Xuzhou Institute of Technology

About: Xuzhou Institute of Technology is a education organization based out in Xuzhou, China. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 1696 authors who have published 1521 publications receiving 13541 citations.

Study on Particulate Structure Characteristics of Diesel Engines Fueled with a Methanol/Biodiesel Blend.

Abstract: Methanol and biodiesel are both alternative fuels of diesel engines. In order to study the effects of methanol on the microstructure of particulates produced from the diesel engine fueled with a me...

Wave propagation for monostable 2-d lattice differential equations with delay

Abstract: In this paper, we are concerned with the wave propagation for a system of 2-D lattice differential equations with delay. Under the monostable assumption, the asymptotic behavior, the monotonicity and uniqueness of traveling wave are established when the wave speed is greater than or equal to the minimal wave speed c*(θ) > 0. In addition, the directional dependence of the minimal wave speed is analyzed numerically.

Quantitative Determination and Removal of Benzo[a]pyrene Residue in Meat Products by Fluorescence and Polymeric Micelle

Abstract: Benzo[a]pyrene (BaP) as a typical polycyclic aromatic hydrocarbon (PAH), is toxic and cancerogenic, and is widely present in processed foods especially in meat products that were smoked or salted. In this study, a robust and efficient method for quantitative determination and removal of BaP residue in meat product using fluorescence methods was introduced. A poly(ethylene glycol) (PEG) labeled at both ends with pyrene (Py-PEG-Py) was prepared and the polymer micelle was applied to remove BaP. The chemical structures of pyrene and BaP were similar so they tend to interact with each other. The steady-state fluorescence spectra showed that the ratios of excimer-to-monomer emission intensities (IE/IM) of the Py-PEG-Py sample remain constant when polymer concentration is below 0.25 g/L. Above this concentration, pyrene excimer is formed by both intramolecular and intermolecular interaction. The concentration indicates the critical micelle concentration (CMC) of Py-PEG-Py in aqueous environment. It was shown that a trace amount of BaP can be detected by fluorescence method. The fluorescence decays obtained at various polymer concentrations were also acquired by time-resolved fluorescence instrument. After the meat products were treated with Py-PEG-Py solution, BaP was completely encapsulated into the polymer micelles due to hydrophobic interaction between BaP and the pyrene pendants. In other words, BaP was fully dissolved into the micelles where the core of micelle was formed by pyrene stacking to create a hydrophobic domain and was completely separated from the meat products. This method is easy, swift, sensitive, and accurate. It can be applied to determine and remove any PAH residues in food.

K_net: Lysine Malonylation Sites Identification With Neural Network

Abstract: Lysine Malonylation (Kmal) is a newly discovered protein post-translational modifications (PTMs) type, which plays an important role in many biological processes. Therefore, identifying and understanding Kmal sites is very critical in the studies of biology and diseases. The typical methods are time-wasting and expensive. Nowadays, many researchers have proposed machine learning (ML) methods to deal with PTMs’s identification issue. Especially, some deep learning (DL) methods are also utilized in this field. In this work, we proposed K_net, which employed Convolutional Neural Network to identify the potential sites. Meanwhile, we proposed a new verification method Split to Equal Validation (SEV), which can well solve the impact of sample imbalance on prediction results. More Specifically, Acc, Sn, Sp, MCC and AUC values were adopted to evaluate the prediction performance of predictors. In total, CNN_Kmal achieved the better performance than other methods.