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Flavor volatiles are important components of alcoholic beverages. In this study, headspace solid-phase microextraction and gas chromatography-mass spectrometry (HS-SPME-GC-MS) were investigated for the determination of flavor-contributing volatiles for apple wine. HS-SPME parameters were defined, including fiber coatings, extraction time, and extraction temperature. Good linearity, recoveries, and repeatability of the SPME method using carboxen-polydimethylsiloxane (carboxen-PDMS) fiber were obtained with r 2 values, recoveries, and relative standard deviations ranging from 0.9112 to 0.9960, 80.23% to 110.21%, and 1.5% to 6.4% respectively using standard solution. No significant effects of ethanol concentration on headspace concentrations of analytes were observed when ethanol concentration changed from 0% to 12% (v/v), indicating that the HS-SPME-GC-MS method can be used for the determination of flavor volatiles in apple wine with an alcohol content below 12% (v/v) as well as in apple juice, and the method enables the monitoring of volatiles in mash during fermentation.

Aims:  To investigate the role of lipopolysaccharide (LPS) structure in the stability of outer membrane and the ability of biofilm formation in Cronobacter sakazakii. Methods and Results:  A C. sakazakii mutant strain LWW02 was constructed by inactivating the gene ESA_04107 encoding for heptosyltransferase I. LPS were purified from LWW02, and changes in their structure were confirmed by thin‐layer chromatography and electrospray ionization mass spectrometry. Comparing with the wild‐type strain BAA‐894, slower growth, higher membrane permeability, higher surface hydrophobicity, stronger ability of autoaggregation and biofilm formation were observed for the mutant strain LWW02. Conclusions:  The gene ESA_04107 encodes heptosyltransferase I in C. sakazakii ATCC BAA‐894. The cleavage of LPS in C. sakazakii could cause its outer membrane defects and increase its ability to form biofilms. Significance and Impact of the Study:  The study is important for understanding the pathogenic mechanism and efficient control of C. sakazakii.

As reuse materials, waste tires mixed with soils are valuable materials to be used for many purposes in geotechnical projects that may be subjected to dynamic loads. The aim of this study is to assess the efficacy of using waste tires in buried pipe protection. To achieve this purpose, a series of laboratory model tests were carried out to investigate the dynamic responses of pipe buried in pure soil and rubber soil mixtures with volume content of 10%, 20% and 30% rubber particles. Test results such as earth pressure and strain of buried pipe are discussed in this study. The results indicate that inclusion of 20%-30% rubber particles in the mixtures leads to a change in earth pressure increment distribution, and these mixtures leads to obvious reductions in earth pressure increments. For the mixtures with 20%-30% rubber particles, the pipe has lower strain under the dynamic loading. Compared with pure soil, the mixtures with 20%-30% rubber particles exhibit better performances in regards to responses of pipe-soil system. Hence, the research undertaken in this paper provides a viable approach to protect the buried pipe subjected to dynamic loading.

A quantitative evaluation method based on a three-dimensional (3D) laser-scanning technique is presented for the objective assessment of fabric fuzziness. Fabric fuzziness, referring to severity of protruding fibers on a fabric surface, has a direct effect on fabric serviceability and needs to be evaluated routinely for quality assurance. In this research, the characterization of fabric fuzziness was realized by using a customized laser scanning system that can produce the 3D surface image of a fabric in a high resolution, and by analyzing the parameters of roughness amplitude distributions extracted from the 3D image. Multi-colored fabrics with different levels of fuzziness were first visually evaluated to obtain the subjective fuzziness grades in reference to a set of expert-rated cotton samples. Then, the fabrics were scanned by the laser system and the surface roughness parameters were calculated from the 3D images for the regression analysis with the subjective fuzziness grades. The result of multivariable regression analysis indicated that the fuzziness grade has a strong correlation with the roughness parameters, and can be estimated automatically after a fabric is scanned. The system demonstrated its fuzziness ratings are invariant to fabrics’ colors, prints, and structures.