Diastereoselective three-component synthesis of beta-amino carbonyl compounds using diazo compounds, boranes, and acyl imines under catalyst-free conditions

Diazo compounds, boranes, and acyl imines undergo a three-component Mannich condensation reaction under catalyst-free conditions to give the anti β-amino carbonyl compounds in high diastereoselectivity. The reaction tolerates a variety of functional groups, and an asymmetric variant was achieved using the (−)-phenylmenthol as chiral auxiliary in good yield and selectivity. These β-amino carbonyl compounds are valuable intermediates, which can be transformed to many potential bioactive molecules.We gratefully acknowledge Philip N. Moquist for editorial review of the manuscript. Preliminary experiments were performed by Y.L. at Boston University. Completion of the work was accomplished under the direction of G.W. at the University of Science and Technology Beijing, China. S.E.S. and Y.L. gratefully acknowledge the NIH for support (NIGMS R01 GM078240). Y.L., J.Y., and G.W. thank the Innovative Foundation from China National Petroleum Corporation (Grant No. 2012D-5006-0504) for financial support. Y.L. also thanks the Beijing Natural Science Foundation (Grant No. 2144052) and China Postdoctoral Science Foundation (2013M540859) for financial support. (NIGMS R01 GM078240 - NIH; 2012D-5006-0504 - Innovative Foundation from China National Petroleum Corporation; 2144052 - Beijing Natural Science Foundation; 2013M540859 - China Postdoctoral Science Foundation)Published versio

Extreme case of Faraday effect: magnetic splitting of ultrashort laser pulses in plasmas

The Faraday effect, caused by a magnetic-field-induced change in the optical properties, takes place in a vast variety of systems from a single atomic layer of graphenes to huge galaxies. Currently, it plays a pivot role in many applications such as the manipulation of light and the probing of magnetic fields and material's properties. Basically, this effect causes a polarization rotation of light during its propagation along the magnetic field in a medium. Here, we report an extreme case of the Faraday effect where a linearly polarized ultrashort laser pulse splits in time into two circularly polarized pulses of opposite handedness during its propagation in a highly magnetized plasma. This offers a new degree of freedom for manipulating ultrashort and ultrahigh power laser pulses. Together with technologies of ultra-strong magnetic fields, it may pave the way for novel optical devices, such as magnetized plasma polarizers. In addition, it may offer a powerful means to measure strong magnetic fields in laser-produced plasmas.Comment: 18 pages, 5 figure

A climatology of the F-layer equivalent winds derived from ionosonde measurements over two decades along the 120°-150°E sector

International audienceThe vertical equivalent winds (VEWs) at the F-layer are analyzed along the 120°-150°E longitude sector with an emphasis on their latitudinal dependence. The VEWs are derived from the monthly median data of fourteen ionosonde stations over two decades. The results show that the VEWs have considerable dependences on the magnetic latitude with an approximate symmetry about the magnetic equator. They are mostly controlled by the electric field drifts in the magnetic equatorial region, and shift to be mostly contributed by neutral winds at mid-latitudes. The relative contribution of the two dynamic factors is regulated by the magnetic dip in addition to their own magnitudes. The VEWs generally have opposite directions and different magnitudes between lower and higher latitudes. At solar minimum, the magnitudes of VEWs are only between -20 and 20m/s at lower latitudes, while at higher latitudes they tend to increase with latitudes, typically having magnitudes between 20-40m/s. At solar maximum, the VEWs are reduced by about 10-20m/s in magnitudes during some local times at higher latitudes. A tidal analysis reveals that the relative importance of major tidal components is also different between lower and higher latitudes. The VEWs also depend on local time, season and solar activity. At higher latitudes, the nighttime VEWs have larger magnitude during post-midnight hours and so do the daytime ones before midday. The VEWs tend to have an inverse relationship with solar activity not only at night, but also by day, which is different from the meridional winds predicted by the HWM93 model. The latitudinal dependence of VEWs has two prevailing trends: one is a maximum at the highest latitudes (as far as the latitudes concerned in the present work); the other is a mid-latitude maximum. These two latitudinal trends are mostly dependent on season, while they depend relatively weakly on local time and solar activity. The latitudinal gradients of VEWs also show a tendency of a mid-latitude maximum, except that there are much stronger latitudinal gradients at southern higher mid-latitudes in some seasons. The gradients during daytime are much smaller at solar maximum than minimum, whereas they are generally comparable at night under both solar activity levels

Non-intrusive Load Monitoring based on Self-supervised Learning

Deep learning models for non-intrusive load monitoring (NILM) tend to require a large amount of labeled data for training. However, it is difficult to generalize the trained models to unseen sites due to different load characteristics and operating patterns of appliances between data sets. For addressing such problems, self-supervised learning (SSL) is proposed in this paper, where labeled appliance-level data from the target data set or house is not required. Initially, only the aggregate power readings from target data set are required to pre-train a general network via a self-supervised pretext task to map aggregate power sequences to derived representatives. Then, supervised downstream tasks are carried out for each appliance category to fine-tune the pre-trained network, where the features learned in the pretext task are transferred. Utilizing labeled source data sets enables the downstream tasks to learn how each load is disaggregated, by mapping the aggregate to labels. Finally, the fine-tuned network is applied to load disaggregation for the target sites. For validation, multiple experimental cases are designed based on three publicly accessible REDD, UK-DALE, and REFIT data sets. Besides, state-of-the-art neural networks are employed to perform NILM task in the experiments. Based on the NILM results in various cases, SSL generally outperforms zero-shot learning in improving load disaggregation performance without any sub-metering data from the target data sets.Comment: 12 pages,10 figure