O risco dos bancos, regulação e a crise financeira internacional

Dissertação de Mestrado, Ciências Económicas e Empresariais, 13 de Julho de 2016, Universidade dos Açores.

Multi-level, Multi-stage and Stochastic Optimization Models for Energy Conservation in Buildings for Federal, State and Local Agencies

Energy Conservation Measure (ECM) project selection is made difficult given real-world constraints, limited resources to implement savings retrofits, various suppliers in the market and project financing alternatives. Many of these energy efficient retrofit projects should be viewed as a series of investments with annual returns for these traditionally risk-averse agencies. Given a list of ECMs available, federal, state and local agencies must determine how to implement projects at lowest costs. The most common methods of implementation planning are suboptimal relative to cost. Federal, state and local agencies can obtain greater returns on their energy conservation investment over traditional methods, regardless of the implementing organization. This dissertation outlines several approaches to improve the traditional energy conservations models. Any public buildings in regions with similar energy conservation goals in the United States or internationally can also benefit greatly from this research. Additionally, many private owners of buildings are under mandates to conserve energy e.g., Local Law 85 of the New York City Energy Conservation Code requires any building, public or private, to meet the most current energy code for any alteration or renovation. Thus, both public and private stakeholders can benefit from this research. The research in this dissertation advances and presents models that decision-makers can use to optimize the selection of ECM projects with respect to the total cost of implementation. A practical application of a two-level mathematical program with equilibrium constraints (MPEC) improves the current best practice for agencies concerned with making the most cost-effective selection leveraging energy services companies or utilities. The two-level model maximizes savings to the agency and profit to the energy services companies (Chapter 2). An additional model presented leverages a single congressional appropriation to implement ECM projects (Chapter 3). Returns from implemented ECM projects are used to fund additional ECM projects. In these cases, fluctuations in energy costs and uncertainty in the estimated savings severely influence ECM project selection and the amount of the appropriation requested. A risk aversion method proposed imposes a minimum on the number of “of projects completed in each stage. A comparative method using Conditional Value at Risk is analyzed. Time consistency was addressed in this chapter. This work demonstrates how a risk-based, stochastic, multi-stage model with binary decision variables at each stage provides a much more accurate estimate for planning than the agency’s traditional approach and deterministic models. Finally, in Chapter 4, a rolling-horizon model allows for subadditivity and superadditivity of the energy savings to simulate interactive effects between ECM projects. The approach makes use of inequalities (McCormick, 1976) to re-express constraints that involve the product of binary variables with an exact linearization (related to the convex hull of those constraints). This model additionally shows the benefits of learning between stages while remaining consistent with the single congressional appropriations framework.

Spatial and Functional Organization of Pig Trade in Different European Production Systems: Implications for Disease Prevention and Control

Understanding the complexity of live pig trade organization is a key factor to predict and control major infectious diseases, such as classical swine fever (CSF) or African swine fever (ASF). Whereas the organization of pig trade has been described in several European countries with indoor commercial production systems, little information is available on this organization in other systems, such as outdoor or small-scale systems. The objective of this study was to describe and compare the spatial and functional organization of live pig trade in different European countries and different production systems. Data on premise characteristics and pig movements between premises were collected during 2011 from Bulgaria, France, Italy, and Spain, which swine industry is representative of most of the production systems in Europe (i.e., commercial vs. small-scale and outdoor vs. indoor). Trade communities were identified in each country using the Walktrap algorithm. Several descriptive and network metrics were generated at country and community levels. Pig trade organization showed heterogeneous spatial and functional organization. Trade communities mostly composed of indoor commercial premises were identified in western France, northern Italy, northern Spain, and north-western Bulgaria. They covered large distances, overlapped in space, demonstrated both scale-free and small-world properties, with a role of trade operators and multipliers as key premises. Trade communities involving outdoor commercial premises were identified in western Spain, south-western and central France. They were more spatially clustered, demonstrated scale-free properties, with multipliers as key premises. Small-scale communities involved the majority of premises in Bulgaria and in central and Southern Italy. They were spatially clustered and had scale-free properties, with key premises usually being commercial production premises. These results indicate that a disease might spread very differently according to the production system and that key premises could be targeted to more cost-effectively control diseases. This study provides useful epidemiological information and parameters that could be used to design risk-based surveillance strategies or to more accurately model the risk of introduction or spread of devastating swine diseases, such as ASF, CSF, or foot-and-mouth disease.

Novel efficient technologies in Europe for axle bearing condition monitoring – the MAXBE project

Axle bearing damage with possible catastrophic failures can cause severe disruptions or even dangerous derailments, potentially causing loss of human life and leading to significant costs for railway infrastructure managers and rolling stock operators. Consequently the axle bearing damage process has safety and economic implications on the exploitation of railways systems. Therefore it has been the object of intense attention by railway authorities as proved by the selection of this topic by the European Commission in calls for research proposals. The MAXBE Project (http://www.maxbeproject.eu/), an EU-funded project, appears in this context and its main goal is to develop and to demonstrate innovative and efficient technologies which can be used for the onboard and wayside condition monitoring of axle bearings. The MAXBE (interoperable monitoring, diagnosis and maintenance strategies for axle bearings) project focuses on detecting axle bearing failure modes at an early stage by combining new and existing monitoring techniques and on characterizing the axle bearing degradation process. The consortium for the MAXBE project comprises 18 partners from 8 member states, representing operators, railway administrations, axle bearing manufactures, key players in the railway community and experts in the field of monitoring, maintenance and rolling stock. The University of Porto is coordinating this research project that kicked-off in November 2012 and it is completed on October 2015. Both on-board and wayside systems are explored in the project since there is a need for defining the requirement for the onboard equipment and the range of working temperatures of the axle bearing for the wayside systems. The developed monitoring systems consider strain gauges, high frequency accelerometers, temperature sensors and acoustic emission. To get a robust technology to support the decision making of the responsible stakeholders synchronized measurements from onboard and wayside monitoring systems are integrated into a platform. Also extensive laboratory tests were performed to correlate the in situ measurements to the status of the axle bearing life. With the MAXBE project concept it will be possible: to contribute to detect at an early stage axle bearing failures; to create conditions for the operational and technical integration of axle bearing monitoring and maintenance in different European railway networks; to contribute to the standardization of the requirements for the axle bearing monitoring, diagnosis and maintenance. Demonstration of the developed condition monitoring systems was performed in Portugal in the Northern Railway Line with freight and passenger traffic with a maximum speed of 220 km/h, in Belgium in a tram line and in the UK. Still within the project, a tool for optimal maintenance scheduling and a smart diagnostic tool were developed. This paper presents a synthesis of the most relevant results attained in the project. The successful of the project and the developed solutions have positive impact on the reliability, availability, maintainability and safety of rolling stock and infrastructure with main focus on the axle bearing health.

Status and the potential for extinction of the largetooth sawfish Pristis pristis in the Atlantic Ocean

1. Sawfishes currently are among the most threatened elasmobranchs in the world. Only two species inhabit Atlantic waters: the largetooth sawfish (Pristis pristis) and the smalltooth sawfish (Pristis pectinata), both having suffered dramatic declines in their ranges. 2. The goal of this study was to evaluate the status of P. pristis in the Atlantic, and estimate local extinction risk based on historical and recent occurrence records. In order to accomplish these goals, a thorough search for historical and recent records of P. pristis in the Atlantic was conducted, by reviewing scientific and popular literature, museum specimens, and contacting regional scientists from the species’ historical range. 3. In total, 801 P. pristis records (1830–2009) document its occurrence in four major regions in the Atlantic: USA (n =41), Mexico and Central America (n =535), South America (n=162), and West Africa (n =48). Locality data were not available for 15 records. 4. Historical abundance centres were the Colorado-San Juan River system in Nicaragua and Costa Rica (and secondarily Lake Izabal of Guatemala), the Amazon estuary, and coastal Guinea-Bissau. 5. Currently, the species faces drastic depletion throughout its entire former range and centres of abundance. It appears to have been extirpated from several areas. The probability of extinction was highest in the USA, northern South America (Colombia to Guyane), and southern West Africa (Cameroon to Namibia). 6. Currently, the Amazon estuary appears to have the highest remaining abundance of P. pristis in the Atlantic, followed by the Colorado–San Juan River system in Nicaragua and Costa Rica and the Bissagos Archipelago in Guinea Bissau. Therefore the protection of these populations is crucial for the preservation and recovery of the species.

Relación entre la calificación de los elementos de un sistema de gestión y los indicadores de accidentalidad en empresas del sector de la construcción en Colombia

El presente estudio tiene como objetivo determinar la relación que existe entre la implementación de un sistema de gestión de seguridad y salud en el trabajo (SGSST), y la frecuencia y la severidad de la accidentalidad en la industria de la construcción en Colombia. Para ello se seleccionaron 35 empresas que realizan actividades relacionadas con la edificación, infraestructura e interventoría, que hubiesen implementado un SGSST para la intervención de los riesgos de accidentes y que contaran con la evaluación del mismo. La evaluación del SGSST está enmarcada en cinco dimensiones o criterios: planeación, política, implementación, manejo integral del accidente y revisión por la gerencia. Cada una evaluada a través de diferentes requisitos y se presentan en una escala de 1 a 10, siendo 10 el nivel más alto del cumplimiento por requisito. Teniendo los resultados de esta calificación, la tasa (proporción entre los accidentes reportados y los trabajadores de cada empresa) y los días de incapacidad (ausentismo por accidente de trabajo), se realizó un análisis de las medidas descriptivas consolidado por las empresas del estudio: tendencia central y dispersión para número de trabajadores, tasa de accidentalidad, días de incapacidad y el resultado de los totales de cada criterio de la evaluación y el gran total. Para estudiar la relación entre los resultados de la evaluación y los indicadores de tasa y días, se llevó a cabo un análisis de correlación y regresión lineal entre los indicadores de accidentalidad y los resultados de las puntuaciones de los criterios. Esta correlación se realizó tanto para la primera evaluación como para la segunda. En las dos mediciones las correlaciones fueron negativas mostrando que existe una disminución en la tasa de accidentalidad y días de incapacidad entre una evaluación y la otra. En el análisis de regresión, en la primera evaluación por cada unidad que aumentó la calificación global, se presentó una reducción de la tasa de frecuencia de 0.140. En la segunda evaluación por cada unidad que aumentó la calificación global, la tasa se redujo en 0.159. Ambos hallazgos soportan la necesidad de implementar un SGSST para ayudar a reducir el número inaceptable de lesiones y enfermedades en la industria de la construcción.

Proton pump inhibitors and the risk of fractures in older adults: a population-based retrospective cohort study

Thesis (Master's)--University of Washington, 2016-06

Decision making models embedded into a web-based tool for assessing pest infestation risk

Current practices in agricultural management involve the application of rules and techniques to ensure high quality and environmentally friendly production. Based on their experience, agricultural technicians and farmers make critical decisions affecting crop growth while considering several interwoven agricultural, technological, environmental, legal and economic factors. In this context, decision support systems and the knowledge models that support them, enable the incorporation of valuable experience into software systems providing support to agricultural technicians to make rapid and effective decisions for efficient crop growth. Pest control is an important issue in agricultural management due to crop yield reductions caused by pests and it involves expert knowledge. This paper presents a formalisation of the pest control problem and the workflow followed by agricultural technicians and farmers in integrated pest management, the crop production strategy that combines different practices for growing healthy crops whilst minimising pesticide use. A generic decision schema for estimating infestation risk of a given pest on a given crop is defined and it acts as a metamodel for the maintenance and extension of the knowledge embedded in a pest management decision support system which is also presented. This software tool has been implemented by integrating a rule-based tool into web-based architecture. Evaluation from validity and usability perspectives concluded that both agricultural technicians and farmers considered it a useful tool in pest control, particularly for training new technicians and inexperienced farmers.

Investment decision framework for infrastructure asset management: a probability-based approach

Australia’s civil infrastructure assets of roads, bridges, railways, buildings and other structures are worth billions of dollars. Road assets alone are valued at around A$ 140 billion. As the condition of assets deteriorate over time, close to A$10 billion is spent annually in asset maintenance on Australia's roads, or the equivalent of A$27 million per day. To effectively manage road infrastructures, firstly, road agencies need to optimise the expenditure for asset data collection, but at the same time, not jeopardise the reliability in using the optimised data to predict maintenance and rehabilitation costs. Secondly, road agencies need to accurately predict the deterioration rates of infrastructures to reflect local conditions so that the budget estimates could be accurately estimated. And finally, the prediction of budgets for maintenance and rehabilitation must provide a certain degree of reliability. A procedure for assessing investment decision for road asset management has been developed. The procedure includes: • A methodology for optimising asset data collection; • A methodology for calibrating deterioration prediction models; • A methodology for assessing risk-adjusted estimates for life-cycle cost estimates. • A decision framework in the form of risk map

Final : report assessing risk and variation in maintenance and rehabilitation costs for road network

This report presents the results of research projects conducted by The Australian Cooperative Research Centre for Construction Innovation, Queensland University of Technology, RMIT University, Queensland Government Department of Main Roads and Queensland Department of Public Works. The research projects aimed at developing a methodology for assessing variation and risk in investment in road network, including the application of the method in assessing road network performance and maintenance and rehabilitation costs for short- and long-term future investment.