A Research on Maximum Symbolic Entropy from Intrinsic Mode Function and Its Application in Fault Diagnosis

Empirical mode decomposition (EMD) is a self-adaptive analysis method for nonlinear and nonstationary signals. It has been widely applied to machinery fault diagnosis and structural damage detection. A novel feature, maximum symbolic entropy of intrinsic mode function based on EMD, is proposed to enhance the ability of recognition of EMD in this paper. First, a signal is decomposed into a collection of intrinsic mode functions (IMFs) based on the local characteristic time scale of the signal, and then IMFs are transformed into a serious of symbolic sequence with different parameters. Second, it can be found that the entropies of symbolic IMFs are quite different. However, there is always a maximum value for a certain symbolic IMF. Third, take the maximum symbolic entropy as features to describe IMFs from a signal. Finally, the proposed features are applied to evaluate the effect of maximum symbolic entropy in fault diagnosis of rolling bearing, and then the maximum symbolic entropy is compared with other standard time analysis features in a contrast experiment. Although maximum symbolic entropy is only a time domain feature, it can reveal the signal characteristic information accurately. It can also be used in other fields related to EMD method

Deciphering Charging Status, Absolute Quantum Efficiency, and Absorption Cross Section of MultiCarrier States in Single Colloidal Quantum Dot

Upon photo- or electrical-excitation, colloidal quantum dots (QDs) are often found in multi-carrier states due to multi-photon absorption and photo-charging of the QDs. While many of these multi-carrier states are observed in single-dot spectroscopy, their properties are not well studied due to random charging/discharging, emission intensity intermittency, and uncontrolled surface defects of single QD. Here we report in-situ deciphering the charging status, and precisely assessing the absorption cross section, and determining the absolute emission quantum yield of mono-exciton and biexciton states for neutral, positively-charged, and negatively-charged single core/shell CdSe/CdS QD. We uncover very different photon statistics of the three charge states in single QD and unambiguously identify their charge sign together with the information of their photoluminescence decay dynamics. We then show their distinct photoluminescence saturation behaviors and evaluated the absolute values of absorption cross sections and quantum efficiencies of monoexcitons and biexcitons. We demonstrate that addition of an extra hole or electron in a QD changes not only its emission properties but also varies its absorption cross section

Guanxintai Exerts Protective Effects on Ischemic Cardiomyocytes by Mitigating Oxidative Stress

Oxidative stress participates in numerous myocardial pathophysiological processes and is considered a therapeutic target for myocardial ischemia and heart failure. Guanxintai (GXT), a traditional Chinese medicine, is commonly used to treat cardiovascular disease on account of its numerous beneficial physiological activities, such as dilating coronary arteries, inhibiting platelet aggregation, and reducing the serum lipid content. However, the antioxidative properties of GXT and potential underlying mechanisms remain to be established. In the present study, we investigated the protective effects of GXT on ischemic cardiomyocytes and the associated antioxidative mechanisms, both in vivo and in vitro. Notably, GXT treatment reduced the degree of cardiomyocyte injury, myocardial apoptosis, and fibrosis and partially improved cardiac function after myocardial infarction. Furthermore, GXT suppressed the level of ROS as well as expression of NADPH oxidase (NOX) and phospho-p38 mitogen-activated protein kinase (MAPK) proteins. Our results collectively suggest that the protective effects of GXT on ischemic cardiomyocytes are exerted through its antioxidative activity of NOX inhibition

The Technology and Application of Improving Bearing Capacity of Deep Peat Soil Subgrade

Peat soil is widely distributed in more than 500 countries around the world, covering an area of over 4 million square kilometers, among which the distribution area in China is about 40000 square kilometers, and most of Peat soil is distributed in swamps and forests. Peat soil is with high content of organic matter, poor engineering properties and low bearing capacity, which is very unfavorable to the safety and functionality of infrastructure construction. The Belt and Road, and the other two parts of the peat soil are studied in this paper. The key technologies of peat soil foundation are studied through literature review and comparative study. This will provide theoretical and technical support for repairing bridges, roads and houses in the distribution area of peat soil, and provide the theoretical basis and technical foundation for the construction of the “peat” Road area. Chinese Library Classification: TU0

Systematic identification of conserved motif modules in the human genome

Background: The identification of motif modules, groups of multiple motifs frequently occurring in DNA sequences, is one of the most important tasks necessary for annotating the human genome. Current approaches to identifying motif modules are often restricted to searches within promoter regions or rely on multiple genome alignments. However, the promoter regions only account for a limited number of locations where transcription factor binding sites can occur, and multiple genome alignments often cannot align binding sites with their true counterparts because of the short and degenerative nature of these transcription factor binding sites. Results: To identify motif modules systematically, we developed a computational method for the entire non-coding regions around human genes that does not rely upon the use of multiple genome alignments. First, we selected orthologous DNA blocks approximately 1-kilobase in length based on discontiguous sequence similarity. Next, we scanned the conserved segments in these blocks using known motifs in the TRANSFAC database. Finally, a frequent pattern mining technique was applied to identify motif modules within these blocks. In total, with a false discovery rate cutoff of 0.05, we predicted 3,161,839 motif modules, 90.8% of which are supported by various forms of functional evidence. Compared with experimental data from 14 ChIP-seq experiments, on average, our methods predicted 69.6% of the ChIP-seq peaks with TFBSs of multiple TFs. Our findings also show that many motif modules have distance preference and order preference among the motifs, which further supports the functionality of these predictions. Conclusions: Our work provides a large-scale prediction of motif modules in mammals, which will facilitate the understanding of gene regulation in a systematic way