7-mi dimenzionální optimalizační úloha: PBO-Přírodními procesy inspirovaný optimalizátor versus 10 let starý algoritmue EPSDE

Origins of the branch of numerical optimizations with use of evolutionary opti-mizers date almost 60 years back. It is the area which does not evolve by big jumps and the advancement sometimes hits stagnation periods. At such stagna-tion times there is a big hungry for the new optimization methods which would fill up the empty space. Many optimizers have appeared in the last decade. These optimizers are more specialized in comparison to optimizers which were pro-posed dozens of years back. The new optimizers are very often derived from old-er optimizers. In this presented paper, a 7-dimensional optimization task is solved which is called persons identification using contour of a human hand. The paper is considered as research and comparative study at the same time. An optimizer called EPSDE is compared to the Polar Bear Optimizer. The EPSDE is a deputy of 3rd generation optimizers derived from algorithm differential evolution. The PBO falls into a group of young optimizers marked as „nature inspired“. The PBO is three times more time-demanding and primarily significantly worse in solving of given task which is very difficult. A comparison of both optimizers was conducted with use of large comparative database.Počátky evoluční numerické optimalizace spadají až do 60. let minulého století. Tato vědní oblast se rozhodně nevyvíjí velkými skoky a často se v průběhu let setkáváme i s obdobím stagnace. V obdobích stagnace je logicky velký hlad po nových metodách, které by zaplnily prázdné místo ve vývoji. V poslední dekádě se objevilo mnoho zajímavých optimalizátorů. Jsou více specializované v porovnání s těmi, které se objevily před desítkami let. V předkládaném článku je presentována komparativní studie nazvaná 7mi dimenzionální optimalizační úloha řešící identifikaci osob s využitím kontury lidské ruky. Studie je uvažována jako výzkumná i komparativní současně. Optimalizátor EPSDE je zde porovnáván vůči optimalizátoru PBO. EPSDE je zástupce třetí generace optimalizátorů odvozených od algoritmu diferenciální evoluce. PBO naopak spadá do kategorie nových, mladých a progresivních a přírodou inspirovaných optimalizátorů. PBO je téměř třikrát časově náročnější v porovnání s EPSDE a navíc danou úlohu řeší velmi špatně

Proteomic analysis of β-1,3-glucanase in grape berry tissues

Grape berries are considered recalcitrant materials in proteomic analysis, because berry tissues contain large amounts of secondary metabolites, especially phenolic compounds, which severely interfere with protein extraction and electrophoresis separation. We report hereby a PVPP/TCA-based protein extraction protocol for grape berries. Phenolic compounds in berry extracts were removed with repeated PVPP cleanups, and proteins were recovered with TCA precipitation. Protein resolution in 2-D gels was gradually improved with the increase of PVPP cleanup steps. By the protocol, about 760 protein spots of berry tissues were clearly resolved in 2-D gels with CBB staining. This protocol was also used to analyze b-1,3-glucanase (EC 3.2.1.39) in berry tissues. An antisynthetic peptide antibody was prepared against 15 amino acid sequence residing on the surface of b-1,3-glucanase molecule. It detected two major spots in 2-D blots of berry extracts. The spots were identified by MALDI-TOF analysis as b-1,3-glucanase. The present study validates that b-1,3-glucanase is present in higher abundance in berry skins than in pulps, and in red berries than in white berries. Therefore, b-1,3-glucanase displays a tissue-specific expression. The preferential accumulation of b-1,3-glucanase in skins may be relevant to berry ripening