This paper presents implementation of optimal search strategy (OSS) in verification of assembly process based on neural vibration learning. The application problem is the complex robot assembly of miniature parts in the example of mating the gears of one multistage planetary speed reducer. Assembly of tube over the planetary gears was noticed as the most difficult problem of overall assembly. The favourable influence of vibration and rotation movement on compensation of tolerance was also observed. With the proposed neural-network-based learning algorithm, it is possible to find extended scope of vibration state parameter. Using optimal search strategy based on minimal distance path between vibration parameter stage sets (amplitude and frequencies of robots gripe vibration) and recovery parameter algorithm, we can improve the robot assembly behaviour, that is, allow the fastest possible way of mating. We have verified by using simulation programs that search strategy is suitable for the situation of unexpected events due to uncertainties.

Peripheral biomarkers of Alzheimer's disease (AD) reflecting early neuropathological change are critical to the development of treatments for this condition. The most widely used indicator of AD pathology in life at present is neuroimaging evidence of brain atrophy. We therefore performed a proteomic analysis of plasma to derive biomarkers associated with brain atrophy in AD. Using gel based proteomics we previously identified seven plasma proteins that were significantly associated with hippocampal volume in a combined cohort of subjects with AD (N = 27) and MCI (N = 17). In the current report, we validated this finding in a large independent cohort of AD (N = 79), MCI (N = 88) and control (N = 95) subjects using alternative complementary methods—quantitative immunoassays for protein concentrations and estimation of pathology by whole brain volume. We confirmed that plasma concentrations of five proteins, together with age and sex, explained more than 35% of variance in whole brain volume in AD patients. These proteins are complement components C3 and C3a, complement factor-I, γ-fibrinogen and alpha-1-microglobulin. Our findings suggest that these plasma proteins are strong predictors of in vivo AD pathology. Moreover, these proteins are involved in complement activation and coagulation, providing further evidence for an intrinsic role of these pathways in AD pathogenesis.

Prostanoids are lipid compounds that mediate a variety of physiological and pathological functions in almost all body tissues and organs. Thromboxane (TX) A2 is a powerful inducer of platelet aggregation and vasoconstriction and it has ulcerogenic activity in the gastrointestinal tract. Overdose or chronic use of a high dose of acetaminophen (N-acetyl-paminophenol, APAP) is a major cause of acute liver failure in the Western world. We investigated whether TXA2 plays a role in host response to toxic effect of APAP. CBA/H Zg mice of both sexes were intoxicated with a single lethal or high sublethal dose of APAP, which was administered to animals by oral gavage. The toxicity of APAP was determined by observing the survival of mice during 48 h, by measuring concentration of alanine-aminotransferase (ALT) in plasma 20-22 h after APAP administration and by liver histology. The results have shown that anti-thromboxane (TX) B2 antibodies (anti-TXB2) and a selective inhibitor of thromboxane (TX) synthase, benzylimidazole (BZI), were significantly hepatoprotective, while a selective thromboxane receptor (TPR) antagonist, daltroban, was slightly protective in this model of acute liver injury. A stabile metabolite of TXA2, TXB2, and a stabile agonist of TPR, U-46619, had no influence on APAP-induced liver damage. Our findings suggest that TXA2 has a pathogenic role in acute liver toxicity induced with APAP, which was highly abrogated by administration of anti-TXB2. According to our results, this protection is mediated, at least in part, through decreased production of TXB2 by liver fragments ex vivo .

An approach has been proposed combining one dimensional inverse gated 13C NMR spectroscopy and a comprehensive two dimensional gas chromatography (GC×GC) to analyze diesel fuels prior and after oxidation under the standard conditions. Classes of hydrocarbons present before and after oxidation have been identified and quantified. A decrease in aromatic iso- and n-paraffinic hydrocarbons and an increase in the total saturated hydrocarbons have been observed after oxidation. In that respect NMR spectroscopy has potential to be used as standard method for determination of oxidation stability. Furthermore, GC×GC has been applied to identify compounds involved in the formation of sediments during oxidation. Obtained results have shown that hydrocarbon composition, especially the normal paraffin content play a role in the formation of sediments in these distillate fuels. This is important since sediments may influence the quality of diesel fuels.