ТЕХНОЛОГИИ ОПРЕДЕЛЕНИЯ МЕСТОПОЛОЖЕНИЯ АБОНЕНТОВ В СИСТЕМАХ СОТОВОЙ СВЯЗИ

Рассмотрены общие принципы определения местоположения мобильной станции, а так же наиболее распространённые методы и технологии

3D modeling of the mechanical behavior of ceramics with pores of different size

Movable cellular automaton method was used for simulating uniaxial compression of 3D porous ceramic samples. Pores were considered explicitly by removing randomly selected automata from the original FCC packing. Distribution of pores in space, their size and the total fraction were varied. It is shown that the relation between mechanical properties of the material and its porosity significantly depends on the pore size. Thus, value of the elastic modulus of the samples with large pores is greater than that of the samples with small pores by average value of 3%-16%. Strength value of the samples with large pores is less than that of the samples with small pores by average value of 12% up to the porosity of 0.55, and then becomes to be greater. When the samples contain small and large pores there is a maximum of mechanical properties at ratio of volumes of large and small pores of about 0.75

Effect of erbium-doped: yttrium, aluminium and garnet laser irradiation on the surface microstructure and roughness of sand-blasted, large grit, acid-etched implants

Aerospace Engineerin

Analysis of microbiota associated with peri-implantitis using 16S rRNA gene clone library

Background: Peri-implantitis (PI) is an inflammatory disease which leads to the destruction of soft and hard tissues around osseointegrated implants. The subgingival microbiota appears to be responsible for peri-implant lesions and although the complexity of the microbiota has been reported in PI, the microbiota responsible for PI has not been identified. Objective: The purpose of this study was to identify the microbiota in subjects who have PI, clinically healthy implants, and periodontitis-affected teeth using 16S rRNA gene clone library analysis to clarify the microbial differences. Design: Three subjects participated in this study. The conditions around the teeth and implants were evaluated based on clinical and radiographic examinations and diseased implants, clinically healthy implants, and periodontally diseased teeth were selected. Subgingival plaque samples were taken from the deepest pockets using sterile paper points. Prevalence and identity of bacteria was analyzed using a 16S rRNA gene clone library technique. Results: A total of 112 different species were identified from 335 clones sequenced. Among the 112 species, 51 (46%) were uncultivated phylotypes, of which 22 were novel phylotypes. The numbers of bacterial species identified at the sites of PI, periodontitis, and periodontally healthy implants were 77, 57, and 12, respectively. Microbiota in PI mainly included Gram-negative species and the composition was more diverse when compared to that of the healthy implant and periodontitis. The phyla Chloroflexi, Tenericutes, and Synergistetes were only detected at PI sites, as were Parvimonas micra, Peptostreptococcus stomatis, Pseudoramibacter alactolyticus, and Solobacterium moorei. Low levels of periodontopathic bacteria, such as Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans, were seen in peri-implant lesions. Conclusions: The biofilm in PI showed a more complex microbiota when compared to periodontitis and periodontally healthy teeth, and it was mainly composed of Gram-negative anaerobic bacteria. Common periodontopathic bacteria showed low prevalence, and several bacteria were identified as candidate pathogens in PI