simultaneous mapping and mutation identification by deep sequencing. Nature Methods, 6(8), 550-551. doi:10.1038/nmeth0809-550Schneider, C. A., Rasband, W. S., & Eliceiri, K. W. (2012). NIH Image to ImageJ: 25 years of image analysis. Nature Methods, 9(7), 671-675. doi:10.1038/nmeth.2089Schomburg, F. M., Bizzell, C. M., Lee, D. J., Zeevaart, J. A. D., & Amasino, R. M. (2002). Overexpression of a Novel Class of Gibberellin 2-Oxidases Decreases Gibberellin Levels and Creates Dwarf Plants. The Plant Cell, 15(1), 151-163. doi:10.1105/tpc.005975Seo, M., Jikumaru, Y., & Kamiya, Y. (2011). Profiling of Hormones and Related Metabolites in Seed Dormancy and Germination Studies. Methods in Molecular Biology, 99-111. doi:10.1007/978-1-61779-231-1_7Sun, T. (2011). The Molecular Mechanism and Evolution of the GA–GID1–DELLA Signaling Module in Plants. Current Biology, 21(9), R338-R345. doi:10.1016/j.cub.2011.02.036Sun, T., & Gubler, F. (2004). MOLECULAR MECHANISM OF GIBBERELLIN SIGNALING IN PLANTS. Annual Review of Plant Biology, 55(1), 197-223. doi:10.1146/annurev.arplant.55.031903.141753Thorvaldsdottir, H., Robinson, J. T., & Mesirov, J. P. (2012). Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Briefings in Bioinformatics, 14(2), 178-192. doi:10.1093/bib/bbs017(2012). The tomato genome sequence provides insights into fleshy fruit evolution. Nature, 485(7400), 635-641. doi:10.1038/nature11119Trapnell, C., Pachter, L., & Salzberg, S. L. (2009). TopHat: discovering splice junctions with RNA-Seq. Bioinformatics, 25(9), 1105-1111. doi:10.1093/bioinformatics/btp120Trapnell, C., Roberts, A., Goff, L., Pertea, G., Kim, D., Kelley, D. R., … Pachter, L. (2012). Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nature Protocols, 7(3), 562-578. doi:10.1038/nprot.2012.016Tsai, H., Howell, T., Nitcher, R., Missirian, V., Watson, B., Ngo, K. J., … Comai, L. (2011). Discovery of Rare Mutations in Populations: TILLING by Sequencing. Plant Physiology, 156(3), 1257-1268. doi:10.1104/pp.110.169748Ueguchi-Tanaka, M., Nakajima, M., Katoh, E., Ohmiya, H., Asano, K., Saji, S., … Matsuoka, M. (2007). Molecular Interactions of a Soluble Gibberellin Receptor, GID1, with a Rice DELLA Protein, SLR1, and Gibberellin. The Plant Cell, 19(7), 2140-2155. doi:10.1105/tpc.106.043729Wickham, H. (2016). ggplot2. Use R! doi:10.1007/978-3-319-24277-4Winter, D., Vinegar, B., Nahal, H., Ammar, R., Wilson, G. V., & Provart, N. J. (2007). An «Electronic Fluorescent Pictograph» Browser for Exploring and Analyzing Large-Scale Biological Data Sets. PLoS ONE, 2(8), e718. doi:10.1371/journal.pone.0000718Xu, H., Liu, Q., Yao, T., & Fu, X. (2014). Shedding light on integrative GA signaling. Current Opinion in Plant Biology, 21, 89-95. doi:10.1016/j.pbi.2014.06.010Yamaguchi, S. (2008). Gibberellin Metabolism and its Regulation. Annual Review of Plant Biology, 59(1), 225-251. doi:10.1146/annurev.arplant.59.032607.09280

    NLP-CIC @ DIACR-Ita: POS and Neighbor Based Distributional Models for Lexical Semantic Change in Diachronic Italian Corpora

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    We present our systems and findings on unsupervised lexical semantic change for the Italian language in the DIACR-Ita shared-task at EVALITA 2020. The task is to determine whether a target word has evolved its meaning with time, only relying on raw-text from two time-specific datasets. We propose two models representing the target words across the periods to predict the changing words using threshold and voting schemes. Our first model solely relies on part-of-speech usage and an ensemble of distance measures. The second model uses word embedding representation to extract the neighbor’s relative distances across spaces and propose “the average of absolute differences" to estimate lexical semantic change. Our models achieved competent results, ranking third in the DIACR-Ita competition. Furthermore, we experiment with the k_neighbor parameter of our second model to compare the impact of using “the average of absolute differences" versus the cosine distance used in (Hamilton, Leskovec, and Jurafsky 2016)
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