Fiscal policy and lending relationships

This paper studies how fiscal policy affects credit market conditions. First, it conducts a FAVAR analysis showing that the credit spread responds negatively to an expansionary government spending shock, while consumption, investment, and lending increase. Second, it illustrates that these results are not mimicked by a DSGE model where the credit spread is endogenized via the inclusion of a banking sector exploiting lending relationships. Third, it demonstrates that introducing deep habits in private and government consumption makes the model able to replicate empirics. Sensitivity checks and extensions show that core results hold for a number of model calibrations and specifications. The presence of banks exploiting lending relationships generates a financial accelerator effect in the transmission of fiscal shocks

Appropriate solid waste management system in Quelimane (Mozambique): study and design of a small-scale center for plastic sorting with wastewater treatment

Appropriate solid waste management (SWM) strategies are necessary to avoid severe environmental and sanitary impacts, especially in low-income countries. Such strategies are most likely to succeed whether implementing actors are supported by scientific research. In this paper, the results of a collaboration between local authorities and researchers are presented and discussed that are the assessment of waste generation in the city of Quelimane (Mozambique), integrating existing and field-collected data and the design of a small-scale center for plastic sorting to complement the SWM system of the city. The center is expected to receive about 0.3-0.4 t/day of plastic waste (5%-7% of the overall amount of plastic waste daily produced in Quelimane). As long-term sustainability represents a typical issue, simplicity of operation was a leading principle in the design of the center; moreover, the design included a treatment plant (WWTP) for generated wastewater, whose management is usually neglected in such interventions. Among others, natural wastewater treatment (constructed wetlands) has been chosen for its affordability. Noteworthy, the so-conceived WWTP appears as a novelty in the scientific literature associated with small-scale plastic sorting plants. The system is designed to treat an average flow of 6 m3/day and consisted of a septic tank followed by a subsurface flow constructed wetland. Overall, the COD (chemical oxygen demand) and TSS (total suspended solids) removal higher than 80% and 90% were estimated, respectively. Based on this work, both the center and the WWTP were successfully realized, which are waiting to become operational. In the authors' opinion, the implemented procedure could become a reference for broader investigations and surveys

Using SPICES for a better service consumption

In this poster we present SPICES (Semantic Platform for the Interaction and Consumption of Enriched Services), a Web based tool that automates the process of consuming a Web service by making use of the semantic annotations that describe them. SPICES supports both traditional WSDL services and RESTful ones and offers end-users the possibility of interacting with them in an easy yet personalised manner, without the need of advanced technical skills -which were traditionally required-, being the complexity that lies underneath hidden to them. SPICES is being developed within the European project SOA4All

Pyridostigmine in pediatric Intestinal pseudo-obstruction. case report of a 2-year old girl and literature review

Pediatric chronic intestinal pseudo-obstruction is a rare disorder characterized by a severe impairment of gastrointestinal motility leading to intestinal obstruction symptoms in the absence of mechanical causes. The diagnosis is usually clinical and diagnostic work is usually aimed to rule out mechanical obstruction and to identify any underlying diseases. Treatment is challenging and requires a multidisciplinary effort. In this manuscript we describe the youngest child successfully treated with the orally administrable, longacting, reversible anti-cholinesterase drug, pyridostigmine. Like other drugs belonging to cholinesterase inhibitors, pyridostigmine enhances gut motility by increasing acetylcholine availability in the enteric nervous system and neuro-muscular junctions. Based on the direct evidence from the reported case, we reviewed the current literature on the use of pyridostigmine in severe pediatric dysmotility focusing on intestinal pseudo-obstruction. The overall data emerged from the few published studies suggest that pyridostigmine is an effective and usually well tolerated therapeutic options for patients with intestinal pseudo-obstruction. More specifically, the main results obtained by pyridostigmine included marked reduction of abdominal distension, reduced need of parenteral nutrition, and improvement of oral feeding. The present case and review on pyridostigmine pave the way for eagerly awaited future randomized controlled studies testing the efficacy of cholinesterase inhibitors in pediatric severe gut dysmotility

Leaning against windy bank lending

Using a dynamic stochastic general equilibrium model with banking, this paper first provides evidence that, during the Great Moderation, monetary policy leaned against the wind blowing from the loan market in the US. It then shows that the extent to which this occurred delivers a small welfare loss relative to the optimised simple interest-rate rule that features only a response to inflation. The source of business cycle fluctuations is crucial for the optimality of a leaning-against-the-wind policy. In fact, the pro-cyclical nature of lending creates a trade-off between inflation and financial stabilisation when supply shocks are prevalent

INSPIRE Network Services SOAP Framework

The goal of this document is to provide a definition and rationale for a proposed INSPIRE SOAP framework (SOAP nodes policy, RPC, attachments, WS-I, WSDL) and description of issues and solutions for the specific geospatial domain, for example GML handling in SOAP messages or interfaces definition of the OGC specifications.JRC.H.6-Spatial data infrastructure

Modelo de predicción de aportaciones mensuales utilizando Redes Neuronales Artificiales. Aplicación a la cuenca del río Amambaí (Brasil)

[EN] Hydrological modeling, for flow prediction purposes, has today several alternatives regarding to traditional modeling. These alternative prediction methods are growing in terms of usage and knowledge in hydrology. The limitations found in the implementation of a classical conceptual hydrological model, either distributed or lumped, in terms of the data required for its application makes that, in some cases and depending on the target, is feasible to choose for an alternative model approach based exclusively on data, such as Artificial Neural Networks (ANN). The ANN are a structured computer system based on the behavior of the human brain, in which inputs data are processed along the network to obtain an output data, and could be an interesting prediction tool, not only because the advantages above-mentioned, concerning to a classical hydrological prediction model, but also because they have a great advantage of being very adaptable for the "modeler" requirements, who defines from the initial design to the training algorithm. Despite being considered as a "black-box" model, its versatility is one of the main advantages of this type of model. Early flow prediction, it is extremely important for any hydroelectric plant, especially for the planning and operation and even more for one like Itaipu (14.000 MW installed capacity) because of its generation and contribution to the electrical systems for both countries, Paraguay (75%) and Brazil (15%). Based on a real need of the Division of Hydrological and Energy Studies of Itaipu to improve its monthly hydrological predictions, a monthly flow prediction model using ANN have been developed for one of the five rivers in the incremental basin, the Amambaí River, located in the state of Mato Grosso do Sul, Brazil. Six ANN have been designed and evaluated varying the inputs data and hidden neurons, obtaining 83% to 90% of correlation coefficient in the verification phase with other events.[ES] La modelación hidrológica, con fines de previsión de caudales tiene hoy varias alternativas con relación a la modelación clásica. Estos métodos alternativos de predicciones, van ganando espacio y conocimiento en hidrología. Las limitaciones encontradas en la implementación de un modelo hidrológico conceptual clásico, ya sea distribuido o agregado, en cuanto a los datos necesarios para su aplicación, hace que en algunos casos y dependiendo del objetivo, sea factible optar por una metodología basada exclusivamente en datos, como son las Redes Neuronales Artificiales (RNA). Las RNA son un sistema computacional estructurado, basado en el funcionamiento del cerebro humano, en el que se procesan datos de entradas a lo largo de la red, para obtener un dato de salida, y pueden ser una interesante herramienta de predicción, que no solo tienen las ventajas mencionadas más arriba, con relación a un modelo clásico de previsión hidrológica, sino que, tienen la gran ventaja de ser muy adaptables a las necesidades del modelador , que define desde el diseño inicial hasta el algoritmo de calibración. Por más que sea considerado como un modelo de caja negra , su versatilidad es una de las principales ventajas para este tipo de modelo. La predicción temprana de caudales, es de fundamental importancia para cualquier hidroeléctrica, especialmente para la planificación y operación y más aún, para una tan importante como la Itaipu (14.000 MW capacidad instalada), por su generación y aporte a los sistemas eléctricos tanto para el Paraguay ( 75%) y el Brasil (15%). Basado en una necesidad real de la División de Estudios Hidrológicos y Energéticos de la Itaipu, de mejorar sus predicciones hidrológicas mensuales, se ha desarrollado un modelo de previsión de caudales mensuales usando RNA, de uno de los cinco ríos de la cuenca incremental, el río Amambaí, localizado en el estado de Mato Grosso do Sul, Brasil. Han sido diseñadas y evaluadas seis RNA variando datos de entradas y neuronas ocultas, y se han obtenido resultados con coeficientes de correlación de 83% a 90% en la fase de verificación con otros eventos.Gomes Villa Trinidad, G. (2017). Modelo de predicción de aportaciones mensuales utilizando Redes Neuronales Artificiales. Aplicación a la cuenca del río Amambaí (Brasil). http://hdl.handle.net/10251/78117TFG

SOAP Primer for INSPIRE Discovery and View Services

This document demonstrates the use of the proposed INSPIRE SOAP Framework for the INSPIRE Discovery and View services. This document focuses on the analysis of the WSDL itself (for both the Discovery and View services), explaining its parts and characteristics, as well as on the analysis of SOAP request and response messages, including headers and potential attachments. Moreover, the primer is providing also examples of user scenarios, with specific code samples.JRC.H.6-Spatial data infrastructure