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Pollack Periodica
Authors: Dávid Nagy, Tamás Mihálydeák, and László Aszalós

similar, and the objects from different groups are dissimilar. This defines an equivalence relation. The similarity is usually based on the distance of the objects. However, sometimes only categorical data are given where distance is meaningless. For

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Resolution and Discovery
Authors: Taťána Fenclová, Zdeněk Jonšta, Miroslav Hnatko, Josef Kraxner, and Pavol Šajgalík

their similarity to human bone, for large active surface to join the tissue with bioceramic and for binding the bioactive substance to the surface of the microspheres. The pores in the microspheres (>100 μm) are not only formed by gas, which is produced

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similarity with natural bone [ 4 ]. The classical methods for Hap preparation include wet chemical processes as well as solid state procedure using precursors either of synthetic and biological nature [ 5 – 8 ]. However, Hap in pure form has poor mechanical

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Scientia et Securitas
Authors: Brigitta Tóth, Ádám Boncz, Bálint File, István Winkler, and Márk Molnár

Összefoglalás. A hálózatkutatás idegtudományi alkalmazása áttörő eredményt hozott a humán kogníció és a neurális rendszerek közötti kapcsolat megértésében. Jelen tanulmány célja a neurális hálózatok néhány kutatási területét mutatja be a laborunkban végzett vizsgálatok eredményein keresztül. Bemutatjuk az agyi aktivitás mérésének és az agyi területek közötti kommunikációs hálózatok modellezésének technikáját. Majd kiemelünk két kutatási terület: 1) az agyi hálózatok életkori változásainak vizsgálatát, ami választ ad arra, hogy hogyan öregszik az emberi agy; 2) az emberi agyak közötti hálózat modelljének vizsgálatát, amely a hatékony emberi kommunikáció idegrendszeri mechanizmusait próbálja feltárni. Tárgyaljuk a humán kommunikációra képes mesterséges intelligencia fejlesztésének lehetőségét is. Végül kitérünk az agyi hálózatok kutatásának biztonságpolitikai vonatkozásaira.

Summary. The human brain consists of 100 billion neurons connected by about 100 trillion synapses, which are hierarchically organized in different scales in anatomical space and time. Thus, it sounds reasonable to assume that the brain is the most complex network known to man. Network science applications in neuroscience are aimed to understand how human feeling, thought and behavior could emerge from this biological system of the brain. The present review focuses on the recent results and the future of network neuroscience. The following topics will be discussed:

Modeling the network of communication among brain areas. Neural activity can be recorded with high temporal precision using electroencephalography (EEG). Communication strength between brain regions then might be estimated by calculating mathematical synchronization indices between source localized EEG time series. Finally, graph theoretical models can describe the relationship between system elements (i.e. efficiency of communication or centrality of an element).

How does the brain age? While for a newborn the high plasticity of the brain provides the foundation of cognitive development, cognition declines with advanced age due to so far largely unknown neural mechanisms. In one of our studies, we demonstrated that there is a correlation between the anatomical development of the brain (at prenatal age) and its network topology. Specifically, the more developed the baby’s brain, the more functionally specialized/modular it was. In another study we found that in older adults, when compared to young adults, connectivity within modules of their brain network is decreased, with an associated decline in their short-term memory capacity. Moreover, Mild Cognitive Impairment patients (early stage of Alzheimer) were characterized with a significantly lower level of connectivity between their brain modules than the healthy elderly.

Human communication via shared network of brain activity. In another study we recorded the brain activity of a speaker and multiple listeners. We investigated the brain network similarity across listeners and between the speaker and listeners. We found that brain activity was significantly correlated among listeners, providing evidence for the fact that the same content is processed via similar neural computations within different brains. The data also suggested that the more the brain activity synchronizes the more the mental state of the individuals overlap. We also found significantly synchronized brain activity between speaker and listeners. Specifically 1) listeners’ brain activity within the speech processing cortices was synchronized to speaker’s brain activity with a time lag, indicating that listeners’ speech comprehension processes replicated the speaker’s speech production processes; and 2) listeners’ frontal cortical activity was synchronized to speaker’s later brain activity, that is, listeners preceded the speaker, indicating that speech content is predicted by the listeners based on the context.

Future challenges. Future research could target artificial intelligence development that is capable of human-like communication. To achieve this, the simultaneous recording of brain activity from listener and speaker is needed together with efficiency of the communication. These data could be then modelled via AI to detect biomarkers of communication efficiency. In general, neurotechnology has been rapidly developing within and outside of research and in clinical fields thus it is time for re-conceptualizing the corresponding human right law in order to avoid unwanted consequences of technological applications.

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average acceleration of the vehicles into speed-acceleration bins. The similarity between the SAPD of a candidate driving cycle and the SAPD of the full dataset is another useful indicator of the representativeness. We used the Quality of Fit (QoF) value

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] ( Fig. 3 ). Fig.3. Illustration of the relationship between mutual information and entropy (Studholme, 1999) used NMI, Eq. (4) , to measure similarity. This measure proved its reliability on the 3D medical images. It is defined as follows: (4) N M I = H

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cloning probability, which refers to the similarity of two implicated flowers. (iv) The switching between local and global pollination can be controlled by interaction probability P n ∈ [0, 1]. To formulate the algorithm update procedure, the assumptions

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sharing. By using the ontology, syntax and semantics are defined to describe the information explicitly. As discussed in [ 30 ], compared to other information modeling methodologies, the use of ontology has some similarities but also some distinct

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Abstract

Human beings live in a complex and magical system of nature. The constitution of everything is like the structure science of architecture, which presents various forms and combinations. The development of structure science makes modern architecture show the high unity of internal structure and external contour. Through the study of branch networks formed by rivers, the mystery of branch growth can be found, for instance fractal self-similarity, preferential growth at the tops, avoidance of homogeneity, etc. Based on the understanding of branch ecosystem, everyone can try to build a sustainable surface structure by mimicking the laws of river network.

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similarity index , International Conference on Advances in Computing, Communications and Informatics (ICACCI) , delhi, India, 24-27 Sept. 2014 , pp. 1573 − 1577 . [3

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