Core-periphery or decentralized? Topological shifts of specialized information on Twitter

In this paper we investigate shifts in Twitter network topology resulting from the type of information being shared. We identified communities matching areas of agricultural expertise and measured the core-periphery centralization of network formations resulting from users sharing generic versus specialized information. We found that centralization increases when specialized information is shared and that the network adopts decentralized formations as conversations become more generic. The results are consistent with classical diffusion models positing that specialized information comes with greater centralization, but they also show that users favor decentralized formations, which can foster community cohesion, when spreading specialized information is secondary

Growers’ risk perception and trust in control options for huanglongbing citrus-disease in Florida and California

Citrus huanglongbing disease is an acute bacterial disease that threatens the sustainability of citrus production across the world. In the USA, the Asian Citrus Psyllid (ACP) is responsible for spreading the disease. Successful suppression of HLB requires action against ACP at large spatial scales, i.e. growers must cooperate. In Florida and California, the regions in which citrus is grown have been split into management areas and growers are encouraged to coordinate spraying of insecticide across these (area-wide control). We surveyed growers from Florida and California to assess the consensus of opinions concerning issues that influence HLB management. Our results show that risk perception and trust in control options are central to the decision by growers on whether to join an area-wide control program. Growers’ perceptions on risk and control efficacy are influenced by information networks and observations about the state of the epidemic and psyllid populations. Researchers and extension agents were reported to have the largest influence on these perceptions. Differences in opinion between California and Florida growers as to the efficacy of treatments were largely a function of experience. A large proportion of growers identified failure of participation as a reason why participation in area-wide control might not occur

Information graphs for binary predictors

Binary predictors are used in a wide range of crop protection decision-making applications. Such predictors provide a simple analytical apparatus for the formulation of evidence related to risk factors, for use in the process of Bayesian updating of probabilities of crop disease. For diagrammatic interpretation of diagnostic probabilities, the receiver operating characteristic is available. Here, we view binary predictors from the perspective of diagnostic information. After a brief introduction to the basic information theoretic concepts of entropy and expected mutual information, we use an example data set to provide diagrammatic interpretations of expected mutual information, relative entropy, information inaccuracy, information updating, and specific information. Our information graphs also illustrate correspondences between diagnostic information and diagnostic probabilities. </jats:p

Protease-activated receptor 2 sensitizes the capsaicin receptor transient receptor potential vanilloid receptor 1 to induce hyperalgesia

Inflammatory proteases (mast cell tryptase and trypsins) cleave protease-activated receptor 2 (PAR2) on spinal afferent neurons and cause persistent inflammation and hyperalgesia by unknown mechanisms. We determined whether transient receptor potential vanilloid receptor 1 (TRPV1), a cation channel activated by capsaicin, protons, and noxious heat, mediates PAR2-induced hyperalgesia. PAR2 was coexpressed with TRPV1 in small- to medium-diameter neurons of the dorsal root ganglia (DRG), as determined by immunofluorescence. PAR2 agonists increased intracellular [Ca2+] ([Ca2+]i) in these neurons in culture, and PAR2-responsive neurons also responded to the TRPV1 agonist capsaicin, confirming coexpression of PAR2 and TRPV1. PAR2 agonists potentiated capsaicin-induced increases in [Ca2+]i in TRPV1-transfected human embryonic kidney (HEK) cells and DRG neurons and potentiated capsaicin-induced currents in DRG neurons. Inhibitors of phospholipase C and protein kinase C (PKC) suppressed PAR2-induced sensitization of TRPV1-mediated changes in [Ca2+]i and TRPV1 currents. Activation of PAR2 or PKC induced phosphorylation of TRPV1 in HEK cells, suggesting a direct regulation of the channel. Intraplantar injection of a PAR2 agonist caused persistent thermal hyperalgesia that was prevented by antagonism or deletion of TRPV1. Coinjection of nonhyperalgesic doses of PAR2 agonist and capsaicin induced hyperalgesia that was inhibited by deletion of TRPV1 or antagonism of PKC. PAR2 activation also potentiated capsaicin-induced release of substance P and calcitonin gene-related peptide from superfused segments of the dorsal horn of the spinal cord, where they mediate hyperalgesia. We have identified a novel mechanism by which proteases that activate PAR2 sensitize TRPV1 through PKC. Antagonism of PAR2, TRPV1, or PKC may abrogate protease-induced thermal hyperalgesia

The Importance of Consistent Global Forest Aboveground Biomass Product Validation

Several upcoming satellite missions have core science requirements to produce data for accurate forest aboveground biomass mapping. Largely because of these mission datasets, the number of available biomass products is expected to greatly increase over the coming decade. Despite the recognized importance of biomass mapping for a wide range of science, policy and management applications, there remains no community accepted standard for satellite-based biomass map validation. The Committee on Earth Observing Satellites (CEOS) is developing a protocol to fill this need in advance of the next generation of biomass-relevant satellites, and this paper presents a review of biomass validation practices from a CEOS perspective. We outline the wide range of anticipated user requirements for product accuracy assessment and provide recommendations for the validation of biomass products. These recommendations include the collection of new, high-quality in situ data and the use of airborne lidar biomass maps as tools toward transparent multi-resolution validation. Adoption of community-vetted validation standards and practices will facilitate the uptake of the next generation of biomass products

Bio-chronostratigraphic calibration of the Upper Carnian-Lower Norian magnetostratigraphic scale at Pizzo Mondello (Sicani Mountains, Sicily).

Pizzo Mondello section is known since 15 years because of the continuous Late Triassic pelagic record of great significance for the establishment of an integrated chronostratigraphy of the Late Triassic (Gullo et al. 1996; Muttoni et al. 2001, 2004). During the last 4 years, Pizzo Mondello section has been studied in detail to provide a new and high resolution integrated bio-chronostratigraphy for the calibration of the magnetostratigraphy and chemostratigraphy proposed by Muttoni et al. (2001, 2004), and now it is one of the GSSP candidates for the definition of the base of the Norian. The lowest 143 m of the Cherty Limestone, straddling the C/N boundary have been studied in detail. The preliminary data of the ongoing research have been presented in all the meetings of the STS from Albuquerque 2007 and here we summarize the final results. The key correlation to the standard marine Triassic Scale is provided by the ammonoids. They are relatively rare, however the available collections document the Upper Carnian Discotropites plinii and Gonionotites italicus Subzones, from meter 15 to meter 80 from the base of the section. The following 15 meters are poor in ammonoids, while higher up the lower part of the Lower Norian Guembelites jandianus Zone is documented by Dimorphites cf. n. sp.1 of Krystyn, 1980. Conodonts are very abundant and have a great potential as practical tool for global correlations. The abundance of specimens at Pizzo Mondello gave the opportunity to point out clear relationships among the five most widespread Upper Camian/Lower Norian conodont genera (Paragondolella, Carnepigondolella, Metapolygnathus, Epigondolella and Norigondolella) and to identify trends of the generic turnovers (Mazza et al. 2010). The two biomarkers so far proposed as possible marker events for the GSSP were the FAD of E. quadrata (sample FNP88A) and the FAD of M. communisti (sample NA35). However, the FAD of E. quadrata occurs within the Gonionotites italicus Subzone, while the FAD of M. communisti is on its top. Halobiids are extremely common in the Cherty Limestone and they have also a great potential for large scale correlations. Nine species of Halobia have been recognized: Halobia carnica, H. lenticularis, H. simplex, H. superba, H. cf. rugosa, H. radiata, H. austriaca, H. styriaca and H. mediterranea. The best possible marker for the base of the Norian is the first occurrence of Halobia austriaca, that is recorded in the middle of the interval between the record of the Gonionotites italicus Subzone and the Guembelites jandianus Zone. Radiolarians were found in few samples but with high diversity assemblages. In the upper Gonionotites italicus Subzone to the Guembelites jandianus Zone there is an overlap of species previously considered Late Carnian with species usually regarded as Early Norian. About 4 m above the FAD of E. quadrata, in the Gonionotites italicus Subzone, the first assemblage with Capnuchosphaera deweveri Kozur & Mostler, Capnuchosphaera tricornis De Wever, Kahlerosphaera norica Kozur & Mock and Xiphothecaella longa Kozur & Mock, usually referred to Early Norian, occurs. These integrated bio-chronostratigraphic studies lead to identify some possible GSSP marker events especially on conodonts and halobiids, which occur in the upper part of magnetozone PM 4n, within PM 4r and in the lower part of PM 5n. Possibly the most suitable magnetostratigraphic event to recognize the basal Norian is the base of magnetozone PM 5n, as already suggested by Krystyn et al. 2002 and Muttoni et al. 2004

Dynamic liquefaction of shear zones in intact loess during simulated earthquake loading

The 2010-2011 Canterbury earthquake sequence in New Zealand exposed loess-mantled slopes in the area to very high levels of seismic excitation (locally measured as >2 g). Few loess slopes showed permanent local downslope deformation, and most of these showed only limited accumulated displacement. A series of innovative dynamic back pressured shear-box tests were undertaken on intact and remoulded loess samples collected from one of the recently active slopes replicating field conditions under different simplified horizontal seismic excitations. During each test, the strength reduction and excess pore water pressures generated were measured as the sample failed. Test results suggest that although dynamic liquefaction could have occurred, a key factor was likely to have been that the loess was largely unsaturated at the times of the large earthquake events. The failure of intact loess samples in the tests was complex and variable due to the highly variable geotechnical characteristics of the material. Some loess samples failed rapidly as a result of dynamic liquefaction as seismic excitation generated an increase in pore-water pressure, triggering rapid loss of strength and thus of shear resistance. Following initial failure, pore pressure dissipated with continued seismic excitation and the sample consolidated, resulting in partial shear-strength recovery. Once excess pore-water pressures had dissipated, deformation continued in a critical effective stress state with no further change in volume. Remoulded and weaker samples, however, did not liquefy, and instead immediately reduced in volume with an accompanying slower and more sustained increase in pore pressure as the sample consolidated. Thereafter excess pressures dissipated and deformation continued at a critical state. The complex behaviour explained why, despite exceptionally strong ground shaking, there was only limited displacement and lack of run-out: dynamic liquefaction was unlikely to occur in the freely draining slopes. Dynamic liquefaction however remained a plausible mechanism to explain loess failure in some of the low-angle toe slopes, where a permanent water table was present in the loess

A Synoptical Classification of the Bivalvia (Mollusca)

The following classification summarizes the suprageneric taxono-my of the Bivalvia for the upcoming revision of the Bivalvia volumes of the Treatise on Invertebrate Paleontology, Part N. The development of this classification began with Carter (1990a), Campbell, Hoeks-tra, and Carter (1995, 1998), Campbell (2000, 2003), and Carter, Campbell, and Campbell (2000, 2006), who, with assistance from the United States National Science Foundation, conducted large-scale morphological phylogenetic analyses of mostly Paleozoic bivalves, as well as molecular phylogenetic analyses of living bivalves. Dur-ing the past several years, their initial phylogenetic framework has been revised and greatly expanded through collaboration with many students of bivalve biology and paleontology, many of whom are coauthors. During this process, all available sources of phylogenetic information, including molecular, anatomical, shell morphological, shell microstructural, bio- and paleobiogeographic as well as strati-graphic, have been integrated into the classification. The more recent sources of phylogenetic information include, but are not limited to, Carter (1990a), Malchus (1990), J. Schneider (1995, 1998a, 1998b, 2002), T. Waller (1998), Hautmann (1999, 2001a, 2001b), Giribet and Wheeler (2002), Giribet and Distel (2003), Dreyer, Steiner, and Harper (2003), Matsumoto (2003), Harper, Dreyer, and Steiner (2006), Kappner and Bieler (2006), Mikkelsen and others (2006), Neulinger and others (2006), Taylor and Glover (2006), Kříž (2007), B. Morton (2007), Taylor, Williams, and Glover (2007), Taylor and others (2007), Giribet (2008), and Kirkendale (2009). This work has also benefited from the nomenclator of bivalve families by Bouchet and Rocroi (2010) and its accompanying classification by Bieler, Carter, and Coan (2010).This classification strives to indicate the most likely phylogenetic position for each taxon. Uncertainty is indicated by a question mark before the name of the taxon. Many of the higher taxa continue to undergo major taxonomic revision. This is especially true for the superfamilies Sphaerioidea and Veneroidea, and the orders Pectinida and Unionida. Because of this state of flux, some parts of the clas-sification represent a compromise between opposing points of view. Placement of the Trigonioidoidea is especially problematic. This Mesozoic superfamily has traditionally been placed in the order Unionida, as a possible derivative of the superfamily Unionoidea (see Cox, 1952; Sha, 1992, 1993; Gu, 1998; Guo, 1998; Bieler, Carter, & Coan, 2010). However, Chen Jin-hua (2009) summarized evi-dence that Trigonioidoidea was derived instead from the superfamily Trigonioidea. Arguments for these alternatives appear equally strong, so we presently list the Trigonioidoidea, with question, under both the Trigoniida and Unionida, with the contents of the superfamily indicated under the Trigoniida.Fil: Carter, Joseph G.. University of North Carolina; Estados UnidosFil: Altaba, Cristian R.. Universidad de las Islas Baleares; EspañaFil: Anderson, Laurie C.. South Dakota School of Mines and Technology; Estados UnidosFil: Araujo, Rafael. Consejo Superior de Investigaciones Cientificas. Museo Nacional de Ciencias Naturales; EspañaFil: Biakov, Alexander S.. Russian Academy of Sciences; RusiaFil: Bogan, Arthur E.. North Carolina State Museum of Natural Sciences; Estados UnidosFil: Campbell, David. Paleontological Research Institution; Estados UnidosFil: Campbell, Matthew. Charleston Southern University; Estados UnidosFil: Chen, Jin Hua. Chinese Academy of Sciences. Nanjing Institute of Geology and Palaeontology; República de ChinaFil: Cope, John C. W.. National Museum of Wales. Department of Geology; Reino UnidoFil: Delvene, Graciela. Instituto Geológico y Minero de España; EspañaFil: Dijkstra, Henk H.. Netherlands Centre for Biodiversity; Países BajosFil: Fang, Zong Jie. Chinese Academy of Sciences; República de ChinaFil: Gardner, Ronald N.. No especifica;Fil: Gavrilova, Vera A.. Russian Geological Research Institute; RusiaFil: Goncharova, Irina A.. Russian Academy of Sciences; RusiaFil: Harries, Peter J.. University of South Florida; Estados UnidosFil: Hartman, Joseph H.. University of North Dakota; Estados UnidosFil: Hautmann, Michael. Paläontologisches Institut und Museum; SuizaFil: Hoeh, Walter R.. Kent State University; Estados UnidosFil: Hylleberg, Jorgen. Institute of Biology; DinamarcaFil: Jiang, Bao Yu. Nanjing University; República de ChinaFil: Johnston, Paul. Mount Royal University; CanadáFil: Kirkendale, Lisa. University Of Wollongong; AustraliaFil: Kleemann, Karl. Universidad de Viena; AustriaFil: Koppka, Jens. Office de la Culture. Section d’Archéologie et Paléontologie; SuizaFil: Kříž, Jiří. Czech Geological Survey. Department of Sedimentary Formations. Lower Palaeozoic Section; República ChecaFil: Machado, Deusana. Universidade Federal do Rio de Janeiro; BrasilFil: Malchus, Nikolaus. Institut Català de Paleontologia; EspañaFil: Márquez Aliaga, Ana. Universidad de Valencia; EspañaFil: Masse, Jean Pierre. Universite de Provence; FranciaFil: McRoberts, Christopher A.. State University of New York at Cortland. Department of Geology; Estados UnidosFil: Middelfart, Peter U.. Australian Museum; AustraliaFil: Mitchell, Simon. The University of the West Indies at Mona; JamaicaFil: Nevesskaja, Lidiya A.. Russian Academy of Sciences; RusiaFil: Özer, Sacit. Dokuz Eylül University; TurquíaFil: Pojeta, John Jr.. National Museum of Natural History; Estados UnidosFil: Polubotko, Inga V.. Russian Geological Research Institute; RusiaFil: Pons, Jose Maria. Universitat Autònoma de Barcelona; EspañaFil: Popov, Sergey. Russian Academy of Sciences; RusiaFil: Sanchez, Teresa Maria. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Córdoba; ArgentinaFil: Sartori, André F.. Field Museum of National History; Estados UnidosFil: Scott, Robert W.. Precision Stratigraphy Associates; Estados UnidosFil: Sey, Irina I.. Russian Geological Research Institute; RusiaFil: Signorelli, Javier Hernan. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico; ArgentinaFil: Silantiev, Vladimir V.. Kazan Federal University; RusiaFil: Skelton, Peter W.. Open University. Department of Earth and Environmental Sciences; Reino UnidoFil: Steuber, Thomas. The Petroleum Institute; Emiratos Arabes UnidosFil: Waterhouse, J. Bruce. No especifica;Fil: Wingard, G. Lynn. United States Geological Survey; Estados UnidosFil: Yancey, Thomas. Texas A&M University; Estados Unido