Is there a trade-off between quality and productivity? The case of diagnostic technologies in Portugal

The purpose of this paper is twofold: first, we compute quality-adjusted measures of productivity change for the three most important diagnostic technologies (i.e., the Computerised Tomography Scan, Electrocardiogram and Echocardiogram) in the major Portuguese hospitals. We use the Malmquist–Luenberger index, which allows to measure productivity growth while controlling for the quality of the production. Second, using non-parametric tests, we analyse whether the implementation of the Prospective Payment System may have had a positive impact on the movements of productivity over time. The results show that the PPS has helped hospitals to use these tools more efficiently and to improve their effectiveness.

Location Privacy Preferences : A Survey-Based Analysis of Consumer Awareness, Trade-off and Decision-Making

Peer reviewed

Location Privacy Preferences : A Survey-Based Analysis of Consumer Awareness, Trade-off and Decision-Making

Peer reviewed

Controller Time and Delay Costs - a Trade-off Analysis

Air traffic controller shortages remain a significant challenge in European ATM. Comparing different rules, we quantify the cost effectiveness of adding controller hours to Area Control Centre regulations to avert the delay cost impact on airlines. Typically, adding controller hours results in a net benefit. Distributions of delay duration and aircraft weight play an important role in determining the total cost of a regulation. Errors are likely to be incurred when analysing performance based on average delay values, particularly at the disaggregate level.

Expanding Agri-Food Production and Employment in the Presence of Climate Policy Constraints: Quantifying the Trade-Off in Ireland

This chapter explores the trade-off between competing objectives of employment creation and climate policy commitments in Irish agriculture. A social accounting matrix (SAM) multiplier model is linked with a partial equilibrium agricultural sector model to simulate the impact of a number of GHG emission reduction scenarios, assuming these are achieved through a constraint on beef production. Limiting the size of the beef sector helps to reduce GHG emissions with a very limited impact on the value of agricultural income at the farm level. However, the SAM multiplier analysis shows that there would be significant employment losses in the wider economy. From a policy perspective, a pragmatic approach to GHG emissions reductions in the agriculture sector, which balances opportunities for economic growth in the sector with opportunities to reduce associated GHG emissions, may be required.

Human capital and the quantity–quality trade-off during the demographic transition

This paper provides an empirical test of the child quantity–quality (QQ) trade-off predicted by unified growth theory. Using individual census returns from the 1911 Irish census, we examine whether children who attended school were from smaller families—as predicted by a standard QQ model. To measure causal effects, we use a selection of models robust to endogeneity concerns which we validate for this application using an Empirical Monte Carlo analysis. Our results show that a child remaining in school between the ages of 14 and 16 caused up to a 27 % reduction in fertility. Our results are robust to alternative estimation techniques with different modeling assumptions, sample selection, and alternative definitions of fertility. These findings highlight the importance of the demographic transition as a mechanism which underpinned the expansion in human capital witnessed in Western economies during the twentieth century.

Determinants of Capital Structure of Swedish limited companies : Testing Trade-off Theory Against Pecking Order Theory

Research question- This thesis investigates the determinants of capital structure of the Swedish companies. In order to do so, the two dominant theories of the corporate structure are studied and their assumptions are tested. Thus, the study researches which one of the two theories is more appealing for the Swedish market. Methodology-The study follows a purely quantitative study, by conducting an econometric analysis. The data are collected from a secondary source and more particularly the "Retriever" database, which contains financial data of the Swedish companies. Findings- The findings indicate that the determinants of the corporate structure for the Swedish market do not differ from other studies which have been conducted in other countries. However, there is a difference when it comes to tax and non-tax shields. The results suggest that in most cases the Pecking Order Theory appears to be more representative for the Swedish market, since most of the coefficient appear to be in favour of it. Moreover, the significance of the effect of the industry for the financial leverage is confirmed.

Quantitative and Qualitative Trade-Off Analysis of Drowsy Driver Detection Methods: Single Electrode Wearable EEG Device, Multi-Electrode Wearable EEG Device, and Head-Mounted Gyroscope

Drowsy driving impairs motorists’ ability to operate vehicles safely, endangering both the drivers and other people on the road. The purpose of the project is to find the most effective wearable device to detect drowsiness. Existing research has demonstrated several options for drowsiness detection, such as electroencephalogram (EEG) brain wave measurement, eye tracking, head motions, and lane deviations. However, there are no detailed trade-off analyses for the cost, accuracy, detection time, and ergonomics of these methods. We chose to use two different EEG headsets: NeuroSky Mindwave Mobile (single-electrode) and Emotiv EPOC (14- electrode). We also tested a camera and gyroscope-accelerometer device. We can successfully determine drowsiness after five minutes of training using both single and multi-electrode EEGs. Devices were evaluated using the following criteria: time needed to achieve accurate reading, accuracy of prediction, rate of false positives vs. false negatives, and ergonomics and portability. This research will help improve detection devices, and reduce the number of future accidents due to drowsy driving.

Using a CGE Model to Identify the Policy Trade-Off between Unemployment and Inflation: The Efficient Phillips Curve

This paper provides a new reading of a classical economic relation: the short-run Phillips curve. Our point is that, when dealing with inflation and unemployment, policy-making can be understood as a multicriteria decisionmaking problem. Hence, we use so-called multiobjective programming in connection with a computable general equilibrium (CGE) model to determine the combinations of policy instruments that provide efficient combinations of inflation and unemployment. This approach results in an alternative version of the Phillips curve labelled as efficient Phillips curve. Our aim is to present an application of CGE models to a new area of research that can be especially useful when addressing policy exercises with real data. We apply our methodological proposal within a particular regional economy, Andalusia, in the south of Spain. This tool can give some keys for policy advice and policy implementation in the fight against unemployment and inflation.

A conservation trade-off? Interspecific differences in seahorse responses to experimental changes in fishing effort

1. A 2-year experimental seining programme and underwater visual censuses were undertaken to quantify the direct effects of active demersal fishing on the population structure and relative abundance of two sympatric seahorse species of conservation concern: the European long-snouted seahorse, Hippocampus guttulatus Cuvier 1829 and the short-snouted seahorse, Hippocampus hippocampus L. The influence of habitat preference on population-level responses to changes in habitat structure following a reduction in fishing effort was also investigated. 2. It was predicted that the benthic habitat would be more structurally complex after fishing ceased and that seahorse densities would increase in response to reduced fishing mortality. Furthermore, it was predicted that the magnitude of the increase in density would be greater for H. guttulatus than for H. hippocampus, because the former species prefers complex vegetated habitats while the latter species uses sparsely vegetated habitats. 3. As predicted, the amount of habitat cover increased significantly when seining ceased, primarily through increases in the abundance of drifting macroalgae and unattached invertebrates. Despite similarities in life histories, the two seahorse species responded differently in terms of magnitude and direction to reduced fishing effort: the abundance of H. guttulatus increased significantly while H. hippocampus decreased in abundance. 4. Results suggest that active demersal fishing may influence the magnitude and direction of the responses of benthic marine fishes to exploitation through its impacts on habitat structure. An increase in habitat cover appeared to favour higher densities of H. guttulatus when seining effort was reduced. By contrast, repeated seining, which maintained less complex habitats, appeared to favour greater abundances of H. hippocampus. 5. Given differences in habitat preference among benthic marine fishes subject to incidental capture in fisheries, simultaneous attempts to manage populations of sympatric species may require complementary strategies that support the persistence of diverse habitat types. Copyright (c) 2006 John Wiley & Sons, Ltd.

Do synergies improve accuracy? A study of speed-accuracy trade-offs during finger force production

We explored possible effects of negative covariation among finger forces in multifinger accurate force production tasks on the classical Fitts's speed-accuracy trade-off. Healthy subjects performed cyclic force changes between pairs of targets ""as quickly and accurately as possible."" Tasks with two force amplitudes and six ratics of force amplitude to target size were performed by each of the four fingers of the right hand and four finger combinations. There was a close to linear relation between movement time and the log-transformed ratio of target amplitude to target size across all finger combinations. There was a close to linear relation between standard deviation of force amplitude and movement time. There were no differences between the performance of either of the two ""radial"" fingers (index and middle) and the multifinger tasks. The ""ulnar"" fingers (little and ring) showed higher indices of variability and longer movement times as compared with both ""radial"" fingers and multifinger combinations. We conclude that potential effects of the negative covariation and also of the task-sharing across a set of fingers are counterbalanced by an increase in individual finger force variability in multifinger tasks as compared with single-finger tasks. The results speak in favor of a feed-forward model of multifinger synergies. They corroborate a hypothesis that multifinger synergies are created not to improve overall accuracy, but to allow the system larger flexibility, for example to deal with unexpected perturbations and concomitant tasks.

The constancy of global regulation across a species: the concentrations of ppGpp and RpoS are strain-specific in Escherichia coli

Background: Sigma factors and the alarmone ppGpp control the allocation of RNA polymerase to promoters under stressful conditions. Both ppGpp and the sigma factor sigma(S) (RpoS) are potentially subject to variability across the species Escherichia coli. To find out the extent of strain variation we measured the level of RpoS and ppGpp using 31 E. coli strains from the ECOR collection and one reference K-12 strain. Results: Nine ECORs had highly deleterious mutations in rpoS, 12 had RpoS protein up to 7-fold above that of the reference strain MG1655 and the remainder had comparable or lower levels. Strain variation was also evident in ppGpp accumulation under carbon starvation and spoT mutations were present in several low-ppGpp strains. Three relationships between RpoS and ppGpp levels were found: isolates with zero RpoS but various ppGpp levels, strains where RpoS levels were proportional to ppGpp and a third unexpected class in which RpoS was present but not proportional to ppGpp concentration. High-RpoS and high-ppGpp strains accumulated rpoS mutations under nutrient limitation, providing a source of polymorphisms. Conclusions: The ppGpp and sigma(S) variance means that the expression of genes involved in translation, stress and other traits affected by ppGpp and/or RpoS are likely to be strain-specific and suggest that influential components of regulatory networks are frequently reset by microevolution. Different strains of E. coli have different relationships between ppGpp and RpoS levels and only some exhibit a proportionality between increasing ppGpp and RpoS levels as demonstrated for E. coli K-12.

O risco do custo e do tempo no escanamento de projetos

Dissertação apresentada ao Instituto Politécnico do Porto para obtenção do Grau de Mestre em Logística Orientada por: Prof. Dr. Pedro Godinho

A long-term swarm intelligence hedging tool applied to electricity markets

This paper proposes a swarm intelligence long-term hedging tool to support electricity producers in competitive electricity markets. This tool investigates the long-term hedging opportunities available to electric power producers through the use of contracts with physical (spot and forward) and financial (options) settlement. To find the optimal portfolio the producer risk preference is stated by a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance estimation and the expected return are based on a forecasted scenario interval determined by a long-term price range forecast model, developed by the authors, whose explanation is outside the scope of this paper. The proposed tool makes use of Particle Swarm Optimization (PSO) and its performance has been evaluated by comparing it with a Genetic Algorithm (GA) based approach. To validate the risk management tool a case study, using real price historical data for mainland Spanish market, is presented to demonstrate the effectiveness of the proposed methodology.

A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn.