Mesobacterium hydrothermale sp. nov., isolated from shallow-sea hydrothermal systems off Kueishantao Island.

A Gram-negative, rod-shaped, non-motile, aerobic bacterium, designated as strain TK19101T, was isolated from the intermediate seawater of yellow vent in the shallow-sea hydrothermal system located near Kueishantao Island. The strain was found to grow at 10-40 °C (optimum, 35 °C), at pH 6.0-8.0 (optimum, 7.0), and in 0-5% (w/v) NaCl (optimum, 1%). Strain TK19101T was catalase-positive and oxidase-positive. The predominant fatty acids (> 10%) in strain TK19101T cells were C16:0, summed feature 8 (C18:1 ω6c and/or C18:1 ω7c), and C18:0. The predominant isoprenoid quinone of strain TK19101T was ubiquinone-10. The polar lipids of strain TK19101T comprised phosphatidylcholine, phosphatidylethanolamine, phosphatidylglycerol, phospholipid, and unknown polar lipid. Phylogenetic analysis based on 16S rRNA gene sequences showed that strain TK19101T belonged to the genus Mesobacterium. Strain TK19101T exhibited highest 16S rRNA gene sequence similarity value to Mesobacterium pallidum MCCC M24557T (97.48%). The estimated average nucleotide identity and digital DNA-DNA hybridization values between strain TK19101T and the closest related species Mesobacterium pallidum MCCC M24557T were 74.88% and 20.30%, respectively. The DNA G + C content was 63.49 mol%. On the basis of the analysis of 16S rRNA gene sequences, genotypic and phylogenetic data, strain TK19101T has a unique phylogenetic status and represents a novel species of genus Mesobacterium, for which the name Mesobacterium hydrothermale sp. nov. is proposed. The type strain is TK19101T (= MCCC 1K08936T = KCTC 8354T).

A 3,3'-Difluoro-2,2'-Bithiophene Based Donor Polymer Realizing High Efficiency (>17%) Single Junction Binary Organic Solar Cells.

In this study, two novel donor-acceptor (D-A) copolymers are designed and synthesized, DTBT-2T and DTBT-2T2F with 2,2'-bithiophene or 3,3'-difluoro-2,2'-bithiophene as the donor unit and dithienobenzothiadiazole as the acceptor unit, and used them as donor materials in non-fullerene organic solar cells (OSCs). Due to enhanced planarity of polymer chains resulted by the intramolecular F···S noncovalent interactions, the incorporation of 3,3'-difluoro-2,2'-bithiophene unit instead of 2,2'-bithiophene into the polymers can enhance their molecular packing, crystallinity and hole mobility. The DTBT-2T:L8-BO based binary OSCs deliver a power conversion efficiency (PCE) of only 9.71% with a Voc of 0.78 V, a Jsc of 20.69 mA cm-2 , and an FF of 59.67%. Moreover, the introduction of fluoro atoms can lower the highest occupied molecular orbital levels. As a result, DTBT-2T2F:L8-BO based single-junction binary OSCs exhibited less recombination loss, more balanced charge mobility, and more favorable morphology, resulting in an impressive PCE of 17.03% with a higher Voc of 0.89 V, a Jsc of 25.40 mA cm-2, and an FF of 75.74%. These results indicate that 3,3'-difluoro-2,2'-bithiophene unit can be used as an effective building block to synthesize high performance polymer donor materials. This work greatly expands the selection range of donor units for constructing high-performance polymers.

Genetic-Algorithm-Based Inverse Optimization Identification Method for Hot-Temperature Constitutive Model Parameters of Ti6Al4V Alloy.

A precise constitutive model is the foundation and key to finite element simulation in material volume forming and the optimization of the hot working process. Hence, to build a precise constitutive model, a method based on a genetic algorithm (GA) for the inverse optimization identification of parameters is presented in this paper. The idea of this method is to continuously adjust the model parameters through GA until the objective function reaches the minimum value. In this study, hot compression experiments were performed on the Gleeble-1500D thermal simulator at temperatures ranging from 800 °C to 1000 °C and strain rates of 0.01 s-1 to 1 s-1. The Arrhenius-type (A-T) model considering strain compensation and the Johnson-Cook (JC) model considering the coupling effects of strain, temperature and strain rate were constructed, respectively, by using the regression method and the parameter inverse optimization identification method. For the purposes of comparing and verifying the reliability of the predictions of the two established constitutive models, the correlation coefficient (R), average absolute relative error (AARE), and relative error (RE) were adopted. The results show that both the optimized A-T model and the optimized JC model have high prediction accuracy. Compared to the optimized JC model, the optimized A-T model demonstrated a higher correlation coefficient, by 0.003, and a lower average absolute relative error, by 1.43%. Furthermore, the relative error distribution of the optimized A-T model was found to be more concentrated than that of the optimized JC model. These results suggest that the A-T model is more appropriate than the JC model for characterizing the high-temperature deformation behavior of Ti6Al4V alloy.

An Inverse Optimization Method for the Parameter Determination of the High-Temperature Damage Model and High-Temperature Damage Graph of Ti6Al4V Alloy.

Ti6AL4V alloy is widely used in the biomedical and energy vehicle industries, among others. Ti6Al4V alloy cannot be fabricated at ambient temperatures; hence, it requires hot forming. However, this method is susceptible to crack defects. The crack defect problem of Ti6AL4V alloy in the hot-forming process cannot be ignored, so we must develop a precise hot-forming damage prediction model. In this study, three high-temperature damage models of Ti6Al4V alloy were developed, considering the temperature and strain rate. These models were derived from the normalized Cockcroft and Latham (NCL), Oyane, and Rice and Tracey (RT) damage models. The damage parameters of the models were identified using a genetic algorithm combined with finite element simulation. The force accumulation error of the Ti6AL4V alloy specimen, which was obtained from a simulated thermal tensile test and an actual test, was used as an optimization target function. Then, the damage parameters were optimized using the genetic algorithm until the target function reached the minimum value. Finally, the optimal damage model parameter was obtained. Through program development, the three high-temperature damage models established in this paper were embedded into Forge® NxT 2.1 finite element software. The simulated thermal tensile test of Ti6AL4V alloy was performed at a temperature of 800-1000 °C and a strain rate of 0.01-5 s-1. The simulated and actual fracture displacements of the tensile specimens were compared. The correlation coefficients (R) were calculated, which were 0.997, 0.951, and 0.912. Of the high-temperature damage models, the normalized Cockcroft and Latham high-temperature damage model had higher accuracy in predicting crack defects of Ti6Al4V alloy during the hot-forming process. Finally, a fracture strain graph and a high-temperature damage graph of Ti6Al4V alloy were constructed. The Ti6Al4V alloy damage evolution and thermal formability were analyzed in relation to the temperature and strain rate.

Effective Synthesis of Ladder-type Oligo(p-aniline)s and Poly(p-aniline)s via Intramolecular SNAr Reaction.

Symmetric ladder-type oligo(p-aniline)s and poly(p-aniline)s were successfully synthesized by an intramolecular ring closure in a highly efficient SNAr reaction from oligo(p-phenylene)s and poly(p-phenylene)s with fluorine (F) and secondary amine (NH) groups. Unlike Cadogan ring closure, the newly designed cyclization reaction will not produce a mixture of symmetric and nonsymmetric structures. Moreover, the introduction of the F atom does not hinder Suzuki polymerization. The result indicates that preparing regular oligomers and polymers with a nitrogen bridge is possible.

Characterization of the Thermal Degradation of Vinegar and the Construction of an Identification Model for Chinese Geographical Indication Vinegars by the Py-GC-MS Technique.

The pyrolysis (Py)-GC-MS technique was first introduced for the identification of two kinds of Chinese geographical indication vinegars because its advantages are that it is a simple and convenient sample pretreatment and inlet method. Abundant Py information about vinegars was obtained using Py-GC-MS; 21 common peaks were selected. With the help of the classical partial least-squares (PLS) modeling method for data analysis, two identification models for Shanxi extra-aged (SX) and Zhenjiang (ZJ) vinegars were established, respectively. An N-reducing method was used to select the variables. The variables were reduced one at a time to build the PLS models with the lowest number of misjudgments. Both models had good recognition rates, identifying over 90% of samples correctly. Thus, combining Py-GC-MS and PLS could be regarded as an effective method for the identification of SX and ZJ vinegars.

[Study on the Identification of Geographical Indication Wuchang Rice Based on the Content of Inorganic Elements].

Wuchang rice is a geographical indication product in China. Due to its high quality and low production, the phenome- non of fake is more and more serious. An effective identification method of Wuchang rice is urgent needed, for the maintenance of its brand image and interest of consumers. Base on the content of inorganic elements which are analyzed by ICP-AES and ICP-MS in rice, the identification model of Wuchang rice is studied combining with principal component analysis (PCA), Fisher discrimination and artificial neural network (ANN) in this paper. The effect on the identification of samples is poor through PCA, while the samples from Wuchang area and other areas can be identified accurately through Fisher discrimination and ANN. The average accurate identification ratio of training and verification set through Fisher discrimination is 93.5%, while the average accurate identification ratio through ANN is 96.4%. The ability to identify of ANN is better than Fisher discrimination. Wuchang rice can be identified accurately through the result of this research which provides a technology for the protection of geographical indications of this product.

Simultaneous determination of metoprolol and α-hydroxymetoprolol in human plasma using excitation-emission matrix fluorescence coupled with second-order calibration methods.

BACKGROUND: Metoprolol (MET) is a ß1-adrenoceptor antagonist, which is widely used in the treatment of cardiovascular diseases, and α-hydroxymetoprolol (α-OHM) is its hydroxylated metabolite. Owing to their similar structures, optimization of the condition for the chromatography approach, which is in common use for determination, is both time consuming and laborious. RESULTS: A new and effective strategy that combines the excitation-emission matrix fluorescence with second-order calibration methods was developed for simultaneous determination of MET and α-OHM in human plasma. CONCLUSION: Although the fluorescence spectra of MET and α-OHM overlapped and a large number of unknown and uncalibrated fluorescent components coexisted, the developed method enables accurate concentrations together with reasonable resolution of excitation and emission profiles for the analytes of interest. An additional advantage of the proposed method is that there is no need for separation and sample pretreatment, in addition to lower cost than traditional methods.

Four-way self-weighted alternating normalized residue fitting algorithm with application for the analysis of serotonin in human plasma.

A novel algorithm, four-way self-weighted alternating normalized residue fitting (SWANRF), which is an extension of its three-way form, for the decomposition of quadrilinear data with new weight factors, was proposed and applied to the quantitative analysis of serotonin contents in plasma samples. It was observed that the third-order calibration could not only retain a "second-order advantage" and but also obtain other advantages. The introduction of a fourth mode can relieve the serious problem of collinearity, which seems to be one of the "third-order advantages". The proposed algorithm shows great potential as a promising alternative for the third-order calibration of a four-way data array by contrasting with four-way parallel factor analysis (four-way PARAFAC). Furthermore, both algorithms mentioned above were utilized to analyze the 5-hydroxytryptamine (serotonin) contents in plasma samples by obtaining four-way array (excitation-emission-pH-sample) data, and produced satisfactory results. The serotonin contents in plasma samples obtained by using four-way SWANRF and four-way PARAFAC were 0.324 ± 0.005 and 0.348 ± 0.006 nmol mL(-1), respectively.