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[Objective] In order to accurately estimate net primary productivity (NPP) of vegetation under the context of rising atmospheric CO2 concentrations. [Methods] A CO2 concentration factor was introduced into the Carnegie-Ames-Stanford Approach (CASA) model to simulate the maximum light use efficiency of different vegetation types. Based on this, the potential of the improved model for NPP estimation was explored. [Results] From 2000 to 2020, the annual average atmospheric CO2 concentration in China's terrestrial areas showed a significant increasing trend, with an average increase of approximately 2.14 μmol/(mon·a). After incorporating the CO2 stress factor, the vegetation types were ranked by maximum light use efficiency in the following order cropland>evergreen broadleaf forest>mixed forest>needleleaf forest>shrub>wetland>grassland (1.85, 1.69, 1.30, 0.87, 0.52, 0.40, 0.40 g/MJ). The estimation accuracy of NPP by the CASA_CO2 model was improved compared to the original CASA model. The R2 between the simulated and measured NPP values at the vegetation level and the comprehensive level increased by -0.1% to 3.7% and 0.5%, respectively, and RMSE decreased by 0.3% to 9.2% and 0.7%, respectively. The RMSE of annual NPP estimation results decreased by 1.9%. The CASA_CO2 model improved the underestimation of overall NPP by the CASA model, reducing it from 10.62% to 9.81%. The CASA_CO2 model underestimated the overall NPP for spring, autumn, and winter by 5.11%, 2.72%, and 2.51%, respectively, while overestimating it for summer by 0.53%. [Conclusion] Considering the impact of CO2 concentration changes on vegetation in the model can improve the accuracy of NPP estimation.

Potato protein deaminated for different durations (0, 0.5, 3, 6 and 12 h) were used to prepare emulsions, and the products obtained were evaluated for droplet size distribution, emulsion stability, microrheological properties and microstructure. The results showed that the droplet volume mean diameter and Turbiscan stability index (TSI) of the emulsion decreased first and then increased with increasing deamidation time. The emulsions with potato protein deaminated for 3 and 6 h exhibited uniform droplet size distribution and good stability, which may be because the increased electrostatic repulsion between the modified protein emulsion droplets prevented their aggregation. The droplet size of the emulsion with potato protein deaminated for 12 h increased and the stability decreased, which may be because of the decreased charge repulsion force and consequent droplet aggregation. The microrheological analysis showed that the emulsion with potato protein deaminated for 6 h had the highest macroscopic viscosity index (MVI) value and the highest viscosity, and the speed of droplet movement was slowed down. There was a strong force between the emulsion droplets, which made the system more stable. This study can provide a reference for further research and development of potato protein products in order to improve the utilization rate of potato protein and expand the application range.

The combination of vision and robotic grinding technology provides robots with "visual perception" capabilities that enable them to accurately locate the area to be ground and perform the grinding tasks efficiently. Based on the rough grinding requirements for wheel hub burrs proposed by a casting company, this paper investigates the application of a vision-guided grinding robot in treating burrs on wheel hub castings. First, through vision system calibration, the conversion from pixel coordinate system to robot base coordinate system is implemented, thus ensuring that the subsequently extracted burr point coordinates can be correctly mapped to the robot's operational coordinate system. Next, the images of the burrs on wheel hub castings are collected and processed. All the burr points are extracted by applying image algorithms. In order to improve grinding accuracy, a height error compensation model is established to adjust the coordinates of the 2D-pixel points; the coordinate error after compensation was reduced by 58.33%. Subsequently, the compensated burr point trajectories are optimized by utilizing an intelligent optimization algorithm to generate the shortest grinding path. Through experimental analysis of the relationship between spindle speed and surface roughness, a grinding trajectory simulation model is constructed, and the simulation results are integrated into the robot system. Finally, actual wheel hub burr grinding experiments are performed to validate the effectiveness and practicality of the proposed solution. [ABSTRACT FROM AUTHOR]

Objective To explore the role of chest pain nurse in the emergency management of patients with ST-elevation myocardial infarction (STEMI). Methods Basing on the requirement of chest pain center construction, a group of chest pain full-time nurses were recruited in emergency room and catheter room for Digital subtraction angiography (DSA), and the emergency care process of STEMI patients was modified. A total of 60 cases in control group adopted routine emergency care mode, and another 58 cases in the experimental group adopted modified emergency care model. The time period of key interventions in the process of emergency management were calculated. Results The duration between hospital admission and admission to the emergency room, between hospital admission and first ECG diagnosis, between clinical admission and blood draw for cardiac troponin T test, cardiac troponin T test, between hospital admission and emergency room discharge, between catheterization room activation and catheterization room admission, between catheterization room admission and onset of PCU, Door-to-Balloon Time (D2B) in the experimental group was shorter than that in the control group, respectively (P＜0. 05). Conclusion In the emergency management of STEMI patients, the establishment of chest pain nurses are helpful to shorten the period first aid in hospital, improve the efficiency of emergency treatment. (目的 探讨专职胸痛护士在ST段抬高型心肌梗死(STEMI)患者急救中的作用。方法 基于胸痛中心建设要求, 通过在急诊室、导管室设立专职胸痛护士岗, 优化STEMI患者急救护理流程, 对流程优化前2019年1月—10月(对照组60例)和流程优化后2020年1月—10月(研究组58例)STEMI患者的相关救治节点时间进行比较。结果 研究组患者入门-抢救室接诊时间、入门-首份心电图诊断时间、接诊-肌钙蛋白抽血时间、肌钙蛋白抽血-肌钙蛋白报告时间、入门-离开急诊时间、导管室激活-到达导管室时间、到达导管室-PCI造影开始时间、门诊-首次球囊扩张(D2B)时间均短于对照组, 差异有统计学意义(P＜0. 05)。结论 在STEMI患者急救中, 设立专职胸痛护士有助于改善STEMI患者院内急救延误环节, 提高急救效率。)

Over a half million new cases of Head and Neck Squamous Cell Carcinoma (HNSCC) are diagnosed annually worldwide, however, 5 year overall survival is only 50% for HNSCC patients. Recently, high throughput technologies have accelerated the genome-wide characterization of HNSCC. However, comprehensive pipelines with statistical algorithms that account for HNSCC biology and perform independent confirmatory and functional validation of candidates are needed to identify the most biologically relevant genes. We applied outlier statistics to high throughput gene expression data, and identified 76 top-scoring candidates with significant differential expression in tumors compared to normal tissues. We identified 15 epigenetically regulated candidates by focusing on a subset of the genes with a negative correlation between gene expression and promoter methylation. Differential expression and methylation of 3 selected candidates (BANK1, BIN2, and DTX1) were confirmed in an independent HNSCC cohorts from Johns Hopkins and TCGA (The Cancer Genome Atlas). We further performed functional evaluation of NOTCH regulator, DTX1, which was downregulated by promoter hypermethylation in tumors, and demonstrated that decreased expression of DTX1 in HNSCC tumors maybe associated with NOTCH pathway activation and increased migration potential.