The Regulation of Skeletal and Cardiac Muscle Blood Flow in Humans. Studies by positron emission tomography with special reference to exercise, adenosine and nitric oxide

Virtually every cell and organ in the human body is dependent on a proper oxygen supply. This is taken care of by the cardiovascular system that supplies tissues with oxygen precisely according to their metabolic needs. Physical exercise is one of the most demanding challenges the human circulatory system can face. During exercise skeletal muscle blood flow can easily increase some 20-fold and its proper distribution to and within muscles is of importance for optimal oxygen delivery. The local regulation of skeletal muscle blood flow during exercise remains little understood, but adenosine and nitric oxide may take part in this process. In addition to acute exercise, long-term vigorous physical conditioning also induces changes in the cardiovasculature, which leads to improved maximal physical performance. The changes are largely central, such as structural and functional changes in the heart. The function and reserve of the heart’s own vasculature can be studied by adenosine infusion, which according to animal studies evokes vasodilation via it’s a_2A receptors. This has, however, never been addressed in humans in vivo and also studies in endurance athletes have shown inconsistent results regarding the effects of sport training on myocardial blood flow. This study was performed on healthy young adults and endurance athletes and local skeletal and cardiac muscle blod flow was measured by positron emission tomography. In the heart, myocardial blood flow reserve and adenosine A_2A receptor density, and in skeletal muscle, oxygen extraction and consumption was also measured. The role of adenosine in the control of skeletal muscle blood flow during exercise, and its vasodilator effects, were addressed by infusing competitive inhibitors and adenosine into the femoral artery. The formation of skeletal muscle nitric oxide was also inhibited by a drug, with and without prostanoid blockade. As a result and conclusion, it can be said that skeletal muscle blood flow heterogeneity decreases with increasing exercise intensity most likely due to increased vascular unit recruitment, but exercise hyperemia is a very complex phenomenon that cannot be mimicked by pharmacological infusions, and no single regulator factor (e.g. adenosine or nitric oxide) accounts for a significant part of exercise-induced muscle hyperemia. However, in the present study it was observed for the first time in humans that nitric oxide is not only important regulator of the basal level of muscle blood flow, but also oxygen consumption, and together with prostanoids affects muscle blood flow and oxygen consumption during exercise. Finally, even vigorous endurance training does not seem to lead to supranormal myocardial blood flow reserve, and also other receptors than A_2A mediate the vasodilator effects of adenosine. In respect to cardiac work, atheletes heart seems to be luxuriously perfused at rest, which may result from reduced oxygen extraction or impaired efficiency due to pronouncedly enhanced myocardial mass developed to excel in strenuous exercise.

Business competence and training needs in Finnish companies operating in the Leningrad Region

Tässä pro gradu -työssä tutkitaan Leningradin alueella, Venäjällä, toimivien suomalaisyritysten liiketoimintaosaamisen koulutustarpeita. Tavoitteena on ollut tutkia, millaisia yritysten koulutustarpeet ovat, sekä lisäksi selvittää yleisemmällä tasolla, miten liiketoimintaosaaminen määritellään. Useat tutkimusta varten haastatellut johtajat pitävät liiketoimintaosaamista erityisesti markkinoilla toimimiseen liittyvänä osaamisena. Myös johtaminen, sekä tuotteet ja teknologia nähdään liiketoimintaosaamisen tärkeinä osina. Yrityksillä on koulutustarpeita seuraavilla alueilla: johtaminen; myynti, markkinat ja asiakkaat; yrityksen sisäinen yhteistyö; kielet, sekä juridiikka ja laskentatoimi. Haastateltavien mukaan markkinoiden nopea kehitys sekä yrityksen kasvu luovat yrityksille koulutustarpeita. Yllättäen myös Venäjän koulutusjärjestelmää itsessään pidetään koulutustarpeiden syynä. Tutkimuksessa mukana olleiden yritysten koulutuskäytännöt ovat keskenään melko erilaisia: koulutusbudjetti, koulutuspäivien määrä ja koulutusorganisaation valintakriteerit vaihtelevatyrityksestä riippuen. Joka tapauksessa yleisin koulutusmuoto näyttää olevan yrityksen sisäinen koulutus. Monet haastateltavat painottavat suuresti uusien työntekijöiden kouluttamista. Selvästikin rekrytointi ja uusien työntekijöiden koulutus vievät suuren osan tutkimusta varten haastateltujen johtajien ajasta. Tärkeä huomio koulutusmarkkinoihin liittyen on se, että lyhyiden, kaikille avoimien koulutusten kohdalla markkinat ovat Pietarissa täynnä. Suurimpana uhkana nähdään alalla vallitseva kouluttajapula.

On the differential evolution algorithm and its appliation to training radial basis function networks

The parameter setting of a differential evolution algorithm must meet several requirements: efficiency, effectiveness, and reliability. Problems vary. The solution of a particular problem can be represented in different ways. An algorithm most efficient in dealing with a particular representation may be less efficient in dealing with other representations. The development of differential evolution-based methods contributes substantially to research on evolutionary computing and global optimization in general. The objective of this study is to investigatethe differential evolution algorithm, the intelligent adjustment of its controlparameters, and its application. In the thesis, the differential evolution algorithm is first examined using different parameter settings and test functions. Fuzzy control is then employed to make control parameters adaptive based on an optimization process and expert knowledge. The developed algorithms are applied to training radial basis function networks for function approximation with possible variables including centers, widths, and weights of basis functions and both having control parameters kept fixed and adjusted by fuzzy controller. After the influence of control variables on the performance of the differential evolution algorithm was explored, an adaptive version of the differential evolution algorithm was developed and the differential evolution-based radial basis function network training approaches were proposed. Experimental results showed that the performance of the differential evolution algorithm is sensitive to parameter setting, and the best setting was found to be problem dependent. The fuzzy adaptive differential evolution algorithm releases the user load of parameter setting and performs better than those using all fixedparameters. Differential evolution-based approaches are effective for training Gaussian radial basis function networks.