Visible-light promoted atom transfer radical addition-elimination (ATRE) reaction for the synthesis of fluoroalkylated alkenes using DMA as electron-donor

Here, we describe a mild, catalyst-free and operationally-simple strategy for the direct fluoroalkylation of olefins driven by the photochemical activity of an electron donor-acceptor (EDA) complex between DMA and fluoroalkyl iodides. The significant advantages of this photochemical transformation are high efficiency, excellent functional group tolerance, and synthetic simplicity, thus providing a facile route for further application in pharmaceuticals and life sciences

Research to Break Oil Shale with High Pressure Water Jet Based on Bionic Nozzle

AbstractOil shale is a sedimentary rock, it is increasingly attracting widespread attention as petroleum supplement energy. Using borehole hydraulic mining techniques to mine oil shale seams at a certain depth in the underground, first and foremost is the use of high pressure water jet to make the overall oil shale ore broken into small pieces and peel them off parent rock. Based on the bionic theories, to design the bionic nozzles are adding several bionic units in the internal flow channel surface of the nozzle, it makes the original smooth flow channel inside the nozzle has become bionic non-smooth surface structure, to some extent, effectively improved the hydraulic characteristics of the nozzle internal flow channel, and reduced the flow resistance of the water. Based on CFD simulation and analysis, the reasons for upgrading effect of the crushed oil shale by the bionic nozzle high pressure water jet are analyzed. Experiments show that, in the same working conditions, bionic nozzle compared with the normal nozzle of the same structure parameters, the diameter of the erosion and crushing pit on oil shale samples expanded 4mm, and the crushing pit depth deepened 3.8mm using bionic nozzle

Model Predictive Control for Continuous-Time Singular Jump Systems with Incomplete Transition Rates

This paper is concerned with model predictive control (MPC) problem for continuous-time Markov Jump Systems (MJSs) with incomplete transition rates and singular character. Sufficient conditions for the existence of a model predictive controller, which could optimize a quadratic cost function and guarantee that the system is piecewise regular, impulse-free, and mean square stable, are given in two cases at each sampling time. Since the MPC strategy is aggregated into continuous-time singular MJSs, a discretetime controller is employed to deal with a continuous-time plant and the cost function not only refers to the singularity but also considers the sampling period. Moreover, the feasibility of the MPC scheme and the mean square admissibility of the closed-loop system are deeply discussed by using the invariant ellipsoid. Finally, a numerical example is given to illustrate the main results

AFFIRM: Affinity Fusion-based Framework for Iteratively Random Motion correction of multi-slice fetal brain MRI

Multi-slice magnetic resonance images of the fetal brain are usually contaminated by severe and arbitrary fetal and maternal motion. Hence, stable and robust motion correction is necessary to reconstruct high-resolution 3D fetal brain volume for clinical diagnosis and quantitative analysis. However, the conventional registration-based correction has a limited capture range and is insufficient for detecting relatively large motions. Here, we present a novel Affinity Fusion-based Framework for Iteratively Random Motion (AFFIRM) correction of the multi-slice fetal brain MRI. It learns the sequential motion from multiple stacks of slices and integrates the features between 2D slices and reconstructed 3D volume using affinity fusion, which resembles the iterations between slice-to-volume registration and volumetric reconstruction in the regular pipeline. The method accurately estimates the motion regardless of brain orientations and outperforms other state-of-the-art learning-based methods on the simulated motion-corrupted data, with a 48.4% reduction of mean absolute error for rotation and 61.3% for displacement. We then incorporated AFFIRM into the multi-resolution slice-to-volume registration and tested it on the real-world fetal MRI scans at different gestation stages. The results indicated that adding AFFIRM to the conventional pipeline improved the success rate of fetal brain super-resolution reconstruction from 77.2% to 91.9%

Evorus: A Crowd-powered Conversational Assistant Built to Automate Itself Over Time

Crowd-powered conversational assistants have been shown to be more robust than automated systems, but do so at the cost of higher response latency and monetary costs. A promising direction is to combine the two approaches for high quality, low latency, and low cost solutions. In this paper, we introduce Evorus, a crowd-powered conversational assistant built to automate itself over time by (i) allowing new chatbots to be easily integrated to automate more scenarios, (ii) reusing prior crowd answers, and (iii) learning to automatically approve response candidates. Our 5-month-long deployment with 80 participants and 281 conversations shows that Evorus can automate itself without compromising conversation quality. Crowd-AI architectures have long been proposed as a way to reduce cost and latency for crowd-powered systems; Evorus demonstrates how automation can be introduced successfully in a deployed system. Its architecture allows future researchers to make further innovation on the underlying automated components in the context of a deployed open domain dialog system.Comment: 10 pages. To appear in the Proceedings of the Conference on Human Factors in Computing Systems 2018 (CHI'18