Luteolin and its C-monoglycosides fromLupinus polyphyllus
The leaves of Lupinus polyphyllus Lindley, a wild-growing biennial plant, in the flowering phase were fixed with steam and dried in a thermostat at 55-60°C. The dry comminuted material (2 kg) was repeatedly extracted with 70% ethanol at room temperature by the steeping method, and the extract was distilled in vacuum. The concentrated residue was treated with 600 ml of hot water and filtered and the resulting filtrate was extracted successively with diethyl ether, yielding fraction i, and ethyl acetate, yielding fraction 2.
The Ultraviolet Spectra of Flavones and Flavonols
The methanol spectra of flavones and flavonols exhibit two major absorption peaks in the region 240 – 400 nm1. These two peaks are commonly referred to as Band I (usually 300 – 380 nm, Table V-1 records the λmaxvalues for Band I for all flavones and flavonols examined in the present investigation), and Band II (usually 240 – 280 nm). Band I is considered to be associated with absorption due to the B-ring cinnamoyl system, and Band II with absorption involving the A-ring benzoyl system (see III) [1].
Research on Fracture Recognition in Well Logging Images: Adversarial Learning with Attention
Semantic recognition of fractures in well logging images is vital for engineers to implement oil and gas exploration. An essential approach to accomplishing the object is to adopt deep learning based on convolutional neural networks. However, due to the lack of annotated labels in well logging images, it is scarcely available to directly train the semantic segmentation network. In this paper, we explore a domain shift model attempting to achieve domain adaptation from one annotated dataset to our target well logging images. This model's core is to utilize adversarial learning, including generator and discriminator, which can prompt the model to generate fracture segmentation similar to the source domain in the target domain. For enhancing the domain adaptive model further, an attention module is introduced, which can suppress redundant noise in semantic segmentation results. We demonstrate that our proposed model performs well by extensive tests and ablation experiments in the ultrasonic well logging images.