Search

The offshore engineering develop fast in recent years, a new method named “big-size sandbag cofferdam” is applied to many practical projects in China. The sandbag is made of geotextile with large sizes in length and width. Sandbags are filled with pumped sea sand and stacked together layer by layer. Many theoretical obstacles remain unsolved, which has restricted the application of this advanced technology. Based on an instability project located in Bohai Bay, the failure mode of the big-size sandbag cofferdam on soft foundation was studied. The results show that the deformation of cofferdam was concentrated on the bottom sandbag, under the action of insufficient foundation bearing capacity and overburden load, the stress of the geotextile at the bottom layer increase sharply during the fast filling, then exceed its ultimate tensile strength, and the cofferdam would be pulled apart from the bottom to top, lead to a continuous penetrating sliding surface failure of big-size sandbag cofferdam.

This review summarizes the application of machine learning in research on the numbing substances of Zanthoxylum bungeanum. Different varieties of Z. bungeanum on the market vary in the composition and content of numbing substances. Traditional methods for the detection and analysis of the composition and content of numbing substances in Z. bungeanum have many limitations, so the introduction of machine learning algorithms has brought new possibilities to this field. Applying machine learning for predictive modeling of the quality of Z. bungeanum and modeling of its drying process, the sensory evaluation of Z. bungeanum, and establishing a germplasm bank for Z. bungeanum is of great significance for the genetic breeding of Z. bungeanum. This article systematically reviews the composition and content of numbing substances in different varieties of Z. bungeanum, and analyzes the application of machine learning algorithms in predictive quality modeling and drying modeling of Z. bungeanum and data analysis of its numbing substances. Integration with machine learning technology enables a deeper understanding of the currently established models, which will provide support for the optimization of the yield and quality of Z. bungeanum based on numbing substances.

Background In the initial promotion of pilot hospice care services (HCS) in China, there is an urgent need to evaluate the quality and effectiveness of HCS comprehensively in pilot institutions. Objective The purpose of this study was to establish a meso-level comprehensive assessment system of hospice care, and to provide a scientific measurement tool for assessing and comparing hospice care in various pilot institutions. Methods An item pool for establishing a comprehensive assessment system for HCS was constructed through a literature review and small-scale expert interviews from April to May 2021, then the items were rated using a 9-1 grading scheme (the highest grade is 9, while 1 is the lowest) in terms of three aspects (relevance, measurability and feasibility) during two rounds of expert consultation conducted using the RAND/UCLA modified Delphi panel method from June to July 2021. Results The Comprehensive Assessment System of Hospice Care (CASHC) was established finally after the items were revised and improved according to the results of two rounds of expert consultation, which consists of 3 primary indicators (structure, process and outcome), 9 secondary indicators (policy guarantee, service provision, patient burden, etc.), 25 tertiary indicators (institutional system guarantee, number of services, per capita cost, etc.) and 81 quaternary indicators (inclusion of institutional development plan, number of hospital discharges and per capita medical cost, etc.). The first round of consultation achieved a response rate of 93.3%, an authority coefficient of 0.900, with values of Kendall's W for the quaternary indicators calculated as 0.194, 0.115, and 0.126, respectively. The second round of consultation achieved a response rate of 92.9% and an authority coefficient of 0.900, with values of Kendall's W for the quaternary indicators of 0.417, 0.241, and 0.322, respectively. Conclusion The CASHC consisting of four-level indicators established using the Donabedian's structure-process-outcome framework is an innovative and practical tool, which can be used to quantify and compare the quality and effectiveness of HCS among different pilot institutions or different regions, contributing to the promotion of the standardization and homogenization of HCS in pilot regions.

Developing new reactive pathway to activate inert C(sp3)−H bonds for valuable oxygenated products remains a challenge. We prepared a series of triazine conjugated organic polymers to photoactivate C−H into aldehyde/ketone via O2→H2O2→⋅OH→Cl⋅→Cl2⋅−. Experiment results showed Cl2⋅− could successively activate C(sp3)−H more effectively than Cl⋅ to generate unstable dichlorinated intermediates, increasing the kinetic rate ratio of dichlorination to monochlorination by a factor of 2,000 and thus breaking traditional dichlorination kinetic constraints. These active intermediates were hydrolyzed into aldehydes or ketones easily, when compared with typical stable dichlorinated complexes, avoiding chlorinated by‐product generation. Moreover, an integrated two‐phase system in an acid solution strengthened the Cl2⋅− mediated process and inhibited product overoxidation, where the conversion rate of toluene reached 16.94 mmol/g/h and the selectivity of benzaldehyde was 99.5 %. This work presents a facile and efficient approach for selective conversion of inert C(sp3)−H bonds using Cl2⋅−. [ABSTRACT FROM AUTHOR]