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Urban waterfront green space is a critical component of urban ecosystems and can provide various types of cultural ecosystem services (CESs). In this study, the CESs of six waterfront green spaces with different planned functions in different areas along the Huangpu River were assessed, and a framework of CES types applicable to the assessment of waterfront green spaces was proposed. Based on an investigation of the basic indicators of different waterfront green spaces and the differences in planning in the regions where they are located, we explored the factors affecting the public's perception of CESs. We found that a waterfront green space with a clear theme and amusement facilities with special features improved public perceptions of CESs. Improved water accessibility and many winding walkways can increase the diversity of outdoor activities. The discrepancy between public perceptions of CESs and the CESs that city managers hope waterfront green spaces to provide in urban planning may be due to a lack of a detailed introduction to facilities for public within green spaces. We suggest promoting the public perception of CESs provided by waterfront green spaces through improved water accessibility and enhanced descriptions of their facilities. The results and suggestions generated from this study offer insights into the future planning and design of urban waterfront green spaces.

The reliability of liquid rocket engines (LREs), which are the main propulsion device of launch vehicles, cannot be overemphasised. The development of fault detection and diagnosis (FDD) technology for LREs can effectively improve the safety and reliability of launch vehicles, which has important theoretical and engineering significance. With the rapid development of artificial intelligence technologies such as machine learning and artificial neural network, data-driven FDD methods have gained increasing attention. However, the scarcity of engine fault samples limits the application of this methods. We proposed a method combining Wasserstein generative adversarial nets (WGANs) and multilayer perceptron (MLP) to perform FDD for LREs with sample imbalance. Wasserstein generative adversarial nets were trained using the fault data from the actual hot-firing ground test of a large LRE. Considerable fault data were generated to expand the data set to balance the ratio of positive and negative samples. Subsequently, the expanded data set was used to train the MLP for FDD of a large LRE. The results showed that the samples generated by the WGAN were authentic, confirming the application of the proposed method as a novel and effective tool for establishing a complete LRE fault database. Furthermore, the diagnosis times of the proposed method on five fault tests were advanced by 0.66, 15.82, 0.24, 0.14 and 1.08 s in relation to those of the conventional red-line cut-off system. Compared with support vector machine and adaptive threshold algorithm, the proposed method also performed better.

AbstractEtlingera velutinabelongs to the Zingiberaceae family. The plant is known as a potent agent for snakebite and food flavoring in the east of Asia. In this study, the essential oil from the rhizomes of E. velutinawas obtained using the hydro-distillation assay. The chemical composition of the oil was identified by chromatographic methods of GC/FID and GC/MS. The MTT assay was run to evaluate the cytotoxicity effect of the essential oil. The oil consists of sesquiterpene hydrocarbon. α-Cubebene (57.4%) and 2-undecanone (28.6%) were the major compounds for the rhizome oil. The MTT assay was run to treat the cell lines with essential oil for evaluation of the cytotoxicity and anti-human colorectal carcinoma properties. The IC50of essential oil was 241 and 214 μg/mL against ileocecal colorectal adenocarcinoma (HCT-8 [HRT-18]) and Burkitt's lymphoma (Ramos.2G6.4C10) cell lines, respectively. The results showed a dose-dependently on The viability of malignant colorectal cell lines in the presence of essential oil. The obtained results revealed the essential oil of the rhizomes of E. velutinais a potent agent against colorectal carcinoma.

Comdb2 is a distributed database system designed for geographical replication and high availability. In contrast with the latest trends in this field, Comdb2 offers full transactional support, a standard relational model, and the expressivity of SQL. Moreover, the system allows for rich stored procedures using a dialect of Lua. Comdb2 implements a serializable system in which reads from any node always return current values. Comdb2 provides transparent High Availability through built-in service discovery and sophisticated retry logic embedded in the standard API.In addition to the relational data model, Comdb2 implements queues for publisher-to-subscriber message delivery. Queues can be combined with table triggers for time-consistent log distribution, providing functionality commonly needed in modern OLTP.In this paper we give an overview of our last twelve years of work. We focus on the design choices that have made Comdb2 the primary database solution within our company, Bloomberg LP (BLP).