No abstract

1,4-Dicarbonyl compounds are versatile scaffolds for the heterocycle synthesis, including the Paal–Knorr reaction. Herein, a feasible electrosynthesis method to access 1,4-dicarbonyl compounds has been developed from simple alkynes and 1,3-dicarbonyl compounds. When the undivided cell is combined with the constant current mode, aryl alkynes containing numerous medicinal motifs with 1,3-dicarbonyl esters or ketones react smoothly. External oxidant and catalyst-free conditions conform to the requirements of green synthesis.

We present a method to accurately measure the birefringence properties of spun fibers using binary polarization rotators. By taking the advantages of binary polarization rotator in polarization analysis, we are able to simultaneously measure both the circular and linear birefringences in a spun fiber with high accuracy. We obtain the circular and the residual linear birefringences of the spun fiber as a function of temperature T to be 3.34 × 10-5.11 × 10T and 8.1 × 10-1.19 × 10T, respectively, with the residual linear birefringence about 4 times less than the circular birefringence. We find, for the first time with the best of authors' knowledge, that the circular and the residual linear birefringences in a spun fiber are highly linear with the temperature, with thermal coefficients of -5.11 × 10 °C and -1.19 × 10°C, respectively, and that the relative changes per °C of the circular and residual linear birefringence are almost identical, with values of -0.152% and -0.147% respectively. We believe that the method and data presented in this paper will be beneficial for making high quality spun fibers, as well as high accuracy fiber optic current sensors.

We present a method to improve distributed strain sensing sensitivity by a reduced-cladding single mode fiber (RC SMF) using a Rayleigh backscattering spectra shift in optical frequency domain reflectometry. Comparing with a standard SMF with 250 μm diameter, a commercial low attenuation RC SMF with 165 μm diameter is shown to enhance the strain sensing sensitivity by about four-fold. Using this property, the system using the RC SMF can achieve smaller minimal measurable strain (MMS) in the same sensing spatial resolution (SSR) or smaller SSR in the same MMS than using the standard SMF. In our experiment, the system using RC SMF can achieve the MMS of 15 μstrain with a SSR of 4.5 cm or the MMS of 3 μstrain with a SSR of 18 cm.

Info-Kmeans, a K-means clustering method employing KL-divergence as the proximity function, is one of the representative methods in information-theoretic clustering. With the explosive growth of online texts such as online reviews and user-generated content, the text is becoming more sparse and much bigger, which poses significant challenges on both effectiveness and efficiency issues of text clustering. In our prior work, we presented a Summation-bAsed Incremental Learning (SAIL) algorithm, which can avoid the zero-feature dilemma of highly sparse texts. In this paper, we propose a sampling-based approximate approach for scaling SAIL algorithm to deal with the large-scale of texts. Particularly, an instance-level random sampling is invoked to reduce the number of instances to be examined during each iteration, which substantially speeds up the clustering on big text data. Furthermore, we prove that the margin of errors introduced by random sampling can be controlled in a small range. Extensive experiments on eight real-life text datasets demonstrate the advantage of the proposed sampling-based approximate clustering method. In particular, our method shows merits in both effectiveness and efficiency on clustering performance.