Using Neural Networks for Relation Extraction from Biomedical Literature

Using different sources of information to support automated extracting of relations between biomedical concepts contributes to the development of our understanding of biological systems. The primary comprehensive source of these relations is biomedical literature. Several relation extraction approaches have been proposed to identify relations between concepts in biomedical literature, namely, using neural networks algorithms. The use of multichannel architectures composed of multiple data representations, as in deep neural networks, is leading to state-of-the-art results. The right combination of data representations can eventually lead us to even higher evaluation scores in relation extraction tasks. Thus, biomedical ontologies play a fundamental role by providing semantic and ancestry information about an entity. The incorporation of biomedical ontologies has already been proved to enhance previous state-of-the-art results.Comment: Artificial Neural Networks book (Springer) - Chapter 1

Stock price development forecasting using neural networks

Stock price forecasting is highly important for the entire market economy as well as the investors themselves. However, stock prices develop in a non-linear way. It is therefore rather complicated to accurately forecast their development. A number of authors are now trying to find a suitable tool for forecasting the stock prices. One of such tools is undoubtedly artificial neural network, which have a potential of accurate forecast based even on non-linear data. The objective of this contribution is to use neural networks for forecasting the development of the ČEZ, a. s. stock prices on the Prague Stock Exchange for the next 62 trading days. The data for the forecast have been obtained from the Prague Stock Exchange database. These are final prices at the end of each trading day when the company shares were traded, starting from the beginning of the year 2012 till September 2017. The data are processed by the Statistica software, generating multiple layer perceptron (MLP) and radial basis function (RBF) networks. In total, there are 10,000 neural network structures, out of which 5 with the best characteristics are retained. Using statistical interpretation of the results obtained, it was found that all retained networks are applicable in practice

Temporal and Bathymetric Variation of Epiphytic Microalgae on Posidonia oceanica (L.) Delile Leaves in Gökçeada (North Aegean, Turkey)

Epiphytic microalgae attached to Posidonia oceanica leaves play a significant role through primary production, nutrient cycling and trophic fluxes in benthic ecosystems. Due to their sensitivity, epiphytic microalgae respond to environmental alterations more quickly than their host. The aim of this study is therefore to evaluate the ecological quality in Gökçeada Underwater Park (North Aegean) using epiphytic microalgal composition and abundance. In this respect, P. oceanica shoots are collected at 6m, 15m and 28m in May, July, October 2009 and January 2010 to estimate the microalgal composition and abundance. Also, P. oceanica descriptors and physico-chemical parameters in the water column of the meadow lower limit are measured. Leaf surface improvement through greater depths, have provided a convenient substratum for epiphytic colonization. A total of 56 taxa belonging to epiphytic microalgae are composed of Bacillariophyceae (91%), Cyanophyceae (7%) and Dinophyceae (2%). Temporal and bathymetric dynamics of the epiphytic community structure and abundance depend on the environmental parameters; such as leaf surface, nutrients and turbidity. Also, a mucilage phenomenon, resulted in a low diversity due to the dominancy of filamentous cyanobacteria. Necessary data is supplied for a less evaluated region affected by agricultural activities and urbanization in the recent years.</jats:p

Evaluating the coastal ecosystem status of two Western and Eastern Mediterranean islands using the seagrass Posidonia oceanica

Mediterranean seagrass Posidonia oceanica is used as a 'biological quality element' in the long-term monitoring programmes of the Water Framework Directive (WFD 2000/60/EC) for the evaluation of ecological status of coastal waters. Due to its low resilience to anthropogenic pressures, P. oceanica meadows have disappeared irreversibly along some of the Mediterranean coasts. The main objective of this survey, is therefore to compare the ecological status of coastal waters and P. oceanica meadows in two islands from Eastern (Gokceada, Turkey) and Western (Corsica, France) Mediterranean Sea based on the Posidonia Biotic Index (BiPo) and the Vitality Index besides concentrating on: (i) their consistency in different environmental conditions present in the Mediterranean Sea, (ii) their effectiveness to discriminate the ecological status of coastal waters in relation to different anthropogenic pressures and (iii) their application capacity to initiate long-term data series for monitoring the evolution of the meadows in less evaluated regions (i.e. from the Eastern Mediterranean). The measurements of several descriptors of P. oceanica are interpreted based on the BiPo and the Vitality indices for 2 regions; 9 sites from Gokceada and 15 sites from Corsica exposed to different human pressures. The mean BiPo and Vitality indices are higher in Corsica than in Gokceada, where the values correspond to a "good" status for Corsica and a "moderate" status in Gokceada. The application of these biotic indices showed their feasibility and comparability to assess the ecological status in different environmental conditions. Significant relationships between the scores of Anthropization index and the EQR values of the BiPo index (r = - 0.745, p < 0.01) and the Vitality index (r = - 0.702, p < 0.01) highlighted their efficiency to determine the seagrass degradation in the sites subjected to higher pressure levels. It can be assumed that this study initiates the development of long-term data series and also meets the essential data deficiency in less evaluated regions

Interior design of passenger coaches using fuzzy optimization

AbstractPassenger coaches are one of the most important mass transportation vehicles for inner city passenger transportation and the proper interior design problem of the passenger coaches affect both passenger satisfaction and service quality. Defining user expectation and meeting them is important to solve this problem, which naturally contains ambiguity and vagueness. The study aims to maximize the total passenger number together with providing user satisfaction while designing interior area of passenger coaches. User expectations are defined by a survey and new design is defined with respect to anthropometric measures of human body. The collected data used to establish a fuzzy mathematic model to capture the ambiguity and vagueness of the problem and the mathematical model is solved using fuzzy optimization with respect to the constraints

Definition of artificial neural networks with comparison to other networks

AbstractDefinition of Artificial Neural Networks (ANNs) is made by computer scientists, artificial intelligence experts and mathematicians in various dimensions. Many of the definitions explain ANN by referring to graphics instead of giving well explained mathematical definitions; therefore, misleading weighted graphs (as in minimum cost flow problem networks) fit the definition of ANN. This study aims to give a clear definition that will differentiate ANN and graphical networks by referring to biological neural networks. The proposed definition of ANN is a mathematical definition, from the point of graph theory which defines ANN as a directed graph. Then differences between ANNs and other networks will be explained by examples using proposed definition

New records of pelagic fauna from the Turkish waters

In this work, three pelagic species have been recorded in the Northern Aegean Sea. The species were collected from depths between 500 and 800 m from 5 stations in summer 2016. While Euphausia krohnii is first recorded from the Turkish coast of the Aegean Sea, Allosergestes sargassi and Flaccisagitta hexaptera are reported for the first time from the Turkish seas. The results of the current study will contribute to the knowledge on the deep-water pelagic fauna of the Northern Aegean Sea

Spatio-temporal dynamic of submerged aquatic macrophytes in Lake Sapanca

Aquatic macrophytes are one of the key components of freshwater ecosystems and contribute to ecosystem functioning and environmental sustainability. They are assumed to be an ideal biomonitoring tool in long-term monitoring programs implemented by the EU Water Framework Directive due to their sensitivity to environmental factors. Therefore, this study focuses on the evaluation of the ecological status in Lake Sapanca using macrophyte composition and abundance in order to make future predictions on the health of aquatic ecosystems and to form effective management. Submerged macrophyte assemblages related to environmental parameters were investigated from February to November of 2017. A total of 12 submerged macrophyte species were recorded in the littoral zone of the lake. The main findings on the most dominant 7 species of this community indicated significant differences among stations and seasons. They also revealed that submerged macrophyte density was shaped in relation to environmental variables, particularly temperature and nutrients. Submerged macrophyte assemblages reached their highest species number and biomass value (5312 gm(-2)) in summer, while no species was recorded in winter. High biomass values of these species corresponded with lower macrophyte diversity. The macrophyte index results demonstrated that Lake Sapanca is at a critical level in terms of nutrient enrichment. More frequent observation of species such as Ceratophyllum demersum and Elodea canadensis, which indicated "massive" nutrient enrichment, revealed that the ecological status of the lake varies from meso-to eutrophic at the local level

Distribution and mortality of the Mediterranean Stony Coral (Cladocora caespitosa Linnaeus, 1767) around Gokceada Island (Northern Aegean Sea)

Cladocora caespitosa colonies around Gokceada Island had discrete and scattered distribution with regional density of 0.12 colonies.m(-2) and a mean cover of 0.27%. The size frequency distribution of the colonies showed a prevalence of small sizes, possibly related to frequent storm events. About 15% of the colonies were affected by mortality, of which 67% were recently dead, probably due to positive thermal anomalies. This is the first report of mortality of this species from the Aegean Sea and from the Turkish coasts. Considering the vulnerability of the species to climate change and harvesting in the island, we suggest that C. caespitosa should be included in the list of species completely prohibited to harvest according to the statements 2012/66 and 2012/65 of Turkish law