Análisis comparativo entre métodos empíricos para el cálculo de la evapotranspiración de referencia en la Región de Tumbes

La evapotranspiración es un factor importante en el desarrollo de Proyectos Ambientales, hidráulicos e hidrológicos, que se relacionan con la gestión del recurso hídrico. Debido a tal importancia es necesario realizar una correcta estimación de este parámetro. En el año 1990, una reunión de expertos convocada por la FAO, acordó utilizar el método FAO Penman-Monteith, como modelo estándar para calcular la Evapotranspiración de referencia, aun así, requiere de información climática, que no siempre están al alcance, por lo que su aplicación se ve restringida. El objetivo de este trabajo es comparar los resultados obtenidos con 8 métodos empíricos simples, tomando como referencia el método estándar FAO Penman-Monteith, utilizando datos meteorológicos mensuales desde el año 2007 al 2020 de la Estación Tumpis. La evaluación del desempeño se realizó mediante los índices estadísticos: error cuadrático medio, error porcentual, coeficiente de correlación de Pearson, índice de concordancia y coeficiente de confiabilidad. Los resultados muestran que el método de Linacre obtiene en desempeño bueno, obteniendo el valor de confiabilidad más alto. Es por ello que se escoge este método para aplicarlo a 6 estaciones SENAMHI, que disponen de datos climáticos limitados del periodo 2015 - 2020, para realizar una interpolación y obtener la representación gráfica de la distribución mensual de la evapotranspiración de referencia en la región de Tumbes

Propuesta de una estructura de costos para la empresa de Calzado ZAFEVI, ubicada en la ciudad de Trujillo, en el año 2008

para la micro y pequeña empresa industrial de fabricación de calzado, específicamente para la empresa de calzado ZAFEVI, ubicada en la ciudad de Trujillo, departamento de La Libertad. Actualmente la mayoría de micro y pequeños empresarios fabricantes de calzado no tienen definido la importancia de contar con una estructura de costos que le permita disponer de información precisa respecto al costo de producción de sus productos, y por ende el costo unitario de dicho producto. Nuestro trabajo tiene como propósito principal dar a conocer la importancia de una estructura de costos en las micro y pequeñas empresas industriales, para llevar a cabo esta investigación fue preciso indagar sobre las distintas etapas del proceso de fabricación para lo cual se diseñaron instrumentos aplicados en la recolección de la información tales como entrevistas y encuestas. Esperamos que éste estudio sirva de apoyo fundamental para la implantación de la estructura de costos de la empresa de calzado ZAFEVI, que le permita identificar, reducir o eliminar en lo posible las actividades que no agregan valor al proceso productivo y como tal sirva de base para la toma de decisiones del propietario. La identificación de los costos de fabricación representa un gran reto para todas las empresas de calzado dado que éste sector de la economía de la zona norte del país se considera fundamental para el desarrollo económico social, es por eso que los fabricantes de calzado deben tomar medidas para mantenerse en mercados altamente competitivos. La investigación esta estructurada de la siguiente manera: En el primer capítulo presentamos el marco metodológico, en el segundo capítulo se encuentran los marcos referenciales teóricos, normativos y filosóficos que sustentan nuestra investigación, en el tercer capítulo se detalla la investigación de campo realizada y en el cuarto capítulo la propuesta de la estructura de costos para la empresa. También presentamos las conclusiones y recomendaciones

Comparison of the confidence in freedom from infection based on different control programmes between EU member states: STOC free

The STOC free project constructed a generic framework that allows a standardised and harmonised description of different control programmes (CP) for cattle diseases. The STOC free model can be used to determine the confidence of freedom from infection that has been achieved in disease CPs, in support of an ongoing assessment of progress towards output-based standards as outlined in the EU Animal Health Law. With this information, and as required, further CP actions can be taken to mitigate the risks of persistence and (re-)introduction on the probability of freedom from infection. Bovine viral diarrhoea virus (BVDV) was chosen as the case disease because of the diversity in CPs in the six participating countries. A Bayesian hidden Markov model was considered the best modelling method. Detailed BVDVCP information was collected in the participating countries and the key aspects for inclusion in the STOCfree model were identified. A first version of STOC free model was developed and tested on simulated data. The risk factors for BVDV infection that needed to be included in the model were defined and default values for these risk factors were quantified. A data collection tool was finalised with which the data for the STOC free model was collected. Subsequently, the developed model was tested and validated using real BVDV CP data from partner countries. Based on the feedback, the model was finalised and the report and corresponding computer code were made publicly available. There were roughly three different BVDV situations that occurred in the partner countries: 1. Endemic situation with a CP operating at herd level, 2. Endemic situation with a CP operating at animal level and 3. BVD free situation. The STOC free model is able to include herd level data only and animal level data has to be aggregated to herd level before the model can be applied. The STOC free model is not applicable for a country that is completely BVDV free given that it needs some infections to estimate its parameters and converge. In the latter situation, a scenario tree model could be a better suited tool, and this was evaluated in the Swedish case study. Further work is needed for generalisation of the method to other diseases and expansion of the method to include socioeconomic aspects of CPs <br/

A modelling framework for the prediction of the herd-level probability of infection from longitudinal data

International audienceThe collective control programmes (CPs) that exist for many infectious diseases of farm animals rely on the application of diagnostic testing at regular time intervals for the identification of infected animals or herds. The diversity of these CPs complicates the trade of animals between regions or countries because the definition of freedom from infection differs from one CP to another. In this paper, we describe a statistical model for the prediction of herd-level probabilities of infection from longitudinal data collected as part of CPs against infectious diseases of cattle. The model was applied to data collected as part of a CP against bovine viral diarrhoea virus (BVDV) infection in Loire-Atlantique, France. The model represents infection as a herd latent status with a monthly dynamics. This latent status determines test results through test sensitivity and test specificity. The probability of becoming status positive between consecutive months is modelled as a function of risk factors (when available) using logistic regression. Modelling is performed in a Bayesian framework, using either Stan or JAGS. Prior distributions need to be provided for the sensitivities and specificities of the different tests used, for the probability of remaining status positive between months as well as for the probability of becoming positive between months. When risk factors are available, prior distributions need to be provided for the coefficients of the logistic regression, replacing the prior for the probability of becoming positive. From these prior distributions and from the longitudinal data, the model returns posterior probability distributions for being status positive for all herds on the current month. Data from the previous months are used for parameter estimation. The impact of using different prior distributions and model implementations on parameter estimation was evaluated. The main advantage of this model is its ability to predict a probability of being status positive in a month from inputs that can vary in terms of nature of test, frequency of testing and risk factor availability/presence. The main challenge in applying the model to the BVDV CP data was in identifying prior distributions, especially for test characteristics, that corresponded to the latent status of interest, i.e. herds with at least one persistently infected (PI) animal. The model is available on Github as an R package (https://github.com/AurMad/STOCfree) and can be used to carry out output-based evaluation of disease CPs

The Lost Library of Anne Conway

The philosopher Anne Conway (1631-1679) owned a large library, and her reading and book ownership shaped her intellectual life in distinctive ways. Until now, however, almost nothing has been known about the details of her reading or her book collection. Current scholarship assumes that her library, like that of her husband, the third Viscount Conway (c. 1623–1683), was lost or dispersed after her death. This article presents previously unrecognised evidence of Conway’s book ownership, and identifies, for the first time, the only books currently known to survive from her personal library. It traces their path to their current location in the Old Library of Jesus College, Cambridge, through the library of the soldier, book collector, and Cambridge Fellow Francis Sterling (c. 1652-1692). The article demonstrates that the newly identified books reveal previously unknown patterns of intellectual exchange amongst Conway’s family, and argues that they have significant implications for our understanding of her early intellectual development

Output-based assessment of herd-level freedom from infection in endemic situations:Application of a Bayesian Hidden Markov model

International audienceCountries have implemented control programmes (CPs) for cattle diseases such as bovine viral diarrhoea virus (BVDV) that are tailored to each country-specific situation. Practical methods are needed to assess the output of these CPs in terms of the confidence of freedom from infection that is achieved. As part of the STOC free project, a Bayesian Hidden Markov model was developed, called STOC free model, to estimate the probability of infection at herd-level. In the current study, the STOC free model was applied to BVDV field data in four study regions, from CPs based on ear notch samples. The aim of this study was to estimate the probability of herd-level freedom from BVDV in regions that are not (yet) free. We additionally evaluated the sensitivity of the parameter estimates and predicted probabilities of freedom to the prior distributions for the different model parameters. First, default priors were used in the model to enable comparison of model outputs between study regions. Thereafter, country-specific priors based on expert opinion or historical data were used in the model, to study the influence of the priors on the results and to obtain country-specific estimates.The STOC free model calculates a posterior value for the model parameters (e.g. herd-level test sensitivity and specificity, probability of introduction of infection) and a predicted probability of infection. The probability of freedom from infection was computed as one minus the probability of infection. For dairy herds that were considered free from infection within their own CP, the predicted probabilities of freedom were very high for all study regions ranging from 0.98 to 1.00, regardless of the use of default or country-specific priors. The priors did have more influence on two of the model parameters, herd-level sensitivity and the probability of remaining infected, due to the low prevalence and incidence of BVDV in the study regions. The advantage of STOC free model compared to scenario tree modelling, the reference method, is that actual data from the CP can be used and estimates are easily updated when new data becomes availabl

Modeling Galaxy-Galaxy Weak Lensing with SDSS Groups

We use galaxy groups selected from the Sloan Digital Sky Survey (SDSS) together with mass models for individual groups to study the galaxy-galaxy lensing signals expected from galaxies of different luminosities and morphological types. We compare our model predictions with the observational results obtained from the SDSS by Mandelbaum et al. (2006) for the same samples of galaxies. The observational results are well reproduced in a $\Lambda$CDM model based on the WMAP 3-year data, but a $\Lambda$CDM model with higher $\sigma_8$, such as the one based on the WMAP 1-year data,significantly over-predicts the galaxy-galaxy lensing signal. We model, separately, the contributions to the galaxy-galaxy lensing signals from different galaxies: central versus satellite, early-type versus late-type, and galaxies in halos of different masses. We also examine how the predicted galaxy-galaxy lensing signal depends on the shape, density profile, and the location of the central galaxy with respect to its host halo.Comment: 16 pages, 8 figures, accepted for publication on MNRA

Cluster Candidates around Low-power Radio Galaxies at z ~ 1-2 in COSMOS

We search for high-redshift (z ~1-2) galaxy clusters using low power radio galaxies (FR I) as beacons and our newly developed Poisson probability method based on photometric redshift information and galaxy number counts. We use a sample of 32 FR Is within the Cosmic Evolution Survey (COSMOS) field from the Chiaberge et al. catalog. We derive a reliable subsample of 21 bona fide low luminosity radio galaxies (LLRGs) and a subsample of 11 high luminosity radio galaxies (HLRGs), on the basis of photometric redshift information and NRAO VLA Sky Survey radio fluxes. The LLRGs are selected to have 1.4 GHz rest frame luminosities lower than the fiducial FR I/FR II divide. This also allows us to estimate the comoving space density of sources with L 1.4 ~= 1032.3 erg s-1 Hz-1 at z ~= 1.1, which strengthens the case for a strong cosmological evolution of these sources. In the fields of the LLRGs and HLRGs we find evidence that 14 and 8 of them reside in rich groups or galaxy clusters, respectively. Thus, overdensities are found around ~70% of the FR Is, independently of the considered subsample. This rate is in agreement with the fraction found for low redshift FR Is and it is significantly higher than that for FR IIs at all redshifts. Although our method is primarily introduced for the COSMOS survey, it may be applied to both present and future wide field surveys such as Sloan Digital Sky Survey Stripe 82, LSST, and Euclid. Furthermore, cluster candidates found with our method are excellent targets for next generation space telescopes such as James Webb Space Telescope