It has been proved that the emotional state of a car driver has a great impact on his driving performance. Emotions can be triggered by internal stimuli (stress) or external stimuli (aggressive scenes). In this paper we propose a system of classification of certain emotional states by analysis of EEG recordings. We present the results of two experiments. In one experiment we recorded EEG data of car drivers in a simulated environment under conditions with a varying stress level. In the other experiment we presented pictures of emotional situations to car drivers. It proves that we were able to assess the state of respondents under extreme emotions.
Presented in this paper is the idea of GIS layers semantic recognition methodology. The aim was to evaluate a possibility of GIS layer recognition based on spatial analysis and performance tests which validate proposed methodology. The final interest was to develop a GIS layer classifier and evaluate its function for independent data set. In my approach to the classification of the GIS data layers I use methods based on the nearest neighbor and histogram of the distance matrix. The reasons for such a solution are in good complexity of the spatial data description and in implementation of these algorithms under statistics software. In the range of the experiment tests I developed methodology for classification and I verified that it is possible to recognize the spatial layer via spatial statistic. Then I developed the classifier based on the Kohonen's Self Organization Maps and evaluated it on a test set. All the executed tests under artificial spatial data and real GIS data show that the proposed methodology is fully relevant and forms a basis for successful use in practical applications. All executed classification models showed that the proposal methodology could directly recognize the GIS layer, as for layers with similar spatial characteristic they recognize only a class of layers. For complete recognition it is necessary to add other information about layers.
Pyridoxal kinase (PLK; EC 2.7.1.35) is a key enzyme in the metabolism of vitamin B6 (VB6) in Bombyx mori. A fusion expressional vector pET-22b-BPLK-His was constructed using a sub-cloning technique, the recombinant B. mori PLK was then expressed in Escherichia coli, purified and characterized. Bioinformatics were used to deduce the protein structure and genomic organization of this enzyme. Using Ni Sepharose affinity column chromatography, the recombinant protein was purified to very high degree (approximately 90%). The recombinant PLK exhibits a high specific enzymatic activity (1800 nmol/min/mg of protein). The maximum catalytic activity of this enzyme was recorded over a narrow pH range (5.5-6.0) and Zn2+ is the most effective cation for catalysis under saturating substrate concentrations. When only triethanolamine is present as the cation, K+ is an activator of PLK. A double reciprocal plot of initial velocity suggests that the enzyme catalyses the reaction by means of a sequential catalytic mechanism. Under optimal conditions, the Km value for the substrates of ATP and pyridoxal are 57.9 ± 5.1 and 44.1 ± 3.9 µM. B. mori's genome contains a single copy of the PLK gene, which is 7.73 kb long and contains five exons and four introns, and is located on the eighth chromosome. The PLK may be a dimer with two identical subunits under native conditions, and it is hypothesized that each monomer contains eight α-helices (α1-8), nine β-strands (β1-9) and two segments of 310 helices. and Shuo-Hao HUANG, Wang MA, Ping-Ping ZHANG, Jian-Yun ZHANG, Yan-Feng XIE, Long-Quan HUANG.
Sepsis is a life threatening condition that arises when the body's response to an infection injures its own tissues and organs. Sepsis can lead to shock, multiple organ failure and death especially if not recognized early and treated promptly. Molecular mechanisms underlying the systemic inflammatory response syndrome associated with sepsis are still not completely defined and most therapies developed to target the acute inflammatory component of the disease are insufficient. In this s tudy we investigated a possibility of combating sepsis in a mouse model by intravenous treatment with recombinant human tissue non - specific alkaline phosphatase (rhTNAP) derived from transgenic rabbit milk. We induced sepsis in mice by intraperitoneal inje ction of LPS and three hours later treated experimental group of mice by intravenous injection with rhTNAP derived from transgenic rabbits. Such treatment was proved to be physiologically effective in this model, as administration of recombinant rhTNAP suc cessfully combated the decrease in body temperature and resulted in increased survival of mice (80 % vs. 30 % in a control group). In a control experiment, also the administration of bovine intestinal alkaline phosphatase by intravenous injection proved to be effective in increasing survival of mice treated with LPS. Altogether, present work demonstrates the redeeming effect of the recombinant tissue non -specific AP derived from milk of genetically modified rabbits in combating sepsis induced by LPS., B. Bender, M. Baranyi, A. Kerekes, L. Bodrogi, R. Brands, P. Uhrin, Z. Bösze., and Obsahuje bibliografii
It was recognized that recombinant inbred strains are a very powerful system for the study of the genetics of hypertension, linkage analysis and gene mapping. Such set of recombinant inbred strains has been developed in the cooperation of Prof V. Křen and Dr. M. Pravenec in Prague. These recombinant inbred strains were used to search for the genes of spontaneous hypertension and to test the phenotypic differences. It was found that 1) the major histocompatibility compex of the rats showed a significant association with blood pressure, 2) the restriction fragment lenght polymorphism in kallikrein gene family as well as renin gene cosegregated with blood pressure, 3) Na+ leak in red blood cells cosegregated with blood pressure, 4) the relative heart and kidney weights are not closely related to mean arterial pressure and 5) the platelet aggregation and blood pressure are independent traits. The results indicate the usefulness of recombinant inbred strains in the analysis of the relationship between phenotype and genotype.
With the rapid development of location-acquisition technologies (GPS, GSM networks, etc.), more and more unstructured, geo-referenced data are accumulated on the Web. Such abundant location-based data imply, to some extent, users interests in places, so these data can be exploited for various location-based services, such as tour recommendation. In this paper, we demonstrate that, through utilizing the location data from a popular photo sharing web site such as Flickr, we can explore interesting landmarks for recommendations. We aim to generate personalized landmark recommendations based on geo-tagged photos for each user. Meanwhile, we also try to answer such a question that when we want to go sightseeing in a large city like Beijing, where should we go? To achieve our goal, first, we present a data field clustering method (DFCM), which is a density-based clustering method initially developed to cluster point objects. By using DFCM, we can cluster a large-scale geo-tagged web photo collection into groups (or landmarks) by location. And then, we provide more friendly and comprehensive overviews for each landmark. Subsequently, we present an improved user similarity method, which not only uses the overview semantic similarity, but also considers the trajectory similarity and the landmark trajectory similarity. Finally, we propose a personalized landmark recommendation algorithm based on the improved user similarity method, and adopt a TF-IDF like strategy to produce the nontrivial landmark recommendation. Experimental results show that our proposed approach can obtain a better performance than several state-of-the-art methods.