FEM Analysis and Experimental Study on the Bending Strength of Ceramic Tiles with the Top- and Back-Sided Polyurea Coating

Mechanical properties enhancement of ceramic tiles by a simple coating technique using polyurea was investigated. Solventless polyurea coatings were employed. The effect of coating sides of the ceramic substrate and film thickness on the mechanical properties were examined in three-point bend tests. The back-coated ceramic tile demonstrated a significant improvement in bending strength (by 25–50%) as compared to the top-coated one. The stress distribution in the substrate was analyzed by the finite element method, and the mechanism of improving mechanical properties was discussed.Изучена возможность улучшения механических свойств керамической плитки путем нанесения покрытия из полимочевины. Использовано покрытие из полимочевины без растворителя. Влияние стороны нанесения покрытия на керамическую основу и толщины пленки на механические свойства исследовано при испытаниях на трехточечный изгиб. Прочность при изгибе керамической плитки с покрытием на нижней стороне существенно лучше (на 25...30%) по сравнению с таковой покрытия, нанесенного на ее лицевyю поверхность. Выполнен анализ распределения напряжений в основе с помощью метода конечных элементов и проведено обсуждение механизма улучшения механических свойств

A weighted q-gram method for glycan structure classification

<p>Abstract</p> <p>Background</p> <p>Glycobiology pertains to the study of carbohydrate sugar chains, or glycans, in a particular cell or organism. Many computational approaches have been proposed for analyzing these complex glycan structures, which are chains of monosaccharides. The monosaccharides are linked to one another by glycosidic bonds, which can take on a variety of comformations, thus forming branches and resulting in complex tree structures. The <it>q</it>-gram method is one of these recent methods used to understand glycan function based on the classification of their tree structures. This <it>q</it>-gram method assumes that for a certain <it>q</it>, different <it>q</it>-grams share no similarity among themselves. That is, that if two structures have completely different components, then they are completely different. However, from a biological standpoint, this is not the case. In this paper, we propose a weighted <it>q</it>-gram method to measure the similarity among glycans by incorporating the similarity of the geometric structures, monosaccharides and glycosidic bonds among <it>q</it>-grams. In contrast to the traditional <it>q</it>-gram method, our weighted <it>q</it>-gram method admits similarity among <it>q</it>-grams for a certain <it>q</it>. Thus our new kernels for glycan structure were developed and then applied in SVMs to classify glycans.</p> <p>Results</p> <p>Two glycan datasets were used to compare the weighted <it>q</it>-gram method and the original <it>q</it>-gram method. The results show that the incorporation of <it>q</it>-gram similarity improves the classification performance for all of the important glycan classes tested.</p> <p>Conclusion</p> <p>The results in this paper indicate that similarity among <it>q</it>-grams obtained from geometric structure, monosaccharides and glycosidic linkage contributes to the glycan function classification. This is a big step towards the understanding of glycan function based on their complex structures.</p

Genes in S and T Subgenomes Are Responsible for Hybrid Lethality in Interspecific Hybrids between Nicotiana tabacum and Nicotiana occidentalis

Many species of Nicotiana section Suaveolentes produce inviable F(1) hybrids after crossing with Nicotiana tabacum (genome constitution SSTT), a phenomenon that is often called hybrid lethality. Through crosses with monosomic lines of N. tabacum lacking a Q chromosome, we previously determined that hybrid lethality is caused by interaction between gene(s) on the Q chromosome belonging to the S subgenome of N. tabacum and gene(s) in Suaveolentes species. Here, we examined if hybrid seedlings from the cross N. occidentalis (section Suaveolentes)×N. tabacum are inviable despite a lack of the Q chromosome.Hybrid lethality in the cross of N. occidentalis×N. tabacum was characterized by shoots with fading color. This symptom differed from what has been previously observed in lethal crosses between many species in section Suaveolentes and N. tabacum. In crosses of monosomic N. tabacum plants lacking the Q chromosome with N. occidentalis, hybrid lethality was observed in hybrid seedlings either lacking or possessing the Q chromosome. N. occidentalis was then crossed with two progenitors of N. tabacum, N. sylvestris (SS) and N. tomentosiformis (TT), to reveal which subgenome of N. tabacum contains gene(s) responsible for hybrid lethality. Hybrid seedlings from the crosses N. occidentalis×N. tomentosiformis and N. occidentalis×N. sylvestris were inviable.Although the specific symptoms of hybrid lethality in the cross N. occidentalis×N. tabacum were similar to those appearing in hybrids from the cross N. occidentalis×N. tomentosiformis, genes in both the S and T subgenomes of N. tabacum appear responsible for hybrid lethality in crosses with N. occidentalis

Kihi-to, a herbal traditional medicine, improves Abeta(25–35)-induced memory impairment and losses of neurites and synapses

<p>Abstract</p> <p>Background</p> <p>We previously hypothesized that achievement of recovery of brain function after the injury requires the reconstruction of neuronal networks, including neurite regeneration and synapse reformation. Kihi-to is composed of twelve crude drugs, some of which have already been shown to possess neurite extension properties in our previous studies. The effect of Kihi-to on memory deficit has not been examined. Thus, the goal of the present study is to determine the <it>in vivo </it>and <it>in vitro </it>effects of Kihi-to on memory, neurite growth and synapse reconstruction.</p> <p>Methods</p> <p>Effects of Kihi-to, a traditional Japanese-Chinese traditional medicine, on memory deficits and losses of neurites and synapses were examined using Alzheimer's disease model mice. Improvements of Aβ(25–35)-induced neuritic atrophy by Kihi-to and the mechanism were investigated in cultured cortical neurons.</p> <p>Results</p> <p>Administration of Kihi-to for consecutive 3 days resulted in marked improvements of Aβ(25–35)-induced impairments in memory acquisition, memory retention, and object recognition memory in mice. Immunohistochemical comparisons suggested that Kihi-to attenuated neuritic, synaptic and myelin losses in the cerebral cortex, hippocampus and striatum. Kihi-to also attenuated the calpain increase in the cerebral cortex and hippocampus. When Kihi-to was added to cells 4 days after Aβ(25–35) treatment, axonal and dendritic outgrowths in cultured cortical neurons were restored as demonstrated by extended lengths of phosphorylated neurofilament-H (P-NF-H) and microtubule-associated protein (MAP)2-positive neurites. Aβ(25–35)-induced cell death in cortical culture was also markedly inhibited by Kihi-to. Since NF-H, MAP2 and myelin basic protein (MBP) are substrates of calpain, and calpain is known to be involved in Aβ-induced axonal atrophy, expression levels of calpain and calpastatin were measured. Treatment with Kihi-to inhibited the Aβ(25–35)-evoked increase in the calpain level and decrease in the calpastatin level. In addition, Kihi-to inhibited Aβ(25–35)-induced calcium entry.</p> <p>Conclusion</p> <p>In conclusion Kihi-to clearly improved the memory impairment and losses of neurites and synapses.</p

A Comprehensive Benchmark of Kernel Methods to Extract Protein–Protein Interactions from Literature

The most important way of conveying new findings in biomedical research is scientific publication. Extraction of protein–protein interactions (PPIs) reported in scientific publications is one of the core topics of text mining in the life sciences. Recently, a new class of such methods has been proposed - convolution kernels that identify PPIs using deep parses of sentences. However, comparing published results of different PPI extraction methods is impossible due to the use of different evaluation corpora, different evaluation metrics, different tuning procedures, etc. In this paper, we study whether the reported performance metrics are robust across different corpora and learning settings and whether the use of deep parsing actually leads to an increase in extraction quality. Our ultimate goal is to identify the one method that performs best in real-life scenarios, where information extraction is performed on unseen text and not on specifically prepared evaluation data. We performed a comprehensive benchmarking of nine different methods for PPI extraction that use convolution kernels on rich linguistic information. Methods were evaluated on five different public corpora using cross-validation, cross-learning, and cross-corpus evaluation. Our study confirms that kernels using dependency trees generally outperform kernels based on syntax trees. However, our study also shows that only the best kernel methods can compete with a simple rule-based approach when the evaluation prevents information leakage between training and test corpora. Our results further reveal that the F-score of many approaches drops significantly if no corpus-specific parameter optimization is applied and that methods reaching a good AUC score often perform much worse in terms of F-score. We conclude that for most kernels no sensible estimation of PPI extraction performance on new text is possible, given the current heterogeneity in evaluation data. Nevertheless, our study shows that three kernels are clearly superior to the other methods