Intra-industry trade and labor costs: The smooth adjustment hypothesis

We study a situation in which, owing to the exhaustion of non-renewable energy sources, conventional motor vehicles will turn out of use. We consider two scenarios: recycling or dismantling these motor vehicles. M|G|∞ queue system is used to study the process. Through it, we conclude that if the rate of dismantling and recycling of motor vehicles is greater than the rate at which they become idle, the system will tend to get balanced. The model allows also performing a brief study about the recycling or dismantling economic interest.

The Tragedy of the Anti-Commons: A New Problem. An Application to the Fisheries.

The operation and management of common property resources (“the commons”) have been exhaustively examined in economics and political science, both in formal analysis and in practical applications. “Tragedy of the Commons” metaphor helps to explain why people overuse shared resources. On the other side, Anti-Commons Theory is a recent theory presented by scientists to explain several situations about new Property Rights concerns. An “anti-commons” problem arises when there are multiple rights to exclude. Little attention has been given to the setting where more than one person is assigned with exclusion rights, which may be exercised. We analyze the “anti-commons” problem in which resources are inefficiently underutilized rather than over-utilized as in the familiar commons setting. In fact, these two problems are symmetrical in several aspects.Anti-Commons Theory; Property Rights

Rehabilitation of abandoned villages through tourism: a solution for sustainable heritage development?

Villages which have been abandoned during recent decades as a result of migration from rural areas constitute a serious problem which is all too common in many European countries. The aim of this paper is to examine the problem in Portugal and conduct a comparative study of four villages, set in a range of geographical and socio-economic contexts, which have been rehabilitated. These villages are associated with: different types of vernacular architecture; different types of traditional landscape; contrasting topographic contexts; and different causes of rural abandonment. The findings of this study point to the main requirements for improvement and recommendations are made for suitable developments in terms of the heritage in its broadest sense, including the surrounding landscape. Heritage character is not only important for the preservation of local identity but may also be associated with products and services which are marketed and is thus an essential factor for the socio-economic sustainability of rehabilitated villages.CIDEHUS centre and IIFA institute of Évora University , European Union FEDR, COMPETE and QREN, Foundation for Science and Technology (FCT)

Tragedies on natural resources a commons and anticommons approach

Ambiguous concepts blur analytical and policy prescription clarity. In the literature on Natural Resources it would be difficult to find a concept as misunderstood as commons. This paper clarifies this confusion and establishes an adequate conceptualisation. A typology of property-rights regimes relevant to common property resources is presented and a new concept – anticommons - is introduced. The reflex of this regimes distinction on the design of the natural resources policy is discussed and this conceptualisation is used to study exemplar cases in the area of fisheries and aquaculture policy in Portugal

Predicting type of delivery by identification of obstetric risk factors through data mining

In Maternity Care, a quick decision has to be made about the most suitable delivery type for the current patient. Guidelines are followed by physicians to support that decision; however, those practice recommendations are limited and underused. In the last years, caesarean delivery has been pursued in over 28% of pregnancies, and other operative techniques regarding specific problems have also been excessively employed. This study identifies obstetric and pregnancy factors that can be used to predict the most appropriate delivery technique, through the induction of data mining models using real data gathered in the perinatal and maternal care unit of Centro Hospitalar of Oporto (CHP). Predicting the type of birth envisions high-quality services, increased safety and effectiveness of specific practices to help guide maternity care decisions and facilitate optimal outcomes in mother and child. In this work was possible to acquire good results, achieving sensitivity and specificity values of 90.11% and 80.05%, respectively, providing the CHP with a model capable of correctly identify caesarean sections and vaginal deliveries

Predicting preterm birth in maternity care by means of data mining

Worldwide, around 9% of the children are born with less than 37 weeks of labour, causing risk to the premature child, whom it is not prepared to develop a number of basic functions that begin soon after the birth. In order to ensure that those risk pregnancies are being properly monitored by the obstetricians in time to avoid those problems, Data Mining (DM) models were induced in this study to predict preterm births in a real environment using data from 3376 patients (women) admitted in the maternal and perinatal care unit of Centro Hospitalar of Oporto. A sensitive metric to predict preterm deliveries was developed, assisting physicians in the decision-making process regarding the patients’ observation. It was possible to obtain promising results, achieving sensitivity and specificity values of 96% and 98%, respectively

Predictive models for hospital bed management using data mining techniques

Series : Advances in intelligent systems and computing, vol. 276It is clear that the failures found in hospital management are usually related to the lack of information and insufficient resources management. The use of Data Mining (DM) can contribute to overcome these limitations in order to identify relevant data on patient’s management and providing important information for managers to support their decisions. Throughout this study, were induced DM models capable to make predictions in a real environment using real data. For this, was adopted the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology. Three distinct techniques were considered: Decision Trees (DT), Naïve Bayes (NB) and Support Vector Machine (SVM) to perform classification tasks. With this work it was explored and assessed the possibility to predict the number of patient discharges using only the number and the respective date. The models developed are able to predict the number of patient discharges per week with acuity values ranging from ≈82.69% to ≈94.23%. The use of this models can contribute to improve the hospital bed management because having the discharges number it is possible forecasting the beds available for the following weeks in a determinated service

Big data for stock market by means of mining techniques

Predict and prevent future events are the major advantages to any company. Big Data comes up with huge power, not only by the ability of processes large amounts and variety of data at high velocity, but also by the capability to create value to organizations. This paper presents an approach to a Big Data based decision making in the stock market context. The correlation between news articles and stock variations it is already proved but it can be enriched with other indicators. In this use case they were collected news articles from three different web sites and the stock history from the New York Stock Exchange. In order to proceed to data mining classification algorithms the articles were labeled by their sentiment, the direct relation to a specific company and geographic market influence. With the proposed model it is possible identify the patterns between this indicators and predict stock price variations with accuracies of 100 percent. Moreover the model shown that the stock market could be sensitive to news with generic topics, such as government and society but they can also depend on the geographic cover