Report on adjusting a high throughput screening tool to support water use phenotyping in forages

Drought severely limits forage productivity. The avoidance of water deficit by increasing the capacity for water uptake or by controlling water loss are common responses. A fine interplay exists between the acquisition of water by roots in drying soil and water loss through transpiration. These two components tend to act simultaneously. The following approach and aim is therefore to provide information of shoot development, root development and water use over time of plants growing under greenhouse conditions with soil from target sites. Greenhouse studies is a vital part of phenotyping for drought conditions as allow the recording of responses that would be otherwise impossible under filed conditions

Reporting biases and survey results: evidence from European professional forecasters

Using data from the ECB's Survey of Professional Forecasters, we investigate the reporting practices of survey participants by comparing their point predictions and the mean/median/mode of their probability forecasts. We find that the individual point predictions, on average, tend to be biased towards favourable outcomes: they suggest too high growth and too low inflation rates. Most importantly, for each survey round, the aggregate survey results based on the average of the individual point predictions are also biased. These findings cast doubt on combined survey measures that average individual point predictions. Survey results based on probability forecasts are more reliable. JEL Classification: C42, E27, E47point estimates, subjective probability distributions, survey methods, Survey of Professional Forecasters (SPF)

FORECAST OF THE EXPECTED NON-EPIDEMIC MORBIDITY OF ACUTE DISEASES USING RESAMPLING METHODS

In epidemiological surveillance it is important that any unusual increase of reported cases be detected as rapidly as possible. Reliable forecasting based on a suitable time series model for an epidemiological indicator is necessary for estimating the expected non-epidemic indicator and to elaborate an alert threshold. Time series analysis of acute diseases often use Gaussian autoregressive integrated moving average models. However, these approaches could be adversely affected by departures from the true underlying distribution. The objective of this paper is to introduce a bootstrap procedure for obtaining prediction intervals in linear models in order to avoid the normality assumption. We present a Monte Carlo study comparing the finite sample properties of the bootstrap prediction intervals with those of alternative methods. Finally, we illustrate the performance of the proposed method with a meningococcal disease incidence series.

From Imitation to Prediction, Data Compression vs Recurrent Neural Networks for Natural Language Processing

In recent studies [1][13][12] Recurrent Neural Networks were used for generative processes and their surprising performance can be explained by their ability to create good predictions. In addition, data compression is also based on predictions. What the problem comes down to is whether a data compressor could be used to perform as well as recurrent neural networks in natural language processing tasks. If this is possible,then the problem comes down to determining if a compression algorithm is even more intelligent than a neural network in specific tasks related to human language. In our journey we discovered what we think is the fundamental difference between a Data Compression Algorithm and a Recurrent Neural Network

Inventario de avifauna del norte de Entre Ríos, Argentina: registros notables y perspectivas de conservación

Biodiversity inventories remain fundamental tools for biodiversity conservation. Neotropical biota has poor faunal inventories. In Argentina, the avifauna of the province of Entre Ríos is still not well known. Here, we present the first exhaustive bird inventory of Northern Entre Ríos. We recorded 317 bird species. Three species were new for the province of Entre Ríos and eight were new for Northern Entre Ríos. We recorded 17 threatened species, 4 biome-restricted species and two restricted range species. The high bird diversity of Northern Entre Ríos contrasts with the lack of effective reserves to ensure the survival of endangered species. Creation of natural reserves in this area is urgent. These protected areas should have a management plan and stable park rangers assigned, to ensure the protection of the avian diversity of Northern Entre Ríos.Los inventarios de Biodiversidad siguen siendo herramientas fundamentales para la conservación de la biodiversidad. La biota neotropical posee inventarios incompletos de fauna. En Argentina, la avifauna de la provincia de Entre Ríos permanece poco estudiada. Presentamos el primer inventario exhaustivo de aves para el norte de Entre Ríos. Registramos 317 especies de aves, tres son nuevas para la provincia de Entre Ríos y ocho son nuevas para el norte de Entre Ríos. Diecisiete especies están consideradas amenazadas, 4 son especies restringidas a un bioma y dos especies son de rango restringido. La alta diversidad de aves del norte de Entre Ríos contrasta con la falta de reservas efectivas que puedan asegurar la supervivencia de las especies amenazadas. La creación de reservas naturales en esta región es urgente. Estas áreas protegidas deberían tener planes de manejo y guardaparques estables asignados, para asegurar la protección de la diversidad de aves del norte de Entre Ríos.Fil: Dardanelli, Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Norte. Estación Experimental Agropecuaria Delta del Paraná; ArgentinaFil: Reales, César Fabricio. Provincia de Entre Ríos. Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción. Universidad Autónoma de Entre Ríos. Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción; ArgentinaFil: Sarquis, Juan Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Limnología "Dr. Raúl A. Ringuelet". Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Instituto de Limnología; Argentin