Hemodynamic mechanisms of the attenuated blood pressure response to mental stress after a single bout of maximal dynamic exercise in healthy subjects

To determine the hemodynamic mechanisms responsible for the attenuated blood pressure response to mental stress after exercise, 26 healthy sedentary individuals (age 29 ± 8 years) underwent the Stroop color-word test before and 60 min after a bout of maximal dynamic exercise on a treadmill. A subgroup (N = 11) underwent a time-control experiment without exercise. Blood pressure was continuously and noninvasively recorded by infrared finger photoplethysmography. Stroke volume was derived from pressure signals, and cardiac output and peripheral vascular resistance were calculated. Perceived mental stress scores were comparable between mental stress tests both in the exercise (P = 0.96) and control (P = 0.24) experiments. After exercise, the blood pressure response to mental stress was attenuated (pre: 10 ± 13 vs post: 6 ± 7 mmHg; P < 0.01) along with lower values of systolic blood pressure (pre: 129 ± 3 vs post: 125 ± 3 mmHg; P < 0.05), stroke volume (pre: 89.4 ± 3.5 vs post: 76.8 ± 3.8 mL; P < 0.05), and cardiac output (pre: 7.00 ± 0.30 vs post: 6.51 ± 0.36 L/min; P < 0.05). Except for heart rate, the hemodynamic responses and the mean values during the two mental stress tests in the control experiment were similar (P > 0.05). In conclusion, a single bout of maximal dynamic exercise attenuates the blood pressure response to mental stress in healthy subjects, along with lower stroke volume and cardiac output, denoting an acute modulatory action of exercise on the central hemodynamic response to mental stress.

Dynamic expression of desmin, α-SMA and TGF-β1 during hepatic fibrogenesis induced by selective bile duct ligation in young rats

We previously described a selective bile duct ligation model to elucidate the process of hepatic fibrogenesis in children with biliary atresia or intrahepatic biliary stenosis. Using this model, we identified changes in the expression of alpha smooth muscle actin (α-SMA) both in the obstructed parenchyma and in the hepatic parenchyma adjacent to the obstruction. However, the expression profiles of desmin and TGF-β1, molecules known to be involved in hepatic fibrogenesis, were unchanged when analyzed by semiquantitative polymerase chain reaction (RT-PCR). Thus, the molecular mechanisms involved in the modulation of liver fibrosis in this experimental model are not fully understood. This study aimed to evaluate the molecular changes in an experimental model of selective bile duct ligation and to compare the gene expression changes observed in RT-PCR and in real-time quantitative PCR (qRT‐PCR). Twenty-eight Wistar rats of both sexes and weaning age (21-23 days old) were used. The rats were separated into groups that were assessed 7 or 60 days after selective biliary duct ligation. The expression of desmin, α-SMA and TGF-β1 was examined in tissue from hepatic parenchyma with biliary obstruction (BO) and in hepatic parenchyma without biliary obstruction (WBO), using RT-PCR and qRT‐PCR. The results obtained in this study using these two methods were significantly different. The BO parenchyma had a more severe fibrogenic reaction, with increased α-SMA and TGF-β1 expression after 7 days. The WBO parenchyma presented a later, fibrotic response, with increased desmin expression 7 days after surgery and increased α-SMA 60 days after surgery. The qRT‐PCR technique was more sensitive to expression changes than the semiquantitative method.

THE GENERALIZED MAXIMUM LIKELIHOOD METHOD APPLIED TO HIGH PRESSURE PHASE EQUILIBRIUM

The generalized maximum likelihood method was used to determine binary interaction parameters between carbon dioxide and components of orange essential oil. Vapor-liquid equilibrium was modeled with Peng-Robinson and Soave-Redlich-Kwong equations, using a methodology proposed in 1979 by Asselineau, Bogdanic and Vidal. Experimental vapor-liquid equilibrium data on binary mixtures formed with carbon dioxide and compounds usually found in orange essential oil were used to test the model. These systems were chosen to demonstrate that the maximum likelihood method produces binary interaction parameters for cubic equations of state capable of satisfactorily describing phase equilibrium, even for a binary such as ethanol/CO2. Results corroborate that the Peng-Robinson, as well as the Soave-Redlich-Kwong, equation can be used to describe phase equilibrium for the following systems: components of essential oil of orange/CO2.

HIGH PRESSURE PHASE EQUILIBRIUM: PREDICTION OF ESSENTIAL OIL SOLUBILITY

This work describes a method to predict the solubility of essential oils in supercritical carbon dioxide. The method is based on the formulation proposed in 1979 by Asselineau, Bogdanic and Vidal. The Peng-Robinson and Soave-Redlich-Kwong cubic equations of state were used with the van der Waals mixing rules with two interaction parameters. Method validation was accomplished calculating orange essential oil solubility in pressurized carbon dioxide. The solubility of orange essential oil in carbon dioxide calculated at 308.15 K for pressures of 50 to 70 bar varied from 1.7± 0.1 to 3.6± 0.1 mg/g. For same the range of conditions, experimental solubility varied from 1.7± 0.1 to 3.6± 0.1 mg/g. Predicted values were not very sensitive to initial oil composition.

Evaluation of noni (Morinda citrifolia) volatile profile by dynamic headspace and gas chromatography-mass spectrometry

Noni is a fruit that has interested the scientific community due to its medicinal and functional activities. Different products that contain noni are already in the market, but their consumption could be impaired by their distinctive unpleasant aroma and flavor. The aim of this work was to evaluate the noni pulp volatile profile by dynamic headspace and gas chromatography-mass spectrometry. Thirty seven volatile compounds were detected, mainly alcohols (63.3%), esters (26.9%), cetones (7.4%), and acids (1.2%).

Kinetic, thermodynamic properties, and optimization of barley hydration

The hydration kinetics of five barley cultivars was studied at six different temperatures ranging from 10 to 35 ºC for 32 hours applying the Peleg model. Response Surface was used to describe dynamic of the process and identify the hydration time for each cultivar. The activation energy (Ea), enthalpy (ΔH*), entropy (ΔS*), and Gibbs free energy (ΔG*) were estimated from the adjusted parameters and Arrhenius equation. Temperature had significant effect on the hydration of the five cultivars. At low temperatures, the stabilization time for hydration was faster. Peleg constants K1 and K2 decreased with increasing temperature. The cultivar BRS BRAU showed the lowest value of initial absorption rate (R0 = 0.149 kg.h-1) at 10 ºC, while the cultivar BRS BOREMA had the highest value of R0 (0.367 kg.h-1 at 35 ºC). The equilibrium moisture content (Me) increased with increasing temperature. The cultivars BRS CAUE and BRS BRAU showed the lowest values of Ea, ΔH*, ΔS* showed negative values, and ΔG* increased with increasing temperature, confirming the effect of temperature on hydration.

Dynamic Competitor Analysis Model Of Welding Quality Management Software

Tämä diplomityö arvioi hitsauksen laadunhallintaohjelmistomarkkinoiden kilpailijoita. Kilpailukenttä on uusi ja ei ole tarkkaa tietoa siitä minkälaisia kilpailijoita on markkinoilla. Hitsauksen laadunhallintaohjelmisto auttaa yrityksiä takaamaan korkean laadun. Ohjelmisto takaa korkean laadun varmistamalla, että hitsaaja on pätevä, hän noudattaa hitsausohjeita ja annettuja parametreja. Sen lisäksi ohjelmisto kerää kaiken tiedon hitsausprosessista ja luo siitä vaadittavat dokumentit. Diplomityön teoriaosuus muodostuu kirjallisuuskatsauksesta ratkaisuliike-toimintaan, kilpailija-analyysin ja kilpailuvoimien teoriaan sekä hitsauksen laadunhallintaan. Työn empiriaosuus on laadullinen tutkimus, jossa tutkitaan kilpailevia hitsauksen laadunhallintaohjelmistoja ja haastatellaan ohjelmistojen käyttäjiä. Diplomityön tuloksena saadaan uusi kilpailija-analyysimalli hitsauksen laadunhallintaohjelmistoille. Mallin avulla voidaan arvostella ohjelmistot niiden tarjoamien primääri- ja sekundääriominaisuuksien perusteella. Toiseksi tässä diplomityössä analysoidaan nykyinen kilpailijatilanne hyödyntämällä juuri kehitettyä kilpailija-analyysimallia.

Variance reduction properties of dynamic hedging models - empirical evidence from BRICS countries

This Master’s Thesis analyses the effectiveness of different hedging models on BRICS (Brazil, Russia, India, China, and South Africa) countries. Hedging performance is examined by comparing two different dynamic hedging models to conventional OLS regression based model. The dynamic hedging models being employed are Constant Conditional Correlation (CCC) GARCH(1,1) and Dynamic Conditional Correlation (DCC) GARCH(1,1) with Student’s t-distribution. In order to capture the period of both Great Moderation and the latest financial crisis, the sample period extends from 2003 to 2014. To determine whether dynamic models outperform the conventional one, the reduction of portfolio variance for in-sample data with contemporaneous hedge ratios is first determined and then the holding period of the portfolios is extended to one and two days. In addition, the accuracy of hedge ratio forecasts is examined on the basis of out-of-sample variance reduction. The results are mixed and suggest that dynamic hedging models may not provide enough benefits to justify harder estimation and daily portfolio adjustment. In this sense, the results are consistent with the existing literature.

Bayesian analysis of SEIR epidemic models

This thesis concerns the analysis of epidemic models. We adopt the Bayesian paradigm and develop suitable Markov Chain Monte Carlo (MCMC) algorithms. This is done by considering an Ebola outbreak in the Democratic Republic of Congo, former Zaïre, 1995 as a case of SEIR epidemic models. We model the Ebola epidemic deterministically using ODEs and stochastically through SDEs to take into account a possible bias in each compartment. Since the model has unknown parameters, we use different methods to estimate them such as least squares, maximum likelihood and MCMC. The motivation behind choosing MCMC over other existing methods in this thesis is that it has the ability to tackle complicated nonlinear problems with large number of parameters. First, in a deterministic Ebola model, we compute the likelihood function by sum of square of residuals method and estimate parameters using the LSQ and MCMC methods. We sample parameters and then use them to calculate the basic reproduction number and to study the disease-free equilibrium. From the sampled chain from the posterior, we test the convergence diagnostic and confirm the viability of the model. The results show that the Ebola model fits the observed onset data with high precision, and all the unknown model parameters are well identified. Second, we convert the ODE model into a SDE Ebola model. We compute the likelihood function using extended Kalman filter (EKF) and estimate parameters again. The motivation of using the SDE formulation here is to consider the impact of modelling errors. Moreover, the EKF approach allows us to formulate a filtered likelihood for the parameters of such a stochastic model. We use the MCMC procedure to attain the posterior distributions of the parameters of the SDE Ebola model drift and diffusion parts. In this thesis, we analyse two cases: (1) the model error covariance matrix of the dynamic noise is close to zero , i.e. only small stochasticity added into the model. The results are then similar to the ones got from deterministic Ebola model, even if methods of computing the likelihood function are different (2) the model error covariance matrix is different from zero, i.e. a considerable stochasticity is introduced into the Ebola model. This accounts for the situation where we would know that the model is not exact. As a results, we obtain parameter posteriors with larger variances. Consequently, the model predictions then show larger uncertainties, in accordance with the assumption of an incomplete model.