Scanning electron microscopy coupled with energydispersive X-ray spectrometry for quick detection of sulfuroxidizing bacteria in environmental water samples

Detection of sulfur-oxidizing bacteria has largely been dependent on targeted gene sequencing technology or traditional cell cultivation, which usually takes from days to months to carry out. This clearly does not meet the requirements of analysis for time-sensitive samples and/or complicated environmental samples. Since energy-dispersive X-ray spectrometry(EDS) can be used to simultaneously detect multiple elements in a sample, including sulfur, with minimal sample treatment, this technology was applied to detect sulfur-oxidizing bacteria using their high sulfur content within the cell. This article describes the application of scanning electron microscopy imaging coupled with EDS mapping for quick detection of sulfur oxidizers in contaminated environmental water samples, with minimal sample handling. Scanning electron microscopy imaging revealed the existence of dense granules within the bacterial cells, while EDS identified large amounts of sulfur within them. EDS mapping localized the sulfur to these granules. Subsequent 16S rRNA gene sequencing showed that the bacteria detected in our samples belonged to the genus Chromatium, which are sulfur oxidizers. Thus, EDS mapping made it possible to identify sulfur oxidizers in environmental samples based on localized sulfur within their cells, within a short time(within 24 h of sampling). This technique has wide ranging applications for detection of sulfur bacteria in environmental water samples.

Speech endpoint detection in low-SNRs environment based on perception spectrogram structure boundary parameter

The Perception Spectrogram Structure Boundary（PSSB）parameter is proposed for speech endpoint detection as a preprocess of speech or speaker recognition.At first a hearing perception speech enhancement is carried out.Then the two-dimensional enhancement is performed upon the sound spectrogram according to the difference between the determinacy distribution characteristic of speech and the random distribution characteristic of noise.Finally a decision for endpoint was made by the PSSB parameter.Experimental results show that,in a low SNR environment from-10 dB to 10 dB,the algorithm proposed in this paper may achieve higher accuracy than the extant endpoint detection algorithms.The detection accuracy of 75.2%can be reached even in the extremely low SNR at-10 dB.Therefore it is suitable for speech endpoint detection in low-SNRs environment.

Optical characteristics and environmental pollutants detection of porous silicon microcavities

Porous silicon microcavities (PSM) optical crystals consisting of a Fabry-Perot microcavity embedded between two distributed Bragg reflectors have been fabricated by electrochemical etching. Scanning electron microscopy (SEM) clearly depicted their physical sandwich construction. The optical feature of the PSM structure was tuned by varying the anodization parameters. Through proper thermal oxidation and surface chemical modifications, the resulting structures were employed as optical sensors for the detection of environmental pollutants including volatile organic vapors (i.e. acetonitrile, toluene, cyclohexane, chloroform, acetone and ethanol) and interior decoration gases (i.e. toluene, ammonia and formaldehyde). Fourier transform infrared spectroscopy (FTIR) spectra confirmed the effective thermal annealing and surface modification chemistry, and the sensing process was accompanied by recording the modified structures' optical responses when exposed to target analytes. The PSM optical sensors showed good stability, sensitivity and selectivity, implying promising applications in gas sensing and en- vironmental monitoring.

Rhynchophorus ferrugineus attack affects a group of compounds rather than rearranging Phoenix canariensis metabolic pathways

The red palm weevil（RPW; Rhynchophorus ferrugineus） is spreading worldwide and severely harming many palm species. However, most studies on RPW focused on insect biology, and little information is available about the plant response to the attack. In the present experiment, we used metabolomics to study the alteration of the leaf metabolome of Phoenix canariensis at initial（1^（st） stage） or advanced（2^（nd） stage）attack by RPW compared with healthy（unattacked） plants.The leaf metabolome significantly varied among treatments. At the 1^（st） stage of attack, plants showed a reprogramming of carbohydrate and organic acid metabolism; in contrast, peptides and lipid metabolic pathways underwent more changes during the 2^（nd） than 1^（st） stage of attack. Enrichment metabolomics analysis indicated that RPW attack mostly affected a particular group of compounds rather than rearranging plant metabolic pathways. Some compounds selectively affected during the 1^（st） rather than 2^（nd） stage（e.g. phenylalanine; tryptophan; cellobiose;xylose; quinate; xylonite; idonate; and iso-threonate; cellobiotol and arbutine） are upstream events in the phenylpropanoid,terpenoid and alkaloid biosynthesis. These compounds could be designated as potential markers of initial RPW attack. However,further investigation is needed to determine efficient early screening methods of RPW attack based on the concentrations of these molecules.