[Determination of 15 3-chloro-1,2-propanediol fatty acid esters in vegetable oils and fritters by ultra performance convergence chromatography-tandem mass spectrometry].

The presence of 3-chloro-1,2-propanediol fatty acid esters (3-MCPDE) in food and processed materials has recently become a topic of concern because of the toxicity of their metabolites. 3-MCPDE structurally similar to glyceride, which makes it difficult to separate or extract them from oils and fritters. A method based on ultra performance convergence chromatography-tandem mass spectrometry (UPC-MS/MS) was established for the determination of 15 3-MCPDE in vegetable oils and fritters.

Preparation of Graphene-Co/Ni/Fe₃O₄ Nanocomposites and Their Electrocatalytic Activity for Reduction of p-Nitrophenol.

Graphene-based nanocomposites of graphene-Co, graphene-Ni, and graphene-Fe₃O₄ were synthesized via improved chemical-carbothermal reduction using graphite and nitrates as starting materials. The Co, Ni, and Fe₃O₄ nanoparticles are uniformly loaded on the surfaces of graphene nanosheets without serious folds and conglomeration. The average dimensions of the Co, Ni, and Fe₃O₄ nanoparticles attached to graphene are approximately 50, 60, and 5 nm, respectively.

Subglottal resonances of American English speaking children.

This paper presents an investigation of children's subglottal resonances (SGRs), the natural frequencies of the tracheo-bronchial acoustic system. A total of 43 children (31 male, 12 female) aged between 6 and 18 yr were recorded. Both microphone signals of various consonant-vowel-consonant words and subglottal accelerometer signals of the sustained vowel /ɑ/ were recorded for each of the children, along with age and standing height.

Robust speaker identification via fusion of subglottal resonances and cepstral features.

This letter investigates the use of subglottal resonances (SGRs) for noise-robust speaker identification (SID). It is motivated by the speaker specificity and stationarity of subglottal acoustics, and the development of noise-robust SGR estimation algorithms which are reliable at low signal-to-noise ratios for large datasets. A two-stage framework is proposed which combines the SGRs with different cepstral features.