Risk management for mathematical optimization under uncertainty

We present a general multistage stochastic mixed 0-1 problem where the uncertainty appears everywhere in the objective function, constraints matrix and right-hand-side. The uncertainty is represented by a scenario tree that can be a symmetric or a nonsymmetric one. The stochastic model is converted in a mixed 0-1 Deterministic Equivalent Model in compact representation. Due to the difficulty of the problem, the solution offered by the stochastic model has been traditionally obtained by optimizing the objective function expected value (i.e., mean) over the scenarios, usually, along a time horizon. This approach (so named risk neutral) has the inconvenience of providing a solution that ignores the variance of the objective value of the scenarios and, so, the occurrence of scenarios with an objective value below the expected one. Alternatively, we present several approaches for risk averse management, namely, a scenario immunization strategy, the optimization of the well known Value-at-Risk (VaR) and several variants of the Conditional Value-at-Risk strategies, the optimization of the expected mean minus the weighted probability of having a "bad" scenario to occur for the given solution provided by the model, the optimization of the objective function expected value subject to stochastic dominance constraints (SDC) for a set of profiles given by the pairs of threshold objective values and either bounds on the probability of not reaching the thresholds or the expected shortfall over them, and the optimization of a mixture of the VaR and SDC strategies.

Dendroecology of Araucaria angustifolia under two geomorphological conditions in the seasonal semideciduous forest and mixed ombrophilous forest ecotone of Paraná, Brazil.

2016

Experimental and analytical study of cracks under biaxial fatigue

Most mechanical components experience multi-axial cyclic loading conditions during service. Experimental analysis of fatigue cracks under such conditions is not easy and most works tend to focus more on the simpler but less realistic case of uni-axial loading. Consequently, there are many uncertainties related to the load sequence effect that are now well known and are not normally incorporated into the growth models. The current work presents a new methodology for evaluating overload effect in biaxial fatigue cracks. The methodology includes evaluation of mixed-mode (KI and KII) stress intensity factor and the Crack Opening Displacement for samples with and without overload cycle under biaxial loading. The methodology is tested under a range of crack lengths. All crack-tip information is obtained with a hybrid methodology that combines experimental full-field digital image correlation data and Williams' elastic model describing the crack-tip field.

Selection and Passage of County Land Preservation Voter Referendum: The Role of Government

County jurisdictions in America are increasingly exercising self-government in the provision of public community services through the context of second order federalism. In states exercising this form of contemporary governance, county governments with “reformed” policy-making structures and professional management practices, have begun to rival or surpass municipalities in the delivery of local services with regional implications such as environmental protection (Benton 2002, 2003; Marando and Reeves, 1993). The voter referendum, a form of direct democracy, is an important component of county land preservation and environmental protection governmental policies. The recent growth and success of land preservation voter referendums nationwide reflects an increase in citizen participation in government and their desire to protect vacant land and its natural environment from threats of over-development, urbanization and sprawl, loss of open space and farmland, deterioration of ecosystems, and inadequate park and recreational amenities. The study’s design employs a sequential, mixed method. First, a quantitative approach employs the Heckman two-step model. It is fitted with variables for the non-random sample of 227 voter referendum counties and all non-voter referendum counties in the U.S. from 1988 to 2009. Second, the qualitative data collected from the in-depth investigation of three South Florida county case studies with twelve public administrator interviews is transformed for integration with the quantitative findings. The purpose of the qualitative method is to complement, explain and enrich the statistical analysis of county demographic, socio-economic, terrain, regional, governance and government, political preference, environmentalism, and referendum-specific factors. The research finds that government factors are significant in terms of the success of land preservation voter referendums; more specifically, the presence of self-government authority (home rule charter), a reformed structure (county administrator/manager or elected executive), and environmental interest groups. In addition, this study concludes that successful counties are often located coastal, exhibit population and housing growth, and have older and more educated citizens who vote democratic in presidential elections. The analysis of case study documents and public administrator interviews finds that pragmatic considerations of timing, local politics and networking of regional stakeholders are also important features of success. Further research is suggested utilizing additional public participation, local government and public administration factors.

Reindeer habitat selection under the risk of brown bear predation during calving season

The depredation of semi-domesticated reindeer by large carnivores reflects an important human-wildlife conflict in Fennoscandia. Recent studies have revealed that brown bears (Ursus arctos) may kill substantial numbers of reindeer calves (Rangifer tarandus tarandus) in forest areas in Sweden. Several authors have suggested that predation risk is an important driver of habitat selection in wild Rangifer populations where predation is a limiting factor, but little is known about these mechanisms in semi-domesticated populations. We examined the habitat selection of female reindeer in relation to spatial and temporal variations in brown bear predation risk on the reindeer calving grounds and evaluated the simultaneous responses of brown bears and reindeer to landscape characteristics. We used GPS data from 110 reindeer years (97 individuals) and 29 brown bear years (19 individuals), from two reindeer herding districts in the forest area of northern Sweden. Our results did not indicate that reindeer alter their behavior in response to spatiotemporal variation in brown bear predation risk, on the scale of the calving range. Instead, we suggest that spatiotemporal behavioral adjustments by brown bears were the main driver of prey-predator interactions in our study system. Contrasting responses by brown bears and reindeer to clear-cuts and young forest indicate that forestry can influence species interactions and possibly yield negative consequences for the reindeer herd. Even if clear-cuts may be beneficial in terms of calf survival, logging activity will eventually cause greater abundance of young regenerating forest, reducing available reindeer habitats and increasing habitat preferred by brown bears. Domestication may have made semi-domesticated reindeer in Fennoscandia less adapted to cope with predators. Areal restrictions, limiting the opportunity for dispersion and escape, possibly make the calves more susceptible to predation. Also, a generally higher population density in semi-domesticated herds compared to wild populations can make dispersion a less efficient strategy and the reindeer calves easier prey. Overall, the lack of ability of the reindeer females to reduce brown bear encounter risk on the scale of the calving range is probably an important reason for the high brown bear predation rates on reindeer calves documented in our study areas. 

The Selection Process of Applications to the Portuguese Innovation Incentive System: Who Gets Financial Support?

Public policies to support entrepreneurship and innovation play a vital role when firms have difficulties in accessing external finance. However, some authors have found evidence of long-term inefficiency in subsidized firms (Bernini and Pelligrini, 2011; Cerqua and Pelligrini, 2014) and ineffectiveness of public funds (Jorge and Suárez, 2011). The aim of the paper is to assess the effectiveness in the selection process of applications to public financial support for stimulating innovation. Using a binary choice model, we investigate which factors influence the probability of obtaining public support for an innovative investment. The explanatory variables are connected to firm profile, the characteristics of the project and the macroeconomic environment. The analysis is based on the case study of the Portuguese Innovation.Incentive System (PIIS) and on the applications managed by the Alentejo Regional Operational Program in the period 2007 – 2013. The results show that the selection process is more focused on the expected impact of the project than on the firm’s past performance. Factors that influence the credit risk and the decision to grant a bank loan do not seem to influence the government evaluator regarding the funding of some projects. Past activities in R&D do not significantly affect the probability of having an application approved under the PIIS, whereas an increase in the number of patents and the number of skilled jobs are both relevant factors. Nevertheless, some evidence of firms’ short-term inefficiency was found, in that receiving public financial support is linked to a smaller increase in productivity compared to non-approved firm applications. At the macroeconomic level, periods with a higher cost of capital in financial markets are linked to a greater probability of getting an application for public support approved, which could be associated with the effectiveness of public support in correcting market failings.

Biological nitrogen fixation and nutrient release from litter of the guachapele leguminous tree under pure and mixed plantation with eucalyptus.

A Pseudosamanea guachapele (guachapele), leguminosa arbórea fixadora de nitrogênio, é uma alternativa para plantios florestais mistos nos trópicos. Como são escassas as informações sobre a espécie em plantios mistos de eucalipto em condições edafoclimáticas brasileiras, foi conduzido um experimento no qual objetivou-se avaliar a contribuição da fixação biológica de nitrogênio para a guachapele e a velocidade de decomposição e de liberação de nutrientes de folhas senescentes de eucalipto e guachapele (oriundas dos plantios puros e consorciado). A porcentagem de N derivado da atmosfera (% Ndfa) foi estimada comparando-se a abundância natural de 15N ( 15N, ) nos tecidos da guachapele com a observada nos tecidos do Eucalyptus grandis, espécie não fixadora, ambas com sete anos de idade. A constante de decomposição (k) e a meia-vida (t1/2) de serapilheira foram estimadas utilizando-se o modelo exponencial aplicado aos dados oriundos de coletas de litterbags. A estimativa da %Ndfa para guachapele, em condições de plantio puro, variou de 17 a 36%, enquanto que, em condições de plantio consorciado, foi de 35 a 60 %. A concentração de N nas folhas senescentes estava positivamente relacionada com a taxa de decomposição, sendo essa decrescente da guachapele para o eucalipto. A t1/2 dos resíduos diferiu significativamente (p < 0.05), sendo de 148, 185 e 218 dias para as folhas de guachapele, mistura das duas espécies e eucalipto, respectivamente. A liberação dos nutrientes (principalmente N, K e Mg) das folhas seguiu a mesma ordem da t1/2 devido à qualidade inicial das mesmas. Os resultados indicam que a guachapele pode beneficiar o plantio misto pela adição de N e por meio da intensificação da decomposição da serapilheira.

Assessing the fit of unidimensional IRT models for binary data under model misspecification

Model misspecification affects the classical test statistics used to assess the fit of the Item Response Theory (IRT) models. Robust tests have been derived under model misspecification, as the Generalized Lagrange Multiplier and Hausman tests, but their use has not been largely explored in the IRT framework. In the first part of the thesis, we introduce the Generalized Lagrange Multiplier test to detect differential item response functioning in IRT models for binary data under model misspecification. By means of a simulation study and a real data analysis, we compare its performance with the classical Lagrange Multiplier test, computed using the Hessian and the cross-product matrix, and the Generalized Jackknife Score test. The power of these tests is computed empirically and asymptotically. The misspecifications considered are local dependence among items and non-normal distribution of the latent variable. The results highlight that, under mild model misspecification, all tests have good performance while, under strong model misspecification, the performance of the tests deteriorates. None of the tests considered show an overall superior performance than the others. In the second part of the thesis, we extend the Generalized Hausman test to detect non-normality of the latent variable distribution. To build the test, we consider a seminonparametric-IRT model, that assumes a more flexible latent variable distribution. By means of a simulation study and two real applications, we compare the performance of the Generalized Hausman test with the M2 limited information goodness-of-fit test and the Likelihood-Ratio test. Additionally, the information criteria are computed. The Generalized Hausman test has a better performance than the Likelihood-Ratio test in terms of Type I error rates and the M2 test in terms of power. The performance of the Generalized Hausman test and the information criteria deteriorates when the sample size is small and with a few items.

Model selection and the vectorial misspecification-resistant information criterion in multivariate time series

The thesis deals with the problem of Model Selection (MS) motivated by information and prediction theory, focusing on parametric time series (TS) models. The main contribution of the thesis is the extension to the multivariate case of the Misspecification-Resistant Information Criterion (MRIC), a criterion introduced recently that solves Akaike’s original research problem posed 50 years ago, which led to the definition of the AIC. The importance of MS is witnessed by the huge amount of literature devoted to it and published in scientific journals of many different disciplines. Despite such a widespread treatment, the contributions that adopt a mathematically rigorous approach are not so numerous and one of the aims of this project is to review and assess them. Chapter 2 discusses methodological aspects of MS from information theory. Information criteria (IC) for the i.i.d. setting are surveyed along with their asymptotic properties; and the cases of small samples, misspecification, further estimators. Chapter 3 surveys criteria for TS. IC and prediction criteria are considered for: univariate models (AR, ARMA) in the time and frequency domain, parametric multivariate (VARMA, VAR); nonparametric nonlinear (NAR); and high-dimensional models. The MRIC answers Akaike’s original question on efficient criteria, for possibly-misspecified (PM) univariate TS models in multi-step prediction with high-dimensional data and nonlinear models. Chapter 4 extends the MRIC to PM multivariate TS models for multi-step prediction introducing the Vectorial MRIC (VMRIC). We show that the VMRIC is asymptotically efficient by proving the decomposition of the MSPE matrix and the consistency of its Method-of-Moments Estimator (MoME), for Least Squares multi-step prediction with univariate regressor. Chapter 5 extends the VMRIC to the general multiple regressor case, by showing that the MSPE matrix decomposition holds, obtaining consistency for its MoME, and proving its efficiency. The chapter concludes with a digression on the conditions for PM VARX models.

Characterization of ENSO changes under idealised radiative forcing in an intermediate complexity general circulation model

Intermediate-complexity general circulation models are a fundamental tool to investigate the role of internal and external variability within the general circulation of the atmosphere and ocean. The model used in this thesis is an intermediate complexity atmospheric general circulation model (SPEEDY) coupled to a state-of-the-art modelling framework for the ocean (NEMO). We assess to which extent the model allows a realistic simulation of the most prominent natural mode of variability at interannual time scales: El-Niño Southern Oscillation (ENSO). To a good approximation, the model represents the ENSO-induced Sea Surface Temperature (SST) pattern in the equatorial Pacific, despite a cold tongue-like bias. The model underestimates (overestimates) the typical ENSO spatial variability during the winter (summer) seasons. The mid-latitude response to ENSO reveals that the typical poleward stationary Rossby wave train is reasonably well represented. The spectral decomposition of ENSO features a spectrum that lacks periodicity at high frequencies and is overly periodic at interannual timescales. We then implemented an idealised transient mean state change in the SPEEDY model. A warmer climate is simulated by an alteration of the parametrized radiative fluxes that corresponds to doubled carbon dioxide absorptivity. Results indicate that the globally averaged surface air temperature increases of 0.76 K. Regionally, the induced signal on the SST field features a significant warming over the central-western Pacific and an El-Niño-like warming in the subtropics. In general, the model features a weakening of the tropical Walker circulation and a poleward expansion of the local Hadley cell. This response is also detected in a poleward rearrangement of the tropical convective rainfall pattern. The model setting that has been here implemented provides a valid theoretical support for future studies on climate sensitivity and forced modes of variability under mean state changes.

Design and management of a supply chain: a joint location-inventory problem under uncertainty (Part A)

In this paper, a joint location-inventory model is proposed that simultaneously optimises strategic supply chain design decisions such as facility location and customer allocation to facilities, and tactical-operational inventory management and production scheduling decisions. All this is analysed in a context of demand uncertainty and supply uncertainty. While demand uncertainty stems from potential fluctuations in customer demands over time, supply-side uncertainty is associated with the risk of “disruption” to which facilities may be subject. The latter is caused by external factors such as natural disasters, strikes, changes of ownership and information technology security incidents. The proposed model is formulated as a non-linear mixed integer programming problem to minimise the expected total cost, which includes four basic cost items: the fixed cost of locating facilities at candidate sites, the cost of transport from facilities to customers, the cost of working inventory, and the cost of safety stock. Next, since the optimisation problem is very complex and the number of evaluable instances is very low, a "matheuristic" solution is presented. This approach has a twofold objective: on the one hand, it considers a larger number of facilities and customers within the network in order to reproduce a supply chain configuration that more closely reflects a real-world context; on the other hand, it serves to generate a starting solution and perform a series of iterations to try to improve it. Thanks to this algorithm, it was possible to obtain a solution characterised by a lower total system cost than that observed for the initial solution. The study concludes with some reflections and the description of possible future insights.

In vitro Microfluidic Model For The Study Of Vaso-occlusive Processes.

Vaso-occlusion, responsible for much of the morbidity of sickle-cell disease, is a complex multicellular process, apparently triggered by leukocyte adhesion to the vessel wall. The microcirculation represents a major site of leukocyte-endothelial interactions and vaso-occlusive processes. We have developed a biochip with subdividing interconnecting microchannels that decrease in size (40 μm to 10 μm in width), for use in conjunction with a precise microfluidic device, to mimic cell flow and adhesion through channels of sizes that approach those of the microcirculation. The biochips were utilized to observe the dynamics of the passage of neutrophils and red blood cells, isolated from healthy and sickle-cell anemia (SCA) individuals, through laminin or endothelial adhesion molecule-coated microchannels at physiologically relevant rates of flow and shear stress. Obstruction of E-selectin/intercellular adhesion molecule 1-coated biochip microchannels by SCA neutrophils was significantly greater than that observed for healthy neutrophils, particularly in the microchannels of 40-15 μm in width. Whereas SCA red blood cells alone did not significantly adhere to, or obstruct, microchannels, mixed suspensions of SCA neutrophils and red blood cells significantly adhered to and obstructed laminin-coated channels. Results from this in vitro microfluidic model support a primary role for leukocytes in the initiation of SCA occlusive processes in the microcirculation. This assay represents an easy-to-use and reproducible in vitro technique for understanding molecular mechanisms and cellular interactions occurring in subdividing microchannels of widths approaching those observed in the microvasculature. The assay could hold potential for testing drugs developed to inhibit occlusive mechanisms such as those observed in SCA and thrombotic diseases.

Viability of using enamel and dentin from bovine origin as a substitute for human counterparts in an intraoral erosion model

This study ascertained whether under dental erosion models that closely mimics the real-life situation enamel and root dentin from bovine origin would be reliable substitutes for human counterparts. Through a 2x2 crossover design, in a first trial, 14 volunteers wore a palatal device containing slabs of bovine and human enamel. Half of the participants ingested (4x daily, for 10 days) orange juice first, crossing over to mineral water, while the remainder received the reverse sequence. In a second trial, volunteers wore devices with slabs of bovine and human root dentin. Except for the duration of each intraoral phase, which lasted 2 rather 10 days, the experiment with root dentin run exactly as for enamel. Dental substrates were analyzed for surface microhardness. Two-way ANOVAs (α=0.05) indicated no difference between the microhardness values recorded for human and bovine enamel (p=0.1350), but bovine root dentin had lower microhardness compared to its human counterpart (p=0.0432). While bovine enamel can reliably substitute its human counterpart in in situ dental erosion models, bovine root dentin does not seem to be a viable alternative to the corresponding human tissue.

Spatial pattern detection modeling of thrips (Thrips tabaci) on onion fields

Onion (Allium cepa) is one of the most cultivated and consumed vegetables in Brazil and its importance is due to the large laborforce involved. One of the main pests that affect this crop is the Onion Thrips (Thrips tabaci), but the spatial distribution of this insect, although important, has not been considered in crop management recommendations, experimental planning or sampling procedures. Our purpose here is to consider statistical tools to detect and model spatial patterns of the occurrence of the onion thrips. In order to characterize the spatial distribution pattern of the Onion Thrips a survey was carried out to record the number of insects in each development phase on onion plant leaves, on different dates and sample locations, in four rural properties with neighboring farms under different infestation levels and planting methods. The Mantel randomization test proved to be a useful tool to test for spatial correlation which, when detected, was described by a mixed spatial Poisson model with a geostatistical random component and parameters allowing for a characterization of the spatial pattern, as well as the production of prediction maps of susceptibility to levels of infestation throughout the area.

Stress distribution in the cervical region of an upper central incisor in a 3D finite element model

The aim of this study was to evaluate the stress distribution in the cervical region of a sound upper central incisor in two clinical situations, standard and maximum masticatory forces, by means of a 3D model with the highest possible level of fidelity to the anatomic dimensions. Two models with 331,887 linear tetrahedral elements that represent a sound upper central incisor with periodontal ligament, cortical and trabecular bones were loaded at 45º in relation to the tooth's long axis. All structures were considered to be homogeneous and isotropic, with the exception of the enamel (anisotropic). A standard masticatory force (100 N) was simulated on one of the models, while on the other one a maximum masticatory force was simulated (235.9 N). The software used were: PATRAN for pre- and post-processing and Nastran for processing. In the cementoenamel junction area, tensile forces reached 14.7 MPa in the 100 N model, and 40.2 MPa in the 235.9 N model, exceeding the enamel's tensile strength (16.7 MPa). The fact that the stress concentration in the amelodentinal junction exceeded the enamel's tensile strength under simulated conditions of maximum masticatory force suggests the possibility of the occurrence of non-carious cervical lesions such as abfractions.