Comparative Chemical Characterization of Potato Powders Using 1H NMR Spectroscopy and Chemometrics.

This study presents the metabolic profiling of potato powders obtained through various processing procedures and commercially available potato powders. The metabolic fingerprinting was conducted using 1H NMR-based metabolomics coupled with machine learning projections. The results indicate hot air-dried potatoes have higher fumarate, glucose, malate, asparagine, choline, gamma aminobutyric acid (GABA), alanine, lactate, threonine, and fatty acids. In comparison, steam-cooked potatoes have higher levels of phenylalanine, sucrose, proline, citrate, glutamate, and valine. Moreover, the contents of metabolites in processed potatoes in this study were higher than those found in commercial potato powders, regardless of the drying or cooking methods used. The results indicate that a new processing technique may be developed to improve the nutritional value of potatoes.

[Observation of and research on intravital microcirculation use of orthogonal polarization multi-spectral technique].

A small, simple intravital microcirculation multi-spectral imaging system was constructed. Orthogonal polarization spectral (OPS) imaging and liquid crystal tunable filter (LCTF) were used for intravital microcirculation multi-spectral imaging. LCTF has excellent imaging quality and low-power loss, without moving parts and image shift. It can provide continuously, rapid and random-access selection of any wavelength in the visible to near-infrared range. An ear of nude mouse was adopted as experiment specimen. The multi-spectral images of ear microvessel of the nude mouse were acquired by this imaging system in two ways (detection polarization angle 90 degrees and 0 degrees). Compared with detection polarization angle 0 degrees way the images acquired by orthogonal polarization spectral imaging way(detection polarization angle 90 degrees) had better contrast and more details. It is concluded that the experiment has proved that the orthogonal polarization multi-spectral technique can enhance the effect of observation of intravital microcirculation.

[New highly phosphorescent heteroleptic tris-cyclometalated iridium (III) complexes: synthesis and photophysical characterization].

New heteroleptic tris-cyclometalated iridium(III) complexes (ppy)2 Ir(LX) (ppy==2-phenylpyridine, LX==Sal (salicylic acid), Msal (4-methylsalicylic acid), FSal(4-trifluoro methyl salicylic acid)) was synthesized and characterized. The molecular structure, photophysical properties and thermal stability were tested and analyzed. The results show that the absorption peaks were located around 270, 370, 450 and 484 nm respectively at room temperature. The two former peaks at 270 and 370 nm should belong to 1pi--pi* transition at ppy and transition from salicylic acid ligands to 2-phenylpyridine; The peaks around 450 and 484 nm can be assigned to the charge transfer transition from Ir to ligand (1MLCT and 3MLCT) and 3pi--pi* transition respectively. The PL emission peaks were located at 520, 522, and 510 nm, respectively. The emission of (ppy), Ir(Sal) and (ppy), Ir (MSal) was mainly ascribed to the radiation transition of triple state 3MLCT, while the emission of (ppy)2 Ir(FSal) was mainly from the radiation transition between Sal and ppy, partly from the radiation transition of single state 1MLCT and triple state 3MLCT. The quantum efficiencies of these complexes were 0.37, 0.33 and 0.29 respectively. The thermal decomposition temperature was from 306 to 328 degrees C. (ppy)2 Ir(LX), being a series of efficient phosphorescent materials with good thermal stability, can be used in the organic electroluminescent devices.

[Development of a new FTIR car-borne oil content analyzer].

Turlun structure was introduced into the Fourier transform interference system in the present paper in order to decrease the size and cost of the whole system and to increase the ability of vibration resistance to meet the requirement of car-borne outdoor monitoring application. The speed deviation of the voice coil motor (VCM) driving system, which is based on feedback of interference wavelength of reference laser and DSP control, is within 5%. The standard oil sample was used to test the performance of the spectrometer. The result shows that the highest resolution of the FTIR oil detector is 2 cm(-1), and the SNR reached 2000:1. Compared with old grating spectrometers, thiskind of instrument is faster, and the quality of spectrum was increased significantly. The portable feature of this instrument will be more convenient for the water pollution detection in field

Low-cost virtual instrumentation system of an energy-dispersive X-ray spectrometer for a scanning electron microscope.

The paper describes an energy-dispersive X-ray spectrometer for a scanning electron microscope (SEM-EDXS). It was constructed using the new architecture of a virtual instrument (VI), which is low-cost, space-saving, fast and flexible way to develop the instrument. Computer-aided teaching (CAT) was used to develop the instrument and operation rather than a traditional instrument technique. The VI was designed using the object-oriented program language C++ and compact programmable logical devices (CPLD). These include spectra collection and processing, quantitative analysis and X-ray-intensity distribution analysis. The procedure is described in detail. The VI system gives an e inverted exclamation markective and user-friendly human interface for the whole analytical task. Some examples are described.

Auto-analysis system for graphite morphology of grey cast iron.

The current method to classify graphite morphology types of grey cast iron is based on traditional subjective observation, and it cannot be used for quantitative analysis. Since microstructures have a great effect on the mechanical properties of grey cast iron and different types have totally different characters, six types of grey cast iron are discussed and an image-processing software subsystem that performs the classification and quantitative analysis automatically based on a kind of composed feature vector and artificial neural network (ANN) is described. There are three kinds of texture features: fractal dimension, roughness and two-dimension autoregression, which are used as an extracted feature input vector of ANN classifier. Compared with using only one, the checkout correct precision increased greatly. On the other hand, to achieve the quantitative analysis and show the different types clearly, the region segmentation idea was applied to the system. The percentages of the regions with different type are reported correctly. Furthermore, this paper tentatively introduces a new empirical method to decide the number of ANN hidden nodes, which are usually considered as a difficulty in ANN structure decision. It was found that the optimum hidden node number of the experimental data was the same as that obtained using the new method.