A Multi-year Beneficial Effect of Seed Priming with Gibberellic Acid-3 (GA) on Plant Growth and Production in a Perennial Grass, Leymus chinensis.

Seed priming is a widely used technique in crops to obtain uniform germination and high-quality seedlings. In this study, we found a long-term effect of seed priming with gibberellic acid-3 (GA) on plant growth and production in Leymus chinensis. Seeds were germinated on agar plates containing 0-200 μM GA, and the germinated seedlings were transplanted to clay planting pots and grown for about one year.

Enrichment of serum biomarkers by magnetic metal-organic framework composites.

Highly efficient extraction of peptides from serum is critical for finding serum biomarkers using mass spectrometry, which still remains a great challenge. Currently, a bottom-up proteomics approach has been applied to discover serum biomarkers. However, the approach was labor intensive, time and cost consuming, and cannot meet the requirements for clinical application.

Rapid Isolation of Phenol Degrading Bacteria by Fourier Transform Infrared (FTIR) Spectroscopy.

Phenol is an important chemical engineering material and ubiquitous in industry wastewater, its existence has become a thorny issue in many developed and developing country. More and more stringent standards for effluent all over the world with human realizing the toxicity of phenol have been announced. Many advanced biological methods are applied to industrial wastewater treatment with low cost, high efficiency and no secondary pollution, but the screening of function microorganisms is certain cumbersome process.

Biocompatible chiral monolithic stationary phase synthesized via atom transfer radical polymerization for high performance liquid chromatographic analysis.

Novel biocompatible chiral monolithic stationary phase was prepared by reverse and direct atom transfer radical polymerization (ATRP) methods. By taking advantages of the controlled/living property of ATRP method, the chiral monolith was prepared by reverse ATRP (RATRP) firstly. An attractive feature of RATRP is the prepared polymer containing a terminal radically transferable atom that can initiate another post-polymerization reaction by direct ATRP.

Emerging enantiomeric resolution materials with homochiral nano-fabrications.

The major scientific challenge of enantiomeric separation is to develop simple, rapid, and sensitive routine analytical methods. Generally, enantio-resolution is still based on "three-point interaction" theory, which indicates that homochiral sites are needed for enantio-selective interaction. However, in recent years, advanced materials with precise homochiral fabrication at the nanoscale have been synthesized, and have shown great potential in development of high-throughput enantio-resolution methods.

Synthesis of magnetic framework composites for the discrimination of Escherichia coli at the strain level.

Rapid and efficient characterization and identification of pathogens at the strain level is of key importance for epidemiologic investigations, which still remains a challenge. In this work, solvothermically Fe3O4-COOH@MIL-101 composites were fabricated by in situ crystallization approach. The composites combine the excellent properties of both chromium (III) terephthalate (MIL-101) and carboxylic-functionalized magnetite (Fe3O4-COOH) particles and possess the efficient peptides/proteins enrichment properties and magnetic responsiveness.

Restricted access chiral stationary phase synthesized via reversible addition-fragmentation chain-transfer polymerization for direct analysis of biological samples by high performance liquid chromatography.

Novel hydrophilic microparticles containing β-cyclodextrin (β-CD) were prepared via one-pot synthesis using reversible addition-fragmentation chain-transfer (RAFT) precipitation polymerization, a "controlled/living" radical polymerization technique. The polymerization was initiated by hydrophilic macromolecular chain-transfer agent [poly(2-hydroxyethyl methacrylate), PHEMA]. The hydrophilic PHEMA on the surface of microparticles can well improve their surface hydrophilicity and lead to their biological compatibility.

[Application of SVR in quantitative analysis of wines].

Fourier transform infrared spectroscopy has been widely used in some related fields, thus induces the rapid development of quantitative analysis method based on Lambert-Beer's Law and chemometrics in recent years. The selection of appropriate pre-processing method and calibration model is extremely crucial to the quantitative analysis. The present paper selected 30 wine samples and used infrared spectroscopy combined with vector regression algorithm SVR quantitative analysis model with standard normal variate, baseline correction and outliers elimination to analyze four representative components of wine.

[SVM-based qualitative analysis of Muscat Hamburg wine produced in Tianjin region].

The purpose was to achieve the identification of Muscat Hamburg wines produced in Tianjin region through scanning and analyzing dry white wine samples of different grape varieties and regions by infrared spectroscopy technology. A support vector machine (SVM) based method was introduced to analyze infrared spectra of dry white wines. The pretreatment processes of the IR spectra were also elaborated, including baseline adjustment, noise Elimination, standard normalization and eliminating the main component of abnormal sample points.

[Analysis of liquor flavor spectra and pattern recognition computation].

Chinese liquor is a complex mixture and contains a large amount of microconstituents, which affects the quality and flavor of liquor. In order to discriminate liquor flavors rapidly, the spectra of liquors were obtained by FTIR and employed as the input patterns of pattern classification algorithms, then liquor flavor discrimination models were built. This paper introduces liquor flavor pattern recognition algorithms comprehensively and systematically for the first time, and the algorithms contain statistical classifications (linear discriminant function, quadratic discriminant function, regularized discriminant analysis, and K nearest neighbor), prototype learning algorithm (learning vector quantization), support vector machine and adaboost algorithm.