Reductive carboxylation of organo (pseudo)halides with CO 2 is ap owerfulm ethod to providec arboxylic acids quickly.Notably,the catalytic reductive carbo-carboxylation of unsaturated hydrocarbons via CO 2 fixation is ah ighly challenging but desirable approach for structurally diverse carboxylic acids.T here are only af ew reports and no examples of alkenes via transition metal catalysis.W er eport the first asymmetric reductive carbo-carboxylation of alkenes with CO 2 via nickel catalysis.Avariety of aryl (pseudo)halides,s uch as aryl bromides,a ryl triflates and inert aryl chlorides of particular note,u ndergo the reaction smoothly to give important oxindole-3-acetic acid derivatives bearing aC3-quaternary stereocenter.T his transformation features mild reaction conditions,w ide substrate scope,f acile scalability,g ood to excellent chemo-, regio-and enantioselectivities.T he method highlights the formal synthesis of (À)-Esermethole, (À)-Physostigmine and (À)-Physovenine,a nd the total synthesis of (À)-Debromoflustramide B, (À)-Debromoflustramine Ba nd (+ +)-Coixspirolactam A; thereby, opening an avenue for the total synthesis of chiral natural products with CO 2 .
Reductive carboxylation of organo (pseudo)halides with CO 2 is ap owerfulm ethod to providec arboxylic acids quickly.Notably,the catalytic reductive carbo-carboxylation of unsaturated hydrocarbons via CO 2 fixation is ah ighly challenging but desirable approach for structurally diverse carboxylic acids.T here are only af ew reports and no examples of alkenes via transition metal catalysis.W er eport the first asymmetric reductive carbo-carboxylation of alkenes with CO 2 via nickel catalysis.Avariety of aryl (pseudo)halides,s uch as aryl bromides,a ryl triflates and inert aryl chlorides of particular note,u ndergo the reaction smoothly to give important oxindole-3-acetic acid derivatives bearing aC3-quaternary stereocenter.T his transformation features mild reaction conditions,w ide substrate scope,f acile scalability,g ood to excellent chemo-, regio-and enantioselectivities.T he method highlights the formal synthesis of (À)-Esermethole, (À)-Physostigmine and (À)-Physovenine,a nd the total synthesis of (À)-Debromoflustramide B, (À)-Debromoflustramine Ba nd (+ +)-Coixspirolactam A; thereby, opening an avenue for the total synthesis of chiral natural products with CO 2 .
A protocol to prepare
With the development and progress of various sensors, the Internet of Things technology has continued to penetrate into people’s lives. Successful application cases of the Internet of Things technology have been seen in various industries. Some scholars have begun to try to apply the Internet of Things technology to the management of various industries. Deep learning technology belongs to the category of artificial intelligence technology. Its main goal is to combine a large number of training samples to train the trained object into an object that can learn sample patterns independently. At present, deep learning has a large number of applications in various intelligent operations and key intelligent recognition fields. Due to the characteristics of its learnable training set, deep learning techniques are often used in the direction of decision analysis. The research adopts a combination of questionnaire survey and modeling analysis to explore the construction of in-depth learning methods for enterprise management intelligent decision-making in the context of the Internet of Things. The research was conducted by telephone interview and online questionnaire, and was supported by nearly 100 technical backbone personnel from 25 large enterprises. The research finds that applying the Internet of Things and deep learning technology to enterprise intelligent management decisions can improve the decision-making accuracy of enterprises, and also provide enterprises with more significant decision-making analysis advantages in the industry competition. This paper first describes the concepts of the Internet of Things, deep learning and intelligent decision-making of enterprise management. Then, in order to sort out the problems existing in the current intelligent decision-making of enterprise management, the author conducted interviews and questionnaires. Through the analysis of the questionnaire data, he found the problems existing in the current intelligent decision-making of enterprise management. Finally, he designed a new strategy of intelligent decision-making of enterprise management based on the Internet of Things and deep learning technology, through the simulation and subsequent investigation and analysis of the newly designed strategy. It is found that the enterprise management intelligent decision-making method designed by combining the Internet of Things and deep learning technology is superior to the traditional enterprise decision-making method in all aspects. The design of the system has been reformed mainly from the aspects of human resource management, digital file management and real-time monitoring of production and operation, so that the popularity of the enterprise’s comprehensive information management has reached 84.2%, the efficiency of intelligent decision-making increased by 28.7% on average. The achievements of the research not only prove the role of IoT technology in promoting enterprises’ in-depth learning, but also put forward new ideas for enterprises’ scientific decision-making.
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