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Sustainable development, intimately linked to the survival of the global human population, has garnered immense attention. The rapid pace of urbanization has exerted a profound influence on the achievement and progress towards the United Nations’ Sustainable Development Goals (SDGs). Nevertheless, a knowledge gap persists regarding the comprehensive impact of urbanization on these goals. The present study delved into the multifaceted impacts of urbanization on SDGs through a comprehensive analysis of four distinct urbanization dimensions: land urbanization (LURB), economic urbanization (EURB), population urbanization (PURB), and social urbanization (SURB). We analyzed the spatiotemporal characteristics of the four-dimensional urbanizations in 31 provinces of China from 1995 to 2015 using impervious surface and statistical data. We employed the Spearman coefficient to investigate the interaction between urbanizations and 17 SDGs. Furthermore, we delved into how economic zone settings influenced these interactions. The results reveal that land expansion, GDP per capita, and the degree of social consumption exhibited stronger synergies with SDGs, whereas the share of the secondary sector and the urban population rate demonstrated more trade-off effects. This underscores the importance of considering the multifaceted nature of urbanization when striving to achieve the SDGs. Additionally, the diverse impact of urbanization patterns on SDG implementation across various economic zones emphasizes the need for tailored and region-specific strategies to maximize the positive outcomes of urbanization and promote sustainable development.

BackgroundThe evaluation of melanoma incidence and mortality trends based on population characteristics, with a particular focus on sex differences, is of utmost importance.MethodsThe gender-stratified analysis of melanoma mortality across various calendar years was conducted. Utilizing the Joinpoint software, we detected alterations in the incidence rates and delineated the mortality trends.ResultsMelanoma’s incidence-based mortality exhibited a rising trajectory between 2005 and 2010, characterized by an annual percent change (APC) of 2.95%. However, there was a significant decrease in mortality from 2015 to 2019, with an APC of -4.39%. Notably, the mortality among men decreased by about 5.84% between 2015 and 2019, while there was no significant downward trend in the mortality rate among women. Subsequent analysis revealed no statistically significant variation in the 2-year survival rate of female patients aged 45-54 years among different age groups (Z=-0.775, p >0.1).ConclusionsBetween 2015 and 2019, against the backdrop of stable melanoma incidence rates in the United States, there was a significant decline in mortality. Our analysis suggests that the utilization of immunotherapy may account for the observed reduction in mortality, with particularly notable benefits for male patients. However, female patients, especially younger women, did not derive significant advantages.

To attain sustainable development goals and understand urban growth patterns, continuous and precise monitoring of built-up area heights is essential. This helps reveal how urban form evolution impacts the thermal environment. Previous research often used isolated images, ignoring the temporal dimension of thermal infrared and reflectance data from Landsat sensors. Additionally, cost-effective and efficient methods for reconstructing time-series built height are lacking. To fill this knowledge gap, we utilized Landsat time-series data to reconstruct the yearly trends in urban form in Beijing, China, spanning from 1990 to 2020. Continuous Change Detection and Classification (CCDC) time series analysis method was used to identify urban growth and renewal years. Employing a reference height for 2020 and logical reasoning method, we reconstructed the annual dynamics of built-up heights, pinpointing years of significant change. Finally, we analyzed the alterations in urban form over the past three decades and their impact on surface temperature changes. Our change detection method achieved an overall accuracy of 86 %, demonstrating its effectiveness in determining the year of change. When compared with data from Lianjia and LiDAR point cloud, our height reconstruction method showed impressive accuracy, with R2 values of 0.9773 and 0.9526, respectively. Analysis of summer and winter LST values revealed distinct temperature patterns across different building heights, with mid-rise buildings exhibiting the highest LST in summer and low-rise buildings registering the highest LST in winter. During periods of urban growth, both mean and amplitude values of LST increased, while during urban renewal (demolition), they decreased. The date of annual temperature peaks advanced during urban growth but delayed during urban renewal (demolition). Our time series analysis framework offers a new method for understanding the yearly dynamics of urban form and its influence on surface temperature, with potential applications in carbon emission and urban climate modeling studies.

Background: Given that only a small subset of patients with advanced non-small-cell lung cancer (aNSCLC) benefit from immune checkpoint inhibitors (ICIs), the effectiveness of ICIs is often compromised by the complex interplay within the tumor microenvironment (TME). Objectives: To identify predictive biomarkers associated with ICI resistance at a multi-omics spatial level. Design: A total of eight aNSCLC patients who received first-line anti-programmed cell death protein-1 (PD-1) monoclonal antibody camrelizumab at Shandong Cancer Hospital and Institute between 2021 and 2022 were included in the discovery cohort. An additional validation cohort of 45 samples from camrelizumab-treated aNSCLC patients was also enrolled. Methods: NanoString GeoMx ® digital spatial profiling was conducted at the transcriptomic and proteomic level within pan-cytokeratin (panCK + ), CD45 + , and CD68 + compartments. For validation, multiplex immunofluorescence (mIF) staining was performed. Results: Distinct spatial expression patterns and levels of immune infiltration were observed between tumor and leukocyte compartments. Higher CD34 expression in the macrophage compartment correlated with poorer prognosis and response to camrelizumab ( p

Abstract Background Nowadays, cancer and cardiac diseases are two of the most causes of death, so cancer treatment‐related cardiac death cannot be ignored. For lung cancer, chest radiotherapy (RT) is essential, but the related cardiotoxicity has not been fully studied. Methods We reviewed the data of 11,455 patients with non‐small cell lung cancer (NSCLC) from the Surveillance, Epidemiology, and End Results database from 2001 to 2015. The change trend for concomitant cardiovascular diseases (CVD)‐specific death was calculated and graphically demonstrated. Univariate and multivariate analyses for survival were performed using Cox risk regression model. Results In our analysis, the overall incidence and mortality from NSCLC declined, but CVD‐specific death increased. Both chemoradiotherapy and radiotherapy alone played a significant role in CVD‐specific death. Analyzed longitudinally from diagnosis, we found that the effect of RT in CVD‐specific death increased continuously over the third years and the hazard ratio for CVD‐specific death was 1.386 times between RT and non‐RT group (HR = 1.386, 95% CI 1.322–1.452; p

Urban Functional Zones (UFZs) serve as the fundamental units of cities, making the classification and recognition of UFZs of paramount importance for urban planning and development. These differences between UFZs not only encompass geographical landscape disparities but also incorporate socio-economic information. Therefore, it is essential to extract high-precision two-dimensional (2D) and three-dimensional (3D) Urban Morphological Parameters (UMPs) and integrate socio-economic data for UFZ classification. In this study, we conducted UFZ classification using airborne LiDAR point clouds, aerial images, and point-of-interest (POI) data. Initially, we fused LiDAR and image data to obtain high-precision land cover distributions, building height models, and canopy height models, which served as accurate data sources for extracting 2D and 3D UMPs. Subsequently, we segmented city blocks based on road network data and extracted 2D UMPs, 3D UMPs, and POI Kernel Density Features (KDFs) for each city block. We designed six classification experiments based on features from single and multiple data sources. K-Nearest Neighbors (KNNs), random forest (RF), and eXtreme Gradient Boosting (XGBoost) were employed to classify UFZs. Furthermore, to address the potential data redundancy stemming from numerous input features, we implemented a feature optimization experiment. The results indicate that the experiment, which combined POI KDFs and 2D and 3D UMPs, achieved the highest classification accuracy. Three classifiers consistently exhibited superior performance, manifesting a substantial improvement in the best Overall Accuracy (OA) that ranged between 8.31% and 17.1% when compared to experiments that relied on single data sources. Among these, XGBoost outperformed the others with an OA of 84.56% and a kappa coefficient of 0.82. By conducting feature optimization on all 107 input features, the classification accuracy of all three classifiers exceeded 80%. Specifically, the OA for KNN improved by 10.46%. XGBoost maintained its leading performance, achieving an OA of 86.22% and a kappa coefficient of 0.84. An analysis of the variable importance proportion of 24 optimized features revealed the following order: 2D UMPs (46.46%) > 3D UMPs (32.51%) > POI KDFs (21.04%). This suggests that 2D UMPs contributed the most to classification, while a ranking of feature importance positions 3D UMPs in the lead, followed by 2D UMPs and POI KDFs. This highlights the critical role of 3D UMPs in classification, but it also emphasizes that the socio-economic information reflected by POI KDFs was essential for UFZ classification. Our research outcomes provide valuable insights for the rational planning and development of various UFZs in medium-sized cities, contributing to the overall functionality and quality of life for residents.

BackgroundPostoperative radiotherapy (PORT) is a therapeutic strategy for patients with non-small cell lung cancer (NSCLC). Nevertheless, some studies suggesting PORT does not improve overall survival (OS) including Lung ART phase III trial. The role of PORT and high-risk groups need to be confirmed.MethodsPatients from the Surveillance, Epidemiology, and End Results program (SEER) from 2004 to 2015 were eligible. Aged ≥18 years with stage IIIA-N2 NSCLC, accepted PORT or not were considered for the study. Cox regression analyses and multivariate competing risk model were performed. Propensity score matching (PSM) was conducted. Data from a single-center study in China were used for validation.ResultsIn all patients with IIIA-N2 NSCLC, death from respiratory illness increased year by year, with right lung-related deaths accounting for the main proportion. In SEER database, PORT was detrimental for OS after PSM (hazard ratio [HR], 1.088; 95% CI, 1.088–1.174; P = 0.031), with a same trend for death from the lungs (HR, 1.13; 95% CI, 1.04–1.22; P = 0.005). Right tumor receiving PORT were prone to death from lung disease(HR, 1.14; 95% CI, 1.02–1.27; P = 0.018). In China single-center cohort, PORT was significantly correlated with deteriorated OS (HR 1.356; 95% CI 1.127–1.632; P

BackgroundSurgery is the main curative therapeutic strategy for patients with initial primary lung cancer (IPLC). Most international guidelines recommend regular follow-ups after discharge to monitor patients for tumor recurrence and metastasis. As the overall survival (OS) in patients with lung cancer improves, their risk of secondary primary lung cancer (SPLC) increases. Previous studies on such patients lack separate assessment of different survival outcomes and evaluation of high-risk factors for SPLC. Therefore, we aimed to determine the correlation between high-risk factors and causes of death in patients with SPLC, based on the Surveillance, Epidemiology, and End Results (SEER) database.MethodsWe screened the SEER database for patients with IPLC and SPLC from 2004 to 2015 and included only patients who underwent surgery since the IPLC and in whom the cancer was pathologically verified of an International Classification of Diseases grade of 0-3 and to be non-small-cell lung cancer. The standardized incidence ratio (SIR) was calculated between variables and SPLC. Multivariable Cox proportional-hazards regression analyses were conducted to calculate the correlation of different variables with overall survival (OS) and cancer-specific survival (CSS). A competing-risk model was conducted for SPLC. The effect of baseline bias on survival outcomes by performing propensity score matching analysis in a 1: 6 ratio (SPLC: IPLC).ResultsFor patients aged 0-49 years, the overall SIR was higher in older patients, reaching a maximum of 27.74 in those aged 40-49 years, and at 11.63 in patients aged 50-59 years. The overall SIR was higher for patients who were more recently diagnosed with IPLC and increased with time after diagnosis. Male sex, SPLC (hazard ratio, 1.6173; 95% confidence interval, 1.5505-1.6869; P < 0.001), cancer grade III or IV, lower lobe of the lung, advanced stage and postoperative radiotherapy (PORT) were independently detrimental to OS. In terms of CSS, PORT was a high-risk factor.ConclusionsPostoperative radiotherapy is a risk factor for second primary lung cancer and detrimental to overall and cancer-specific survival in patients who had initial primary lung cancer. These data support the need for life-long follow-up of patients who undergo treatment for IPLC to screen for SPLC.

As one of the most representative endocrine disrupting compounds, dioctyl phthalate (DEHP) is difficult to remove due to its bio-refractory characteristic. In this study, an immobilization technology was applied in an MBR system to improve the degradation of DEHP. The degradation efficiency of DEHP was significantly improved and the number of degradation genes increased by 1/3. A bacterial strain that could effectively degrade DEHP was isolated from activated sludge and identified as Bacillus sp. The degradation pathway of DEHP was analyzed by GC-MS. DEHP was decomposed into phthalates (DBP) and Diuretic sylycol (DEP), then further to Phthalic acid (PA). PA was oxidized, dehydrogenated, and decarboxylated into protocatechins, further entered the TCA cycle through orthotopic ring opening. The DEHP degrading strain was immobilized by sodium alginate and calcium chloride under the optimized immobilization conditions, and added to MBR systems. The removal rate of DEHP (5 mg/L) (91.9%) and the number of 3, 4-dioxygenase gene copies was significantly improved by adding immobilized bacteria. Micromonospora, Rhodococcus, Bacteroides and Pseudomonas were the dominant genuses, and the results of bacterial community structure analysis show that immobilization technology is beneficial to system stability. The results showed the potential applications of the immobilized technique in DEHP wastewater treatment in MBR.

Extraction of urban objects, and analysis of two- and three-dimensional (2D and 3D) morphological parameters, as well as 2D and 3D landscape metrics in urban environments are valuable for updating GIS databases and for civic applications, urban planning, disaster risk assessment, and climate and sustainability studies. However, few studies have reported the extraction of 3D buildings at different scales in urban areas or developed a method for accuracy evaluation. This study aims at developing a method of multi-scale 3D building information extraction (MS3DB) to fill this research gap. Surface flatness and the variance in the normal direction were extracted from the point cloud data, and gray-level co-occurrence matrix was extracted from normalized digital surface models as labeling features, which were fused into a graph-cut the algorithm to determine building labeling. In addition, 2D and 3D building morphological parameters were extracted at the grid-scale, and a set of 3D building landscape metrics were designed at the city-block scale. Accuracy of the extraction of 3D building information was evaluated at the object, grid, and block scales. The model achieved high accuracy in extracting the building labels using data from the northern part of Brooklyn, New York, USA. The results show that the MS3DB method yields limited accuracy in extracting the building edges, whereas other parameters (e.g., area, volume, and planar area index) were extracted with high accuracy at the grid scale (R2 > 0.92). The block-scale landscape analysis shows the advantages of integrating 2D and 3D features (e.g., differences in the vertical landscape) in characterizing the structure of urban buildings and exhibits moderate accuracy (R2 > 0.79).

The removal characteristics of antibiotic resistance genes and mobile genetic elements from livestock wastewater (dominated by quinolone antibiotics) treated with MFC were evaluated by High-throughput quantitative (HT-qPCR). The results showed that 144 ARGs and 8 MEGs were detected in the livestock wastewater. After MFC treatment, the number of AGRs decreased as a whole, and the relative abundance of macrolide-lincosamide-streptogramin group B (MLSB) and aminoglycosider decreased by 62.7% and 92.9%, respectively. MGEs decreased by 57.3% and multidrug genes decreased by 90%. After MFC treatment, the absolute abundance of tetracycline in raw sewage decreased by two orders of magnitude from 5.8 × 105 copies L−1 to 5.1.× 103 copies L−1. However, MFC was less efficient in the removal of vancomycin and beta-lactamase genes. It was also found that chloramphenicol resistance genes slightly increased. Illumina sequencing showed that Syntrophobacterales and Synergistales were predominant in MFCs. Desulfovibrio was resistant to high concentration of moxifloxacin hydrochloride. The removal efficiency of MFC for moxifloxacin hydrochloride at a concentration of 5 mg L−1 was 86.55%. The maximum power density and coulomb efficiency were 109.3 mV·cm−3 and 41.97%, respectively. With the increase of antibiotic concentration, the sewage treatment efficiency and electrical performance were inhibited. This study shows that untreated livestock wastewater had a great risk of gene horizontal transfer. Although MFC had limited treatment capacity for high-concentration quinolone wastewater, it is an effective method to reduce ARGs and the risk of horizontal gene transfer.

Previous research on urban impervious surface monitoring has ignored the differences, spatial patterns, and driving factors of impervious surfaces among the various functional zones in cities. In this paper, we extracted the impervious surface coverage of Tianjin in 1990, 1995, 2000, 2005, 2010, and 2015 based on the Classification and Regression Tree model. Then, using the methods of quantitative geography, we systematically analyzed the spatiotemporal variations of impervious surface coverage among the functional zones in Tianjin from 1990 to 2015. Additionally, the driving mechanisms of impervious surface growths among different functional zones were investigated. The results showed that (1) the growth of impervious surfaces shows two spatially separate core areas of growth. The core functional zone (CFZ) had the highest impervious surface coverage, and the ecological conservation zone (ECZ) had the lowest impervious surface coverage. (2) High-high aggregation regions of impervious surface coverage were mainly located in CFZ, while low-low aggregation regions of impervious surface coverage area were mainly located in ECZ. (3) Influences of social-economic factors on area growths of impervious surface are stronger in urban function expanded zone, coastal city key development zone, Beijing–Tianjin coordinated development zone, and urban-rural coordinated development zone than those in CFZ. Our results can provide a point of reference for decision-making regarding urban planning management.

Maize (Zea mays L.) lodging is an important factor limiting its yield increase worldwide. EDAH (containing 27% ethephon and 3% DA-6) is commonly used to decrease lodging. There is an urgent need to select efficient application methods of agrochemical for better spray deposition. In our research, an unmanned aerial vehicle (UAV) (15 L ha−1 and 30 L ha−1) with EDAH dosages of 72 and 90 g a.i. ha−1, and electric knapsack sprayers (EKS) (450 L ha−1) with dosages of 90 g a.i. ha−1 were used to compare the droplet deposition distribution, uniformity and maize growth. According to our research, EDAH applied by UAV had a higher droplet deposition rate than EKS; EKS had a higher droplet coverage rate, deposition density, droplet distribution uniformity. At the same dosage of EDAH, the UAV had a better effect on controlling maize growth than EKS, and almost equal effects were detected when the dosage applied by the UAVs was decreased by 20%. Considering the lodging occurrence and yield, we recommend that the dosage of EDAH applied by UAVs should be 72 g a.i. ha−1 when there is weak lodging and 90 g a.i. ha−1 when there is heavy lodging, with a spray volume of 15 L ha−1.

Brassinolides (BRs) are naturally-occurring phytohormones, which are essentially important to improve the crop adoptive capacity to various stresses. Spray volume (SV) and agrochemical application methods are associated with chemical deposition and field efficiency. The objective of this study was to compare the possible effects of 28-Homobrassinolide (HBL) dosages 18, 22, and 30 mg a.i. ha−1 for unmanned aerial vehicle (UAV) sprayers (15 L ha−1 and 30 L ha−1) and 22 mg a.i. ha−1 for Knapsack manual sprayers (KMS) (450 L ha−1) at maize silking stage on droplets deposition distribution, photosynthetic parameters, grain filling process and yield. The results showed that the droplet deposition of UAV (15, 30 L ha−1) was 47.04%, 8.89% higher than KMS. However, the UAV sprayer had a poor droplet deposition distribution. HBL significantly increased the photosynthetic parameters, grain filling rate, and yield. A UAV spray volume of 15 L ha−1 with 22 mg a.i. ha−1 significantly increased grains yield by 4.16–5.64%, 7.5–12.09% compared to KMS and CK in both years. Considering the high efficiency of the UAV sprayer and better effects of HBL on final yield, spraying 22~30 mg a.i. ha−1 with UAV spray volume 15 L ha−1 at the silking stage could be a better strategy.

Identifying the driving factors of urban land surface temperatures (U-LSTs) is critical in improving urban thermal environments and in supporting the sustainable development of cities. Previous studies have demonstrated that two- and three-dimensional (2D and 3D) urban structure parameters (USPs) largely influence seasonal U-LSTs. However, the effects of 2D and 3D USPs on seasonal U-LSTs at different spatial scales still await a general explanation. In this study, we used very-high-resolution remotely sensed data to investigate how 2D and 3D USPs impact seasonal U-LSTs at different spatial scales (including pixel and city block scales). In addition, the influences of various functional zones on U-LSTs were analyzed. The results show that, (1) generally, the links between USPs and U-LSTs at the city block scale were more obvious than those at the pixel scale, e.g., the Pearson correlation coefficient (r) between U-LST and the mean building height at the city block scale (summer: r = −0.156) was higher than that at the pixel scale (summer: r = −0.081). Tree percentage yielded a considerable cooling effect on summer U-LSTs on both the pixel (r = −0.199) and city block (r = −0.369) scales, and the effect was more obvious in regions with tall trees. (2) The independently total explained variances (R2) of 3D USPs on seasonal U-LSTs were considerably higher than those of 2D USPs in most urban functional zones (UFZs), suggesting the distinctive roles of 3D USPs in U-LST regulation at the local scale. Three-dimensional USPs (R2 value = 0.66) yielded more decisive influences on summer U-LSTs than 2D USPs did (R2 value = 0.48). (3) Manufacturing zones yielded the highest U-LST, followed by residential and commercial zones. Notably, it is found that the explained variances of the total study area for seasonal U-LSTs were significantly lower than those of each UFZ, suggesting the different roles of 2D and 3D USPs played in various UFZs and that it is critical to explain U-LST variations by using UFZs.

This study presents a new approach for Urban Functional Zone (UFZ) mapping by integrating two-dimensional (2D) Urban Structure Parameters (USPs), three-dimensional (3D) USPs, and the spatial patterns of land covers, which can be divided into two steps. Firstly, we extracted various features, i.e., spectral, textural, geometrical features, and 3D USPs from very-high-resolution (VHR) images and light detection and ranging (LiDAR) point clouds. In addition, the multi-classifiers (MLCs), i.e., Random Forest, K-Nearest Neighbor, and Linear Discriminant Analysis classifiers were used to perform the land cover mapping by using the optimized features. Secondly, based on the land cover classification results, we extracted 2D and 3D USPs for different land covers and used MLCs to classify UFZs. Results for the northern part of Brooklyn, New York, USA, show that the approach yielded an excellent accuracy of UFZ mapping with an overall accuracy of 91.9%. Moreover, we have demonstrated that 3D USPs could considerably improve the classification accuracies of UFZs and land covers by 6.4% and 3.0%, respectively.

Light detection and range (LiDAR) intensity is an important feature describing the characteristics of a target. The direct use of original intensity values has limitations for users, because the same objects may have different spectra, while different objects may have similar spectra in the overlapping regions of airborne LiDAR intensity data. The incidence angle and range constitute the geometric configuration of the airborne measurement system, which has an important influence on the LiDAR intensity. Considering positional shift and rotation angle deviation of the laser scanner and the inertial measurement unit (IMU), a new method for calculating the incident angle is presented based on the rigorous geometric measurement model for airborne LiDAR. The improved approach was applied to experimental intensity data of two forms from a RIEGL laser scanner system mounted on a manned aerial platform. The results showed that the variation coefficient of the intensity values after correction in homogeneous regions is lower than that obtained before correction. The overall classification accuracy of the corrected intensity data of the first form (amplitude) is significantly improved by 30.01%, and the overall classification accuracy of the corrected intensity data of second form (reflectance) increased by 18.21%. The results suggest that the correction method is applicable to other airborne LiDAR systems. Corrected intensity values can be better used for classification, especially in more refined target recognition scenarios, such as road mark extraction and forest monitoring. This study provides useful guidance for the development of future LiDAR data processing systems.

It is valuable to study the land use/land cover (LULC) classification for suburbs. The fusion of Light Detection and Ranging (LiDAR) data and aerial imagery is often regarded as an effective method for the LULC classification; however, more in-depth analysis would be required to explore effective information for enhancing the suburban LULC classification. In this study, first, both aerial imageries and point clouds were simultaneously collected. Then, LiDAR-derived models, i.e., normalized digital surface model (nDSM) and surface intensity model (IM), were generated from the elevation and intensity of point clouds. Further, considering the surface characteristics of ground objects in suburb, we proposed a new LiDAR-derived model, namely surface roughness model (RM), to reveal the degree of surface fluctuations. Additionally, various combinations of aerial imageries and the LiDAR-derived data were used to analyze the effects of multi-variable fusion under different scenarios and optimize the multi-variable integration for suburban LULC classification. The mean decrease impurity method was used to identify the importance of variables; three machine learning classifiers, i.e., random forest (RF), k-nearest neighbor (KNN) and artificial neural network (ANN) were adopted in various scenarios. The results were as follows. The fusion of aerial imagery and all the LiDAR-derived models, i.e., nDSM, RM and IM, with RF classifier performs best in the suburban LULC classification (overall accuracy = 84.75%, kappa coefficient = 0.80). Variable importance analysis shows that nDSM has the highest variable importance proportion (VIP) value, followed by RM, IM, and spectral information, indicating the feasibility of this proposed LiDAR-derived model-RM. This research presents effective methods relating to the application of aerial imagery and LiDAR-derived model for the complex suburban surface scenarios.

Under the dual‐carbon goal, due to the long‐term operation of thermal power units under wide load and frequent fluctuating load after heat supply transformation, the dynamic process of subcritical units is modeled, and a frequency modulation optimization technology based on frequency signal accuracy is proposed to ensure the accuracy of the speed signal and improve the qualification rate of primary frequency modulation action. At the same time, the frequency regulation technology of steam engine side control optimization under boundary working conditions is proposed, so as to realize the sensitivity and rapidity of the digital electric hydraulic control system. The coordination optimization technology under boundary working conditions is proposed, and the primary frequency regulation performance of the unit is improved through a series of optimization adjustments. Finally, the engineering application is carried out and the optimization effect is analyzed. [ABSTRACT FROM AUTHOR]