Optimal regime switching under risk aversion and uncertainty

echnology adoption is key for corporate strategy, often determining the success or failure of a company as a whole. However, risk aversion often raises the reluctance to make a timely technology switch, particularly when this entails the abandonment of an existing market regime and entry in a new one. Consequently, which strategy is most suitable and the optimal timing of regime switch depends not only on market factors, such as the definition of the market regimes, as well as economic and technological uncertainty, but also on attitudes towards risk. Therefore, we develop a utility-based, regime-switching framework for evaluating different technology-adoption strategies under price and technological uncertainty. We assume that a decisionmaker may invest in each technology that becomes available (compulsive) or delay investment until a new technology arrives and then invest in either the older (laggard) or the newer technology (leapfrog). Our results indicate that, if market regimes are asymmetric, then greater risk aversion and price uncertainty in a new regime may accelerate regime switching. In addition, the feasibility of a laggard strategy decreases (increases) as price uncertainty in an existing (new) regime increases. Finally, although risk aversion typically favours a compulsive and a laggard strategy, a leapfrog strategy may be feasible under risk aversion provided that the output price and the rate of innovation are sufficiently high

Tracking Hydroplasticization by DSC: Movement of Water Domains Bound to Poly(Meth)Acrylates during Latex Film Formation

The film formation step of latexes constitutes one of the challenges of these environmentally friendly waterborne polymers, as the high glass transition (TG) polymers needed to produce hard films to be used as coatings will not produce coherent films at low temperature. This issue has been dealt by the use of temporary plasticizers added with the objective to reduce the TG of the polymers during film formation, while being released to the atmosphere afterwards. The main problem of these temporary plasticizers is their volatile organic nature, which is not recommended for the environment. Therefore, different strategies have been proposed to overcome their massive use. One of them is the use of hydroplasticization, as water, abundant in latexes, can effectively act as plasticizer for certain types of polymers. In this work, the effect of three different grafted hydroplasticizers has been checked in a (meth)acrylate copolymer, concluding that itaconic acid showed the best performance as seen by its low minimum film-formation temperature, just slightly modified water resistance and better mechanical properties of the films containing itaconic acid. Furthermore, film formation monitoring has been carried out by Differential Scanning Calorimety (DSC), showing that itaconic acid is able to retain more strongly the water molecules during the water losing process, improving its hydroplasticization capacity.This research was funded by the Industrial Liaison Program of POLYMAT and by the Basque Government “Grupos Consolidados del Sistema Universitario Vasco”, grant number IT999-16

New Transient Feature for Metal Oxide Gas Sensor Response Processing

AbstractThis paper presents the performance of metal oxide gas sensor response processing for the concentration detection of an analyte diluted in a neutral atmosphere. In the field of electronic nose, two applications are generally studied: identification of a gaseous atmosphere from other atmospheres, or the determination of the concentration of one gaseous atmosphere. This second application needs more accuracy either in the measurement set-up or in the response analysis. We propose in this study the performance comparison between two traditional features extracted from the sensor response and a new feature corresponding to the maximum (Peak) of the derivative curve of the time sensor response. The performance of this feature to obtain fast odor concentration identifications is discussed and compared to other traditional features

Estoques de Carbono Orgânico em Solos do Corredor de Nacala, Moçambique.

Apoiado por cooperações internacionais, Moçambique tem buscado desenvolver uma agricultura sustentável e auto - suficiente em alimentos. O objetivo deste trabalho foi avaliar estoques de carbono e suas implicações em solos de uma área piloto do Corredor de Nacala, em Moçambique. Em amostras de oito perfis de solo foram determinadas características físicas, químicas, COT e calculado o estoque de carbono do solo (ECS) para horizontes e camadas de 0 - 30 e 0 - 100 cm. Os teores de COT foram baixos e o ECS não diferiu para classes de solo e condições de drenagem. O ECS da camada de 0 - 30 cm representou mais de 50% do estoque da camada de 0 - 100 cm. A adoção de práticas conservacionistasde manejo do solo, como o abandono da queima deresíduos, redução da mobilização do solo e uso de plantas de cobertura com alta produção de resíduos são recomendáveis, assim como estudos mais específicos para melhor entendimento da dinâmica da matéria orgânica nesses pedoambientes

Situación actual de Dictamnus hispanicus Webb (Rutaceae) en la provincia de Alicante: distribución y aspectos etnobotánicos

Spanish Burning bush (Dictamnus hispanicus), is a endemic species of the Eastern half of the Iberian peninsula, which has outstanding relevance in the province of Alicante (Valencian Community, Spain) due to its traditional use, as a component of the ?herberos? ? herbal spirit drinks?. However, there is still little information on other uses of the species in the same province. In order to increase this knowledge, semi-structured interviews (n=90) have been made, and information on its distribution range has been completed using Geographic Information Systems; the species has been rederred to 27 1×1 km UTM squares. 5 phytonyms in Valencian language (74.44% of the informants) and 6 in Castilian or Spanish (25.66%) have been collected. 9 applications uses have been identified: liqueurs (spirits), menstruation regulation, respiratory diseases relieve, intestinal inflammations, alleviation of hard digestion, aerophagia, bad breath, abortion, flavouring cabinets and prevention against the proliferation of moths

Estimativas de perdas de solo para sub-bacias hidrográficas do Estado do Rio de Janeiro.

O Estado do Rio de Janeiro apresenta uma diversidade de ambientes, baixadas litorâneas, Serras, Mar de Morros, e grandes vales, onde é possível encontrar usos da terra que variam da agricultura em larga escala (cana de açúcar), pecuária extensiva, pequenos pólos agrícolas, até grandes fragmentos conservados da mata atlântica. Para obter um diagnóstico da vuInerabilidade do ambiente que considere as características ambientais do terreno associadas a outros fatores ambientais e ao uso da terra, escolheu-se a Equação Universal de Perda de Solo. Este é um modelo usual para estimativa de erosão laminar, indicadora de vulnerabilidade do terreno, e que foi aplicada para todo o Estado do Rio de Janeiro. Para um melhor enfoque territorial relacionado à conservação ambiental as estimativas foram sumarizadas por sub-bacias hidrográficas. Verificou-se que 64% das terras apresentam perdas muito baixas, com valores inferiores a 10 ton/ha.ano; e aproximadamente 2% apresentam perdas extremamente elevadas, acima de 200 ton/ha.ano, e cerca de 21% das sub-bacias hidrográficas apresentam perdas médias muito baixas, com valores menores que 10 ton/ha.ano, e menos de 1% apresentam perdas muito altas, entre 100 e 131 ton/ha.ano

Hybrid MSRM-Based Deep Learning and Multitemporal Sentinel 2-Based Machine Learning Algorithm Detects Near 10k Archaeological Tumuli in North-Western Iberia

This paper presents an algorithm for large-scale automatic detection of burial mounds, one of the most common types of archaeological sites globally, using LiDAR and multispectral satellite data. Although previous attempts were able to detect a good proportion of the known mounds in a given area, they still presented high numbers of false positives and low precision values. Our proposed approach combines random forest for soil classification using multitemporal multispectral Sentinel-2 data and a deep learning model using YOLOv3 on LiDAR data previously pre-processed using a multi–scale relief model. The resulting algorithm significantly improves previous attempts with a detection rate of 89.5%, an average precision of 66.75%, a recall value of 0.64 and a precision of 0.97, which allowed, with a small set of training data, the detection of 10,527 burial mounds over an area of near 30,000 km2, the largest in which such an approach has ever been applied. The open code and platforms employed to develop the algorithm allow this method to be applied anywhere LiDAR data or high-resolution digital terrain models are available