Construction of a Risk Prediction Model for Postpartum Stress Urinary Incontinence Based on Machine Learning

Pregnancy pregnancy and childbirth is one of the main causes of Stress Urinary Incontinence (SUI). SUI not only affects women's physical health, but also affects women's mental health. 48 puerperae with SUI 6-8 weeks postpartum and 118 puerperae without urinary incontinence during the same period were selected in a hospital in eastern China. Patient information was retrieved from medical records, and postpartum women were asked to complete the International Urinary Incontinence Counseling Questionnaire Short Form (ICI-Q-SF). The early prediction model of SUI was constructed based on the random forest ensemble learning method. Compared with the results of the traditional logistic regression model, the random forest model has better prediction performance and can be used as a screening tool for high-risk groups of SUI during pregnancy to guide clinical work

Operation Optimization Method of Distribution Network with Wind Turbine and Photovoltaic Considering Clustering and Energy Storage

The problem of distribution network operation optimization is diversified and uncertain. In order to solve this problem, this paper proposes a method of distribution network operation optimization considering wind-solar clustering, which includes source load and storage. Taking the total operating cost as the objective function, it includes network loss cost, unit operating cost, and considers a variety of constraints such as energy storage device constraints and demand response constraints. This paper aims to optimize the operation according to different wind-solar clustering scenes to improve the economy of distribution network. Taking the 365-day wind-solar output curves as the research object, K-means clustering is carried out, and the best k value is obtained by elbow rule. The second-order cone programming method and solver are used to solve the optimization model of each typical scenario, and the operation optimization analysis of each typical scenario obtained by clustering is carried out. Taking IEEE33 system and local 365-day wind-solar units output scenes as examples, the period is 24 h, which verifies the effectiveness of the proposed method. The proposed method has guiding significance for the operation optimization of distribution network

The Influence of Exogenous Nitrogen Input on the Characteristics of Phytolith-Occluded Carbon in the <i>Kandelia obovata</i> Soil System

Phytolith-occluded Ccarbon (PhytOC) is an important carbon sink in wetland ecosystems and a mechanism for long-term carbon sequestration. In recent years, nitrogen pollution has become increasingly severe and poses a threat to the healthy development of coastal ecological environments and socio-economic development; therefore, studying the impact of nitrogen deposition on the sequestration potential of PhytOC in the soil of coastal wetlands is highly significant. In the present study, two indoor tidal simulation experiments were set up with and without the planting of vegetation. The sequestration capacity and factors that influence soil PhytOC in the Kandelia obovata soil system were compared and analyzed under five nitrogen concentrations. The analysis shows that with the introduction of Kandelia obovata, the occluded carbon content of the soil phytoliths was significantly increased by 31.45% compared with the non-plant group, and the PhytOC content of the soil increased by 7.94%. The exogenous nitrogen input reduced the PhytOC content of the soil, with a rate of decline exceeding 26%. The PhytOC of the soil phytoliths and the PhytOC content of the soil in the planting group increased with increasing nitrogen concentration, while that of the non-plant group decreased as the concentration of nitrogen increased. The non-plant group was more affected by the exogenous nitrogen concentration than the planting group, and the soil microbial biomass carbon and microbial biomass nitrogen were the main factors that influenced changes in the PhytOC. In conclusion, nitrogen input has a significant inhibitory effect on soil PhytOC sequestration potential in coastal wetlands. Planting Kandelia obovata helps to improve the stability of carbon in wetland soil