[Research advance on quantitative assessment methods of ecosystem water conservation service functions]. / ç”Ÿæ€ç³»ç»Ÿæ°´æºæ¶µå »æœåŠ¡åŠŸèƒ½å®šé‡è¯„ä¼°æ–¹æ³•ç ”ç©¶è¿›å±•.

The water conservation service function, which is one of the most important ecological service function in the regional system, directly reflects the regulation role of a region in precipitation, the redistribution function of precipitation, and the ecohydrological value. With the development of the comprehensive evaluation method and the deepening of research on water conservation service function, relevant evaluation calculation process has changed significantly. Nowadays, in the assessment of the water conservation service function, it is necessary not only to calculate and evaluate relevant indicators, but also to localize specific parameters in the model and analyze the effectiveness of the overall model for specific study areas. However, the current literature review lacks systematic summaries of model evaluation methods. Meanwhile, the review is also insufficient on model validity verification and significance analysis methods, the result verification and applicability analysis methods such as parameter localization in water conservation studies. We reviewed the research advance on typical ecosystem water conservation ser-vice assessment methods with a specific focus on the model assessment methods that have developed rapidly in recent years. At the same time, we summarized methods commonly used for parameter localization, as well as validity testing and sensitivity analysis of simulation results, and discussed existing problems and future directions in this field.

Simultaneous removal of antibiotic resistance genes and improved dewatering ability of waste activated sludge by Fe(II)-activated persulfate oxidation.

Waste activated sludge properties vary widely with different regions due to the difference in living standards and geographical distribution, making a big challenge to developing a universally effective sludge dewatering technique. The Fe(II)-activated persulfate (S2O82-) oxidation process shows excellent ability to disrupt sludge cells and extracellular polymeric substances (EPS), and release bound water from sludge flocs. In this study, the discrepancies in the physicochemical characteristics of sludge samples from seven representative cities in China (e.g., dewaterability, EPS composition, surface charge, microbial community, relative abundance of antibiotic resistance genes (ARGs), etc.) were investigated, and the role of Fe(II)-S2O82- oxidation in enhancing removal of antibiotic resistance genes and dewatering ability were explored. The results showed significant differences between the EPS distribution and chemical composition of sludge samples due to different treatment processes, effluent sources, and regions. The Fe(II)-S2O82- oxidation pretreatment had a good enhancement of sludge dewatering capacity (up to 76 %). Microbial analysis showed that the microbial community in each sludge varied significantly depending on the types of wastewater, the wastewater treatment processes, and the regions, but Fe(II)-S2O82- oxidation was able to attack and rupture the sludge zoogloea indiscriminately. Genetic analysis further showed that a considerable number of ARGs were detected in all of these sludge samples and that Fe(II)-S2O82- oxidation was effective in removing ARGs by higher than 90 %. The highly active radicals (e.g., SO4-·, ·OH) produced in this process caused drastic damage to sludge microbial cells and DNA stability while liberating the EPS/cell-bound water. Co-occurrence network analysis highlighted a positive correlation between population distribution and ARGs abundance, while variations in microbial communities were linked to regional differences in living standards and level of economic development. Despite these variations, the Fe(II)-S2O82- oxidation consistently achieved excellent performance in both ARGs removal and sludge dewatering. The significant modularity of associations between different microbial communities also confirms its ability to reduce horizontal gene transfer (HGT) by scavenging microbes.

Research on the potential for China to achieve carbon neutrality: A hybrid prediction model integrated with elman neural network and sparrow search algorithm.

China's carbon reduction is of substantial significance in combating global climate change. In the context of the COVID-19 epidemic hit and economic and social development uncertainty, this study intends to discover whether China can attain the strategic destination of carbon peaking by 2030 and carbon neutrality by 2060 on schedule. Toward this aim, the grey relation analysis (GRA) is applied to filter the elements influencing carbon emissions to downgrade the dimensionality of indicators. A hybrid prediction is proposed integrated with Elman neural network (ENN) and sparrow search algorithm (SSA) to explore the potential for China to carbon neutrality from 2020 to 2060. The results reveal eight elements including GDP per capita, population, urbanization, total energy consumption and others are highly correlated with carbon emissions. China has a good chance of carbon peaking from 2028 to 2030, with a value of 11568.6-12330.5 Mt, while only one scenario can achieve carbon neutrality in 2060. In the neutral scenario, China should reach a proportion of renewable energy exceeding 80%, the urbanization rate reaching 85% and energy consumption controlling within 6.5 billion tons. A set of countermeasures for carbon abatement are presented to facilitate the implementation of carbon neutrality strategy.

Innovation Network Reconfiguration Makes Infrastructure Megaprojects More Resilient.

Innovation management of infrastructure megaprojects is a challenging task. There are many risks in the process of innovation in engineering technology, such as shortage of funds, policy fluctuations, and difficulties in the transformation of achievements. Meanwhile, innovation organizations involve multiple participants, which makes cooperation complicated. Therefore, resilient innovation is proposed and considered as a tool that can optimize innovation management. The resilience of innovation depends largely on partnerships at the organizational level, which is rarely explored in current studies. This research aims to examine the relationship between organizational resilience and innovation network characteristics. Based on a survey of 164 participants in infrastructure innovation projects, the structural equation model (SEM) is used to explore the factors that influence organizational resilience. The findings show that there is a positive correlation between network characteristics and organizational resilience. Furthermore, the strength of network connections has a direct impact on the preventive and resistance ability of resilience. Network heterogeneity has an impact on the dual ability of resilience. Finally, a case study of the Qinghai-Tibet Railway innovation network shows that based on the above influence paths, we can find a strategy to reconstruct the network to improve resilience.

Application of Mathematical Models in Economic Variable Input and Output Models under the Scientific Visualization.

At present, with the development of society and economy, some new problems have emerged continuously. Among them, the more serious problem is that enterprises pay too much attention to economic benefits, which leads to problems in the development of many enterprises. Therefore, the problem caused by too much emphasis on economic benefits is one of the major economic problems. After this problem, our country's economy began to focus on economic input and output in the subsequent development process. And, related personnel have also studied the economic input-output technology and model, which is an economic quantitative analysis method that has been widely used in various aspects of the economic field since its emergence. This paper firstly elaborates the theoretical knowledge involved, such as economic data, economic variables, and visualization techniques. Secondly it analyzes the application of scientific visualization techniques in the processing of economic variable data, which includes the techniques of preprocessing, mapping, drawing, and displaying the data. Finally, this paper investigates the application of mathematical models in economic variables input and output and the application of mathematical models in economic research, which can help us to better understand and use the knowledge of economics, thus providing strong support for solving practical problems. Also, this helps people to understand and grasp more about the macroarea, microaspect, and even the country as a whole.

Quantitative assessment of iron in heart and liver phantoms using dual-energy computed tomography.

The aim of the present study was to determine the correlation between dual-energy computed tomography (DECT) Hounsfield units (HU) and iron concentration, as well as the correlation between HU and magnetic resonance imaging (MRI)-derived R2* values, in phantoms of the heart and liver tissue. Phantoms were constructed containing pig heart or liver tissue and varying concentrations of iron (0.1, 5, 10, 15, 20 and 25 mg/ml). The phantoms were then examined by DECT and MRI. Linear regression analysis was used to determine the correlations between HU and iron concentration and HU and R2* values. The HU value of DECT increased with increasing iron concentrations in the liver and heart phantoms in a linear manner. The slope of the HU value change against iron concentration revealed that ΔH80-140 provided a better discernment of iron concentration as compared with ΔH100-140. The derived R2 values were all >0.9 for the associations of DECT and MRI measurements with iron concentrations. Therefore, DECT may be used for the determination of iron concentration in the liver and heart tissue, with the results correlating with those obtained with MRI.

Nitroglycerine use in transcatheter arterial (chemo)embolization in patients with hepatocellular carcinoma and dual-energy CT assessment of Lipiodol retention.

OBJECTIVES: To investigate whether the addition of nitroglycerine to transcatheter arterial (chemo)embolization (TAE/TACE) can increase the delivery and effectiveness of TAE/TACE in patients with hepatocellular carcinoma (HCC) by dual-energy CT. METHODS: HCC patients (BCLC stage A or B) were randomized to (n = 51) or not to (n = 50) receive nitroglycerine and an emulsion of Lipiodol with or without doxorubicin, followed by embolization with Gelfoam pledgets. Dual-energy CT was performed pre- and 1 to 3 months post-embolization to assess changes in tumour diameter and Lipiodol levels in tumours. RESULTS: Median tumour diameter decreased from baseline in both groups with and without nitroglycerine (7.11 % vs. 12.5 %, respectively), and was statistically significant in the group receiving nitroglycerine (P = 0.023). There was no difference between the two groups in disease response (P = 0.237). The concentration and percentage of Lipiodol retained in tumours were significantly greater in patients treated with nitroglycerine compared to those without (median concentration 15.05 mg/mL vs. 4.40 mg/mL, respectively, P < 0.001; median percentage 82.01 % vs. 36.75 %, respectively, P < 0.001). CONCLUSIONS: Nitroglycerine increased delivery of the Lipiodol emulsion via TAE/TACE to HCC tumours with significant tumour reduction. Dual-energy CT can accurately quantify the amount of Lipiodol deposited in tumours. KEY POINTS: • Nitroglycerine improves delivery of tumour-targeted therapy via enhanced permeability and retention. • In hepatocellular carcinoma, nitroglycerine added to TAE/TACE showed greater tumour reduction. • Dual-energy CT can reliably quantify the amount of Lipiodol in TAE/TACE.