A Comprehensive Analysis of Macrosegregation Formation During Twin-Roll Casting

Metallurgical and Materials Transactions B - A two-phase Eulerian–Eulerian volume-averaged model is used to predict the formation of macrosegregation during the twin-roll casting of...     

Chemistry and Toxicology of Major Bioactive Substances in Inocybe Mushrooms

Mushroom poisoning has always been a threat to human health. There are a large number of reports about ingestion of poisonous mushrooms every year around the world. It attracts the attention of researchers, especially in the aspects of toxin composition, toxic mechanism and toxin application in poisonous mushroom. Inocybe is a large genus of mushrooms and contains toxic substances including muscarine, psilocybin, psilocin, aeruginascin, lectins and baeocystin. In order to prevent and remedy mushroom poisoning, it is significant to clarify the toxic effects and mechanisms of these bioactive substances. In this review article, we summarize the chemistry, most known toxic effects and mechanisms of major toxic substances in Inocybe mushrooms, especially muscarine, psilocybin and psilocin. Their available toxicity data (different species, different administration routes) published formerly are also summarized. In addition, the treatment and medical application of these toxic substances in Inocybe mushrooms are also discussed. We hope that this review will help understanding of the chemistry and toxicology of Inocybe mushrooms as well as the potential clinical application of its bioactive substances to benefit human beings.     

Study of haze emission efficiency based on new co-opetition data envelopment analysis

As haze intensifies in China, controlling haze emission has become the country's top priority for environmental protection. Because haze moves across different regions, it is necessary to develop a data envelopment analysis (DEA) model underpinned by both competition and cooperation to evaluate the haze emission efficiency in different provinces. This study innovatively adopts the spatial econometrics to construct the co-opetition matrices of Chinese provinces, then builds the co-opetition DEA model to evaluate the haze emission efficiency of them, and finally uses the haze data of 2015 as an example to assess the applicability of the model. The results of the study include the following: First, compared with the traditional CCR (A. Charnes & W. W. Cooper & E. Rhodes) model, this study constructs the co-opetition DEA cross-efficiency model that integrates haze's feature of cross-border moving; thus, it is more in line with the reality of haze emission and movement. Second, compared with the efficiency value gained from the CCR model, the haze emission efficiency values for Tianjin and Guangdong, two decision-making units, register greater variance when using the DEA model. The reason might lie in that they have a different spatial transportation relationship with their surrounding provinces. Third, the haze emission efficiency of provinces, according to the evaluation based on the co-opetition DEA method, varies greatly: Those with high efficiency are mostly inland provinces with slow economic growth and adverse climatic conditions, whereas many of the provinces with low efficiency are located in the relatively prosperous East China. The specific co-opetition DEA model constructed in this study enriches the research on the DEA model, which can be applied to the emission efficiency evaluation of similar pollutants around the world and can contribute empirical support to the haze reducing efforts of the government with its empirical results.     

两阶段领域自适应学习

针对领域自适应问题中源域和目标域的联合分布差异最小化问题,提出两阶段领域自适应学习方法.在第一阶段考虑样本标签和数据结构的判别信息,通过学习一个共享投影变换,使投影后的共享空间中边缘分布的差异最小.第二阶段利用源域标记数据和目标域非标记数据学习一个带结构风险的自适应分类器,不仅能最小化源域和目标域条件分布差异,还能进一步保持源域和目标域边缘分布的流形一致性.在3个基准数据集上的实验表明,文中方法在平均分类准确率和Kappa系数两项评价指标上均表现较优.     

Nonhydrolyzable Heptose Bis- and Monophosphate Analogues Modulate Pro-inflammatory TIFA-NF-κB Signaling

d -Glycero-d -manno-heptose-1β,7-bisphosphate (HBP) and d -glycero-d -manno-heptose-1β-phosphate (H1P) are bacterial metabolites that were recently shown to stimulate inflammatory responses in host cells through the activation of the TIFA-dependent NF-κB pathway. To better understand structure-based activity in relation to this process, a family of nonhydrolyzable phosphonate analogues of HBP and H1P was synthesized. The inflammation modulation by which these molecules induce the TIFA-NF-κB signal axis was evaluated in vivo at a low-nanomolar concentration (6 nM) and compared to that of the natural metabolites. Our data showed that three phosphonate analogues had similar stimulatory activity to HBP, whereas two phosphonates antagonized HBP-induced TIFA-NF-κB signaling. These results open new horizons for the design of pro-inflammatory and innate immune modulators that could be used as vaccine adjuvant.     

Wearing prediction of stellite alloys based on opposite degree algorithm

In order to predict the wearing of stellite alloys,the related methods of rare metals data processing were discussed. The method of opposite degree(OD) algorithm was put forward to predict the wearing of stellite alloys.OD algorithm is based on prior numerical data, posterior numerical data and the opposite degree between numerical forecast data. To compare the performance of predicted results based on different algorithms, the back propagation(BP) and radial basis function(RBF) neural network methods were introduced. Predicted results show that the relative error of OD algorithm is smaller than those of BP and RBF neural network methods. OD algorithm is an effective method to predict the wearing of stellite alloys and it can be applied in practice.     

Se doped nickel-molybdenum bimetal sulfide with enhanced electrochemical activity for hydrogen evolution reaction

In this work, we synthesized Se doped MoS₂@Ni₃S₂ with nanosheets coated nanorods structure supported on Ni foam (MoNiSeS). Firstly, MoS₂@Ni₃S₂ (MoNiS) nanorods was synthesized by hydrothermal method. After selenization treatment, MoSe₂ successfully formed on the edge of MoS₂ nanosheets and particle Ni₃S₂ transformed into NiSe, in which MoSe₂ and NiSe acted as new phase in MoNiSeS. The obtained MoNiSeS only needs a low overpotential of 68 mV to reach the current density of 10 mA cm^?2, and has a low Tafel plots of 72.77 mV dec^?1 and good electrochemical durability, whose electrochemical activity is much better than that of MoNiS and NiSeS, implying the introduction of Mo and Se is beneficial to improve the electrocatalytic performance of NiS for HER. In addition, the proper amount of Mo source, which has an effect on the morphology of product, has also been investigated. For MoNiSeS, the typical nanosheets coated nanarods expose more active sites and the synergic effects is good to the improvement of the catalytic activity. Meanwhile, WNiSeS has also been prepared using the same method and the corresponding results show that the electrochemical activity of WNiSeS is much better than that of NiSeS, proving the universality of this strategy.     

Lead-free sodium niobate nanowires with strong piezo-catalysis for dye wastewater degradation

In this work, the hydrothermally-synthesized sodium niobate nanowires were used to decompose Rhodamine B dye solution through the piezo-catalytic effect. With the sodium niobate catalyst, a high piezo-catalytic degradation ratio of ～80% was achieved under the excitation of vibration for the Rhodamine B dye solution (～5?mg/l). These active species in the catalytic process, hydroxyl radicals and superoxide radicals with the strong oxidation ability, were also observed, which confirmed the key role of piezoelectric effect for piezo-catalysis. The piezo-catalysis of sodium niobate nanowires provides a high-efficiency and reusable tool in application in depredating the dye wastewater.