Effect of gender on training-induced vascular remodeling in SHR

There is accumulating evidence that physical inactivity, associated with the modern sedentary lifestyle, is a major determinant of hypertension. It represents the most important modifiable risk factor for cardiovascular diseases, which are the leading cause of morbidity and mortality for both men and women. In addition to involving sympathetic overactivity that alters hemodynamic parameters, hypertension is accompanied by several abnormalities in the skeletal muscle circulation including vessel rarefaction and increased arteriole wall-to-lumen ratio, which contribute to increased total peripheral resistance. Low-intensity aerobic training is a promising tool for the prevention, treatment and control of high blood pressure, but its efficacy may differ between men and women and between male and female animals. This review focuses on peripheral training-induced adaptations that contribute to a blood pressure-lowering effect, with special attention to differential responses in male and female spontaneously hypertensive rats (SHR). Heart, diaphragm and skeletal muscle arterioles (but not kidney arterioles) undergo eutrophic outward remodeling in trained male SHR, which contributed to a reduction of peripheral resistance and to a pressure fall. In contrast, trained female SHR showed no change in arteriole wall-to-lumen ratio and no pressure fall. On the other hand, training-induced adaptive changes in capillaries and venules (increased density) were similar in male and female SHR, supporting a similar hyperemic response to exercise.

The use of genes for performance enhancement: doping or therapy?

Recent biotechnological advances have permitted the manipulation of genetic sequences to treat several diseases in a process called gene therapy. However, the advance of gene therapy has opened the door to the possibility of using genetic manipulation (GM) to enhance athletic performance. In such ‘gene doping’, exogenous genetic sequences are inserted into a specific tissue, altering cellular gene activity or leading to the expression of a protein product. The exogenous genes most likely to be utilized for gene doping include erythropoietin (EPO), vascular endothelial growth factor (VEGF), insulin-like growth factor type 1 (IGF-1), myostatin antagonists, and endorphin. However, many other genes could also be used, such as those involved in glucose metabolic pathways. Because gene doping would be very difficult to detect, it is inherently very attractive for those involved in sports who are prepared to cheat. Moreover, the field of gene therapy is constantly and rapidly progressing, and this is likely to generate many new possibilities for gene doping. Thus, as part of the general fight against all forms of doping, it will be necessary to develop and continually improve means of detecting exogenous gene sequences (or their products) in athletes. Nevertheless, some bioethicists have argued for a liberal approach to gene doping.

Use of the Wasserman equation in optimization of the duration of the power ramp in a cardiopulmonary exercise test: a study of Brazilian men

This study aimed to analyze the agreement between measurements of unloaded oxygen uptake and peak oxygen uptake based on equations proposed by Wasserman and on real measurements directly obtained with the ergospirometry system. We performed an incremental cardiopulmonary exercise test (CPET), which was applied to two groups of sedentary male subjects: one apparently healthy group (HG, n=12) and the other had stable coronary artery disease (n=16). The mean age in the HG was 47±4 years and that in the coronary artery disease group (CG) was 57±8 years. Both groups performed CPET on a cycle ergometer with a ramp-type protocol at an intensity that was calculated according to the Wasserman equation. In the HG, there was no significant difference between measurements predicted by the formula and real measurements obtained in CPET in the unloaded condition. However, at peak effort, a significant difference was observed between oxygen uptake (V˙O2)peak(predicted)and V˙O2peak(real)(nonparametric Wilcoxon test). In the CG, there was a significant difference of 116.26 mL/min between the predicted values by the formula and the real values obtained in the unloaded condition. A significant difference in peak effort was found, where V˙O2peak(real)was 40% lower than V˙O2peak(predicted)(nonparametric Wilcoxon test). There was no agreement between the real and predicted measurements as analyzed by Lin’s coefficient or the Bland and Altman model. The Wasserman formula does not appear to be appropriate for prediction of functional capacity of volunteers. Therefore, this formula cannot precisely predict the increase in power in incremental CPET on a cycle ergometer.

Analyzing and Computing the Sustainability Gains of Building Automation

Smart home implementation in residential buildings promises to optimize energy usage and save significant amount of energy simply due to a better understanding of user's energy usage profile. Apart from the energy optimisation prospects of this technology, it also aims to guarantee occupants significant amount of comfort and remote control over home appliances both at home locations and at remote places. However, smart home investment just like any other kind of investment requires an adequate measurement and justification of the economic gains it could proffer before its realization. These economic gains could differ for different occupants due to their inherent behaviours and tendencies. Thus it is pertinent to investigate the various behaviours and tendencies of occupants in different domain of interests and to measure the value of the energy savings accrued by smart home implementations in these domains of interest in order to justify such economic gains. This thesis investigates two domains of interests (the rented apartment and owned apartment) for primarily two behavioural tendencies (Finland and Germany) obtained from observation and corroborated by conducted interviews to measure the payback time and Return on Investment (ROI) of their smart home implementations. Also, similar measures are obtained for identified Australian use case. The research finding reveals that building automation for the Finnish behavioural tendencies seems to proffers a better ROI and payback time for smart home implementations.

Evaluation of the use of PetrifilmTM EB count plates for the enumeration of Enterobacteriaceae in poultry samples

A test that is rapid, simple, accurate, not expensive, gives rapid results, and is sensitive enough to detect low levels of microorganisms would be the most suitable for food industry routine laboratories, or even for a public health laboratories. A ready-to-use alternative, commercially available method is the PetrifilmTM EB method. The aim of this study was to evaluate whether there is a statistically significant difference between the conventional methods based on Violet Red Bile Glucose Agar and the alternative 3M TM Petrifilm (EB) method for the enumeration of Enterobacteriaceae in poultry carcasses. This study also assessed whether the alternative method showed ability to produce results that were directly proportional to the concentration of the target (approximately 270 colony-forming unit.mL-1). A total of 120 poultry carcasses samples showed a significant difference (p < 0.05) between the populations obtained by the two methods, and the conventional method showed low proportionality between the dilutions. On the other hand, the PetrifilmTM EB quantification system showed the capacity to produce results that are proportional to the concentration of the analyte in samples in the concentration range from 1 to 256 colony-forming unit.mL-1.

Use of intravascular ultrasonography for the characterization of coronary artery disease in patients with chronic kidney disease

INTRODUCTION: Chronic kidney disease patients present a very high cardiovascular mortality. Nevertheless, a comparative description of lesion characteristics, using intravascular ultrasound in dialysis patients, has not yet been reported. The objective of the present study was to analyze the plaque morphology through intravascular ultrasound in comparison to their counterparts with normal renal function. METHODS: Patients were screened for coronary artery disease, and the coronary angiography was performed when indicated. Plaque morphology was evaluated by ultrasound, and findings were compared to a group of patients with coronary artery disease, who presented normal renal function, it carefully matched for all Framingham risk factors and lesion location at the coronary artery tree. RESULTS: One hundred and thirty-nine patients from a single center of hemodialysis were screened for the study. Patients with coronary lesions confirmed at the angiography presented lower hemoglobin (10.8 ± 1.5 versus 12.0 ± 19; p < 0.046) levels and higher levels of low-density lipoprotein (110.6 ± 25.8 versus 75.5 ± 43.1; p < 0.004), when compared to the ones without coronary artery disease. The ultrasound revealed greater proximal reference diameter (4.1 ± 0.6 versus 3.7 ± 0.5; p < 0.007), smaller crossed sectional area (4.2±1.6 versus 5.2 ± 1.8; p < 0.02), and the calcification was located in a deeper arterial layer (69 versus 9%; p < 0.004) in patients with chronic kidney disease when compared to the Control Group. CONCLUSION: Lesions of the patients with chronic kidney disease presented a larger proximal diameter and intense calcification in the deeper layer of the vessel, which suggest a greater positive remodeling effect in response to a more aggressive atherosclerotic process in the medial section of the artery.

Heat Demand Forecasting Models’ Development: Use of Data Mining Tools in SQL Server Analysis Services

This thesis introduces heat demand forecasting models which are generated by using data mining algorithms. The forecast spans one full day and this forecast can be used in regulating heat consumption of buildings. For training the data mining models, two years of heat consumption data from a case building and weather measurement data from Finnish Meteorological Institute are used. The thesis utilizes Microsoft SQL Server Analysis Services data mining tools in generating the data mining models and CRISP-DM process framework to implement the research. Results show that the built models can predict heat demand at best with mean average percentage errors of 3.8% for 24-h profile and 5.9% for full day. A deployment model for integrating the generated data mining models into an existing building energy management system is also discussed.

Modelling of changes in electricity end-use and their impacts on electricity distribution

The electricity distribution sector will face significant changes in the future. Increasing reliability demands will call for major network investments. At the same time, electricity end-use is undergoing profound changes. The changes include future energy technologies and other advances in the field. New technologies such as microgeneration and electric vehicles will have different kinds of impacts on electricity distribution network loads. In addition, smart metering provides more accurate electricity consumption data and opportunities to develop sophisticated load modelling and forecasting approaches. Thus, there are both demands and opportunities to develop a new type of long-term forecasting methodology for electricity distribution. The work concentrates on the technical and economic perspectives of electricity distribution. The doctoral dissertation proposes a methodology to forecast electricity consumption in the distribution networks. The forecasting process consists of a spatial analysis, clustering, end-use modelling, scenarios and simulation methods, and the load forecasts are based on the application of automatic meter reading (AMR) data. The developed long-term forecasting process produces power-based load forecasts. By applying these results, it is possible to forecast the impacts of changes on electrical energy in the network, and further, on the distribution system operator’s revenue. These results are applicable to distribution network and business planning. This doctoral dissertation includes a case study, which tests the forecasting process in practice. For the case study, the most prominent future energy technologies are chosen, and their impacts on the electrical energy and power on the network are analysed. The most relevant topics related to changes in the operating environment, namely energy efficiency, microgeneration, electric vehicles, energy storages and demand response, are discussed in more detail. The study shows that changes in electricity end-use may have radical impacts both on electrical energy and power in the distribution networks and on the distribution revenue. These changes will probably pose challenges for distribution system operators. The study suggests solutions for the distribution system operators on how they can prepare for the changing conditions. It is concluded that a new type of load forecasting methodology is needed, because the previous methods are no longer able to produce adequate forecasts.

The role of nuclear and other conventional power plants in the flexible energy system

This thesis reviews the role of nuclear and conventional power plants in the future energy system. The review is done by utilizing freely accesible publications in addition to generating load duration and ramping curves for Nordic energy system. As the aim of the future energy system is to reduce GHG-emissions and avoid further global warming, the need for flexible power generation increases with the increased share of intermittent renewables. The goal of this thesis is to offer extensive understanding of possibilities and restrictions that nuclear power and conventional power plants have regarding flexible and sustainable generation. As a conclusion, nuclear power is the only technology that is able to provide large scale GHG-free power output variations with good ramping values. Most of the currently operating plants are able to take part in load following as the requirement to do so is already required to be included in the plant design. Load duration and ramping curves produced prove that nuclear power is able to cover most of the annual generation variation and ramping needs in the Nordic energy system. From the conventional power generation methods, only biomass combustion can be considered GHG-free because biomass is considered carbon neutral. CFB combusted biomass has good load follow capabilities in good ramping and turndown ratios. All the other conventional power generation technologies generate GHG-emissions and therefore the use of these technologies should be reduced.

Use of airborne laser scanner data in demanding forest conditions

Most of the applications of airborne laser scanner data to forestry require that the point cloud be normalized, i.e., each point represents height from the ground instead of elevation. To normalize the point cloud, a digital terrain model (DTM), which is derived from the ground returns in the point cloud, is employed. Unfortunately, extracting accurate DTMs from airborne laser scanner data is a challenging task, especially in tropical forests where the canopy is normally very thick (partially closed), leading to a situation in which only a limited number of laser pulses reach the ground. Therefore, robust algorithms for extracting accurate DTMs in low-ground-point-densitysituations are needed in order to realize the full potential of airborne laser scanner data to forestry. The objective of this thesis is to develop algorithms for processing airborne laser scanner data in order to: (1) extract DTMs in demanding forest conditions (complex terrain and low number of ground points) for applications in forestry; (2) estimate canopy base height (CBH) for forest fire behavior modeling; and (3) assess the robustness of LiDAR-based high-resolution biomass estimation models against different field plot designs. Here, the aim is to find out if field plot data gathered by professional foresters can be combined with field plot data gathered by professionally trained community foresters and used in LiDAR-based high-resolution biomass estimation modeling without affecting prediction performance. The question of interest in this case is whether or not the local forest communities can achieve the level technical proficiency required for accurate forest monitoring. The algorithms for extracting DTMs from LiDAR point clouds presented in this thesis address the challenges of extracting DTMs in low-ground-point situations and in complex terrain while the algorithm for CBH estimation addresses the challenge of variations in the distribution of points in the LiDAR point cloud caused by things like variations in tree species and season of data acquisition. These algorithms are adaptive (with respect to point cloud characteristics) and exhibit a high degree of tolerance to variations in the density and distribution of points in the LiDAR point cloud. Results of comparison with existing DTM extraction algorithms showed that DTM extraction algorithms proposed in this thesis performed better with respect to accuracy of estimating tree heights from airborne laser scanner data. On the other hand, the proposed DTM extraction algorithms, being mostly based on trend surface interpolation, can not retain small artifacts in the terrain (e.g., bumps, small hills and depressions). Therefore, the DTMs generated by these algorithms are only suitable for forestry applications where the primary objective is to estimate tree heights from normalized airborne laser scanner data. On the other hand, the algorithm for estimating CBH proposed in this thesis is based on the idea of moving voxel in which gaps (openings in the canopy) which act as fuel breaks are located and their height is estimated. Test results showed a slight improvement in CBH estimation accuracy over existing CBH estimation methods which are based on height percentiles in the airborne laser scanner data. However, being based on the idea of moving voxel, this algorithm has one main advantage over existing CBH estimation methods in the context of forest fire modeling: it has great potential in providing information about vertical fuel continuity. This information can be used to create vertical fuel continuity maps which can provide more realistic information on the risk of crown fires compared to CBH.

The effects of derivative use on equity fund performance

Investing in mutual funds has become more popular than ever and the amount of money invested in mutual funds registered in Finland has hit its all-time high. Mutual funds provide a relatively low-cost method for private investors to invest in stock market and achieve diversified portfolios. In finance there is always a tradeoff between risk and return, where higher expected returns can usually be achieved only by taking higher risks. Diversifying the portfolio gets rid some of the risk but systematic risk cannot be diversified away. These risks can be managed by hedging the investments with derivatives. The use of derivatives should improve the performance of the portfolios using them compared to the funds that don’t. However, previous studies have shown that the risk exposure and return performance of derivative users does not considerably differ from nonusers. The purpose of this study is to examine how the use of derivatives affects the performance of equity funds. The funds studied were 155 equity funds registered in Finland in 2013. Empirical research was done by studying the derivative use of the funds during a 6-year period between 2008–2013. The performance of the funds was studied quantitatively by using several different performance measures used in mutual fund industry; Sharpe Ratio, Treynor Ratio, Jensen's alpha, Sortino Ratio, M2 and Omega Ratio. The effect of derivative use on funds' performance was studied by using a dummy variable and comparing performance measures of derivative-users and nonusers. The differences in performance measures between the two groups were analyzed with statistical tests. The hypothesis was that funds' derivative use should improve their performance relative to the funds that don't use them. The results of this study are in line with previous studies that state that the use of derivatives does not improve mutual funds' performance. When performance was measured with Jensen's alpha, funds that did not use derivatives performed better than the ones that used them. When measured with other performance measures, the results didn’t differ between two groups.

(Re)writing the other/self : autoethnography in the transcultural arena of representation

Abstract: In Imperial Eyes Mary Louise Pratt (1992: 7, emphasis original) defines autoethnography as "instances in which colonized subjects undertake to represent themselves in ways that engage with the colonizer's own terms ... in response to or in dialogue with . . . metropolitan representations." Although Pratt's conceptualization of autoethnography has much to offer post-colonial studies, it has received little attention in the field. In this thesis, I interrogate Pratt's notion of autoethnography as a theoretical tool for understanding the self-representations of subordinate peoples within transcultural terrains of signification. I argue that autoethnography is a concept that allows us to move beyond some theoretical dualisms, and to recognize the (necessary) coexistence of subordinate peoples' simultaneous accommodation of and resistance to dominant representations of themselves. I suggest that even when autoethnographic expressions seem to rely on or to reproduce dominant knowledges, their very existence as speech acts implicitly resists dominant discourses which objectify members of oppressed populations and re-create them as Native Informants. I use Pratt's concept to analyze two books by Islamic feminist sociologist Fatima Memissi. Memissi's Dreams ofTrespass and Scheherazade Goes West illustrate the simultaneity of accommodation and disruption evident in autoethnographic communication. Across the two books, Memissi shows herself renegotiating the discourses which discipline her (and her speech). She switches back and forth between the positions of reader and author, demonstrates the reciprocity of the disciplinary gaze (she looks back at her dominants, reading their own reading of her representation of her social group), and provides a model of autoethnographic dialogue.

Vulnerability to adverse consequences of drinking and problem drinker status as predicted by risky drinking behaviours, drug use, sex differences and affect : a test of multiple models /

Although alcohol problems and alcohol consumption are related, consumption does not fully account for differences in vulnerability to alcohol problems. Therefore, other factors should account for these differences. Based on previous research, it was hypothesized that risky drinking behaviours, illicit and prescription drug use, affect and sex differences would account for differences in vulnerability to alcohol problems while statistically controlling for overall alcohol consumption. Four models were developed that were intended to test the predictive ability of these factors, three of which tested the predictor sets separately and a fourth which tested them in a combined model. In addition, two distinct criterion variables were regressed on the predictors. One was a measure of the frequency that participants experienced negative consequences that they attributed to their drinking and the other was a measure of the extent to which participants perceived themselves to be problem drinkers. Each of the models was tested on four samples from different populations, including fIrst year university students, university students in their graduating year, a clinical sample of people in treatment for addiction, and a community sample of young adults randomly selected from the general population. Overall, support was found for each of the models and each of the predictors in accounting for differences in vulnerability to alcohol problems. In particular, the frequency with which people become intoxicated, frequency of illicit drug use and high levels of negative affect were strong and consistent predictors of vulnerability to alcohol problems across samples and criterion variables. With the exception of the clinical sample, the combined models predicted vulnerability to negative consequences better than vulnerability to problem drinker status. Among the clinical and community samples the combined model predicted problem drinker status better than in the student samples.

The use of explicit algorithms and episodic context to teach subtraction to students with learning problems in mathematics /

This research attempted to address the question of the role of explicit algorithms and episodic contexts in the acquisition of computational procedures for regrouping in subtraction. Three groups of students having difficulty learning to subtract with regrouping were taught procedures for doing so through either an explicit algorithm, an episodic content or an examples approach. It was hypothesized that the use of an explicit algorithm represented in a flow chart format would facilitate the acquisition and retention of specific procedural steps relative to the other two conditions. On the other hand, the use of paragraph stories to create episodic content was expected to facilitate the retrieval of algorithms, particularly in a mixed presentation format. The subjects were tested on similar, near, and far transfer questions over a four-day period. Near and far transfer algorithms were also introduced on Day Two. The results suggested that both explicit and episodic context facilitate performance on questions requiring subtraction with regrouping. However, the differential effects of these two approaches on near and far transfer questions were not as easy to identify. Explicit algorithms may facilitate the acquisition of specific procedural steps while at the same time inhibiting the application of such steps to transfer questions. Similarly, the value of episodic context in cuing the retrieval of an algorithm may be limited by the ability of a subject to identify and classify a new question as an exemplar of a particular episodically deflned problem type or category. The implications of these findings in relation to the procedures employed in the teaching of Mathematics to students with learning problems are discussed in detail.

Coaches' use of and impressions of computer-mediated communication (CMC) media /

The study examined coaches' usage of text-based computer-mediated communication (CMC) media (e.g., text-messaging, email) in the coach-player relationship. Data were collected by surveying Ontario-based male baseball coaches (n = 86) who coached players between 15 and 18 years old. Predictions were made regarding how demographic factors such as age and coaching experience affected coaches' CMC use and opinions. Results indicated that over 76% of respondents never used any CMC media other than email and team websites in their interactions with players. Results also revealed that coaches' usage rates contrasted with their opinion of the usefulness of the media, and their perception of players' use of the media. Coaches characterized most CMC media as limited, unnecessary, and sometimes inappropriate. Additional research should explore players' CMC usage rates and possible guidelines for use of the new media in authority relationships. Academia needs to keep pace with the developments in this area.