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EU-Projekt INSYSME : innovative Systeme für erdbebentaugliche Ausfachungswände aus Ziegelmauerwerk
(2014)
Molecular-genetic identification of emerged novel invasive pathogens of Asiatic Elm Ulmus pumila L
(2014)
The dwarf elm Ulmus pumila L. (Ulmaceae) is one of indigenous species of flora in Kazakhstan and forms a basis of dendroflora in virtually all settlements of the region. In the past decade, multiple outbreaks of previously unknown diseases of the small-leaved elm have been registered. In our study, by the molecular-genetic analysis it was found that the pathogens responsible for the outbreaks are microfungi belonging to the genus Fusarium – F. solani and F. oxysporum. The nucleotide sequences (ITS regions) isolated from the diseased trees showed very high similarity with the GenBank control numbers EU625403.1 and FJ478128.1 (100.0 and 99.0 % respectively). Oncoming research will focus on the search of natural microbial antagonists of the discovered phytopathogens.
Network theory provides novel concepts that promise an improved characterization of interacting dynamical systems. Within this framework, evolving networks can be considered as being composed of nodes, representing systems, and of time-varying edges, representing interactions between these systems. This approach is highly attractive to further our understanding of the physiological and pathophysiological dynamics in human brain networks. Indeed, there is growing evidence that the epileptic process can be regarded as a large-scale network phenomenon. We here review methodologies for inferring networks from empirical time series and for a characterization of these evolving networks. We summarize recent findings derived from studies that investigate human epileptic brain networks evolving on timescales ranging from few seconds to weeks. We point to possible pitfalls and open issues, and discuss future perspectives.
One of the priority trends of carbon nanotechnology is creation of nanocomposite systems. Such carbon nanostructured composites were produced using - raw materials based on the products of agricultural waste, such as grape stones, apricot stones, rice husk. These products have a - wide spectrum of application and can be obtained in large quantities. The Institute of Combustion Problems has carried out the work on synthesis of the nanostructured carbon sorbents for multiple applications including the field of biomedicine. The article presents the data on the synthesis and physico-chemical properties of carbonaceous sorbents using physicochemical methods of investigation: separation and purification of biomolecules; isolation of phytohormone - fusicoccin; adsorbent INGO-1 in the form of an adsorption column for blood detoxification, oral (entero) sorbent - INGO-2; the study of efferent and probiotic properties and sorption activity in regard to the lipopolysaccharide (LPS), new biocomposites - based on carbonized rice husk (CRH) and cellular microorganisms; the use of CRH in wound treatment. A new material for blood detoxication (INGO-1) has been obtained. Adsorption of p-cresyl sulfate and indoxyl sulfate has shown that active carbon adsorbent can remove clinically significant level of p-cresyl sulfate and indoxyl sulfate from human plasma. Enterosorbent INGO-2 possesses high adsorption activity in relation to Gram-negative bacteria and their endotoxins. INGO-2 slows down the growth of conditionally pathogenic microorganisms, without having a negative effect on bifido and lactobacteria. The use of enterosorbent INGO-2 for sorption therapy may provide a solution to a complex problem - detoxication of the digestive tract and normalization of the intestinal micro ecology. The immobilized probiotic called "Riso-lact" was registered at the Ministry of Health of the Republic of Kazakhstan as a biologically active food additive. The developed technology is patented and provides production of the medicine in the form of freeze-dried biomass immobilized in vials.
The scope of this study is the measurement of endotoxin adsorption rate for carbonized rice husk. It showed good adsorption properties for LPS. During the batch experiments, several techniques were used and optimized for improving the material’s adsorption behavior. Also, with the results obtained it was possible to differentiate the materials according to their adsorption capacity and kinetic characteristics.
Background
True date palms (Phoenix dactylifera L.) are impressive trees and have served as an indispensable source of food for mankind in tropical and subtropical countries for centuries. The aim of this study is to differentiate date palm tree varieties by analysing leaflet cross sections with technical/optical methods and artificial neural networks (ANN).
Results
Fluorescence microscopy images of leaflet cross sections have been taken from a set of five date palm tree cultivars (Hewlat al Jouf, Khlas, Nabot Soltan, Shishi, Um Raheem). After features extraction from images, the obtained data have been fed in a multilayer perceptron ANN with backpropagation learning algorithm.
Conclusions
Overall, an accurate result in prediction and differentiation of date palm tree cultivars was achieved with average prediction in tenfold cross-validation is 89.1% and reached 100% in one of the best ANN.