A multiple-trait analysis of ecohydrological acclimatisation in a dryland phreatophytic shrub

Water is the main limiting factor for groundwater-dependent ecosystems (GDEs) in drylands. Predicted climate change (precipitation reductions and temperature increases) and anthropogenic activities such as groundwater drawdown jeopardise the functioning of these ecosystems, presenting new challenges for their management. We developed a trait-based analysis to examine the spatiotemporal variability in the ecophysiology of Ziziphus lotus, a long-lived phreatophyte that dominates one of the few terrestrial GDEs of semiarid regions in Europe. We assessed morpho-functional traits and stem water potential along a naturally occurring gradient of depth-to-groundwater (DTGW, 2–25 m) in a coastal aquifer, and throughout the species-growing season. Increasing DTGW and salinity negatively affected photosynthetic and transpiration rates, increasing plant water stress (lower predawn and midday water potential), and positively affected Huber value (sapwood cross-sectional area per leaf area), reducing leaf area and likely, plant hydraulic demand. However, the species showed greater salt-tolerance at shallow depths. Despite groundwater characteristics, higher atmospheric evaporative demand in the study area, which occurred in summer, fostered higher transpiration rates and water stress, and promoted carbon assimilation and water loss more intensively at shallow water tables. This multiple-trait analysis allowed us to identify plant ecophysiological thresholds related to the increase in salinity, but mostly in DTGW (13 m), and in the evaporative demand during the growing season. These findings highlight the existence of tipping points in the functioning of a long-lived phreatophyte in drylands and can contribute to the sustainable management of GDEs in southern Europe, paving the way for further studies on phreatophytic species

Is the New Mayo Clinic Quadratic Equation Useful for the Estimation of Glomerular Filtration Rate in Type 2 Diabetic Patients?

OBJECTIVE—To test the Mayo Clinic Quadratic (MCQ) equation against isotopic glomerular filtration rate, compared with the Modification of Diet in Renal Disease (MDRD) and the Cockcroft-Gault formulas, in type 2 diabetes

Electrocatalytic performance of SiO2-SWCNT nanocomposites prepared by electroassisted deposition

“The final publication is available at Springer via http://dx.doi.org/10.1007/s12678-013-0144-3”Composite materials made of porous SiO2 matrices filled with single-walled carbon nanotubes (SWCNTs) were deposited on electrodes by an electroassisted deposition method. The synthesized materials were characterized by several techniques, showing that porous silica prevents the aggregation of SWCNT on the electrodes, as could be observed by transmission electron microscopy and Raman spectroscopy. Different redox probes were employed to test their electrochemical sensing properties. The silica layer allows the permeation of the redox probes to the electrode surface and improves the electrochemical reversibility indicating an electrocatalytic effect by the incorporation of dispersed SWCNT into the silica films.This work was financed by the following research projects: MAT2010-15273 of the Spanish Ministerio de Economia y Competitividad and FEDER, PROMETEO/2013/038 of the GV, and CIVP16A1821 of the Fundacion Ramon Areces. Alonso Gamero-Quijano and David Salinas-Torres acknowledge Generalitat Valenciana (Santiago Grisolia Program) and Ministerio de Economia y Competitividad, respectively, for the funding of their research fellowships.Gamero-Quijano, A.; Huerta, F.; Salinas-Torres, D.; Morallón, E.; Montilla, F. (2013). Electrocatalytic performance of SiO2-SWCNT nanocomposites prepared by electroassisted deposition. Electrocatalysis. 4(4):259-266. https://doi.org/10.1007/s12678-013-0144-3S25926644P. Alivisatos, Nat. Biotechnol. 22, 47 (2004)S. Stankovich, D.A. Dikin, G.H. Dommett, K.M. Kohlhaas, E.J. Zimney, E.A. Stach, R.D. Piner, S.T. Nguyen, R.S. Ruoff, Nature 442, 282 (2006)D.W. Schaefer, R.S. Justice, Macromolecules 40, 8501 (2007)M. Endo, M.S. Strano, P.M. Ajayan, Carbon Nanotubes 111, 13 (2008)C.E. Banks, R.G. Compton, Analyst 131, 15 (2006)R.H. Baughman, A.A. Zakhidov, W.A. de Heer, Science 297, 787 (2002)Y.H. Lin, F. Lu, Y. Tu, Z.F. Ren, Nano Letters 4, 191 (2004)B.R. Azamian, J.J. Davis, K.S. Coleman, C.B. Bagshaw, M.L.H. Green, J. Am. Chem. Soc. 124, 12664 (2002)W. Yang, K. Ratinac, S. Ringer, P. Thordarson, J.G. Gooding, F. Braet, Angew. Chem. Int. Ed. 49, 2114 (2010)C.E. Banks, R.G. Compton, Analyst 130, 1232 (2005)L. Mazurenko, M. Etienne, O. Tananaiko, V. Zaitsev, A. Walcarius, Electrochim. Acta 83, 359 (2012)J.M.P. Paloma Yáñez-Sedeño, J. Riu, F.X. Rius, TrAC Trends in Analytical Chemistry 29, 939 (2010)Z.J. Wang, M. Etienne, S. Poller, W. Schuhmann, G.W. Kohring, V. Mamane, A. Walcarius, Electroanalysis 24, 376 (2012)R. Bandyopadhyaya, E. Nativ-Roth, O. Regev, R. Yerushalmi-Rozen, Nano Letters 2, 25 (2002)C. Park, Z. Ounaies, K.A. Watson, R.E. Crooks, J. Smith, S.E. Lowther, J.W. Connell, E.J. Siochi, J.S. Harrison, T.L.S. Clair, Chem. Phys. Lett. 364, 303 (2002)O. Matarredona, H. Rhoads, Z.R. Li, J.H. Harwell, L. Balzano, D.E. Resasco, Journal of Physical Chemistry B 107, 13357 (2003)L. Vaisman, H. Wagner, G. Marom, Advances in Colloid and Interface Science 128, 37 (2006)Y.C. Xing, Journal of Physical Chemistry B 108, 19255 (2004)J.J. Liang, Y. Huang, L. Zhang, Y. Wang, Y.F. Ma, T.Y. Guo, Y.S. Chen, Adv. Funct. Mater. 19, 2297 (2009)D. Salinas-Torres, F. Huerta, F. Montilla, E. Morallón, Electrochim. Acta 56, 2464 (2011)Z.F. Ren, Z.P. Huang, J.W. Xu, J.H. Wang, P. Bush, M.P. Siegal, P.N. Provencio, Science 282, 1105 (1998)W.Z. Li, S.S. Xie, L.X. Qian, B.H. Chang, B.S. Zou, W.Y. Zhou, R.A. Zhao, G. Wang, Science 274, 1701 (1996)M. Terrones, N. Grobert, J. Olivares, J.P. Zhang, H. Terrones, K. Kordatos, W.K. Hsu, J.P. Hare, P.D. Townsend, K. Prassides, A.K. Cheetham, H.W. Kroto, D.R.M. Walton, Nature 388, 52 (1997)R. Toledano, D. Mandler, Chem. Mater. 22, 3943 (2010)J.H. Rouse, Langmuir 21, 1055 (2005)X.B. Yan, B.K. Tay, Y. Yang, Journal of Physical Chemistry B 110, 25844 (2006)J. Lim, P. Malati, F. Bonet, B. Dunn, J. Electrochem. Soc. 154, A140 (2007)L.D. Zhu, C.Y. Tian, J.L. Zhai, R.L. Yang, Sensors and Actuators B-Chemical 125, 254 (2007)F. Montilla, M.A. Cotarelo, E. Morallón, J. Mater. Chem. 19, 305 (2009)D. Salinas-Torres, F. Montilla, F. Huerta, E. Morallón, Electrochim. Acta 56, 3620 (2011)T. Dobbins, R. Chevious, Y. Lvov, Polymers 3, 942 (2011)R. Esquembre, J.A. Poveda, C.R. Mateo, Journal of Physical Chemistry B 113, 7534 (2009)M.L. Ferrer, R. Esquembre, I. Ortega, C.R. Mateo, F. del Monte, Chem. Mater. 18, 554 (2006)M.J. O'Connell, S. Sivaram, S.K. Doorn, Physical Review B 69, 235415 (2004)C. Domingo, G. Santoro, Opt. Pura Apl 40, 175 (2007)M.S. Dresselhaus, G. Dresselhaus, R. Saito, A. Jorio, Physics Reports 409, 47 (2005)R.L. McCreery, Chem. Rev. 108, 2646 (2008)C.G. Zoski, in Handbook of Electrochemistry, 1st ed (Elsevier, Amsterdam, 2007

Discovery of a Long-Lived, High Amplitude Dusty Infrared Transient

This article has been accepted for publication in Monthly Notices of the Royal Astronomical Society. ©: 2016 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved.We report the detection of an infrared selected transient which has lasted at least 5 years, first identified by a large mid-infrared and optical outburst from a faint X-ray source detected with the Chandra X-ray Observatory. In this paper we rule out several scenarios for the cause of this outburst, including a classical nova, a luminous red nova, AGN flaring, a stellar merger, and intermediate luminosity optical transients, and interpret this transient as the result of a Young Stellar Object (YSO) of at least solar mass accreting material from the remains of the dusty envelope from which it formed, in isolation from either a dense complex of cold gas or massive star formation. This object does not fit neatly into other existing categories of large outbursts of YSOs (FU Orionis types) which may be a result of the object's mass, age, and environment. It is also possible that this object is a new type of transient unrelated to YSOs.Peer reviewedFinal Published versio

COVID-19 publications: Database coverage, citations, readers, tweets, news, Facebook walls, Reddit posts

© 2020 The Authors. Published by MIT Press. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1162/qss_a_00066The COVID-19 pandemic requires a fast response from researchers to help address biological, medical and public health issues to minimize its impact. In this rapidly evolving context, scholars, professionals and the public may need to quickly identify important new studies. In response, this paper assesses the coverage of scholarly databases and impact indicators during 21 March to 18 April 2020. The rapidly increasing volume of research, is particularly accessible through Dimensions, and less through Scopus, the Web of Science, and PubMed. Google Scholar’s results included many false matches. A few COVID-19 papers from the 21,395 in Dimensions were already highly cited, with substantial news and social media attention. For this topic, in contrast to previous studies, there seems to be a high degree of convergence between articles shared in the social web and citation counts, at least in the short term. In particular, articles that are extensively tweeted on the day first indexed are likely to be highly read and relatively highly cited three weeks later. Researchers needing wide scope literature searches (rather than health focused PubMed or medRxiv searches) should start with Dimensions (or Google Scholar) and can use tweet and Mendeley reader counts as indicators of likely importance

Leaf-level photosynthetic capacity in lowland Amazonian and high elevation, Andean tropical moist forests of Peru

We examined whether variations in photosynthetic capacity are linked to variations in theenvironment and/or associated leaf traits for tropical moist forests (TMFs) in the Andes/west-ern Amazon regions of Peru. We compared photosynthetic capacity (maximal rate of carboxylation of Rubisco (Vcmax),and the maximum rate of electron transport (Jmax)), leaf mass, nitrogen (N) and phosphorus(P) per unit leaf area (Ma,Naand Pa, respectively), and chlorophyll from 210 species at 18field sites along a 3300-m elevation gradient. Western blots were used to quantify the abun-dance of the CO₂-fixing enzyme Rubisco. Area- and N-based rates of photosynthetic capacity at 25°C were higher in upland than low-land TMFs, underpinned by greater investment of N in photosynthesis in high-elevation trees. Soil [P] and leaf Pa were key explanatory factors for models of area-based Vcmax and Jmax but did not account for variations in photosynthetic N-use efficiency. At any given Na and Pa, the fraction of N allocated to photosynthesis was higher in upland than lowland species. For a smallsubset of lowland TMF trees examined, a substantial fraction of Rubisco was inactive. These results highlight the importance of soil- and leaf-P in defining the photosyntheticcapacity of TMFs, with variations in N allocation and Rubisco activation state further influenc-ing photosynthetic rates and N-use efficiency of these critically important forests

Mathematical properties of weighted impact factors based on measures of prestige of the citing journals

The final publication is available at Springer via http://dx.doi.org/10.1007/s11192-015-1741-0An abstract construction for general weighted impact factors is introduced. We show that the classical weighted impact factors are particular cases of our model, but it can also be used for defining new impact measuring tools for other sources of information as repositories of datasets providing the mathematical support for a new family of altmet- rics. Our aim is to show the main mathematical properties of this class of impact measuring tools, that hold as consequences of their mathematical structure and does not depend on the definition of any given index nowadays in use. In order to show the power of our approach in a well-known setting, we apply our construction to analyze the stability of the ordering induced in a list of journals by the 2-year impact factor (IF2). We study the change of this ordering when the criterium to define it is given by the numerical value of a new weighted impact factor, in which IF2 is used for defining the weights. We prove that, if we assume that the weight associated to a citing journal increases with its IF2, then the ordering given in the list by the new weighted impact factor coincides with the order defined by the IF2. We give a quantitative bound for the errors committed. We also show two examples of weighted impact factors defined by weights associated to the prestige of the citing journal for the fields of MATHEMATICS and MEDICINE, GENERAL AND INTERNAL, checking if they satisfy the increasing behavior mentioned above.Ferrer Sapena, A.; Sánchez Pérez, EA.; González, LM.; Peset Mancebo, MF.; Aleixandre Benavent, R. (2015). Mathematical properties of weighted impact factors based on measures of prestige of the citing journals. Scientometrics. 105(3):2089-2108. https://doi.org/10.1007/s11192-015-1741-0S208921081053Ahlgren, P., & Waltman, L. (2014). The correlation between citation-based and expert-based assessments of publication channels: SNIP and SJR vs. Norwegian quality assessments. Journal of Informetrics, 8, 985–996.Aleixandre Benavent, R., Valderrama Zurián, J. C., & González Alcaide, G. (2007). Scientific journals impact factor: Limitations and alternative indicators. El Profesional de la Información, 16(1), 4–11.Altmann, K. G., & Gorman, G. E. (1998). The usefulness of impact factor in serial selection: A rank and mean analysis using ecology journals. Library Acquisitions-Practise and Theory, 22, 147–159.Arnold, D. N., & Fowler, K. K. (2011). Nefarious numbers. Notices of the American Mathematical Society, 58(3), 434–437.Beliakov, G., & James, S. (2012). Using linear programming for weights identification of generalized bonferroni means in R. In: Proceedings of MDAI 2012 modeling decisions for artificial intelligence. Lecture Notes in Computer Science, Vol. 7647, pp. 35–44.Beliakov, G., & James, S. (2011). Citation-based journal ranks: The use of fuzzy measures. Fuzzy Sets and Systems, 167, 101–119.Buela-Casal, G. (2003). Evaluating quality of articles and scientific journals. Proposal of weighted impact factor and a quality index. Psicothema, 15(1), 23–25.Dorta-Gonzalez, P., & Dorta-Gonzalez, M. I. (2013). Comparing journals from different fields of science and social science through a JCR subject categories normalized impact factor. Scientometrics, 95(2), 645–672.Dorta-Gonzalez, P., Dorta-Gonzalez, M. I., Santos-Penate, D. R., & Suarez-Vega, R. (2014). Journal topic citation potential and between-field comparisons: The topic normalized impact factor. Journal of Informetrics, 8(2), 406–418.Egghe, L., & Rousseau, R. (2002). A general frame-work for relative impact indicators. Canadian Journal of Information and Library Science, 27(1), 29–48.Gagolewski, M., & Mesiar, R. (2014). Monotone measures and universal integrals in a uniform framework for the scientific impact assessment problem. Information Sciences, 263, 166–174.Garfield, E. (2006). The history and meaning of the journal impact factor. JAMA, 295(1), 90–93.Habibzadeh, F., & Yadollahie, M. (2008). Journal weighted impact factor: A proposal. Journal of Informetrics, 2(2), 164–172.Klement, E., Mesiar, R., & Pap, E. (2010). A universal integral as common frame for Choquet and Sugeno integral. IEEE Transaction on Fuzzy System, 18, 178–187.Leydesdorff, L., & Opthof, T. (2010). Scopus’s source normalized impact per paper (SNIP) versus a journal impact factor based on fractional counting of citations. Journal of the American Society for Information Science and Technology, 61, 2365–2369.Li, Y. R., Radicchi, F., Castellano, C., & Ruiz-Castillo, J. (2013). Quantitative evaluation of alternative field normalization procedures. Journal of Informetrics, 7(3), 746–755.Moed, H. F. (2010). Measuring contextual citation impact of scientific journals. Journal of Informetrics, 4, 265–277.NISO. (2014). Alternative metrics initiative phase 1. White paper. http://www.niso.org/apps/group-public/download.php/13809/Altmetrics-project-phase1-white-paperOwlia, P., Vasei, M., Goliaei, B., & Nassiri, I. (2011). Normalized impact factor (NIF): An adjusted method for calculating the citation rate of biomedical journals. Journal of Biomedical Informatics, 44(2), 216–220.Pinski, G., & Narin, F. (1976). Citation influence for journal aggregates of scientific publications: Theory, with application to the literature of physics. Information Processing and Management, 12, 297–312.Pinto, A. C., & Andrade, J. B. (1999). Impact factor of scientific journals: What is the meaning of this parameter? Quimica Nova, 22, 448–453.Raghunathan, M. S., & Srinivas, V. (2001). Significance of impact factor with regard to mathematics journals. Current Science, 80(5), 605.Ruiz Castillo, J., & Waltman, L. (2015). Field-normalized citation impact indicators using algorithmically constructed classification systems of science. Journal of Informetrics, 9, 102–117.Saha, S., Saint, S., & Christakis, D. A. (2003). Impact factor: A valid measure of journal quality? Journal of the Medical Library Association, 91, 42–46.Torra, V., & Narukawa, Y. (2008). The h-index and the number of citations: Two fuzzy integrals. IEEE Transaction on Fuzzy System, 16, 795–797.Torres-Salinas, D., & Jimenez-Contreras, E. (2010). Introduction and comparative study of the new scientific journals citation indicators in journal citation reports and scopus. El Profesional de la Información, 19, 201–207.Waltman, L., & van Eck, N. J. (2008). Some comments on the journal weighted impact factor proposed by Habibzadeh and Yadollahie. Journal of Informetrics, 2(4), 369–372.Waltman, L., van Eck, N. J., van Leeuwen, T. N., & Visser, M. S. (2013). Some modifications to the SNIP journal impact indicator. Journal of Informetrics, 7, 272–285.Zitt, M. (2011). Behind citing-side normalization of citations: some properties of the journal impact factor. Scientometrics, 89, 329–344.Zitt, M., & Small, H. (2008). Modifying the journal impact factor by fractional citation weighting: The audience factor. Journal of the American Society for Information Science and Technology, 59, 1856–1860.Zyczkowski, K. (2010). Citation graph, weighted impact factors and performance indices. Scientometrics, 85(1), 301–315

ATL9, a RING Zinc Finger Protein with E3 Ubiquitin Ligase Activity Implicated in Chitin- and NADPH Oxidase-Mediated Defense Responses

Pathogen associated molecular patterns (PAMPs) are signals detected by plants that activate basal defenses. One of these PAMPs is chitin, a carbohydrate present in the cell walls of fungi and in insect exoskeletons. Previous work has shown that chitin treatment of Arabidopsis thaliana induced defense-related genes in the absence of a pathogen and that the response was independent of the salicylic acid (SA), jasmonic acid (JA) and ethylene (ET) signaling pathways. One of these genes is ATL9 ( = ATL2G), which encodes a RING zinc-finger like protein. In the current work we demonstrate that ATL9 has E3 ubiquitin ligase activity and is localized to the endoplasmic reticulum. The expression pattern of ATL9 is positively correlated with basal defense responses against Golovinomyces cichoracearum, a biotrophic fungal pathogen. The basal levels of expression and the induction of ATL9 by chitin, in wild type plants, depends on the activity of NADPH oxidases suggesting that chitin-mediated defense response is NADPH oxidase dependent. Although ATL9 expression is not induced by treatment with known defense hormones (SA, JA or ET), full expression in response to chitin is compromised slightly in mutants where ET- or SA-dependent signaling is suppressed. Microarray analysis of the atl9 mutant revealed candidate genes that appear to act downstream of ATL9 in chitin-mediated defenses. These results hint at the complexity of chitin-mediated signaling and the potential interplay between elicitor-mediated signaling, signaling via known defense pathways and the oxidative burst