Various Regions Of China Research Articles

Investigation on the Cultural Characteristics of Ethnic and Folk Dances in Various Regions of China

Investigation on the Cultural Characteristics of Ethnic and Folk Dances in Various Regions of China

Morphological and Molecular Characterization of Paragonimus Species Isolated from Freshwater Crabs in Southern Yunnan, China.

Paragonimus species are highly prevalent in various regions of China. The study's objective is to isolate and identify Paragonimus from natural habitats and compare the phylogenetic diversity of Paragonimus in southern Yunnan province, China. Metacercariae of Paragonimus was isolated from crabs, and morphologic identification was performed by microscopy. Metacercariae were injected into experimental Paragonimus free Sprague Dawley rats. After 114 days, adult worms and eggs were isolated from multiple organs. Morphologic identification confirmed the initial identification. DNA was extracted from 5 adult worms, and molecular characterization was performed by amplification and sequencing of CO1 and ITS2 regions, followed by phylogenetic analysis. Out of 447 crabs captured, 186 crabs were found to be infected. A total of 4 species of Paragonimus was observed from naturally infected crabs. Paragonimus microrchis (2), Paragonimus heterotremus (1), Paragonimus proliferus (1), and Paragonimus skrjabini (1) were isolated and identified. A total of 32 sequences were downloaded from the National Center for Biotechnology Information, and 5 sequences generated in the study were used for phylogenetic analysis. In the phylogenetic tree of the CO1 gene, Paragonimus proliferus, Paragonimus heterotremus, and Paragonimus skrjabini were clustered with the same species, and the confidence values of their branches were >95%. A congruent phylogenetic relationship was observed with the ITS2 phylogenetic tree. In the phylogenetic tree constructed with the combined dataset of CO1 and ITS2 datasets, Paragonimus proliferus, Paragonimus heterotremus, and Paragonimus skrjabini clustered with the same species, and their branch confidence values were >94%. Paragonimus microrchis clustered with Paragonimus bangkokensis in both datasets. Phylogenetic analysis revealed robustness of the double loci method as against the single-locus method with either CO1 or ITS2 alone. Paragonimus species isolated from the southern Yunnan province, China, was phylogenetically diverse, and the analysis revealed the clustering of multiple species of Paragonimus isolated from different geographic locations.

Experiences of Autonomy in Marriage and Divorce Within the Chinese Traditional System

The Chinese traditional system features a hierarchical familial culture. When confronted with individualization and autonomy in choices of marriage and divorce, the system remains resilient and intervenes in the lives of young families. To analyze the discourses of divorced urban young adults, 46 participants (23 women and 23 men) aged 24–39 years were recruited from various regions in China. Through an analysis of the stressors involved in marriage and divorce, the concrete values and the conceptions shared in a unitary system of traditions were elicited. The promise of stability in a marriage was the appeal of this system while the focus on offspring was the general interest with evolutionary elements that justify this system. The concept of the individual autonomy of divorce grew from marital experiences and would be confined to the traditional system if its appeal remains unchallenged.

Current Situation and Development Trend of Urban Traffic Engineering Management

With the continuous progress of social civilization and the development of the times, the industrial economy and people's living conditions in various regions of China have changed with each passing day in recent years. Relevant state departments have also paid more attention to the transportation industry. As the core of economic development, urban transportation projects are more complex than those in township areas and have higher requirements for managers. With the improvement of people's quality of life, the modes of transportation have become diverse. To ensure that all parts of the city can be carried out in an orderly manner and provide people with more unobstructed transportation facilities, we should constantly keep up with the pace of development of the times and improve the urban traffic engineering management. In this paper, the author mainly analyzes the current situation of urban traffic engineering management, and puts forward a series of effective measures to promote the development of urban traffic management.

Dlhawksworthia flavoparmeliae sp. nov., a new endolichenic fungus in Phaeosphaeriaceae

The genus Dlhawksworthia presently includes three species. All the previously described species have been isolated from plants. Besides, none of these three species have ever been recorded in China. We conducted surveys in various regions of China to isolate and identify endolichenic fungi associated with diverse lichen species. During these surveys, we isolated both previously known and undescribed fungi associated with lichens. Among these, there was an isolate of an unknown fungus. The morphological and molecular analyses indicated that this isolate represented a new species from the genus Dlhawksworthia. As a consequence, we described this fungus as Dlhawksworthia flavoparmeliae sp. nov. This is the first report of Dlhawksworthia isolated from a lichen in China and globally.

Geographic Origin Discrimination of Millet Using Vis-NIR Spectroscopy Combined with Machine Learning Techniques.

Millet is a primary food for people living in the dry and semi-dry regions and is dispersed within most parts of Europe, Africa, and Asian countries. As part of the European Union (EU) efforts to establish food originality, there is a global need to create Protected Geographical Indication (PGI) and Protected Designation of Origin (PDO) of crops and agricultural products to ensure the integrity of the food supply. In the present work, Visible and Near-Infrared Spectroscopy (Vis-NIR) combined with machine learning techniques was used to discriminate 16 millet varieties (n = 480) originating from various regions of China. Five different machine learning algorithms, namely, K-nearest neighbor (K-NN), Linear discriminant analysis (LDA), Logistic regression (LR), Random Forest (RF), and Support vector machine (SVM), were used to train the NIR spectra of these millet samples and to assess their discrimination performance. Visible cluster trends were obtained from the Principal Component Analysis (PCA) of the spectral data. Cross-validation was used to optimize the performance of the models. Overall, the F-Score values were as follows: SVM with 99.5%, accompanied by RF with 99.5%, LDA with 99.5%, K-NN with 99.1%, and LR with 98.8%. Both the linear and non-linear algorithms yielded positive results, but the non-linear models appear slightly better. The study revealed that applying Vis-NIR spectroscopy assisted by machine learning technique can be an essential tool for tracing the origins of millet, contributing to a safe authentication method in a quick, relatively cheap, and non-destructive way.

Multiscale Simulation of Precipitation Over East Asia by Variable Resolution CAM‐MPAS

AbstractThis study evaluates the precipitation over East Asia simulated by the variable resolution CAM‐MPAS featuring the Model for Prediction Across Scales (MPAS) atmospheric dynamical core coupled with the physics parameterizations of the Community Atmosphere Model (CAM) version 5.4. Two CAM‐MPAS experiments, one with a global quasi‐uniform resolution mesh of 120 km (MPAS‐UR) and the other with a variable resolution mesh of 30–120 km refined over East Asia (MPAS‐VR), are conducted from 1989 to 2005 following the Atmospheric Model Intercomparison Project protocol. Two regional climate model simulations at ∼25 km resolution from the Coordinated Regional Downscaling Experiment East Asia second plan are also analyzed for comparison. Results show that CAM‐MPAS performs better than the selected regional models in simulating the precipitation climatology over East Asia. Compared with MPAS‐UR, MPAS‐VR with refinement over East Asia better simulates the precipitation over and around the Tibetan Plateau (TP), the upper‐level circulation, the precipitation frequency and intensity in various regions of China, and the interannual precipitation pattern associated with the East Asian summer monsoon. Both decreased grid spacing and the use of finer‐scale terrain information contribute to the improvements in MPAS‐VR relative to MPAS‐UR. However, decreased grid spacing is more essential for simulating the precipitation magnitude over TP and the location of peak precipitation south of TP, likely due to the better resolved physical and dynamical processes associated with orographic precipitation. The 30–120 km CAM‐MPAS model is shown to be a promising tool for precipitation simulation over East Asia.

Spatio-Temporal Patterns of CO2 Emissions and Influencing Factors in China Using ESDA and PLS-SEM

Controlling carbon dioxide (CO2) emissions is the foundation of China’s goals to reach its carbon peak by 2030 and carbon neutrality by 2060. This study aimed to explore the spatial and temporal patterns and driving factors of CO2 emissions in China. First, we constructed a conceptual model of the factors influencing CO2 emissions, including economic growth, industrial structure, energy consumption, urban development, foreign trade, and government management. Second, we selected 30 provinces in China from 2006 to 2019 as research objects and adopted exploratory spatial data analysis (ESDA) methods to analyse the spatio-temporal patterns and agglomeration characteristics of CO2 emissions. Third, on the basis of 420 data samples from China, we used partial least squares structural equation modelling (PLS-SEM) to verify the validity of the conceptual model, analyse the reliability and validity of the measurement model, calculate the path coefficient, test the hypothesis, and estimate the predictive power of the structural model. Fourth, multigroup analysis (MGA) was used to compare differences in the influencing factors for CO2 emissions during different periods and in various regions of China. The results and conclusions are as follows: (1) CO2 emissions in China increased year by year from 2006 to 2019 but gradually decreased in the eastern, central, and western regions. The eastern coastal provinces show spatial agglomeration and CO2 emission hotspots. (2) Confirmatory analysis showed that the measurement model had high reliability and validity; four latent variables (industrial structure, energy consumption, economic growth, and government management) passed the hypothesis test in the structural model and are the determinants of CO2 emissions in China. Meanwhile, economic growth is a mediating variable of industrial structure, energy consumption, foreign trade, and government administration on CO2 emissions. (3) The calculated results of the R2 and Q2 values were 76.3% and 75.4%, respectively, indicating that the structural equation model had substantial explanatory and high predictive power. (4) Taking two development stages and three main regions as control groups, we found significant differences between the paths affecting CO2 emissions, which is consistent with China’s actual development and regional economic pattern. This study provides policy suggestions for CO2 emission reduction and sustainable development in China.

Path of Smart Servitization and Transformation in the Textile Industry: A Case Study of Various Regions in China

This study uses 31 provinces and municipalities from China’s textile industry as a research sample and divides the region into four geographical areas: eastern, central, western, and northeastern. It quantified smart servitization in the textile industry using input–output data and applied the fuzzy set qualitative comparison analysis to identify potential pathways for promoting smart servitization in the textile industry. The study’s findings indicate that there are significant geographical differences in the level of smart servitization in the textile industry across China. Moreover, the transformation and development of the textile industry require the co-operation of numerous factors, and the Chinese textile industry’s transformation paths can be summarized as “high-input” path, “technology—aggregation” path, “open” path, and “economic-agglomeration” path.

The Impact of Outward Foreign Direct Investment on Carbon Emission toward China’s Sustainable Development

It is of practical significance to evaluate whether enhancing outward foreign direct investment (OFDI) can promote carbon mitigation under the new urbanization background toward China’s sustainable development and carbon neutrality. The impact of OFDI on carbon emissions is investigated from the dual perspectives of the urbanization threshold and the mediating path by using panel data from China’s 30 provinces during the period of 2003–2015 and considering both population and land. The results show that there is a significant impact from interprovincial OFDI on CO2 emissions with the double threshold effect of urbanization, and that OFDI expansion will increase CO2 emissions with urbanization; however, the different stages of urbanization show inverted U-shaped characteristics that first rise and then fall. The optimization of industrial structures has not passed the mediating effects test during the sample period, while the rationalization of the industrial structure provides a mediating effect in the primary stage of urbanization and a suppressing effect in the high level stage of urbanization. Import dependence only shows a masking effect in the intermediate stage of urbanization, while the technical level shows an intermediary effect in the primary stage of urbanization and a masking effect in the intermediate stage. The intensification of OFDI has brought different effects on economic and social production in various regions of China under urbanization, which has further affected regional carbon emissions. Discussing these effects would help to provide constructive suggestions for the regional coordination of development, new urbanization construction and urban low carbon transformation.

Dynamical Seasonal Prediction of Tropical Cyclone Activity Using the FGOALS-f2 Ensemble Prediction System

AbstractThere is a distinct gap between tropical cyclone (TC) prediction skill and the societal demand for accurate predictions, especially in the western Pacific (WP) and North Atlantic (NA) basins, where densely populated areas are frequently affected by intense TC events. In this study, seasonal prediction skill for TC activity in the WP and NA of the fully coupled FGOALS-f2 V1.0 dynamical prediction system is evaluated. In total, 36 years of monthly hindcasts from 1981 to 2016 were completed with 24 ensemble members. The FGOALS-f2 V1.0 system has been used for real-time predictions since June 2017 with 35 ensemble members, and has been operationally used in the two operational prediction centers of China. Our evaluation indicates that FGOALS-f2 V1.0 can reasonably reproduce the density of TC genesis locations and tracks in the WP and NA. The model shows significant skill in terms of the TC number correlation in the WP (0.60) and the NA (0.61) from 1981 to 2015; however, the model underestimates accumulated cyclone energy. When the number of ensemble members was increased from 2 to 24, the correlation coefficients clearly increased (from 0.21 to 0.60 in the WP, and from 0.18 to 0.61 in the NA). FGOALS-f2 V1.0 also successfully reproduces the genesis potential index pattern and the relationship between El Niño–Southern Oscillation and TC activity, which is one of the dominant contributors to TC seasonal prediction skill. However, the biases in large-scale factors are barriers to the improvement of the seasonal prediction skill, e.g., larger wind shear, higher relative humidity, and weaker potential intensity of TCs. For real-time predictions in the WP, FGOALS-f2 V1.0 demonstrates a skillful prediction for track density in terms of landfalling TCs, and the model successfully forecasts the correct sign of seasonal anomalies of landfalling TCs for various regions in China.

Ensemble Projection of Extreme Precipitation Over China Based on Three Dynamical Downscaling Simulations

Based on the outputs of the global climate models (GCMs) HadGEM2-ES, NorESM1-M and MPI-ESM-LR from Coupled Model Intercomparison Project Phase 5 (CMIP5) and the downscaling results with the regional climate model (RCM) REMO, the ability of the climate models to reproduce the extreme precipitation in China during the current period (1986–2005) is evaluated. Then, the future extreme precipitation in the mid (2036–2065) and the late 21st century (2066–2095) is projected under the RCP8.5 scenario. The results show that the RCM simulations have great improvements compared with the GCMs, and the ensemble mean of the RCM results (ensR) outperforms each single RCM simulation. The annual precipitation of the RCM simulations is more consistent with the observation than that of the GCMs, with the overestimation of the peak precipitation reduced, and the ensR further reduces the bias. For the extreme precipitation, the RCM simulations significantly decrease the underestimation of intensity in the GCMs. The RCM simulations and the ensR can greatly improve the simulations of Rx5day and CWD compared with the GCMs, decreasing the wet bias in North China and Northwest China. In the future, the consecutive dry days (CDD) will decrease in the northern arid regions, especially in North China and Northeast China. However, the southern regions will experience longer dry period. Both the amount and the intensity of precipitation will increase in various regions of China. The number of wet days will decrease in the south and increase in the north area. The significantly greater Rx5day and R95t indicate more intensive extreme precipitation in the future, and the intensity in the late 21st century will be stronger than that in the middle. Attribution analysis indicates that the extreme precipitation indices especially the R95t have significant positive temporal and spatial correlations with the water vapor flux.

Soil Organic Carbon Enrichment Triggers In Situ Nitrogen Interception by Phototrophic Biofilms at the Soil-Water Interface: From Regional Scale to Microscale.

Phototrophic biofilms are easy to grow at sediment/soil-water interfaces (SWIs) in shallow aquatic ecosystems and greatly impact nutrient biogeochemical cycles. However, the pathways by which they contribute to nitrogen interception and interact with sediment/soil remains largely unknown. Here, we conducted a field investigation in paddy fields in various regions of China and found that nitrogen immobilized in biofilm biomass significantly positively correlated with soil organic carbon (SOC) content. A microcosm experiment showed that this was due to increased bacterial and algal diversity, biomass accumulation, and inorganic nitrogen assimilation at high SOC, especially high dissolved organic carbon (DOC) levels. The metatranscriptomics results further verified that many KO groups of PSII, PSI, AP, and PC in antenna proteins and glutamate synthesis were distinctly expressed at elevated SOC and DOC levels. Our results elucidated the effects and possible pathways of how SOC enrichment triggers photosynthesis and nitrogen immobilization by phototrophic biofilms. The results will provide meaningful information for in situ nitrogen interception by using phototrophic biofilms at the SWI in human-made wetlands to change internal nitrogen cycling.

Stakeholder efforts to mitigate antiretroviral therapy interruption among people living with HIV during the COVID-19 pandemic in China: a qualitative study.

IntroductionThe COVID‐19 pandemic has affected antiretroviral therapy (ART) continuity among people living with HIV (PLHIV) worldwide. We conducted a qualitative study to explore barriers to ART maintenance and solutions to ART interruption when stringent COVID‐19 control measures were implemented in China, from the perspective of PLHIV and relevant key stakeholders.MethodsBetween 11 February and 15 February 2020, we interviewed PLHIV, community‐based organization (CBO) workers, staff from centres for disease control and prevention (CDC) at various levels whose work is relevant to HIV care (CDC staff), HIV doctors and nurses and drug vendors from various regions in China. Semi‐structured interviews were conducted using a messaging and social media app. Challenges and responses relevant to ART continuity during the COVID‐19 pandemic were discussed. Themes were identified by transcript coding and mindmaps.ResultsSixty‐four stakeholders were recruited, including 16 PLHIV, 17 CBO workers, 15 CDC staff, 14 HIV doctors and nurses and two drug vendors. Many CDC staff, HIV doctors and nurses responsible for ART delivery and HIV care were shifted to COVID‐19 response efforts. Barriers to ART maintenance were (a) travel restrictions, (b) inadequate communication and bureaucratic obstacles, (c) shortage in personnel, (d) privacy concerns, and (e) insufficient ART reserve. CBO helped PLHIV maintain access to ART through five solutions identified from thematic analysis: (a) coordination to refill ART from local CDC clinics or hospitals, (b) delivery of ART by mail, (c) privacy protection measures, (d) mental health counselling, and (e) providing connections to alternative sources of ART. Drug vendors contributed to ART maintenance by selling out‐of‐pocket ART.ConclusionsSocial and institutional disruption from COVID‐19 contributed to increased risk of ART interruption among PLHIV in China. Collaboration among key stakeholders was needed to maintain access to ART, with CBO playing an important role. Other countries facing ART interruption during current or future public health emergencies may learn from the solutions employed in China.

Performance and risk of energy industrial firms with stock pledge in China

We investigate the effect of stock pledges on the firms' performance and risk in energy industry of China. The results show that the performance of firms decreases in the existence of stock pledge. Stock pledge generally decreases stock return volatility, except for the increase in forced liquidation pressure. Stock pledge increases downside risk and crashes. Finally, we demonstrate the different effects of the stock pledge in various regions of China.

An assessment of Planet satellite imagery for county-wide mapping of rice planting areas in Jiangsu Province, China with one-class classification approaches

ABSTRACT There is a growing demand of the spatial distribution of major crops at the field level in recent years for the precision management of farmlands in developing countries. However, most previous studies used low or medium resolution images (e.g. Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat) to map the planting areas of rice in various regions of China. As a new source of satellite imagery, the 3 m Planet satellite imagery with daily revisit frequency has rarely been used for mapping crop types. In particular, it is still unclear how well the Planet imagery would perform in mapping the rice planting areas in the Lower Reaches of the Yangtze River Plain of China where image acquisition is strongly limited by rainy and cloudy weather conditions. To overcome the spectral confusion between rice and non-rice vegetation types, this study proposed one-class classification approaches with Planet imagery from the early and late seasons of rice crops over three counties (Guanyun, Rugao and Wujiang) across Jiangsu Province in eastern China. Apart from the traditional use of mono-temporal imagery from the late season (Strategy I), we developed two strategies to make use of the bi-temporal imagery from the early and late seasons, with one being direct classification using stacked images (Strategy II) and the other being stepwise classification (Strategy III). All classifications were performed with the popular machine learning classifier one-class support vector machine (OCSVM) and evaluated from the aspects of classification accuracy and area estimation accuracy. The results showed Strategy I could achieve an overall classification accuracy of 83.02% and kappa coefficient (ƙ) of 0.65. The overall accuracy (OA) can be significantly improved by Strategy II (OA = 84.44% and ƙ = 0.69) and further by Strategy III (OA = 90.42% and ƙ = 0.81). In terms of area estimation, the estimates from Strategy III were consistent with the government reported statistical data with a relative error (RE) within 10% at the county level. At the town level, the correspondence between Planet-derived rice planting areas and the Landsat-8 derived reference data was significantly improved with Strategy III as compared to the other two for Guanyun and Wujiang. The stepwise classification approach (Strategy III) developed with Planet imagery has great values in monitoring rice paddies over the regions with fragmentized distribution of rice fields.

Analysis of the Role of General Practitioners Services in Rural Areas during the COVID-19 Epidemic

Since the outbreak of the COVID-19, various regions of China have been rapidly deployed under the leadership of the Central Committee of the Party to actively prevent and control the COVID-19. The rural areas of my country have weak links to the prevention and management of public health emergencies. Problems include lack of medical and health resources and farmers’ low awareness of epidemic prevention. Situations that correspond to the prevention and management of the COVID-19 are more serious. As the patient’s first contact and “gatekeeper” in the fight against the epidemic, the general practitioner is responsible for the “first visit-subsequent ongoing intervention”. This article is about the prevention and control of the COVID-19 epidemics and epidemic prevention in terms of dissemination of knowledge, informed crowd control, joint prevention and control, and standardized management of people. This is a summary of the efforts of general practitioners. Quarantine at home, interactive referrals to medical consortiums, special care for contracted families. The function during the management period aims to analyze the role played by general practitioners during the epidemic and to provide new ideas for the prevention and management of the epidemic. Provide more targeted general practitioner-style services in rural areas to promote the implementation and improvement of health and poverty alleviation. The health level of the rural population provides a theoretical standard.

An Empirical Study on Scientific Research Performance of Universities in Different Regions of China Based on PCA and Malmquist Index Method

This paper uses principal component analysis (PCA) and entropy method to construct the evaluation index system of the scientific research performance of universities in 31 provinces and cities in China. Based on the traditional DEA model, the development trend of the scientific research performance of the research objects from 2015 to 2019 is dynamically evaluated by the Malmquist index method. The results show that the scientific research performance of universities in various regions of China is not ideal, and the level of scientific research performance is declining. The total factor productivity of scientific research in the central and western regions is much higher than that in the eastern region. The main factor that hinders the improvement of scientific research performance is the efficiency of technological progress. Finally, aiming at the existing problems, some feasible suggestions are put forward to further improve the input-output efficiency of scientific research in universities.

Intelligent Monitoring Analysis of Power Grid Monitoring Information Based on Big Data Mining

With the rapid economic progress of various regions in China, the demand for electricity is also gradually increasing. In order to effectively solve this problem, we increase the coverage of the grid and the upper limit of power consumption. This has not only led to the economic development of some regions. Big data analysis technology has also been widely used [1]. However, the increase of power consumption also increases the burden of power grid staff. The working pressure of intelligent monitoring system of power grid monitoring information is also increased. In order to simplify the process of power grid information monitoring, data mining technology will be applied to the construction of intelligent monitoring system. According to the theory of power grid inspection, big data information monitoring technology can monitor the operation of power grid in real time. This paper briefly analyzes the current power grid information monitoring problems. This paper puts forward the structure design of power grid monitoring information system based on data mining. Finally, this paper proposes an effective data mining information monitoring algorithm.

The Chinese Thoracic Oncology Group (CTONG) therapeutic option scoring system: a multiple-parameter framework to assess the value of lung cancer treatment options.

BackgroundCurrently, there is no standard context that conforms to the Chinese national framework for evaluating medical decisions regarding the treatment of lung cancer.MethodsThis draft was formulated after a systematic review and a focus group discussion among 20 experts, who were senior physicians with extensive clinical experience from the Chinese Thoracic Oncology Group (CTONG) task force. Subsequently, a draft and a five-point Likert scale were sent to 300 CTONG working group members. These were modified according to feedback from a four-round modified Delphi approach. Hence, the first version of the ‘Therapeutic option of lung cancer: CTONG scoring system’ was formulated. Afterward, a corresponding questionnaire was designed to collect opinions on the weight allocation of various indicators. This was issued through the WeChat platform, “Oncology News” application and e-mails from October 23, 2020, to November 25, 2020. Participants from numerous occupations in cancer-related fields from various regions of China were included in the study. Overall and subgroup analyses regarding weight allocations were performed. The differences between participant-allocated and reference weights were considered to adjust the framework.ResultsThe framework contained four aspects and six indicators, including efficacy [progression-free survival (PFS)/overall survival (OS) and subsequent treatment], safety [treatment-related severe adverse event (SAE), dose adjustment], quality of life (Qol), and compensation. The reference weights were 50%, 5%, 10%, 5%, 10%, and 20% for each indicator. By November 25, 2020, 1,043 valid questionnaires had been obtained. The majority of the questionnaires were completed by physicians (86.5%). Subgroup analysis among the various groups showed an overall consistent trend. Besides, significant differences between the participant-allocated and reference weights were found among PFS/OS (difference: −11.5%), compensation (difference: −10.1%), and subsequent treatment (difference: 9.7%) indicators. After discussion, the final weight allocations were set at 45%, 10%, 15%, 5%, 10%, and 15% for PFS/OS, subsequent treatment, treatment-related SAE, dose adjustment, Qol, and compensation, respectively.ConclusionsThe CTONG scoring system, as an objective evaluation model that involves multiple parameters, is a breakthrough method for evaluating the therapeutic value of lung cancer treatment options in China, which is worthy of further verification in future clinical practice.