Direct methane conversion to methanol by ionic liquid-dissolved platinum catalysts

Ternary systems of inorganic Pt salts and oxides, ionic liquids and concentrated sulfuric acid are effective at catalyzing the direct, selective oxidation of methane to methanol and appear to be more water tolerant than the Catalytica reaction

Novel Broadband Amplifier for Mid-Infrared Semiconductor laser and applications in spectroscopy

An amplifier design for broadband Mid-IR buried-hetero (BH) structure epitaxial laser is presented, and external cavity design based on this amplifier is described. Spectroscopy results characterizing such single frequency lasers are demonstrated with whispering gallery mode CaF2 disc/ball, saturated absorption in hollow waveguide and direct chemical analysis in water

Preparation of a Modified PTFE Fibrous Photo-Fenton Catalyst and Its Optimization towards the Degradation of Organic Dye

Polytetrafluoroethylene (PTFE) fiber was grafted with acrylic acid to impart the carboxyl groups onto the fiber surface, which were used to coordinate with both transition metal ions Fe(III) and Cu(II) and a rare metal ion Ce(III) to prepare the metal grafted PTFE fiber complexes as the novel heterogeneous Fenton catalysts for the degradation of the azo dye in water under visible irradiation. Some factors affecting the preparation process, such as nature and concentration of metal ions in the coordination solution, grafting degree of PTFE and reaction temperature were optimized with respect to the content and strength of metal fixation on the fiber and dye degradation efficiency. The results indicated that increasing metal ion concentrations in solution and grafting degree of PTFE fiber as well as higher coordination temperature led to a significant increase in metal content, especially Fe(III) and Cu(II) content of the complexes. Fe(III) ions fixed on the fiber showed the better catalytic performance than Cu(II) and Ce(III) ions fixed when three different complexes with similar metal content being employed, respectively. Moreover, Increasing Fe content or incorporation of Cu(II) ions could significantly improve the catalytic activity of the complexes

Optimal Accelerated Variance Reduced EXTRA and DIGing for Strongly Convex and Smooth Decentralized Optimization

We study stochastic decentralized optimization for the problem of training machine learning models with large-scale distributed data. We extend the famous EXTRA and DIGing methods with accelerated variance reduction (VR), and propose two methods, which require the time of $O((\sqrt{n\kappa_s}+n)\log\frac{1}{\epsilon})$ stochastic gradient evaluations and $O(\sqrt{\kappa_b\kappa_c}\log\frac{1}{\epsilon})$ communication rounds to reach precision $\epsilon$, where $\kappa_s$ and $\kappa_b$ are the stochastic condition number and batch condition number for strongly convex and smooth problems, $\kappa_c$ is the condition number of the communication network, and $n$ is the sample size on each distributed node. Our stochastic gradient computation complexity is the same as the single-machine accelerated variance reduction methods, such as Katyusha, and our communication complexity is the same as the accelerated full batch decentralized methods, such as MSDA, and they are both optimal. We also propose the non-accelerated VR based EXTRA and DIGing, and provide explicit complexities, for example, the $O((\kappa_s+n)\log\frac{1}{\epsilon})$ stochastic gradient computation complexity and the $O((\kappa_b+\kappa_c)\log\frac{1}{\epsilon})$ communication complexity for the VR based EXTRA. The two complexities are also the same as the ones of single-machine VR methods, such as SAG, SAGA, and SVRG, and the non-accelerated full batch decentralized methods, such as EXTRA, respectively

Renovation and Reuse of Reactive Dyeing Effluent by a Novel Heterogeneous Fenton System Based on Metal Modified PTFE Fibrous Catalyst/H 2

Cu-Fe bimetallic grafted polytetrafluoroethylene (PTFE) fiber complexes were prepared and optimized as the novel heterogeneous Fenton catalysts for the degradation of reactive dyes under UV irradiation. Cotton fabrics were dyed with three reactive dyes, namely, Reactive Red 195, Reactive Yellow 145, and Reactive Blue 222, in tap fresh water using exhaustion process. The spent dyeing effluents were then collected and degraded with the optimized Cu-Fe bimetallic grafted PTFE fiber complex/H2O2 system. The treated dyeing effluents were characterized and reused for the dyeing of cotton fabrics through the same process. The effect of reuse process number on quality of the dyed cotton fabrics was examined. The results indicated that the Cu-Fe bimetallic modified PTFE fiber complex with a Cu/Fe molar ratio of 2.87 was found to be the most effective fibrous catalyst, which enhanced complete decolorization of the treated dyeing effluents with H2O2 in 4 h. However, the TOC removal for the treated dyeing effluents was below 80%. The dyeing quality was not affected for three successive cycles. The increase in residual TOC value influences fourth dyeing cycle. Further TOC reduction of the treated effluents is needed for its repeated reuse in more than three dyeing cycles

Prediction of Gene Expression Patterns With Generalized Linear Regression Model

Cell reprogramming has played important roles in medical science, such as tissue repair, organ reconstruction, disease treatment, new drug development, and new species breeding. Oct4, a core pluripotency factor, has especially played a key role in somatic cell reprogramming through transcriptional control and affects the expression level of genes by its combination intensity. However, the quantitative relationship between Oct4 combination intensity and target gene expression is still not clear. Therefore, firstly, a generalized linear regression method was constructed to predict gene expression values in promoter regions affected by Oct4 combination intensity. Training data, including Oct4 combination intensity and target gene expression, were from promoter regions of genes with different cell development stages. Additionally, the quantitative relationship between gene expression and Oct4 combination intensity was analyzed with the proposed model. Then, the quantitative relationship between gene expression and Oct4 combination intensity at each stage of cell development was classified into high and low levels. Experimental analysis showed that the combination height of Oct4-inhibited gene expression decremented by a temporal exponential value, whereas the combination width of Oct4-promoted gene expression incremented by a temporal logarithmic value. Experimental results showed that the proposed method can achieve goodness of fit with high confidence

Survey on the Overwintering of Syrphids in Changbai Mountains and Experiments on Artificial Protection of the Overwintering Syrphid Flies

Originating text in Chinese.Citation: Gao, Junfeng, Zhang, Guangxin, Qin, Yongchun, Yu, Kai, Li, Minghai, Qin, Yi. (1993). Survey on the Overwintering of Syrphids in Changbai Mountains and Experiments on Artificial Protection of the Overwintering Syrphid Flies. Chinese Journal of Biological Control, 9(3), 142-144

Zoom Out and Observe: News Environment Perception for Fake News Detection

Fake news detection is crucial for preventing the dissemination of misinformation on social media. To differentiate fake news from real ones, existing methods observe the language patterns of the news post and "zoom in" to verify its content with knowledge sources or check its readers' replies. However, these methods neglect the information in the external news environment where a fake news post is created and disseminated. The news environment represents recent mainstream media opinion and public attention, which is an important inspiration of fake news fabrication because fake news is often designed to ride the wave of popular events and catch public attention with unexpected novel content for greater exposure and spread. To capture the environmental signals of news posts, we "zoom out" to observe the news environment and propose the News Environment Perception Framework (NEP). For each post, we construct its macro and micro news environment from recent mainstream news. Then we design a popularity-oriented and a novelty-oriented module to perceive useful signals and further assist final prediction. Experiments on our newly built datasets show that the NEP can efficiently improve the performance of basic fake news detectors.Comment: ACL 2022 Main Conference (Long Paper