An eclectic third generation model of financial and exchange rate crises

This paper presents an eclectic model that systematizes the dynamics of self-fulfilling crises, using the main aspects of the three typologies of third generation models, to describe the stylized facts that hasten the withdrawal of a pegged exchange rate system. The most striking contributions are the implications for economic policy as well the vanishing role of exchange rate as an instrument of macroeconomic adjustment, when balance-sheet effects are a real possibility.speculative attack, financial liberalization, financial panic, financial and exchange rate crisis

Contingency plan selection under interdependent risks

Managing supply chain risks (SCRs) has become an increasingly strategic key factor over the last decade, aimed at pursuing and maintaining business success. These types of risks clearly pose an important challenge to managers nowadays, and evaluating uncertainty affecting business scenarios is crucial. Indeed, COVID-19 has been dangerously affecting supply chains of global manufacturers, and is indicated as a main trigger cause of supply chain disruptions for a huge number of enterprises. Major effects derived from epidemic outbreaks on supply chains should be further adequately investigated since enterprises have been adopting poor risk management plans [1] to face them. Many companies, for instance, have been assuming a passive attitude towards the management of pandemic effects, simply waiting for the situation to come back to normality at hopefully short notice. On the other side, those companies that are more proactively reacting to the pandemic have been encountering countless difficulties in implementing risk management plans at operational levels [2]. Given these preliminaries, the present contribution is aimed at proposing a way for managing risks due to COVID-19. The main objectives of the present contribution can be formalised as follows: 1. analysing critical supply chain risks and related interdependence relationships to establish priorities on mitigation/prevention actions and most influential risks; 2. proposing a structured method capable to get the vector of risks’ weights and ease the selection of the most suitable contingency strategy on the basis of companies’ needs. These objectives are herein addressed by means of a Multi-Criteria Decision-Making (MCDM) approach based on the use of the Analytic Network Process (ANP), suggested to analyse and weight risks by taking into account relations of dependence existing among the same risks and effects. Results will be formalised in the field of automotive industry as offering a significant input for the process of contingency strategy selection while simultaneously considering uncertainty affecting evaluations on the basis of the specific business context features

On the role of pre and post-processing in environmental data mining

The quality of discovered knowledge is highly depending on data quality. Unfortunately real data use to contain noise, uncertainty, errors, redundancies or even irrelevant information. The more complex is the reality to be analyzed, the higher the risk of getting low quality data. Knowledge Discovery from Databases (KDD) offers a global framework to prepare data in the right form to perform correct analyses. On the other hand, the quality of decisions taken upon KDD results, depend not only on the quality of the results themselves, but on the capacity of the system to communicate those results in an understandable form. Environmental systems are particularly complex and environmental users particularly require clarity in their results. In this paper some details about how this can be achieved are provided. The role of the pre and post processing in the whole process of Knowledge Discovery in environmental systems is discussed

Constrained consistency enforcement in AHP

Decision-making in the presence of intangible elements must be based on a robust, but subtle, balance between expert know-how and judgment consistency when eliciting that know-how. This balance is frequently achieved as a trade-off reached after a feedback process softens the tension frequently found between one force steadily pulling towards (full) consistency, and another force driven by expert feeling and opinion. The linearization method, developed by the authors in the framework of the analytic hierarchy process, is a pull-towards-consistency mechanism that shows the path from an inconsistent body of judgment elicited from an expert towards consistency, by suggesting optimal changes to the expert opinions. However, experts may be reluctant to alter some of their issued opinions, and may wish to impose constraints on the adjustments suggested by the consistency-enforcement mechanism. In this paper, using the classical Riesz representation theorem, the linearization method is accommodated to consider various types of constraints imposed by experts during the abovementioned feedback process

Pattern recognition and clustering of transient pressure signals for burst location

A large volume of the water produced for public supply is lost in the systems between sources and consumers. An important-in many cases the greatest-fraction of these losses are physical losses, mainly related to leaks and bursts in pipes and in consumer connections. Fast detection and location of bursts plays an important role in the design of operation strategies for water loss control, since this helps reduce the volume lost from the instant the event occurs until its effective repair (run time). The transient pressure signals caused by bursts contain important information about their location and magnitude, and stamp on any of these events a specific "hydraulic signature". The present work proposes and evaluates three methods to disaggregate transient signals, which are used afterwards to train artificial neural networks (ANNs) to identify burst locations and calculate the leaked flow. In addition, a clustering process is also used to group similar signals, and then train specific ANNs for each group, thus improving both the computational efficiency and the location accuracy. The proposed methods are applied to two real distribution networks, and the results show good accuracy in burst location and characterization111

Iliopsoas and Gluteal Muscles Are Asymmetric in Tennis Players but Not in Soccer Players

To determine the volume and degree of asymmetry of iliopsoas (IL) and gluteal muscles (GL) in tennis and soccer players.IL and GL volumes were determined using magnetic resonance imaging (MRI) in male professional tennis (TP) and soccer players (SP), and in non-active control subjects (CG) (n = 8, 15 and 6, respectively).The dominant and non-dominant IL were hypertrophied in TP (24 and 36%, respectively, P<0.05) and SP (32 and 35%, respectively, P<0.05). In TP the asymmetric hypertrophy of IL (13% greater volume in the non-dominant than in the dominant IL, P<0.01) reversed the side-to-side relationship observed in CG (4% greater volume in the dominant than in the contralateral IL, P<0.01), whilst soccer players had similar volumes in both sides (P = 0.87). The degree of side-to-side asymmetry decreased linearly from the first lumbar disc to the pubic symphysis in TP (r = -0.97, P<0.001), SP (r = -0.85, P<0.01) and CG (r = -0.76, P<0.05). The slope of the relationship was lower in SP due to a greater hypertrophy of the proximal segments of the dominant IL. Soccer and CG had similar GL volumes in both sides (P = 0.11 and P = 0.19, for the dominant and contralateral GL, respectively). GL was asymmetrically hypertrophied in TP. The non-dominant GL volume was 20% greater in TP than in CG (P<0.05), whilst TP and CG had similar dominant GL volumes (P = 0.14).Tennis elicits an asymmetric hypertrophy of IL and reverses the normal dominant-to-non-dominant balance observed in non-active controls, while soccer is associated to a symmetric hypertrophy of IL. Gluteal muscles are asymmetrically hypertrophied in TP, while SP display a similar size to that observed in controls. It remains to be determined whether the different patterns of IL and GL hypertrophy may influence the risk of injury

Enhanced water demand analysis via symbolic approximation within an epidemiology-based forecasting framework

Epidemiology-based models have shown to have successful adaptations to deal with challenges coming from various areas of Engineering, such as those related to energy use or asset management. This paper deals with urban water demand, and data analysis is based on an Epidemiology tool-set herein developed. This combination represents a novel framework in urban hydraulics. Specifically, various reduction tools for time series analyses based on a symbolic approximate (SAX) coding technique able to deal with simple versions of data sets are presented. Then, a neural-network-based model that uses SAX-based knowledge-generation from various time series is shown to improve forecasting abilities. This knowledge is produced by identifying water distribution district metered areas of high similarity to a given target area and sharing demand patterns with the latter. The proposal has been tested with databases from a Brazilian water utility, providing key knowledge for improving water management and hydraulic operation of the distribution system. This novel analysis framework shows several benefits in terms of accuracy and performance of neural network models for water demand112sem informaçãosem informaçã

Ajuste y calibraci\uf3n, con la llegada de nuevos datos, de un modelo epidemiol\uf3gico simple

Los denominados sistemas din\ue1micos est\ue1n presentes en cualquier \ue1mbito evolutivo. Modelos matem\ue1ticos adecuados (f\uedsicos, sociales, econ\uf3micos, biol\uf3gicos, etc.) constituyen un laboratorio `in vitro' de tales sistemas, que permiten su estudio, simulaci\uf3n y conocimiento. Tales modelos dependen de determinados par\ue1metros que caracterizan el modelo. Partiendo de condiciones iniciales dadas, permiten estimar la evoluci\uf3n del sistema y facilitan as\ued la toma de decisiones. Para que la precisi\uf3n de un modelo sea aceptable, los resultados que produce son comparados con datos provenientes de una monitorizaci\uf3n adecuada, tan en tiempo real como sea posible, del sistema. Con los datos monitorizados, el modelo puede ser ajustado. Sin embargo, la propia din\ue1mica del modelo es, a su vez, cambiante, por lo que los par\ue1metros deben ser reajustados en determinados momentos y el modelo recalibrado. Es el caso de un modelo epid\ue9mico cuando se utiliza para el seguimiento de una epidemia real, en el que distintos par\ue1metros pueden cambiar, por ejemplo, cuando un gobierno impone el confinamiento, lo que disminuye la ratio de contactos. En este art\uedculo presentamos un modelo epidemiol\uf3gico simple y procedemos al ajuste y reajuste del mismo utilizando datos obtenidos en diferentes momentos de tiempo. En la asignatura Matem\ue1ticas II de la doble titulaci\uf3n TELECO+ADE, los alumnos utilizan herramientas suficientes para entender la idea subyacente al ajuste y reajuste de modelos. El modelo epidemiol\uf3gico que presentamos en este art\uedculo es suficientemente simple como para ser resoluble `a mano'. Esto permite introducir al alumno en el importante campo de los sistemas din\ue1micos y su calibraci\uf3n, algo esencial para que los resultados de predicci\uf3n producidos sean \ufatiles para la toma de decisiones

Differentiation of soybean quality parameters according to production environment: linkage to the origin

The objective of this study was to quantify quality parameters (protein and oil) from soybean produced in different environments in the SE of Buenos Aires, hypothesizing that concentration of both grain components is associated with the environments where they are produced.EEA BalcarceFil: Carpaneto, Bárbara Bettina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto de Innovación para la Producción Agropecuaria y el Desarrollo Sostenible; Argentina.Fil: Eiza, Maximiliano Joaquín. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto de Innovación para la Producción Agropecuaria y el Desarrollo Sostenible; Argentina.Fil: Montoya, Marina Rosa. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto de Innovación para la Producción Agropecuaria y el Desarrollo Sostenible; Argentina.Fil: González Belo, Raúl. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina.Fil: Izquierdo, Natalia. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina.Fil: Quiroz, Facundo José. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto de Innovación para la Producción Agropecuaria y el Desarrollo Sostenible; Argentina