Food Swamps, Obesity & Health Zoning Restrictions on Fast Food Restaurants

Protecting public health is the most legitimate use of zoning, and yet there is minimal progress in applying it to the obesity problem. Zoning could potentially be used to address both unhealthy and healthy food retailers, but lack of evidence regarding the impact of zoning and public opinion on zoning changes are barriers to implementing zoning restrictions on fast food on a larger scale. My dissertation addresses these gaps in our understanding of health zoning as a policy option for altering built, food environments.

Chapter 1 examines the relationship between food swamps and obesity and whether spatial mapping might be useful in identifying priority geographic areas for zoning interventions. I employ an instrumental variables (IV) strategy to correct for the endogeneity problems associated with food environments, namely that individuals may self-select into certain neighborhoods and may consider food availability in their decision process. I utilize highway exits as a source of exogenous variation .Using secondary data from the USDA Food Environment Atlas, ordinary least squares (OLS) and IV regression models were employed to analyze cross-sectional associations between local food environments and the prevalence of obesity. I find even after controlling for food desert effects, food swamps have a positive, statistically significant effect on adult obesity rates.

Chapter 2 applies theories of message framing and prospect theory to the emerging discussion around health zoning policies targeting food environments and to explore public opinion toward a list of potential zoning restrictions on fast-food restaurants (beyond moratoriums on new establishments). In order to explore causality, I employ an online survey experiment manipulating exposure to vignettes with different message frames about health zoning restrictions with two national samples of adult Americans age 18 and over (N1=2,768 and N2=3,236). The second sample oversamples Black Americans (N=1,000) and individuals with high school as their highest level of education. Respondents were randomly assigned to one of six conditions where they were primed with different message frames about the benefits of zoning restrictions on fast food retailers. Participants were then asked to indicate their support for six zoning policies on a Likert scale. Subjects also answered questions about their food store access, eating behaviors, health status and perceptions of food stores by type.

I find that a message frame about Nutrition and increasing Equity in the food system was particularly effective at increasing support for health zoning policies targeting fast food outlets across policy categories (Conditional, Youth-related, Performance and Incentive) and across racial groups. This finding is consistent with an influential environmental justice scholar’s description of “injustice frames” as effective in mobilizing supporters around environmental issues (Taylor 2000). I extend this rationale to food environment obesity prevention efforts and identify Nutrition combined with Equity frames as an arguably universal campaign strategy for bolstering public support of zoning restrictions on fast food retailers.

Bridging my findings from both Chapters 1 and 2, using food swamps as a spatial metaphor may work to identify priority areas for policy intervention, but only if there is an equitable distribution of resources and mobilization efforts to improve consumer food environments. If the structural forces which ration access to land-use planning persist (arguably including the media as gatekeepers to information and producers of message frames) disparities in obesity are likely to widen.

A recessionary debate: who suffered more? A study of sectoral well-being and economic insecurity in Ireland

The aim of this thesis is to identify the relationship between subjective well-being and economic insecurity for public and private sector workers in Ireland using the European Social Survey 2010-2012. Life satisfaction and job satisfaction are the indicators used to measure subjective well-being. Economic insecurity is approximated by regional unemployment rates and self-perceived job insecurity. Potential sample selection bias and endogeneity bias are accounted for. It is traditionally believed that public sector workers are relatively more protected against insecurity due to very institution of public sector employment. The institution of public sector employment is made up of stricter dismissal practices (Luechinger et al., 2010a) and less volatile employment (Freeman, 1987) where workers are subsequently less likely to be affected by business cycle downturns (Clark and Postal-Vinay, 2009). It is found in the literature that economic insecurity depresses the well-being of public sector workers to a lesser degree than private sector workers (Luechinger et al., 2010a; Artz and Kaya, 2014). These studies provide the rationale for this thesis in testing for similar relationships in an Irish context. Sample selection bias arises when a selection into a particular category is not random (Heckman, 1979). An example of this is non-random selection into public sector employment based on personal characteristics (Heckman, 1979; Luechinger et al., 2010b). If selection into public sector employment is not corrected for this can lead to biased and inconsistent estimators (Gujarati, 2009). Selection bias of public sector employment is corrected for by using a standard Two-Step Heckman Probit OLS estimation method. Following Luechinger et al. (2010b), the propensity for individuals to select into public sector employment is estimated by a binomial probit model with the inclusion of the additional regressor Irish citizenship. Job satisfaction is then estimated by Ordinary Least Squares (OLS) with the inclusion of a sample correction term similar as is done in Clark (1997). Endogeneity is where an independent variable included in the model is determined within in the context of the model (Chenhall and Moers, 2007). The econometric definition states that an endogenous independent variable is one that is correlated with the error term (Wooldridge, 2010). Endogeneity is expected to be present due to a simultaneous relationship between job insecurity and job satisfaction whereby both variables are jointly determined (Theodossiou and Vasileiou, 2007). Simultaneity, as an instigator of endogeneity, is corrected for using Instrumental Variables (IV) techniques. Limited Information Methods and Full Information Methods of estimation of simultaneous equations models are assed and compared. The general results show that job insecurity depresses the subjective well-being of all workers in both the public and private sectors in Ireland. The magnitude of this effect differs among sectoral workers. The subjective well-being of private sector workers is more adversely affected by job insecurity than the subjective well-being of public sector workers. This is observed in basic ordered probit estimations of both a life satisfaction equation and a job satisfaction equation. The marginal effects from the ordered probit estimation of a basic job satisfaction equation show that as job insecurity increases the probability of reporting a 9 on a 10-point job satisfaction scale significantly decreases by 3.4% for the whole sample of workers, 2.8% for public sector workers and 4.0% for private sector workers. Artz and Kaya (2014) explain that as a result of many austerity policies implemented to reduce government expenditure during the economic recession, workers in the public sector may for the first time face worsening perceptions of job security which can have significant implications for their well-being (Artz and Kaya, 2014). This can be observed in the marginal effects where job insecurity negatively impacts the well-being of public sector workers in Ireland. However, in accordance with Luechinger et al. (2010a) the results show that private sector workers are more adversely impacted by economic insecurity than public sector workers. This suggests that in a time of high economic volatility, the institution of public sector employment held and was able to protect workers against some of the well-being consequences of rising insecurity. In estimating the relationship between subjective well-being and economic insecurity advanced econometric issues arise. The results show that when selection bias is corrected for, any statistically significant relationship between job insecurity and job satisfaction disappears for public sector workers. Additionally, in order to correct for endogeneity bias the simultaneous equations model for job satisfaction and job insecurity is estimated by Limited Information and Full Information Methods. The results from two different estimators classified as Limited Information Methods support the general findings of this research. Moreover, the magnitude of the endogeneity-corrected estimates are twice as large as those not corrected for endogeneity bias which is similarly found in Geishecker (2010, 2012). As part of the analysis into the effect of economic insecurity on subjective well-being, the effects of other socioeconomic variables and work-related variables are examined for public and private sector workers in Ireland.

A 3.6 Ma sedimentological, geochemical and palynological record of sediment core ICDP5011-1 in Lake Elgygytgyn, NE Russia

Understanding the evolution of Arctic polar climate from the protracted warmth of the middle Pliocene into the earliest glacial cycles in the Northern Hemisphere has been hindered by the lack of continuous, highly resolved Arctic time series. Evidence from Lake El'gygytgyn, NE Arctic Russia, shows that 3.6-3.4 million years ago, summer temperatures were ~8°C warmer than today when pCO2 was ~400 ppm. Multiproxy evidence suggests extreme warmth and polar amplification during the middle Pliocene, sudden stepped cooling events during the Pliocene-Pleistocene transition, and warmer than present Arctic summers until ~2.2 Ma, after the onset of Northern Hemispheric glaciation. Our data are consistent with sea-level records and other proxies indicating that Arctic cooling was insufficient to support large-scale ice sheets until the early Pleistocene.

Application of computer-aided tomography techniques to visualize kelp holdfast structure reveals the importance of habitat complexity for supporting marine biodiversity

Ecosystem engineers that increase habitat complexity are keystone species in marine systems, increasing shelter and niche availability, and therefore biodiversity. For example, kelp holdfasts form intricate structures and host the largest number of organisms in kelp ecosystems. However, methods that quantify 3D habitat complexity have only seldom been used in marine habitats, and never in kelp holdfast communities. This study investigated the role of kelp holdfasts (Laminaria hyperborea) in supporting benthic faunal biodiversity. Computer-aided tomography (CT-) scanning was used to quantify the three-dimensional geometrical complexity of holdfasts, including volume, surface area and surface fractal dimension (FD). Additionally, the number of haptera, number of haptera per unit of volume, and age of kelps were estimated. These measurements were compared to faunal biodiversity and community structure, using partial least-squares regression and multivariate ordination. Holdfast volume explained most of the variance observed in biodiversity indices, however all other complexity measures also strongly contributed to the variance observed. Multivariate ordinations further revealed that surface area and haptera per unit of volume accounted for the patterns observed in faunal community structure. Using 3D image analysis, this study makes a strong contribution to elucidate quantitative mechanisms underlying the observed relationship between biodiversity and habitat complexity. Furthermore, the potential of CT-scanning as an ecological tool is demonstrated, and a methodology for its use in future similar studies is established. Such spatially resolved imager analysis could help identify structurally complex areas as biodiversity hotspots, and may support the prioritization of areas for conservation.

Application of computer-aided tomography techniques to visualize kelp holdfast structure reveals the importance of habitat complexity for supporting marine biodiversity

Ecosystem engineers that increase habitat complexity are keystone species in marine systems, increasing shelter and niche availability, and therefore biodiversity. For example, kelp holdfasts form intricate structures and host the largest number of organisms in kelp ecosystems. However, methods that quantify 3D habitat complexity have only seldom been used in marine habitats, and never in kelp holdfast communities. This study investigated the role of kelp holdfasts (Laminaria hyperborea) in supporting benthic faunal biodiversity. Computer-aided tomography (CT-) scanning was used to quantify the three-dimensional geometrical complexity of holdfasts, including volume, surface area and surface fractal dimension (FD). Additionally, the number of haptera, number of haptera per unit of volume, and age of kelps were estimated. These measurements were compared to faunal biodiversity and community structure, using partial least-squares regression and multivariate ordination. Holdfast volume explained most of the variance observed in biodiversity indices, however all other complexity measures also strongly contributed to the variance observed. Multivariate ordinations further revealed that surface area and haptera per unit of volume accounted for the patterns observed in faunal community structure. Using 3D image analysis, this study makes a strong contribution to elucidate quantitative mechanisms underlying the observed relationship between biodiversity and habitat complexity. Furthermore, the potential of CT-scanning as an ecological tool is demonstrated, and a methodology for its use in future similar studies is established. Such spatially resolved imager analysis could help identify structurally complex areas as biodiversity hotspots, and may support the prioritization of areas for conservation.

Fatores críticos de sucesso como antecedentes da aceitação de um sistema de informação em uma universidade federal

In recent decades the public sector comes under pressure in order to improve its performance. The use of Information Technology (IT) has been a tool increasingly used in reaching that goal. Thus, it has become an important issue in public organizations, particularly in institutions of higher education, determine which factors influence the acceptance and use of technology, impacting on the success of its implementation and the desired organizational results. The Technology Acceptance Model - TAM was used as the basis for this study and is based on the constructs perceived usefulness and perceived ease of use. However, when it comes to integrated management systems due to the complexity of its implementation,organizational factors were added to thus seek further explanation of the acceptance of such systems. Thus, added to the model five TAM constructs related to critical success factors in implementing ERP systems, they are: support of top management, communication, training, cooperation, and technological complexity (BUENO and SALMERON, 2008). Based on the foregoing, launches the following research problem: What factors influence the acceptance and use of SIE / module academic at the Federal University of Para, from the users' perception of teachers and technicians? The purpose of this study was to identify the influence of organizational factors, and behavioral antecedents of behavioral intention to use the SIE / module academic UFPA in the perspective of teachers and technical users. This is applied research, exploratory and descriptive, quantitative with the implementation of a survey, and data collection occurred through a structured questionnaire applied to a sample of 229 teachers and 30 technical and administrative staff. Data analysis was carried out through descriptive statistics and structural equation modeling with the technique of partial least squares (PLS). Effected primarily to assess the measurement model, which were verified reliability, convergent and discriminant validity for all indicators and constructs. Then the structural model was analyzed using the bootstrap resampling technique like. In assessing statistical significance, all hypotheses were supported. The coefficient of determination (R ²) was high or average in five of the six endogenous variables, so the model explains 47.3% of the variation in behavioral intention. It is noteworthy that among the antecedents of behavioral intention (BI) analyzed in this study, perceived usefulness is the variable that has a greater effect on behavioral intention, followed by ease of use (PEU) and attitude (AT). Among the organizational aspects (critical success factors) studied technological complexity (TC) and training (ERT) were those with greatest effect on behavioral intention to use, although these effects were lower than those produced by behavioral factors (originating from TAM). It is pointed out further that the support of senior management (TMS) showed, among all variables, the least effect on the intention to use (BI) and was followed by communications (COM) and cooperation (CO), which exert a low effect on behavioral intention (BI). Therefore, as other studies on the TAM constructs were adequate for the present research. Thus, the study contributed towards proving evidence that the Technology Acceptance Model can be applied to predict the acceptance of integrated management systems, even in public. Keywords: Technology

Prediction of Sudden Cardiac Arrest for Patients with Congestive Heart Failure

Thesis (Ph.D.)--University of Washington, 2016-07

Using Surface Spectroscopy to Help Interpret STM Images of Chemisorbed Molecules: Application to the Study of the Hydrogenation of Ketones and a-Ketoesters on Pt

Depuis que la haute énantiopureté est nécessaire dans l’industrie pharmaceutique, les études visant à découvrir les mécanismes pour l’hydrogénation énantiosélective de cétones ou céto-esters sur les surfaces, et à rechercher de nouveaux et plus performants catalyseurs asymétriques, sont d’une grande importance. La microscopie à effet tunnel (STM), la spectroscopie infrarouge de réflexion-absorption, la spectroscopie de désorption à température programmée et la spectrométrie de photoélectrons induits par rayons X sont des méthodes performantes facilitant la compréhension des mécanismes de réaction. En plus de nous permettre de comprendre les mécanismes réactionnels, les études peuvent fournir des informations sur la dynamique des réactions en catalyse hétérogène ainsi que sur le développement de la théorie de la fonctionnelle de la densité (DFT) afin de calculer des interactions faibles dans les processus de surface. D’autres parts, les calculs DFT fournissent une aide essentielle à l’interprétation des données de STM et spectroscopie de surface. Dans cette thèse, certains cétones et céto-esters sur la surface de platine sont étudiées par les techniques sophistiquées mentionnées ci-dessus. Mes études démontrent que la combinaison de l’utilisation de la spectroscopie de routine, des nanotechnologies et de nombreux calculs élaborés, est une méthode efficace pour étudier les réactions à la surface car ces techniques explorent les différents aspects de la surface ainsi que s’entraident mutuellement lors de certaines interprétations.

Capital structure of Finnish firms – Estimating the effects of firm characteristics on capital structure

One of the most disputable matters in the theory of finance has been the theory of capital structure. The seminal contributions of Modigliani and Miller (1958, 1963) gave rise to a multitude of studies and debates. Since the initial spark, the financial literature has offered two competing theories of financing decision: the trade-off theory and the pecking order theory. The trade-off theory suggests that firms have an optimal capital structure balancing the benefits and costs of debt. The pecking order theory approaches the firm capital structure from information asymmetry perspective and assumes a hierarchy of financing, with firms using first internal funds, followed by debt and as a last resort equity. This thesis analyses the trade-off and pecking order theories and their predictions on a panel data consisting 78 Finnish firms listed on the OMX Helsinki stock exchange. Estimations are performed for the period 2003–2012. The data is collected from Datastream system and consists of financial statement data. A number of capital structure characteristics are identified: firm size, profitability, firm growth opportunities, risk, asset tangibility and taxes, speed of adjustment and financial deficit. A regression analysis is used to examine the effects of the firm characteristics on capitals structure. The regression models were formed based on the relevant theories. The general capital structure model is estimated with fixed effects estimator. Additionally, dynamic models play an important role in several areas of corporate finance, but with the combination of fixed effects and lagged dependent variables the model estimation is more complicated. A dynamic partial adjustment model is estimated using Arellano and Bond (1991) first-differencing generalized method of moments, the ordinary least squares and fixed effects estimators. The results for Finnish listed firms show support for the predictions of profitability, firm size and non-debt tax shields. However, no conclusive support for the pecking-order theory is found. However, the effect of pecking order cannot be fully ignored and it is concluded that instead of being substitutes the trade-off and pecking order theory appear to complement each other. For the partial adjustment model the results show that Finnish listed firms adjust towards their target capital structure with a speed of 29% a year using book debt ratio.

Antimony-based type-II superlattice infrared detectors

Numerous applications within the mid- and long-wavelength infrared are driving the search for efficient and cost effective detection technologies in this regime. Theoretical calculations have predicted high performance for InAs/GaSb type-II superlattice structures, which rely on mature growth of III-V semiconductors and offer many levels of freedom in design due to band structure engineering. This work focuses on the fabrication and characterization of type-II superlattice infrared detectors. Standard UV-based photolithography was used combined with chemical wet or dry etching techniques in order to fabricate antinomy-based type-II superlattice infrared detectors. Subsequently, Fourier transform infrared spectroscopy and radiometric techniques were applied for optical characterization in order to obtain a detector's spectrum and response, as well as the overall detectivity in combination with electrical characterization. Temperature dependent electrical characterization was used to extract information about the limiting dark current processes. This work resulted in the first demonstration of an InAs/GaSb type-II superlattice infrared photodetector grown by metalorganic chemical vapor deposition. A peak detectivity of 1.6x10^9 Jones at 78 K was achieved for this device with a 11 micrometer zero cutoff wavelength. Furthermore the interband tunneling detector designed for the mid-wavelength infrared regime was studied. Similar results to those previously published were obtained.

Análise e proposição de estratégias de estimação e controle de velocidade para motores de indução trifásicos

This study presents a proposal of speed servomechanisms without the use of mechanical sensors (sensorless) using induction motors. A comparison is performed and propose techniques for pet rotor speed, analyzing performance in different conditions of speed and load. For the determination of control technique, initially, is performed an analysis of the technical literature of the main control and speed estimation used, with their characteristics and limitations. The proposed technique for servo sensorless speed induction motor uses indirect field-oriented control (IFOC), composed of four controllers of the proportional-integral type (PI): rotor flux controller, speed controller and current controllers in the direct and quadrature shaft. As the main focus of the work is in the speed control loop was implemented in Matlab the recursive least squares algorithm (RLS) for identification of mechanical parameters, such as moment of inertia and friction coefficient. Thus, the speed of outer loop controller gains can be self adjusted to compensate for any changes in the mechanical parameters. For speed estimation techniques are analyzed: MRAS by rotóricos fluxes MRAS by counter EMF, MRAS by instantaneous reactive power, slip, locked loop phase (PLL) and sliding mode. A proposition of estimation in sliding mode based on speed, which is performed a change in rotor flux observer structure is displayed. To evaluate the techniques are performed theoretical analyzes in Matlab simulation environment and experimental platform in electrical machinery drives. The DSP TMS320F28069 was used for experimental implementation of speed estimation techniques and check the performance of the same in a wide speed range, including load insertion. From this analysis is carried out to implement closed-loop control of sensorless speed IFOC structure. The results demonstrated the real possibility of replacing mechanical sensors for estimation techniques proposed and analyzed. Among these, the estimator based on PLL demonstrated the best performance in various conditions, while the technique based on sliding mode has good capacity estimation in steady state and robustness to parametric variations.

Spectral Frame Analysis and Learning through Graph Structure

This dissertation investigates the connection between spectral analysis and frame theory. When considering the spectral properties of a frame, we present a few novel results relating to the spectral decomposition. We first show that scalable frames have the property that the inner product of the scaling coefficients and the eigenvectors must equal the inverse eigenvalues. From this, we prove a similar result when an approximate scaling is obtained. We then focus on the optimization problems inherent to the scalable frames by first showing that there is an equivalence between scaling a frame and optimization problems with a non-restrictive objective function. Various objective functions are considered, and an analysis of the solution type is presented. For linear objectives, we can encourage sparse scalings, and with barrier objective functions, we force dense solutions. We further consider frames in high dimensions, and derive various solution techniques. From here, we restrict ourselves to various frame classes, to add more specificity to the results. Using frames generated from distributions allows for the placement of probabilistic bounds on scalability. For discrete distributions (Bernoulli and Rademacher), we bound the probability of encountering an ONB, and for continuous symmetric distributions (Uniform and Gaussian), we show that symmetry is retained in the transformed domain. We also prove several hyperplane-separation results. With the theory developed, we discuss graph applications of the scalability framework. We make a connection with graph conditioning, and show the in-feasibility of the problem in the general case. After a modification, we show that any complete graph can be conditioned. We then present a modification of standard PCA (robust PCA) developed by Cand\`es, and give some background into Electron Energy-Loss Spectroscopy (EELS). We design a novel scheme for the processing of EELS through robust PCA and least-squares regression, and test this scheme on biological samples. Finally, we take the idea of robust PCA and apply the technique of kernel PCA to perform robust manifold learning. We derive the problem and present an algorithm for its solution. There is also discussion of the differences with RPCA that make theoretical guarantees difficult.

Desenvolvimento de um biossensor para monitorização de acetilcolina, um biomarcador associado à Doença de Alzheimer

A presente dissertação teve como objetivo o desenvolvimento e caracterização de sensores potenciométricos com base em polímeros de impressão molecular (MIP, do inglês, Molecularly Imprinted Polymer) para a determinação da molécula alvo, a acetilcolina. A acetilcolina (ACh) é um neurotransmissor que está associado à doença de Alzheimer. Os materiais biomiméticos desenvolvidos para a interação com a ACh foram obtidos por polimerização em bulk, recorrendo a uma combinação de nanotubos de carbono com monómeros de anilina, dispersos em solvente plastificante oNFOE e PVC. Para aferir sobre o efeito da impressão de ACh na resposta dos materiais MIP, foram igualmente preparados e avaliados materiais de controlo, ou seja, materiais sem impressão molecular (NIP). O controlo da constituição química destes materiais foi realizado recorrendo a Espectroscopia de Raman e Espectroscopia de Infravermelho com transformada de Fourier (FTIR, do inglês Fourier Transformed Infrared Spectroscopy). Os materiais desenvolvidos foram integrados em membranas seletivas de ião, preparadas com ou sem aditivo iónico lipófilo, de carga negativa ou positiva. A avaliação das características gerais das membranas baseou-se na comparação das caraterísticas dos diversos elétrodos. Estas caraterísticas foram obtidas a partir de curvas de calibração, conseguidas para valores de pH diferentes. Em meio ácido, mais precisamente para pH 4, as membranas com materiais impressos e aditivo aniónico foram as que apresentaram as melhores características analíticas, quer em termos de sensibilidade (+83,86 mV década-1) quer em gama de linearidade (de 3,52×10-5 a 1,73×10-3 M). O estudo de seletividade realizado aos sensores revelou que os elétrodos cuja membrana possuía aditivo aniónico apresentavam menores valores de log KPOT. A presença desse constituinte fez com que a seletividade aumentasse nesses mesmos elétrodos. A espécie menos interferente foi a creatina e a mais interferente a creatinina. Os elétrodos foram, ainda, aplicados em amostras de soro sintético. A qualidade dos resultados obtidos dependeu do nível de concentração em estudo, sendo possível identificar uma região onde os resultados foram exatos e precisos. De uma forma geral, os biossensores com MIP e aditivo aniónico apresentaram um desempenho adequado à prossecução deste estudo em amostras reais.

Modeling height-diameter relationship in pinus pinaster ait. in the forest intervention zone of Lomba, NE-Portugal

In this work, the relationship between diameter at breast height (d) and total height (h) of individual-tree was modeled with the aim to establish provisory height-diameter (h-d) equations for maritime pine (Pinus pinaster Ait.) stands in the Lomba ZIF, Northeast Portugal. Using data collected locally, several local and generalized h-d equations from the literature were tested and adaptations were also considered. Model fitting was conducted by using usual nonlinear least squares (nls) methods. The best local and generalized models selected, were also tested as mixed models applying a first-order conditional expectation (FOCE) approximation procedure and maximum likelihood methods to estimate fixed and random effects. For the calibration of the mixed models and in order to be consistent with the fitting procedure, the FOCE method was also used to test different sampling designs. The results showed that the local h-d equations with two parameters performed better than the analogous models with three parameters. However a unique set of parameter values for the local model can not be used to all maritime pine stands in Lomba ZIF and thus, a generalized model including covariates from the stand, in addition to d, was necessary to obtain an adequate predictive performance. No evident superiority of the generalized mixed model in comparison to the generalized model with nonlinear least squares parameters estimates was observed. On the other hand, in the case of the local model, the predictive performance greatly improved when random effects were included. The results showed that the mixed model based in the local h-d equation selected is a viable alternative for estimating h if variables from the stand are not available. Moreover, it was observed that it is possible to obtain an adequate calibrated response using only 2 to 5 additional h-d measurements in quantile (or random) trees from the distribution of d in the plot (stand). Balancing sampling effort, accuracy and straightforwardness in practical applications, the generalized model from nls fit is recommended. Examples of applications of the selected generalized equation to the forest management are presented, namely how to use it to complete missing information from forest inventory and also showing how such an equation can be incorporated in a stand-level decision support system that aims to optimize the forest management for the maximization of wood volume production in Lomba ZIF maritime pine stands.

Fatores críticos de sucesso como antecedentes da aceitação de um sistema de informação em uma universidade federal

In recent decades the public sector comes under pressure in order to improve its performance. The use of Information Technology (IT) has been a tool increasingly used in reaching that goal. Thus, it has become an important issue in public organizations, particularly in institutions of higher education, determine which factors influence the acceptance and use of technology, impacting on the success of its implementation and the desired organizational results. The Technology Acceptance Model - TAM was used as the basis for this study and is based on the constructs perceived usefulness and perceived ease of use. However, when it comes to integrated management systems due to the complexity of its implementation,organizational factors were added to thus seek further explanation of the acceptance of such systems. Thus, added to the model five TAM constructs related to critical success factors in implementing ERP systems, they are: support of top management, communication, training, cooperation, and technological complexity (BUENO and SALMERON, 2008). Based on the foregoing, launches the following research problem: What factors influence the acceptance and use of SIE / module academic at the Federal University of Para, from the users' perception of teachers and technicians? The purpose of this study was to identify the influence of organizational factors, and behavioral antecedents of behavioral intention to use the SIE / module academic UFPA in the perspective of teachers and technical users. This is applied research, exploratory and descriptive, quantitative with the implementation of a survey, and data collection occurred through a structured questionnaire applied to a sample of 229 teachers and 30 technical and administrative staff. Data analysis was carried out through descriptive statistics and structural equation modeling with the technique of partial least squares (PLS). Effected primarily to assess the measurement model, which were verified reliability, convergent and discriminant validity for all indicators and constructs. Then the structural model was analyzed using the bootstrap resampling technique like. In assessing statistical significance, all hypotheses were supported. The coefficient of determination (R ²) was high or average in five of the six endogenous variables, so the model explains 47.3% of the variation in behavioral intention. It is noteworthy that among the antecedents of behavioral intention (BI) analyzed in this study, perceived usefulness is the variable that has a greater effect on behavioral intention, followed by ease of use (PEU) and attitude (AT). Among the organizational aspects (critical success factors) studied technological complexity (TC) and training (ERT) were those with greatest effect on behavioral intention to use, although these effects were lower than those produced by behavioral factors (originating from TAM). It is pointed out further that the support of senior management (TMS) showed, among all variables, the least effect on the intention to use (BI) and was followed by communications (COM) and cooperation (CO), which exert a low effect on behavioral intention (BI). Therefore, as other studies on the TAM constructs were adequate for the present research. Thus, the study contributed towards proving evidence that the Technology Acceptance Model can be applied to predict the acceptance of integrated management systems, even in public. Keywords: Technology