Catalytic and Base-free Suzuki-type α-Arylation of Cyclic 1,3-Dicarbonyls via a Cyclic Iodonium Ylide Strategy.

To date, it remains challenging to achieve a general and catalytic α-arylation of cyclic 1,3-dicarbonyls, particularly ubiquitous heteroaromatic ones. In most cases, the preparation of their medically significant arylated derivatives requires multistep synthetic sequences. Herein, we introduce a new, convenient strategy involving the conversion of cyclic 1,3-dicarbonyls to cyclic iodonium ylides (CIYs), followed by rhodium-catalyzed α-arylation with arylboronic reagents via carbene coupling.

Combining Artificial Neural Network and Ordinary Kriging to Predict Wetland Soil Organic Carbon Concentration in China's Liao River Basin.

Accurate prediction of wetland soil organic carbon concentration and an understanding of its controlling factors are important for studying regional climate change and wetland carbon cycles; with that knowledge mechanisms can be put in place that are conducive to sustainable ecosystem management for environmental health. In this study, a hybrid approach combining an artificial neural network and ordinary kriging and 103 soil samples at three soil depth ranges (0-30, 30-60, and 60-100 cm) were used to predict wetland soil organic carbon concentration in China's Liao River Basin. The model evaluation indicated that a combination of artificial neural network and ordinary kriging and limited soil samples achieved good performance in predicting wetland soil organic carbon concentration.