IL-12, IL-6 and IFN-gamma production by lymphocytes of pregnant women with rheumatoid arthritis remission during pregnancy.

BACKGROUND: Rheumatoid arthritis (RA) is an autoimmune disease with progressive activity. The RA remission was observed in women during pregnancy, but the mechanism responsible for remission is hypothetical only and concerns mechanisms of immune regulation such as lymphocyte subpopulations and interleukin production. AIMS: The lymphocyte subpopulations and interleukin production in vitro in a group of healthy non-pregnant women, healthy pregnant women and pregnant women suffering from RA may help towards a better understanding of regulation of the immune processes. METHODS: The investigations were performed in trimester III--2 days after delivery and 6 weeks after delivery. Peripheral blood lymphocytes were isolated on Gradisol gradient and analysed immediately or after having been cultured for 72 hours in RPMI medium supplemented with 10% FCS. The cultures were terminated after 72 h, supernatants stored at -72 degrees C for interleukin evaluation. The concentrations of IFN-gamma, IL-2, IL-6, IL-12, TNF-alpha and its soluble receptors R-I, R-II were estimated in non-stimulated and PHA (Sigma, 5 microg/ml) stimulated culture supernatants using ELISA Endogen kits according to the manufacturer's instructions. RESULTS: The general pattern of T cell subpopulation distribution was similar in all analysed groups. Decreased IFN-gamma, IL-12 and increased IL-6 production by lymphocytes after PHA stimulation was found in trimester III in pregnant women with RA as compared to healthy pregnant woman. CONCLUSION: The obtained results suggest that in pregnant women with RA the TH1 cell response predominates, contrary to healthy pregnant women with TH2 type functional response. These phenomena were not observed after delivery

Neuronal modeling of power system development. Part 2. Models of IEEE RTS system

W pracy zamieszczono wybrane wyniki badań dotyczące modelowania neuralnego rozwoju systemu elektroenergetycznego na bazie danych testowych IEEE RTS 96., m.in.: sposób tworzenia macierzy danych wejściowych oraz wyjściowych, sposób doboru parametrów sieci, itp. W wyniku projektowania i uczenia SSN uzyskano modele rozwoju SEE, które poddano badaniom wrażliwości m.in. na zmianę liczby warstw ukrytych oraz liczby neuronów w warstwie.The paper presents selected results of research on the modeling of neural development of the power system test data based on the IEEE RTS 96, m.in .: how to create a matrix of data input and output, how to select the network parameters and the like. As a result of learning design and development of the ANN models were obtained SEE, which has been tested sensitivity among to change the number of hidden layers and the number of neurons in a layer

Design and research on artificial neural networks as electrical power system development models based on IEEE RTS data

The paper presents selected results of research on the design of artificial neural networks and training them using the electrical power system development model (EPS or EP system) based on IEEE RTS 96 test data, i.a. creation of training and test files, development of architecture of the artificial neural network, selection of parameters of the network, selection of appropriate training and testing method, etc. As a result of the development and training an ANN, the following EP system development models were obtained, which were examined for sensitivity to changes of the number of hidden layers, number of neurons in a layer, activation function, training method, etc. Subsequently, simulation models for studying fitness of the obtained models to the real systems. Interesting results were obtained, e.g. the method of the neural modelling of the system, the optimal architecture of the ANN that is a model of the system, possibilities and directions to improve a neural model of the system, etc

Paradigms development models power system. Part 2 Comparative methods for the identification

W pracy zamieszczono wybrane wyniki przeprowadzonych badań porównawczych metod i modeli identyfikacji rozwoju krajowego systemu elektroenergetycznego (KSE lub system KSE) na wybranym przykładzie danych liczbowych z lat 1980-2010 [7], Zaproponowano algorytmy identyfikacji, a następnie przeprowadzono identyfikację z wykorzystaniem m.in metody arx, armax, ar, bj uzyskując modele rozwoju KSE. Porównano też metody z punktu widzenia wykorzystania otrzymanych modeli do projektowania rozwoju systemu KSE. Do przeprowadzenia identyfikacji wykorzystano środowisko MATLABAi Simulinka z System Identification Toolboxem stosując metody identyfikacji takie jak: arx (ang. AutoRegressive with eXogenous input) model autoregresji z zewnętrznym wymuszeniem, armax (ang. AutoRegressive Moving Average with eXogeneus input), oe (ang. output error) model błędu wejściowego oraz bj model Box-Jenkinsa. Identyfikację przeprowadzono w 8 eksperymentach, a uzyskane wyniki wykorzystano do badań porównawczych, które przeprowadzono w Simulinku budując odpowiednie modele w postaci schematów blokowych.The paper presents some results of comparative studies on the identification of methods and models applied to build a model for development of the power system (or system EEE EE) on the selected numerical example. Identification algorithms have been developed and were identified using the method m.in arx, ARMAX, ar, bj obtain models of KSE. It was also an attempt to compare the methods in terms of the use of models to design received the development of the EE. In order to carry out the experiments, identification numbers, data from the years 1980-2010 published including in the annals of Polish Electrical Power Engineering Statistics and the Central Statistical Office. Used to carry out the identification of the MATLAB environment Identification System Toolbox. EE system identification was performed using the following identification methods such as arx (autoregressive with exogenous called input) autoregressive model with external forcing, armax (autoregressive called Moving Average with eXogeneus input), for which a substitute in the equation nf = nd = 0, oe (called output error) model input error on = nc = nd = 0, bj Box-Jenkins model, at = 0 The identification was carried out in five experiments, and the results were used for comparative studies that were conducted in Simulink building appropriate models

Systemimical [!] evolutionary algorithm model for improving the system electric power exchange. Part 2, The implementation and some results

Artykuł jest kontynuacją pracy o tym samym tytule głównym i podtytułem Część 1. Istota i możliwości metody. W niniejszym artykule pokazano w jaki praktyczny sposób można utworzyć Populację Początkową (PP) na bazie modelu parametrycznego arx Towarowej Giełdy Energii Elektrycznej (TGEE) otrzymanego w wyniku identyfikacji z wykorzystaniem danych liczbowych notowanych na Rynku Dnia Następnego (RDN). Pokazano też systemowy sposób konstruowania funkcji krzepkości jak też systemowych operatorów krzyżowania i mutacji, a także metody selekcji. Algorytm zaimplementowano w języku Matlab i przetestowano z wykorzystaniem danych TGEE. Uzyskano wiele interesujących wyników badań, w tym w zakresie przebiegu algorytmu jak też wizualizacji wybranych wyniki badań.The paper is a continuation of the article under the same title and subtitle the main part 1 The essence and the possibility of implementing. This article shows how a practical way to create initial population (PP) based on parametric model arx Power Exchange Electricity (TGEE) obtained as a result of identification using the figures listed on the Day Ahead Market (DAM). It also shows a process for designing a system as well as robustness features of system the crossover and mutation and selection methods. The algorithm is implemented in Matlab and tested using data TGEE. They obtained many interesting results, including the course of the algorithm as well as the visualization of selected results

Planning in production in coal mining with using information collected in GIS systems

Planując produkcję węgla kamiennego, musimy przygotowywać z wieloletnim wyprzedzeniem informacje o przewidywanych do realizacji zadaniach związanych z robotami górniczymi, zakupami wyposażenia czy też właściwą produkcją. Wiarygodność informacji dotyczącej wielkości zasobów oraz jakości węgla, który ma być eksploatowany, stanowi jedną z kluczowych informacji, jakie są niezbędne dla prawidłowego funkcjonowania kopalni węgla kamiennego.While planning production of coal we have to prepare information connected with planned mining works, buying of proper equipement or proper production of coal with advance of many years. Credibility of information containing the size of resources or the quality of coal, which is to be exploited, is vital for coal mine to function properly

Qualitative risk analysis in private sector projects

Jakościowa analiza ryzyka jest procesem, który polega na oszacowaniu wielkości prawdopodobieństwa oraz skutków wystąpienia czynników ryzyka, określonych na etapie identyfikacji. Ma ona umożliwić dokonanie hierarchizacji zidentyfikowanych czynników według ich potencjalnego wpływu na osiągnięcie celów projektu, wskazując kierownikowi projektu ryzyko priorytetowe (ze względu na przyjęte kryterium, np. poziom ryzyka, prawdopodobieństwo lub dotkliwość skutków), przeznaczone do dalszej analizy. W artykule zaprezentowano hierarchię czynników ryzyka w projektach planowanych i realizowanych w sektorze prywatnym, utworzoną na podstawie przeprowadzonych badań empirycznych oraz przedstawiono rekomendacje dla poprawy obecnej sytuacji.Qualitative risk analysis is the estimation of the probability and impact of risks that have been identified during identification phase. It should allow to make a hierarchy of identified risks according to their potential impact on the achievement of the project objectives. It should also show to the project manager the priority risk (in accordance with criteria such as the level of risk, the likelihood or severity of effects) for further analysis. The article presents the hierarchy of risks in private sector projects that is based on empirical research and makes recommendations for improving the current situation

Self-Organizing Wireless Ad-Hock Sensor Networks

The main target of this article is to review the main items connected with Smart Dust and their resolving proposals by research workers. In chapter 1 contains hardware description, chapter 2 contains software description divided Into positioning problems, routing, description of TinyOS, tools used for building working environment and security, chapter 3 contains conclusions and proposals for future development

Dealing with Non-Convexity in Geographic Routing in Smart Dust Networks

The paper proposes a new approach to greedy geographic routing for sensor networks with non-convex covering structure