NIGER-DELTA: ENVIRONMENT, OGONI CRISIS AND THE STATE

Among the well agreed-on benefits of a guideline computerisation, with respect to the traditional text format, there are the disambiguation, the possibility of looking at the guideline at different levels of detail and the possibility of generating patient-tailored suggestions. Nevertheless, the connection of guidelines with patient records is still a challenging problem, as well as their effective integration into the clinical workflow. In this paper, we describe the evolution of our environment for representing and running guidelines. The main new features concern the choice of a commercial product as the middle layer with the electronic patient record, the consequent possibility of gathering information from different legacy systems, and the extension of this "virtual medical record" to the storage of process data. This last feature allows managing exceptions, i.e. decisions that do not comply with guidelines

A mechanistic model of Botrytis cinerea on grapevines that includes weather, vine growth stage, and the main infection pathways

A mechanistic model for Botrytis cinerea on grapevine was developed. The model, which accounts for conidia production on various inoculum sources and for multiple infection pathways, considers two infection periods. During the first period (“inflorescences clearly visible” to “berries groat-sized”), the model calculates: i) infection severity on inflorescences and young clusters caused by conidia (SEV1). During the second period (“majority of berries touching” to “berries ripe for harvest”), the model calculates: ii) infection severity of ripening berries by conidia (SEV2); and iii) severity of berry-to-berry infection caused by mycelium (SEV3). The model was validated in 21 epidemics (vineyard × year combinations) between 2009 and 2014 in Italy and France. A discriminant function analysis (DFA) was used to: i) evaluate the ability of the model to predict mild, intermediate, and severe epidemics; and ii) assess how SEV1, SEV2, and SEV3 contribute to epidemics. The model correctly classified the severity of 17 of 21 epidemics. Results from DFA were also used to calculate the daily probabilities that an ongoing epidemic would be mild, intermediate, or severe. SEV1 was the most influential variable in discriminating between mild and intermediate epidemics, whereas SEV2 and SEV3 were relevant for discriminating between intermediate and severe epidemics. The model represents an improvement of previous B. cinerea models in viticulture and could be useful for making decisions about Botrytis bunch rot control

Development and validation of a weather-based model for predicting infection of loquat fruit by Fusicladium eriobotryae

A mechanistic, dynamic model was developed to predict infection of loquat fruit by conidia of Fusicladium eriobotryae, the causal agent of loquat scab. The model simulates scab infection periods and their severity through the sub-processes of spore dispersal, infection, and latency (i.e., the state variables); change from one state to the following one depends on environmental conditions and on processes described by mathematical equations. Equations were developed using published data on F. eriobotryae mycelium growth, conidial germination, infection, and conidial dispersion pattern. The model was then validated by comparing model output with three independent data sets. The model accurately predicts the occurrence and severity of infection periods as well as the progress of loquat scab incidence on fruit (with concordance correlation coefficients .0.95). Model output agreed with expert assessment of the disease severity in seven loquatgrowing seasons. Use of the model for scheduling fungicide applications in loquat orchards may help optimise scab management and reduce fungicide applications.This work was funded by Cooperativa Agricola de Callosa d'En Sarria (Alicante, Spain). Three months' stay of E. Gonzalez-Dominguez at the Universita Cattolica del Sacro Cuore (Piacenza, Italy) was supported by the Programa de Apoyo a la Investigacion y Desarrollo (PAID-00-12) de la Universidad Politecnica de Valencia. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.González Domínguez, E.; Armengol Fortí, J.; Rossi, V. (2014). Development and validation of a weather-based model for predicting infection of loquat fruit by Fusicladium eriobotryae. PLoS ONE. 9(9):1-12. https://doi.org/10.1371/journal.pone.0107547S11299Sánchez-Torres, P., Hinarejos, R., & Tuset, J. J. (2009). Characterization and Pathogenicity ofFusicladium eriobotryae, the Fungal Pathogen Responsible for Loquat Scab. Plant Disease, 93(11), 1151-1157. doi:10.1094/pdis-93-11-1151Gladieux, P., Caffier, V., Devaux, M., & Le Cam, B. (2010). Host-specific differentiation among populations of Venturia inaequalis causing scab on apple, pyracantha and loquat. Fungal Genetics and Biology, 47(6), 511-521. doi:10.1016/j.fgb.2009.12.007González-Domínguez, E., Rossi, V., Armengol, J., & García-Jiménez, J. (2013). Effect of Environmental Factors on Mycelial Growth and Conidial Germination ofFusicladium eriobotryae, and the Infection of Loquat Leaves. Plant Disease, 97(10), 1331-1338. doi:10.1094/pdis-02-13-0131-reGonzález-Domínguez, E., Rossi, V., Michereff, S. J., García-Jiménez, J., & Armengol, J. (2014). Dispersal of conidia of Fusicladium eriobotryae and spatial patterns of scab in loquat orchards in Spain. European Journal of Plant Pathology, 139(4), 849-861. doi:10.1007/s10658-014-0439-0Becker, C. M. (1994). Discontinuous Wetting and Survival of Conidia ofVenturia inaequalison Apple Leaves. Phytopathology, 84(4), 372. doi:10.1094/phyto-84-372Hartman, J. R., Parisi, L., & Bautrais, P. (1999). Effect of Leaf Wetness Duration, Temperature, and Conidial Inoculum Dose on Apple Scab Infections. Plant Disease, 83(6), 531-534. doi:10.1094/pdis.1999.83.6.531Holb, I. J., Heijne, B., Withagen, J. C. M., & Jeger, M. J. (2004). Dispersal of Venturia inaequalis Ascospores and Disease Gradients from a Defined Inoculum Source. Journal of Phytopathology, 152(11-12), 639-646. doi:10.1111/j.1439-0434.2004.00910.xRossi, V., Giosue, S., & Bugiani, R. (2003). Influence of Air Temperature on the Release of Ascospores of Venturia inaequalis. Journal of Phytopathology, 151(1), 50-58. doi:10.1046/j.1439-0434.2003.00680.xStensvand, A., Gadoury, D. M., Amundsen, T., Semb, L., & Seem, R. C. (1997). Ascospore Release and Infection of Apple Leaves by Conidia and Ascospores ofVenturia inaequalisat Low Temperatures. Phytopathology, 87(10), 1046-1053. doi:10.1094/phyto.1997.87.10.1046Machardy WE (1996) Apple scab. Biology, epidemiology and management. St. Paul: APS Press. 545.James, J. R. (1982). Environmental Factors Influencing Pseudothecial Development and Ascospore Maturation ofVenturia inaequalis. Phytopathology, 72(8), 1073. doi:10.1094/phyto-72-1073Li, B., Zhao, H., Li, B., & Xu, X.-M. (2003). Effects of temperature, relative humidity and duration of wetness period on germination and infection by conidia of the pear scab pathogen (Venturia nashicola). Plant Pathology, 52(5), 546-552. doi:10.1046/j.1365-3059.2003.00887.xLi, B.-H., Xu, X.-M., Li, J.-T., & Li, B.-D. (2005). Effects of temperature and continuous and interrupted wetness on the infection of pear leaves by conidia of Venturia nashicola. Plant Pathology, 54(3), 357-363. doi:10.1111/j.1365-3059.2005.01207.xUMEMOTO, S. 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Phytopathology, 72(10), 1339. doi:10.1094/phyto-72-1339MARZO, L., FRISULLO, S., LOPS, F., & ROSSI, V. (1993). Possible dissemination of Spilocaea oleagina conidia by insects (Ectopsocus briggsi). EPPO Bulletin, 23(3), 389-391. doi:10.1111/j.1365-2338.1993.tb01341.xLOPS, F., FRISULLO, S., & ROSSI, V. (1993). Studies on the spread of the olive scab pathogen, Spilocaea oleagina. EPPO Bulletin, 23(3), 385-387. doi:10.1111/j.1365-2338.1993.tb01340.xObanor, F. O., Walter, M., Jones, E. E., & Jaspers, M. V. (2007). Effect of temperature, relative humidity, leaf wetness and leaf age on Spilocaea oleagina conidium germination on olive leaves. European Journal of Plant Pathology, 120(3), 211-222. doi:10.1007/s10658-007-9209-6Obanor, F. O., Walter, M., Jones, E. E., & Jaspers, M. V. (2010). Effects of temperature, inoculum concentration, leaf age, and continuous and interrupted wetness on infection of olive plants by Spilocaea oleagina. Plant Pathology, 60(2), 190-199. doi:10.1111/j.1365-3059.2010.02370.xViruega, J. R., Moral, J., Roca, L. F., Navarro, N., & Trapero, A. (2013). Spilocaea oleaginain Olive Groves of Southern Spain: Survival, Inoculum Production, and Dispersal. Plant Disease, 97(12), 1549-1556. doi:10.1094/pdis-12-12-1206-reViruega, J. R., Roca, L. F., Moral, J., & Trapero, A. (2011). Factors Affecting Infection and Disease Development on Olive Leaves Inoculated withFusicladium oleagineum. Plant Disease, 95(9), 1139-1146. doi:10.1094/pdis-02-11-0126Eikemo, H., Gadoury, D. M., Spotts, R. A., Villalta, O., Creemers, P., Seem, R. C., & Stensvand, A. (2011). Evaluation of Six Models to Estimate Ascospore Maturation in Venturia pyrina. Plant Disease, 95(3), 279-284. doi:10.1094/pdis-02-10-0125Li, B.-H., Yang, J.-R., Dong, X.-L., Li, B.-D., & Xu, X.-M. (2007). A dynamic model forecasting infection of pear leaves by conidia of Venturia nashicola and its evaluation in unsprayed orchards. 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Relating UMLS semantic types and task-based ontology to computer-interpretable clinical practice guidelines, Proceedings of ,

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