RESUMEN
We report herein an efficient NHC-catalyzed kinetic resolution of acyclic tertiary propargylic alcohols that provides them in high to excellent enantioselectivity. This is the first example of kinetic resolution realized by enantioselective acylation. The recovered enantioenriched alcohols can be facilely converted into other valuable compounds such as densely functionalized tertiary alcohols and carbmates in high yields and excellent stereopurity. Density functional theory calculations were performed to determine the reaction mechanism and to understand the origin of enantiodiscrimination.
RESUMEN
COVID-19 is currently the biggest threat that challenges all of humankind's health and property. One promising and effective way to control the rapid spreading of this infection is searching for primary close contacts of the confirmed cases. In response, we propose COVID-19 Tracer, a low-cost passive searching system to find COVID-19 patients' close contacts. The main idea is utilizing ubiquitous WiFi probe requests to describe the location similarity, which is then achieved by two designed range-free judgment indicators: location similarity coefficient and close contact distance. We have carried out extensive experiments in a school office building, and the experimental results show an average accuracy of more than 98%, demonstrating our system's effectiveness in judging close contacts. Last but not least, we have developed a prototype system for a school building to find potential close contacts.
Asunto(s)
COVID-19 , Trazado de Contacto , Trazado de Contacto/métodos , Recolección de Datos , Humanos , Instituciones AcadémicasRESUMEN
The study of visible light indoor position has received considerable attention. The visible light indoor position has problems such as deployment difficulty and high cost. In our system, we propose a new fingerprint construction algorithm to simplify visible light indoor position. This method can realize the rapid construction of a visible fingerprint database and prove that the fingerprint database can be used repeatedly in different environments. We proved the theoretical feasibility of this method through theoretical derivation. We carried out extensive experiments in two classic real indoor environments. Experimental results show that reverse fingerprinting can be achieved. In 95% of cases, the positioning accuracy can be guaranteed to be less than 10 cm.
RESUMEN
In this paper, we propose a novel gesture recognition system based on a smartphone. Due to the limitation of Channel State Information (CSI) extraction equipment, existing WiFi-based gesture recognition is limited to the microcomputer terminal equipped with Intel 5300 or Atheros 9580 network cards. Therefore, accurate gesture recognition can only be performed in an area relatively fixed to the transceiver link. The new gesture recognition system proposed by us breaks this limitation. First, we use nexmon firmware to obtain 256 CSI subcarriers from the bottom layer of the smartphone in IEEE 802.11ac mode on 80 MHz bandwidth to realize the gesture recognition system's mobility. Second, we adopt the cross-correlation method to integrate the extracted CSI features in the time and frequency domain to reduce the influence of changes in the smartphone location. Third, we use a new improved DTW algorithm to classify and recognize gestures. We implemented vast experiments to verify the system's recognition accuracy at different distances in different directions and environments. The results show that the system can effectively improve the recognition accuracy.