Spatial model of site index based on Y-ray spectrometry and a digital elevation model for two Pinus species in Tuan Toolara State Forest, Queensland, Australia

Site index prediction models are an important aid for forest management and planning activities. This paper introduces a multiple regression model for spatially mapping and comparing site indices for two Pinus species (Pinus elliottii Engelm. and Queensland hybrid, a P. elliottii x Pinus caribaea Morelet hybrid) based on independent variables derived from two major sources: g-ray spectrometry (potassium (K), thorium (Th), and uranium (U)) and a digital elevation model (elevation, slope, curvature, hillshade, flow accumulation, and distance to streams). In addition, interpolated rainfall was tested. Species were coded as a dichotomous dummy variable; interaction effects between species and the g-ray spectrometric and geomorphologic variables were considered. The model explained up to 60% of the variance of site index and the standard error of estimate was 1.9 m. Uranium, elevation, distance to streams, thorium, and flow accumulation significantly correlate to the spatial variation of the site index of both species, and hillshade, curvature, elevation and slope accounted for the extra variability of one species over the other. The predicted site indices varied between 20.0 and 27.3 m for P. elliottii, and between 23.1 and 33.1 m for Queensland hybrid; the advantage of Queensland hybrid over P. elliottii ranged from 1.8 to 6.8 m, with the mean at 4.0 m. This compartment-based prediction and comparison study provides not only an overview of forest productivity of the whole plantation area studied but also a management tool at compartment scale.

A Bayesian latent class safety performance function for identifying motor vehicle crash blackspots

The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.

Joint Regression and Association Models for Repeated Categorical Responses

The focus of this study is on statistical analysis of categorical responses, where the response values are dependent of each other. The most typical example of this kind of dependence is when repeated responses have been obtained from the same study unit. For example, in Paper I, the response of interest is the pneumococcal nasopharengyal carriage (yes/no) on 329 children. For each child, the carriage is measured nine times during the first 18 months of life, and thus repeated respones on each child cannot be assumed independent of each other. In the case of the above example, the interest typically lies in the carriage prevalence, and whether different risk factors affect the prevalence. Regression analysis is the established method for studying the effects of risk factors. In order to make correct inferences from the regression model, the associations between repeated responses need to be taken into account. The analysis of repeated categorical responses typically focus on regression modelling. However, further insights can also be gained by investigating the structure of the association. The central theme in this study is on the development of joint regression and association models. The analysis of repeated, or otherwise clustered, categorical responses is computationally difficult. Likelihood-based inference is often feasible only when the number of repeated responses for each study unit is small. In Paper IV, an algorithm is presented, which substantially facilitates maximum likelihood fitting, especially when the number of repeated responses increase. In addition, a notable result arising from this work is the freely available software for likelihood-based estimation of clustered categorical responses.

Field evaluation of tolerance to Tobacco streak virus in sunflower germplasm, and observations of seasonal disease spread

Strong statistical evidence was found for differences in tolerance to natural infections of Tobacco streak virus (TSV) in sunflower hybrids. Data from 470 plots involving 23 different sunflower hybrids tested in multiple trials over 5 years in Australia were analysed. Using a Bayesian Hierarchical Logistic Regression model for analysis provided: (i) a rigorous method for investigating the relative effects of hybrid, seasonal rainfall and proximity to inoculum source on the incidence of severe TSV disease; (ii) a natural method for estimating the probability distributions of disease incidence in different hybrids under historical rainfall conditions; and (iii) a method for undertaking all pairwise comparisons of disease incidence between hybrids whilst controlling the familywise error rate without any drastic reduction in statistical power. The tolerance identified in field trials was effective against the main TSV strain associated with disease outbreaks, TSV-parthenium. Glasshouse tests indicate this tolerance to also be effective against the other TSV strain found in central Queensland, TSV-crownbeard. The use of tolerant germplasm is critical to minimise the risk of TSV epidemics in sunflower in this region. We found strong statistical evidence that rainfall during the early growing months of March and April had a negative effect on the incidence of severe infection with greatly reduced disease incidence in years that had high rainfall during this period.

The connection between on-farm assessed welfare (A-index) and production parameters of the sows

Tämän tutkimuksen tavoitteena oli selvittää tilalla määritetyn hyvinvoinnin yhteyttä emakoiden tuotantotuloksiin. Hyvinvointia arvioitiin suomalaisen hyvinvointi-indeksin, A-indeksi, avulla. Tuotantotuloksina käytettiin kahta erilaista tuotosaineistoa, jotka molemmat pohjautuivat kansalliseen tuotosseuranta aineistoon. Hyvinvointimääritykset tehtiin 30 porsastuotantosikalassa maaliskuun 2007 aikana. A-indeksi koostuu kuudesta kategoriasta ’liikkumismahdollisuudet’, ’alustan ominaisuudet’, ’sosiaaliset kontaktit’, ’valo, ilma ja melu’, ’ruokinta ja veden saanti’ sekä ’eläinten terveys ja hoidon taso’. Jokaisessa kategoriassa on 3-10 pääosin ympäristöperäistä muuttujaa, jotka vaihtelevat osastoittain. Maksimipistemäärä osastolle on 100. Hyvinvointimittaukset tehtiin porsitus-, tiineytys- ja joutilasosastoilla. Erillisten tiineytysosastojen pienen lukumäärän takia (n=7) tilakohtaiset tiineytys- ja joutilasosastopisteet yhdistettiin ja keskiarvoja käytettiin analyyseissä. Yhteyksiä tuotokseen tutkittiin kahden eri aineiston avulla 1) Tilaraportti aineisto (n=29) muodostuu muokkaamattomista tila- ja tuotostuloksista tilavierailua edeltävän vuoden ajalta, 2) POTSIaineisto (n=30) muodostuu POTSI-ohjelmalla (MTT) muokatusta tuotantoaineistosta, joka sisältää managementtiryhmän (tila, vuosi, vuodenaika) vaikutuksen ensikoiden ja emakoiden pahnuekohtaiseen tuotokseen. Yhteyksiä analysointiin korrelaatio- ja regressioanalyysien avulla. Vaikka osallistuminen tutkimukseen oli vapaaehtoista, molempien tuotantoaineistojen perusteella tutkimustilat edustavat keskituottoista suomalaista sikatilaa. A-indeksin kokonaispisteet vaihtelivat välillä 37,5–64,0 porsitusosastolla ja 39,5–83,5 joutilasosastolla. Tilaraporttiaineistoa käytettäessä paremmat pisteet porsitusosaston ’eläinten terveys ja hoidon taso’ -kategoriasta lyhensivät eläinten lisääntymissykliä, lisäsivät syntyvien pahnueiden ja porsaiden määrää sekä alensivat kuolleena syntyneiden lukumäärää. Regressiomallin mukaan ’eläinten terveys ja hoidon taso’ -kategoria selitti syntyvien porsaiden lukumäärän, porsimisvälin pituuden sekä keskiporsimiskerran vaihtelua. Paremmat pisteet joutilasosaston ’liikkumismahdollisuudet’ kategoriasta alensivat syntyneiden pahnueiden sekä syntyneiden että vieroitettujen porsaiden lukumäärää. Regressiomallin mukaan ensikkopahnueiden osuus ja ”liikkumismahdollisuudet” kategorian pisteet selittivät vieroitettujen porsaiden lukumäärän vaihtelua. POTSI-aineiston yhteydessä kuolleena syntyneiden porsaiden lukumäärän aleneminen oli ensikoilla yhteydessä parempiin porsitusosaston ’sosiaalisiin kontakteihin’ ja emakoilla puolestaan joutilasosaston parempiin ’eläinten terveys ja hoidon taso’ pisteisiin. Kahden eri tuotantoaineiston avulla saadut tulokset erosivat toisistaan. Seuraavissa tutkimuksissa onkin suositeltavampaa käyttää Tilaraporttiaineistoja, joissa tuotokset ilmoitetaan vuosikohtaisina. Tämän tutkimuksen perusteella hyvinvoinnilla ja tuotoksella on yhteyksiä, joilla on myös merkittävää taloudellista vaikutusta. Erityisesti hyvä eläinten hoito ja eläinten terveys lisäävät tuotettujen porsaiden määrää ja lyhentävät lisääntymiskiertoa. Erityishuomiota tulee kiinnittää vapaana olevien joutilaiden emakoiden sosiaaliseen stressiin ja rehunsaannin varmistamiseen kaikille yksilöille.

Modeling and Forecasting Implied Volatility: Implications for Trading, Pricing, and Risk Management

Modeling and forecasting of implied volatility (IV) is important to both practitioners and academics, especially in trading, pricing, hedging, and risk management activities, all of which require an accurate volatility. However, it has become challenging since the 1987 stock market crash, as implied volatilities (IVs) recovered from stock index options present two patterns: volatility smirk(skew) and volatility term-structure, if the two are examined at the same time, presents a rich implied volatility surface (IVS). This implies that the assumptions behind the Black-Scholes (1973) model do not hold empirically, as asset prices are mostly influenced by many underlying risk factors. This thesis, consists of four essays, is modeling and forecasting implied volatility in the presence of options markets’ empirical regularities. The first essay is modeling the dynamics IVS, it extends the Dumas, Fleming and Whaley (DFW) (1998) framework; for instance, using moneyness in the implied forward price and OTM put-call options on the FTSE100 index, a nonlinear optimization is used to estimate different models and thereby produce rich, smooth IVSs. Here, the constant-volatility model fails to explain the variations in the rich IVS. Next, it is found that three factors can explain about 69-88% of the variance in the IVS. Of this, on average, 56% is explained by the level factor, 15% by the term-structure factor, and the additional 7% by the jump-fear factor. The second essay proposes a quantile regression model for modeling contemporaneous asymmetric return-volatility relationship, which is the generalization of Hibbert et al. (2008) model. The results show strong negative asymmetric return-volatility relationship at various quantiles of IV distributions, it is monotonically increasing when moving from the median quantile to the uppermost quantile (i.e., 95%); therefore, OLS underestimates this relationship at upper quantiles. Additionally, the asymmetric relationship is more pronounced with the smirk (skew) adjusted volatility index measure in comparison to the old volatility index measure. Nonetheless, the volatility indices are ranked in terms of asymmetric volatility as follows: VIX, VSTOXX, VDAX, and VXN. The third essay examines the information content of the new-VDAX volatility index to forecast daily Value-at-Risk (VaR) estimates and compares its VaR forecasts with the forecasts of the Filtered Historical Simulation and RiskMetrics. All daily VaR models are then backtested from 1992-2009 using unconditional, independence, conditional coverage, and quadratic-score tests. It is found that the VDAX subsumes almost all information required for the volatility of daily VaR forecasts for a portfolio of the DAX30 index; implied-VaR models outperform all other VaR models. The fourth essay models the risk factors driving the swaption IVs. It is found that three factors can explain 94-97% of the variation in each of the EUR, USD, and GBP swaption IVs. There are significant linkages across factors, and bi-directional causality is at work between the factors implied by EUR and USD swaption IVs. Furthermore, the factors implied by EUR and USD IVs respond to each others’ shocks; however, surprisingly, GBP does not affect them. Second, the string market model calibration results show it can efficiently reproduce (or forecast) the volatility surface for each of the swaptions markets.

Kesämökkikäynnin virkistysarvon määrittäminen matkakustannusmenetelmällä

Tämän tutkielman tarkoituksena on määrittää kesämökkikäynnin virkistysarvo. Aihetta ei ole aikaisemmin tutkittu, vaikka kesämökkeily on merkittävä osa suomalaista elämää. Kesämökkikäynnin virkistysarvo tarkoittaa hyötyä, jonka yksilö saa kesämökillä virkistäytymisestä. Virkistäytyminen kesämökillä pitää sisällään kaiken kesämökillä ja sen ympäristössä tapahtuvan harrastamisen ja rentoutumisen. Koska ympäristö on tärkeässä osassa mökillä virkistäytymisessä, tässä tutkielmassa on lisäksi tarkoitus tutkia, kuinka mökkiympäristön ominaisuudet vaikuttavat virkistysarvoon. Tarkasteltavina ympäristön ominaisuuksina ovat virkistäytymisen estävät leväkukinnot ja mökin rannattomuus. Koska mökkeily toisaalta myös kuormittaa ympäristöä, tutkielmassa tutkitaan myös, kuinka sähköistys, ympäristöä kuormittava kesämökin ominaisuus, vaikuttaa virkistysarvoon. Virkistysarvo on markkinaton hyöty, joten sen määrittämiseen on käytettävä jotain markkinattomien hyödykkeiden arvottamismenetelmää. Tässä työssä arvottaminen tapahtuu matkakustannusmenetelmällä, jota käytetään yleisesti ympäristön tarjoamien virkistyspalveluiden taloudelliseen arvottamiseen. Kesämökkikäyntien kysyntää kuvaava matkakustannusmallin ekonometrinen mallintaminen suoritetaan negatiivisella binomimallilla. Tutkielman tulosten mukaan noin neljän päivän pituinen käynti sähköistetyllä kesämökillä, jossa on ranta eivätkä levät häiritse virkistäytymistä, tuottaa 167-205 euron suuruisen virkistyshyödyn. Virkistäytymisen estävät leväkukinnot laskevat arvoa 40 prosentilla ja mökin rannattomuus 45 prosentilla. Käynti sähköistetyllä mökillä tuottaa 3-5 prosenttia korkeamman virkistyshyödyn kuin käynti sähköistämättömällä mökillä. Suomessa kesän aikana tehtävien mökkikäyntien yhteenlaskettu virkistyshyöty on 430-530 miljoonaa, jos mökillä on ranta, jossa levistä ei ole haittaa. Häiritsevät leväkukinnot laskevat yhteenlaskettua virkistyshyötyä 30 miljoonalla ja rannattomuus 10-20 miljoonalla. Sähköistys nostaa yhteenlaskettua virkistyshyötyä 20-30 miljoonalla eurolla.

Development of foreign direct investment in Finland

During 1990 to 2009, Foreign Direct Investment (FDI henceforth) in Finland has fluctuated greatly. This paper focused on analyzing the overall development and basic characteristics of Foreign Direct Investment in Finland, covering the period from 1990 to present. By comparing FDI in Finland with FDI in other countries, the picture of Finland’s FDI position in the world market is clearer. A lot of statistical data, tables and figures are used to describe the trend of Foreign Direct Investment in Finland. All the data used in this study were obtained from Statistics Finland, UNCTAD, OECD, World Bank and International Labor Office, Investment map website and etc. It is also found that there is a big, long-lasting and increasing imbalance of the inward FDI and outward FDI in Finland, the performance of outward FDI is stronger than the inward FDI in Finland. Finland’s position of FDI in the world is rather modest. And based on existing theories, I tried to analyze the factors that might determine the size of the inflows of FDI in Finland. The econometric model of my thesis is based on time series data ranging from 1990 to 2007. A Log linear regression model is adopted to analyze the impact of each variable. The regression results showed that Labor Cost and Investment in Education have a negative influence on the FDI inflows into Finland. Too high labor cost is the main impediment of FDI in Finland, explaining the relative small size of FDI inflows into Finland. GDP and Economy openness have a significant positive impact on the inflows of FDI into Finland; other variables do not emerge as significant factor in affecting the size of FDI inflows in Finland as expected. Meanwhile, the impacts of the most recent financial and economic crisis on FDI in the world and in Finland are discussed as well. FDI inflows worldwide and in Finland have suffered from a big setback from the 2008 global crisis. The economic crisis has undoubtedly significant negative influence on the FDI flows in the world and in Finland. Nevertheless, apart from the negative impact, the crisis itself also brings in chances for policymakers to implement more efficient policies in order to create a pro-business and pro-investment climate for the recovery of FDI inflows. . The correspondent policies and measures aiming to accelerate the recovery of the falling FDI were discussed correspondently.

Factors affecting partitioning of private forest holdings in Finland.

Questions of the small size of non-industrial private forest (NIPF) holdings in Finland are considered and factors affecting their partitioning are analyzed. This work arises out of Finnish forest policy statements in which the small average size of holdings has been seen to have a negative influence on the economics of forestry. A survey of the literature indicates that the size of holdings is an important factor determining the costs of logging and silvicultural operations, while its influence on the timber supply is slight. The empirical data are based on a sample of 314 holdings collected by interviewing forest owners in the years 1980-86. In 1990-91 the same holdings were resurveyed by means of a postal inquiry and partly by interviewing forest owners. The principal objective in compiling the data is to assist in quantifying ownership factors that influence partitioning among different kinds of NIPF holdings. Thus the mechanism of partitioning were described and a maximum likelihood logistic regression model was constructed using seven independent holding and ownership variables. One out of four holdings had undergone partitioning in conjunction with a change in ownership, one fifth among family owned holdings and nearly a half among jointly owned holdings. The results of the logistic regression model indicate, for instance, that the odds on partitioning is about three times greater for jointly owned holdings than for family owned ones. Also, the probabilities of partitioning were estimated and the impact of independent dichotomous variables on the probability of partitioning ranged between 0.02 and 0.10. The low value of the Hosmer-Lemeshow test statistic indicates a good fit of the model and the rate of correct classification was estimated to be 88 per cent with a cutoff point of 0.5. The average size of holdings undergoing ownership changes decreased from 29.9 ha to 28.7 ha over the approximate interval 1983-90. In addition, the transition probability matrix showed that the trends towards smaller size categories mostly involved in the small size categories, less than 20 ha. The results of the study can be used in considering the effects of the small size of holdings for forestry and if the purpose is to influence partitioning through forest or rural policy.

Optimization of an ammonia reactor using regression analysis

This paper presents an optimization algorithm for an ammonia reactor based on a regression model relating the yield to several parameters, control inputs and disturbances. This model is derived from the data generated by hybrid simulation of the steady-state equations describing the reactor behaviour. The simplicity of the optimization program along with its ability to take into account constraints on flow variables make it best suited in supervisory control applications.

Large-MIMO Receiver based on Linear Regression of MMSE Residual

Multiple input multiple output (MIMO) systems with large number of antennas have been gaining wide attention as they enable very high throughputs. A major impediment is the complexity at the receiver needed to detect the transmitted data. To this end we propose a new receiver, called LRR (Linear Regression of MMSE Residual), which improves the MMSE receiver by learning a linear regression model for the error of the MMSE receiver. The LRR receiver uses pilot data to estimate the channel, and then uses locally generated training data (not transmitted over the channel), to find the linear regression parameters. The proposed receiver is suitable for applications where the channel remains constant for a long period (slow-fading channels) and performs quite well: at a bit error rate (BER) of 10(-3), the SNR gain over MMSE receiver is about 7 dB for a 16 x 16 system; for a 64 x 64 system the gain is about 8.5 dB. For large coherence time, the complexity order of the LRR receiver is the same as that of the MMSE receiver, and in simulations we find that it needs about 4 times as many floating point operations. We also show that further gain of about 4 dB is obtained by local search around the estimate given by the LRR receiver.

Optimization of degree of sphericity of primary phase during cooling slope casting of A356 Al alloy: Taguchi method and regression analysis

The present work presents the results of experimental investigation of semi-solid rheocasting of A356 Al alloy using a cooling slope. The experiments have been carried out following Taguchi method of parameter design (orthogonal array of L-9 experiments). Four key process variables (slope angle, pouring temperature, wall temperature, and length of travel of the melt) at three different levels have been considered for the present experimentation. Regression analysis and analysis of variance (ANOVA) has also been performed to develop a mathematical model for degree of sphericity evolution of primary alpha-Al phase and to find the significance and percentage contribution of each process variable towards the final outcome of degree of sphericity, respectively. The best processing condition has been identified for optimum degree of sphericity (0.83) as A(3), B-3, C-2, D-1 i.e., slope angle of 60 degrees, pouring temperature of 650 degrees C, wall temperature 60 degrees C, and 500 mm length of travel of the melt, based on mean response and signal to noise ratio (SNR). ANOVA results shows that the length of travel has maximum impact on degree of sphericity evolution. The predicted sphericity obtained from the developed regression model and the values obtained experimentally are found to be in good agreement with each other. The sphericity values obtained from confirmation experiment, performed at 95% confidence level, ensures that the optimum result is correct and also the confirmation experiment values are within permissible limits. (c) 2014 Elsevier Ltd. All rights reserved.

Velocidade da onda de pulso em adultos jovens acompanhados por 18 anos: impacto de variáveis pressóricas, antropométricas, metabólicas, inflamatórias e de função endotelial. Estudo do Rio de Janeiro.

Dados sobre a avaliação não invasiva da rigidez vascular e suas relações com variáveis de risco cardiovascular são escassos em jovens. Objetiva avaliar a relação entre a velocidade de onda de pulso (VOP) e a pressão arterial (PA), variáveis antropométricas, metabólicas, inflamatórias e de disfunção endotelial em indivíduos adultos jovens. Foram estudados 96 indivíduos (51 homens) do Estudo do Rio de Janeiro, em duas avaliações, A1 e A2, com intervalo de 17,691,58 anos (16 a 21 anos). Em A1 foram avaliados em suas escolas (10-15 anos - média 12,421,47 anos) e em A2 foram novamente avaliados em nível ambulatorial (26-35 anos - média 30,091,92 anos). Em A1 foram obtidos pressão arterial (PA) e índice de massa corporal (IMC). Em A2 foram obtidos a velocidade da onda de pulso (VOP)-método Complior, PA, IMC, circunferência abdominal (CA), glicose, perfil lipídico, leptina, insulina, adiponectina, o índice de resistência à insulina HOMA-IR, proteína C-Reativa ultrassensível (PCRus) e as moléculas de adesão E-selectina, Vascular Cell Adhesion Molecule-1(VCAM-1) e Intercellular Adhesion Molecule-1 (ICAM-1). Foram obtidos, ainda, a variação da PA e do IMC entre as 2 avaliações. Em A2 os indivíduos foram estratificados segundo o tercil da VOP para cada sexo. Como resultados temos: 1) Os grupos foram constituídos da seguinte forma: Tercil 1:homens com VOP < 8,69 m/s e mulheres com VOP < 7,66 m/s; Tercil 2: homens com VOP ≥ 8,69 m/s e < 9,65m/s e mulheres com VOP ≥ 7,66 m/s e < 8,31m/s;Tercil 3:homens com VOP ≥ 9,65 m/s e mulheres com VOP ≥ 8,31 m/s. 2) O grupo com maior tercil de VOP mostrou maiores médias de PA sistólica (PAS) (p=0,005), PA diastólica (PAD) (p=0,007), PA média (PAM) (p=0,004), variação da PAD (p=0,032), variação da PAM (p=0,003), IMC (p=0,046), variação do IMC (p=0,020), insulina (p=0,019), HOMA-IR (p=0,021), E-selectina (p=0,032) e menores médias de adiponectina (p=0,016), além de maiores prevalências de diabetes mellitus/intolerância à glicose (p=0,022) e hiperinsulinemia (p=0,038); 3) Houve correlação significativa e positiva da VOP com PAS (p<0,001), PAD (p<0,001), PP (p=0,048) e PAM (p<0,001) de A2, com a variação da pressão arterial (PAS, PAD e PAM) (p<0,001) entre as duas avaliações, com o IMC de A2 (p=0,005) e com a variação do IMC (p<0,001) entre as duas avaliações, com CA (p=0,001), LDLcolesterol (p=0,049) e E-selectina (p<0,001) e correlação negativa com HDLcolesterol (p<0,001) e adiponectina (p<0,001); 4)Em modelo de regressão múltipla, após ajuste do HDL-colesterol, LDLcolesterol e adiponectina para sexo, idade, IMC e PAM, apenas o sexo masculino e a PAM mantiveram correlação significativa com a VOP. A VOP em adultos jovens mostrou relação significativa com variáveis de risco cardiovascular, destacando-se o sexo masculino e a PAM como importantes variáveis no seu determinismo. Os achados sugerem que a medida da VOP pode ser útil para a identificação do acometimento vascular nessa faixa etária.

Catch rates and demographics of loggerhead sea turtles (Caretta caretta) captured from the Charleston, South Carolina, shipping channel during the period of mandatory use of turtle excluder devices (TEDs)

Trawling was conducted in the Charleston, South Carolina, shipping channel between May and August during 2004–07 to evaluate loggerhead sea turtle (Caretta caretta) catch rates and demographic distributions. Two hundred and twenty individual loggerheads were captured in 432 trawling events during eight sampling periods lasting 2–10 days each. Catch was analyzed by using a generalized linear model. Data were fitted to a negative binomial distribution with the log of standardized sampling effort (i.e., an hour of sampling with a net head rope length standardized to 30.5 m) for each event treated as an offset term. Among 21 variables, factors, and interactions, five terms were significant in the final model, which accounted for 45% of model deviance. Highly significant differences in catch were noted among sampling periods and sampling locations within the channel, with greatest catch furthest seaward consistent with historical observations. Loggerhead sea turtle catch rates in 2004–07 were greater than in 1991–92 when mandatory use of turtle excluder devices was beginning to be phased in. Concurrent with increased catch rates, loggerheads captured in 2004–07 were larger than in 1991–92. Eighty-five percent of loggerheads captured were ≤75.0 cm straight-line carapace length (nuchal notch to tip of carapace) and there was a 3.9:1 female-to-male bias, consistent with limited data for this location two decades earlier. Only juvenile loggerheads ≤75.0 cm possessed haplotypes other than CC-A01 or CC-A02 that dominate in the region. Six rare and one un-described haplotype were predominantly found in June 2004.

Predicting the distribution of Vibrio vulnificus in Chesapeake Bay

Vibrio vulnificus is a gram-negative pathogenic bacterium endemic to coastal waters worldwide, and a leading cause of seafood related mortality. Because of human health concerns, understanding the ecology of the species and potentially predicting its distribution is of great importance. We evaluated and applied a previously published qPCR assay to water samples (n = 235) collected from the main-stem of the Chesapeake Bay (2007 – 2008) by Maryland and Virginia State water quality monitoring programs. Results confirmed strong relationships between the likelihood of Vibrio vulnificus presence and both temperature and salinity that were used to develop a logistic regression model. The habitat model demonstrated a high degree of concordance (93%), and robustness as subsequent bootstrapping (n=1000) did not change model output (P > 0.05). We forced this empirical habitat model with temperature and salinity predictions generated by a regional hydrodynamic modeling system to demonstrate its utility in future pathogen forecasting efforts in the Chesapeake Bay.