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The scientific and reasonable division of geographical units of cultivated land reserve resource areas is an important foundation for comprehensive land consolidation (CLC). Saline–alkali land is an important cultivated land reserve resource, and is significant for ensuring food security. This paper constructs a two-level land consolidation index system for cultivated land reserve resource areas. The Kruskal graph theory clustering algorithm was used to divide the study area into four types of ecological zones. On the basis of ecological zones, the study area was further divided into three types of consolidation units. Finally, the spatial relationship between ecological zoning and land use types was clarified, and the classification distribution of land consolidation potential was determined through an analysis of the CLC of two-level geographical units. Da'an City, Jilin province, China, was selected as the study area. The results of this study show the following: (1) In Da'an City, the conservation priority areas are concentrated in the north, the development priority areas are concentrated in the central and southern areas, and the comprehensive upgrade areas and adjustment rebuilding areas are in the transition zones. (2) The CLC potential trend is low in the north but high in the south in Da'an City. This paper proposes a framework for a geographical unit delineation method for saline–alkali-enriched cultivated land reserve resource zones, and analyzes the spatial layout of ecological protection demands and land consolidation potential in Da'an City. The results and conclusions of this study will provide a reference for CLC in cultivated land reserve resource areas. [ABSTRACT FROM AUTHOR]

The development of smart farming comes with a lot of data problems. Studies have shown this is due to insufficient cognition of the structural relationship between data and events. Shili Theory is an attractive concept. To embed intelligent agricultural technology in events and the natural environment, especially to unify and standardize agricultural production data, firstly, this paper has defined the concept of Shili Theory which researches the natural regularity of the event by Shili Mirrored Structure. Secondly, this paper has proposed a Shili Mirrored Structure based on the technology development path (from the human brain memory mechanism to the information storage mechanism to intelligent technology). Finally, the structure has been applied to develop an intelligent system of agricultural production data management. In rice production of Jilin Province, it forms the event chain of the whole plant 5T (seed, seeding, paddy shoot, grain, product period operation) and grain period 5T (harvesting, field stacking, drying, warehousing, storing). The system application shows that this management structure can reduce data flow, improve data utilization, and enhance the correlation between data and events. It can realize the quality improvement of the agricultural production process, especially revealing the 8.83% significant latent loss in rice harvest. [ABSTRACT FROM AUTHOR]

Rapid urbanization is intensifying land use transitions in China by shrinking cropland and increasing land development, exacerbating land abuse, and causing environmental degradation. There are clear needs to improve land use and address these problems; however, most previous studies focused on either structural or layout optimization. In contrast, this paper proposed a method for comprehensive optimization of land use areas, layout, and structure. This involved coupling multiobjective dynamic planning (MODP), Conversion of Land Use and its Effects at Small regional extent (CLUE-S), and minimal cumulative resistance (MCR) models. In this approach, the MODP model predicted future changes that were based on areas of current land use, and the CLUE-S model simulated various future types that were based on the analysis of geographic land use and economic data. In addition, the MODP and CLUE-S models optimized the amounts and spatial distributions of land use types, respectively. The MCR model could then partition the simulation results for ecological optimization. In this paper, an illustrative application was presented that partitioned Changchun City, Jilin Province, China into construction-prohibited, restricted construction, suitable for construction, and key construction areas (which accounted for 17.41%, 30.24%, 25.32%, and 27.04%, respectively of the total area). The optimization result met expectations and provided potentially valuable reference data for spatial land use planning and ecological protection in the focal region. The proposed method to optimize the ecological layout of land use that was based on multimodel coupling considered operability and objectivity; therefore, facilitating practical applications of the results in Changchun and the presented methodology elsewhere. [ABSTRACT FROM AUTHOR]

Understanding changes of soil organic carbon (SOC) in top layers of croplands and their driving factors is a vital prerequisite in decision-making for maintaining sustainable agriculture. However, high-precision estimation of SOC of croplands at regional scale is still an issue to be solved. Based on soil samples, synthetic image of bare soil and geographical data, this paper predicted SOC density of croplands using Random Forest model in the Black Soil Region of Jilin Province, China in 2005 and 2020, and analyzed its influencing factors. Results showed that random forest model that integrates bare soil composite images improve the accuracy and robustness of SOC density prediction. From 2005 to 2020, the total SOC storage in croplands decreased from 89.96 to 82.79 Tg C with an annual decrease of 0.48 Tg C yr−1. The mean value of SOC density of croplands decreased from 3.42 to 3.32 kg/m2, and high values are distributed in middle parts. Changes of SOC represented significant heterogeneity spatially. 62.14% of croplands with SOC density greater than 4.0 kg/m2 decreased significantly, and 38.60% of croplands with SOC density between 2.5 and 3.0 kg/m2 significantly increased. Climatic factors made great contributions to SOC density, however, their relative importance (RI) to SOC density decreased from 44.65% to 37.26% during the study period. Synthetic images of bare soil constituted 23.54% and 26.29% of RI in the SOC density prediction, respectively, and the contribution of each band was quite different. The RIs of topographic and vegetation factors were low but increased significantly from 2005 to 2020. This study can aid local land managers and governmental agencies in assessing carbon sequestration potential and carbon credits, thus contributing to the protection and sustainable use of black soils. [ABSTRACT FROM AUTHOR]

There is a centralization of the core content in the text information of the new crown epidemic notification. This paper proposes a joint learning text information extraction method: TBR-NER (topic-based recognition named entity recognition) based on topic recognition and named entity recognition to predict the labeled risk areas and epidemic trajectory information in text information. Transfer learning and data augmentation are used to solve the problem of data scarcity caused by the initial local outbreak of the epidemic, and mutual understanding is achieved by topic self-labeling without introducing additional labeled data. Taking the epidemic cases in Hebei and Jilin provinces as examples, the reliability and effectiveness of the method are verified by five types of topic recognition and 15 types of entity information extraction. The experimental results show that, compared with the four existing NER methods, this method can achieve optimality faster through the mutual learning of each task at the early stage of training. The optimal accuracy in the independent test set can be improved by more than 20%, and the minimum loss value is significantly reduced. This also proves that the joint learning algorithm (TBR-NER) mentioned in this paper performs better in such tasks. The TBR-NER model has specific sociality and applicability and can help in epidemic prediction, prevention, and control. [ABSTRACT FROM AUTHOR]

Accurately assessing the susceptibility of debris flow disasters is of great significance for reducing the cost of disaster prevention and mitigation, as well as disaster losses. Machine learning (ML) models have been widely used in the susceptibility assessment of debris flow disasters. However, these models often have randomness in the selection of non-disaster data, which can lead to redundant information and poor applicability and accuracy of susceptibility evaluation results. To address this issue, this paper focuses on debris flow disasters in Yongji County, Jilin Province, China; optimizes the sampling method of non-disaster datasets in machine learning susceptibility assessment; and proposes a susceptibility prediction model that couples information value (IV) with artificial neural network (ANN) and logistic regression (LR) models. A debris flow disaster susceptibility distribution map with higher accuracy was drawn based on this model. The model's performance is evaluated using the area under the receiver operating characteristic curve (AUC), information gain ratio (IGR), and typical disaster point verification methods. The results show that the rainfall and topography were found to be decisive factors in the occurrence of debris flow disasters, and the IV-ANN model established in this study had the highest accuracy (AUC = 0.968). Compared to traditional machine learning models, the coupling model produced an increase in economic benefit of about 25% while reducing the average disaster prevention and control investment cost by about 8%. Based on model's susceptibility map, this paper proposes practical disaster prevention and control suggestions that promote sustainable development in the region, such as establishing monitoring systems and information platforms to aid disaster management. [ABSTRACT FROM AUTHOR]

In recent years, the volcanic activity of Changbai Mountain has been accompanied by several earthquakes, and the frequent human engineering activities have led to a gradual increase in the number of collapses in the region, which severely impacts residents' lives and property safety. In northeastern China, the Changbai Mountain area in the southeastern Jilin Province is a typical mountain environment. This paper selects 12 evaluation indicators to build a hazard assessment system, including slope, aspect, elevation, curvature, lithology, NDVI, land use type, distance from the fault, the river from the road, volcanic earthquake, and annual average precipitation. Using emotional weight (G1 method) and objective weight (WOE-CV method), the hazard due to collapses in the study area is evaluated too. Among them, the transcendence probability of volcanic earthquakes greater than VI degree represents the relationship between Changbai Mountain volcanic earthquakes and the assessment of geological collapse hazard. The results show that high- and very high-hazard areas are mainly distributed in densely populated areas and national and provincial trunk lines, with apparent spatial agglomeration characteristics. The low-hazard area, medium-hazard area, high-hazard area and very high-hazard area accounted for 19.33%, 44.19%, 33.85% and 2.63% of the total area of the study area, respectively. By comparing the previous geological hazard survey reports in the area with the collapse hazard zoning map in this paper, 87.72% of the known collapse hazard areas are distributed within high and very high hazard zones, indicating that the conclusions of the article are more accurate and in line with the actual situation. Results from collapse-related hazards can provide relevant guidance for preventing and controlling geological risks posed by volcanic earthquakes affecting Changbai Mountain. [ABSTRACT FROM AUTHOR]

During tunnel construction, accurately ascertaining the adverse geological condition in front of the tunnel face is essential to ensure construction safety and decrease economic loss. As an accurate wave velocity modelling method, seismic full-waveform inversion (FWI) still faces many difficulties when applied in a tunnel observation environment because of fewer observation data and smaller offset than ground seismic detection. This paper analysed the FWI for tunnel active seismic forward prospecting with a single shot. We adopted the N -order time integral wavefield and normalized integration objective function method to improve the stability and reduce the dependence of FWI on the initial model. Based on two assumptions on the wave velocity distribution in the tunnel, we proposed a 1-D velocity structure correction method to reduce the multiplicity of inversion. Then the improved tunnel FWI method based on these two inversion strategies was applied to a synthetic model with a rectangular anomaly and a lithology interface, verifying the method's effectiveness. Based on typical adverse geological bodies during tunnelling, three additional adverse geological models were built and verified the reliability of the methods in tunnel detection environments. There are still some false anomalies interference in the inversion results of the synthetic models from the inversion results. However, these problems are acceptable in limited tunnel observation space. Then the method was applied in a field example in the Yinsong water supply project in Jilin Province, China, and verified the effect on field data. Finally, the influence of the shot number on the inversion effect and the method's robustness are discussed. [ABSTRACT FROM AUTHOR]

With rapid industrialization and urbanization in China, a large rural population has migrated to cities and left their rural homestead land (RHL) idled. Land use policy on RHL utilization is crucial to the efficient use of land resources. However, due to farmers' limited knowledge of regulations and lack of participation in rural land governance, their preference is sometimes overlooked in the policy-making process. The purpose of this paper is to examine farmers' preferences for the two primary RHL utilization programs, i.e., transfer and surrender. We conducted a farmer household survey of 405 households in rural areas in Changchun at Jilin Province, China in 2018 and estimated farmers' willingness to participate in the mechanisms using a bivariate ordered probit model. Various options under the two mechanisms are also investigated. We find a positive correlation between rural households' willingness to participate in these two mechanisms. This is the first comprehensive study taking into consideration the correlation and tradeoff in farmers' choice between the two mechanisms. The results shed light on the heterogeneity of households' needs and interests in RHL utilization, an important component to be considered in rural development policy-making decisions. [ABSTRACT FROM AUTHOR]

It is widely recognized that urban resilience is one of the core goals of urban development. As an important part of a city, the resilience level of urban human settlements directly affects the development trend of urban resilience. However, at present, research results on the resilience of urban human settlements are very rare, are mainly concentrated in the central region of China, and rarely take into account the economically backward northeastern region. Therefore, in order to better improve the anti-risk ability of the urban human settlement environment system in three provinces of Northeast China, fully implement the strategic goal of "Comprehensive Revitalization of Northeast China", and achieve high-quality urban development, this paper focuses on 34 prefecture-level cities in three provinces of Northeast China and proposes an urban human settlement resilience evaluation system with 36 indicators in five dimensions, namely, the natural system, human system, housing system, supporting system, and social system. Using the entropy weight method, the Dagum Gini coefficient, and a geographical probe model, the changes in the resilience level of each city from 2005 to 2020 were measured, and the urban living environment was assessed in terms of the adaptability and resilience of the development level in each subsystem based on the temporal and spatial evolution law and its influencing factors. The following conclusions were drawn: (1) The development level of urban human settlement resilience in the three provinces in Northeast China showed an N-shaped development trend from 2005 to 2020, but the regional differences were significant, and the overall spatial pattern was "high in the south and low in the north". (2) In terms of the overall difference, the overall difference in urban human settlement resilience in the three northeastern provinces of China was small: the inter-regional difference was the main source of the difference, and the intra-regional difference was the secondary source. The regional differences were in the order of Heilongjiang Province > Liaoning Province > Jilin Province, indicating that Jilin Province had the smallest difference and that the resilience level of urban human settlements does not show a balanced development trend. In terms of the average Gini coefficient between regions, the order of difference was Liaoning Province–Heilongjiang Province > Jilin Province–Liaoning Province > Jilin Province–Heilongjiang Province, indicating that the difference between Liaoning Province and Heilongjiang Province was the most significant. (3) The "natural system", "human system", "living system", "supporting system", and "social system" had significant spatial and temporal heterogeneity and significantly affected the resilience level of urban human settlements in the three provinces in Northeast China. Among them, the "social system" has always been the main factor affecting the resilience level of urban human settlements. [ABSTRACT FROM AUTHOR]

Sea ice and freshwater ice can be different in terms of physical and acoustic characteristics, such as density, salinity, etc. In this paper, under-ice ambient noise in the Mudan river (Jilin Province, Northeast of China) is analyzed using the data recorded by autonomous hydrophones to test if the river ice environment is an effective analog for studying under-ice noise of multi-year ice sheets in the Arctic. The noise spectrum level below 250 Hz and above 1 kHz decreases linearly with the increase in the logarithmic frequency in a quiet environment. The ice cracks are detected and extracted, and Pearson correlation analysis between meteorological information and cracks is carried out. Frequency correlation matrixes are calculated to obtain the correlation between pairs of frequencies and evaluate the frequency correlation of ice crack noise of two hydrophones under different depths, different distances, and different times. Finally, the paper compares the experimental results with Arctic under-ice noise in the literature. Similarities with Arctic under-ice noise are observed in the experiment, including noise spectrum, cracks' peak frequency, and correlations between temperature and crack intensity. This paper believes that the study of under-ice noise in freshwater rivers can be used to simulate multi-year ice regions in the Arctic in terms of thermal-induced cracks and meteorological correlation. And future research is needed to prove this judgment further. [ABSTRACT FROM AUTHOR]

Passenger flow is an important benchmark for measuring tourism benefits, and accurate tourism passenger flow prediction is of great significance to the government and related tourism enterprises and can promote the sustainable development of China's tourism industry. For daily passenger flow time series data, a passenger flow forecasting method based on convolutional neural network (CNN) and improved quantile regression long short-term memory network (QRLSTM), denoted as CNN-IQRLSTM, is proposed with reconstructed correlation features and in the form of sliding windows as inputs. First, four discrete variables such as whether the day is a weekend and holiday are created by time; then, a sliding window of width 42 is used to pass the passenger flow data into the network sequentially; finally, the loss function of the sparse Laplacian improved QRLSTM is introduced for passenger flow prediction, and the point prediction and interval prediction results under different quartiles are obtained. The application of quantile regression captures the overall picture of the data, enhances the robustness, fit, predictive power and nonlinear processing capability of neural networks, and fills the gap between quantile regression and neural network methods in the field of passenger flow prediction. CNN can effectively handle complex input data, and the improved nonlinear QR model can provide passenger flow quantile prediction information. The method is applied to the tourism traffic prediction of four 5A scenic spots in Jilin Province, and the effectiveness of the method is verified. The results show that the method proposed in this paper fits best in point prediction and has higher prediction accuracy. The MAPE of the Changbai Mountain dataset was 0.07, the MAPE of the puppet palace museum dataset was 0.05, the fit of the Sculpture Park dataset reached 93%, and the fit of the net moon lake dataset was as high as 99%. Meanwhile, the interval prediction results show that the method has a larger interval coverage as well as a smaller interval average width, which improves the prediction efficiency. In 95% of the interval predictions, the interval coverage of Changbai Mountain data is 99% and the interval average width is 0.49. It is a good reference value for the management of different scenic spots. [ABSTRACT FROM AUTHOR]

This paper examines the spatial spillover effects of public transportation infrastructure on regional economy in Northeast China, the "rust belt" region in China. The dataset consists of socioeconomic data from 47 cities in the area during the period of year 2005 through 2015. Accessibility is used as an explanatory variable to reflect the influence of infrastructure on economic development. In order to avoid the endogenous, queen contiguity matrix is used to define the spatial weight matrix. In the paper, the dynamic panel data model is also used to explore the effects of high-speed railways in the whole study area and attempted to confirm the spatial differences among Heilongjiang Province, Jilin Province, and Liaoning Province. The results show that the high-speed railways increase the cities' connection in terms of accessibility, and a significant positive spillover effect exists after the construction of high-speed railways (HSR), indicating the extensive economic benefits of HSR construction, despite of the overall economic difficulty experienced by this region. [ABSTRACT FROM AUTHOR]

The serious problem of wind power curtailment in northern China has created a pressing need to enhance the peak-shaving ability of the power system. As the main source of power supply in northern China, combined heat and power (CHP) units have significant potential for peak-shaving. Currently, the Chinese government encourages CHP plants to increase their peak-shaving capacity by installing power-to-heat (P2H) equipment. In addition, the government has implemented auxiliary service market policies to encourage CHP plants to provide peak-shaving services. In order to maximize economic benefits for CHP plants, this paper proposes an optimal configuration method of P2H equipment with the static payback time (SPT) as the objective function. Cost and income models of installing the P2H equipment are constructed by taking into account the auxiliary service market policies. The peak-shaving income model of the CHP plant is derived emphatically as a key part of the proposed method. Finally, the district heating region in Jilin province is used as a case study example. The results show that adding the P2H equipment is significantly effective in improving the peak-shaving ability of CHP units, and investing in heat pumps is more cost-effective than electric boilers. The proposed method can be applied to other northern regions relying on CHP units for central heating, providing a valuable solution to the problem of wind power curtailment in these regions. [ABSTRACT FROM AUTHOR]

The "carbon peak and carbon neutral" emission target has set new requirements for the supply chain structure, exacerbated by the complexity and vulnerability of the agricultural sector and global supply chains after the COVID-19 outbreak. Under these circumstances, the resilience evaluation of the agricultural supply chain based on green transformation became an important subject. Based on this topic with outstanding problems, this paper evaluates the resilience level of the agricultural supply chain in northeast China with the goal of achieving the "double carbon" objective. By focusing on its resilience, we selected Heilongjiang, Jilin, and Liaoning provinces as research subjects and collected the agricultural supply chain-related data from 2010 to 2019. Based on the relationship between supply chain nodes and the operation system, an evaluation model containing three levels was established. The entropy weight method and TOWA operator were used to carry out secondary weighting on the evaluation system and time levels containing 12 indicators, following the evaluation of the resilience level of the agricultural supply chain in three static and dynamic dimensions using the grey correlation method. The results show that the importance of the evaluation level of "internode resilience level" has always been a priority during the decade. Therefore, it is pointed out that the resilience construction and green transformation of the agricultural supply chain should be strengthened and implemented from the following three aspects: strengthening agricultural modernization, optimizing supply chain operation, and the implementation and promotion of effective policies. [ABSTRACT FROM AUTHOR]

Different types of distresses affect cement concrete pavement at different degrees. The determination of dominant distresses of the pavement preventive maintenance (PM) and its judgement standard can provide corresponding basis for PM decision. In this paper, 22 military airports in Northeast China, such as Heilongjiang Province, Jilin Province, and Liaoning Province, were selected to collect the data of pavement distresses. Based on the structural equation model (SEM), the structural relationship between the influencing factors of each distress and the pavement damage was established, and the goodness-of-fit of the model was tested. In addition, through path analysis, the influence degree of five kinds of latent variables such as joint distress, surface distress, vertical distress, repair distress, and fracture distress on pavement damage was obtained. Four distresses, such as corner peeling, surface peeling, surface crack, and interplate slip, were identified as the dominant distresses of PM of cement concrete pavement. On this basis, a binary classification model of confusion matrix was constructed. The basic evaluation index, receiver operating characteristic (ROC) curve, and Kolmogorov–Smirnov (KS) curve were used to comprehensively determine the judgement standard of the dominant distresses of pavement PM from multiple evaluation angles (corner peeling rate ≤ 35%, surface peeling rate ≤ 30%, surface crack rate ≤ 8%, and interplate slip rate ≤ 0.5%). The judgement standard can be combined with the corresponding prediction model to determine the optimal timing of PM of cement concrete pavement and provide pavement maintenance managers with the support of decision-making. [ABSTRACT FROM AUTHOR]

Following the trends of Chinese rural transformation development, and the sustainable development goals for resources and environment, reasonable arranging the potential development space and the ecological space, so as to optimize the distributions of rural settlement would be the key challenge for rural areas in ecologically fragile regions. From the perspective of maintaining regional ecological security, this paper takes Da'an City, a typical ecological fragile region in Jilin Province, as the case area, constructing the comprehensive ecological security pattern (ESP) on basis of landscape ecology, and applying the landscape pattern indexes to quantitative analysis the spatial distribution characteristics of rural settlements. Then, different optimization directions and management strategies are put forward for rural settlements in each secure zone under the comprehensive ESP. The experimental results showed that 1) the area of the low security zone, the general security zone, the moderate security zone and the extreme security zone was 1570.18 km2, 1463.36 km2, 1215.80 km2 and 629.77 km2, representing 32.18%, 29.99%, 24.92% and 12.91% of the total area of the target area, respectively. 2) The rural settlements in Da'an City were characterized by a high degree of fragmentation with a large number of small-scale patches. 3) The area of rural settlements in the ecological relocation zone, the in situ remediation zone, the limited development zone and the key development zone was 22.80 km2, 42.31 km2, 36.28 km2 and 19.40 km2, accounting for 18.88%, 35.03%, 30.04% and 16.06% of the total area of rural settlements, respectively. Then, different measures were proposed for settlements in different optimization zones in order to scientifically plan important ecological space, production space and living space in rural areas. This paper aims to provide fundamental support for rural settlements based on redistribution from the perspective of landscape ecology and provide insights for rural planning and rural habitat environmental improvement. [ABSTRACT FROM AUTHOR]

In recent years, college students have emerged as the main players in Chinese innovation and start-ups. Based on the TPB theory, this paper introduced the start-up education variables and established the influence model of start-up education for university students in China on the motivation of start-up. In this paper, a questionnaire containing five variables, including behavior attitude, subjective norms, perceived behavior control, entrepreneurship education and entrepreneurial intention, was investigated for students from six universities in Jilin Province, China, and statistical analysis was carried out using SPSS23.0. The study found that the entrepreneurship education of college students had the greatest impact on entrepreneurial intentions compared to the three elements of planned behavioral theory: behavioral attitudes, subjective norms and perceived behavioral control. This paper has a guiding significance in strengthening start-up education in universities. This study was conducted only for students from six universities in Jilin Province, China, and the scope of the study needs to be expanded throughout China in order to generalize the research results. [ABSTRACT FROM AUTHOR]

The water carrying capacity and the water carrying state are two similar concepts, and there are no clear boundaries between them, so there exists confusion during the evaluation process. Additionally, current evaluation methods cannot meet the dynamic change requirements under different control measures. This study emphasizes the difference between the two concepts and points out that the core of the water carrying capacity is the determination of thresholds. In contrast, that of the water carrying state is a state evaluation. A coupled iterative model is proposed based on the extended Fourier amplitude sensitivity test algorithm and a modified state-space method. In order to evaluate and regulate the water carrying state dynamically, the iterative calculation is introduced into the evaluation of the water carrying state. During the iterative process, the water resources in the non-overloaded area are allocated to the surrounding adjacent overloaded areas until the water resource carrying state of the original overloaded area reaches an acceptable level, and the total amount of water resources allocation during multiple iterations is given. In this study, we take Jilin Province as the research object. We hope that the iterative coupling model of the water carrying state proposed in this paper can be widely applied in the future. [ABSTRACT FROM AUTHOR]

Jilin Province is one of the important grain-producing regions in China, the frequent drought and waterlogging events in this region have seriously impacted local agricultural production, therefore, it is particularly necessary to explore the spatiotemporal variations in drought and waterlogging and how they effect on maize yields. In this paper, we use the daily meteorological data recorded at 27 meteorological stations in Jilin Province from 1961 to 2020 to calculate the modified crop water deficit index (mCWDI), which were based on the daily crop coefficient (Kc) corresponding to different growth stages for each station. The spatiotemporal evolution processes of drought and waterlogging during the growing season in Jilin Province were analysed by the linear regression model, and the impacts of drought and waterlogging conditions on maize yields in Jilin Province under different growing seasons were quantified by means of the correlation analysis and multiple regression analysis methods. The results showed that the effective precipitation during the whole reproductive period showed a spatial distribution pattern of decreasing from southeast to northwest, with precipitation totals ranging from 335.02 to 677.38 mm, while the spatial distribution of the water demand showed the opposite trend. The south-eastern region of Jilin Province was in a state of water surplus, while the precipitation in other areas could not meet the water requirements of maize, resulting in decreasing drought frequency trends from northwest to southeast and from the early stage to the developmental stage of maize; in addition, increasing trends were observed in the middle and late reproductive stages of maize. The waterlogging frequency in the south-eastern region showed the spatial distribution characteristics of being higher in the early and late reproductive periods and lower in the development period of maize, and the growth rate of the maize-waterlogging frequency was higher in central Jilin Province than in other areas. Moreover, drought showed a more significant negative correlation with the maize yield in Jilin Province, while waterlogging showed a positive correlation. The relative importance results show that drought has a greater impact on maize yields than waterlogging, and the impacts of drought and waterlogging events on maize yields are mainly concentrated in the middle and late growth periods. The findings could inform the development of contingency plans for farmers to minimize crop losses and ensure food security in the region. [ABSTRACT FROM AUTHOR]

Soil moisture plays an important role in crop yield estimation, irrigation management, etc. Remote sensing technology has potential for large-scale and high spatial soil moisture mapping. However, offline remote sensing data processing is time-consuming and resource-intensive, and significantly hampers the efficiency and timeliness of soil moisture mapping. Due to the high-speed computing capabilities of remote sensing cloud platforms, a High Spatial Resolution Soil Moisture Estimation Framework (HSRSMEF) based on the Google Earth Engine (GEE) platform was developed in this study. The functions of the HSRSMEF include research area and input datasets customization, radar speckle noise filtering, optical-radar image spatio-temporal matching, soil moisture retrieving, soil moisture visualization and exporting. This paper tested the performance of HSRSMEF by combining Sentinel-1, Sentinel-2 images and in-situ soil moisture data in the central farmland area of Jilin Province, China. Reconstructed Normalized Difference Vegetation Index (NDVI) based on the Savitzky-Golay algorithm conforms to the crop growth cycle, and its correlation with the original NDVI is about 0.99 (P < 0.001). The soil moisture accuracy of the random forest model (R2 = 0.942, RMSE = 0.013 m3/m3) is better than that of the water cloud model (R2 = 0.334, RMSE = 0.091 m3/m3). HSRSMEF transfers time -consuming offline operations to cloud computing platforms, achieving rapid and simplified high spatial resolution soil moisture mapping. [ABSTRACT FROM AUTHOR]

The development statuses of cities are intimately associated with their spatial scales. Multiscale trajectories of cities are lenses through which can be discerned the pattern and tendency of regional development. In this paper, using comparisons of demographic and economic development, geographic detectors, and hierarchical logistic regressions, we examine the evolutionary characteristics and influential factors of multiscale urban development in Jilin Province, China. The findings show that alongside the "top-down" transformations of the spatial scales, the typologies of urban development tend to diversify. Economic and political factors played key roles in the divergence of growth and shrinkage of prefecture-level, while natural and social factors had strong effects on the divergence between growth and shrinkage of county-level cities and small towns. Moreover, urban development has demonstrated scale connection: towns under the jurisdictions of absolutely growing county-level cities are likely to be subjected to smart shrinkage; towns under the jurisdictions of smartly growing county-level cities are prone to potential shrinkage; towns under the jurisdictions of absolutely shrinking county-level cities are at risk of absolute shrinkage. Our findings recommend that regional policies take multiscale spaces into account to capture regularity of regional development. [ABSTRACT FROM AUTHOR]

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Ground-penetrating radar (GPR) is an efficient and nondestructive geophysical method with great potential for detecting soil water content at the farmland scale. However, a key challenge in soil detection is obtaining soil water content rapidly and in real-time. In recent years, deep learning methods have become more widespread in the earth sciences, making it possible to use them for soil water content inversion from GPR data. In this paper, we propose a neural network framework GPRSW based on deep learning of GPR data. GPRSW is an end-to-end network that directly inverts volumetric soil water content (VSWC) through single-channel GPR data. Synthetic experiments show that GPRSW accurately identifies different VSWC boundaries in the model in time depth. The predicted VSWC and model fit well within 40 ns, with a maximum error after 40 ns of less than 0.10 cm3 × cm−3. To validate our method, we conducted GPR measurements at the experimental field of the Academy of Agricultural Sciences in Gongzhuling City, Jilin Province and applied GPRSW to VSWC measurements. The results show that predicted values of GPRSW match with field soil samples and are consistent with the overall trend of the TDR soil probe samples, with a maximum difference not exceeding 0.03 cm3 × cm−3. Therefore, our study shows that GPRSW has the potential to be applied to obtain soil water content from GPR data on farmland. [ABSTRACT FROM AUTHOR]

Soil nutrient content is an important index to determine the amount of fertilizer. Traditional soil nutrient content is obtained by manual sampling, which greatly increases the cost of agricultural production input. In order to solve this problem, this paper studies the relationship between soil nutrients, fertilizer amount, yield and the next year's soil nutrients, and establishes an optimized BP neural network model to realize the prediction of soil nutrient content. Aiming at the problem that the traditional BP neural network model will affect the prediction accuracy due to the different weights and thresholds, the Grey Wolf algorithm with reverse learning mechanism is introduced to obtain the optimal solution of BP neural network weights and thresholds. The soil nutrient content data collected in chenjiadian village, Nongan County, Jilin Province for five consecutive years were used to test the model. The data of the first four years were used as the training set and the data of the fifth year as the test set. The prediction results of BP neural network model, Grey Wolf algorithm optimized BP neural network model and Grey Wolf algorithm optimized BP neural network model with reverse learning mechanism were compared The prediction accuracy of BP neural network model optimized by Grey Wolf algorithm with reverse learning mechanism reached 88.7%, which was better than the first two models. It can provide basis for the fertilization decision of variable rate fertilization in the next year, so as to reduce the input of labor cost. [ABSTRACT FROM AUTHOR]

The current methods for evaluating the operating condition of electricity transmission lines (ETLs) and providing early warning have several problems, such as the low correlation of data, ignoring the influence of seasonal factors, and strong subjectivity. This paper analyses the sensitive factors that influence dynamic key evaluation indices such as grounding resistance, sag, and wire corrosion, establishes the evaluation criteria of the ETL operation state, and proposes five ETL status levels and seven principles for selecting evaluation indices. Nine grade I evaluation indices and twenty-nine grade II evaluation indices, including passageway and meteorological environments, are determined. The cloud model theory is embedded and used to propose a warning technology for the operation state of ETLs based on inspection defect parameters and the cloud model. Combined with the inspection defect parameters of a line in the Baicheng district of Jilin Province and the critical evaluation index data such as grounding resistance, sag, and wire corrosion, which are used to calculate the timeliness of the data, the solid line is evaluated. The research shows that the dynamic evaluation model is correct and that the ETL status evaluation and early warning method have reasonable practicability. [ABSTRACT FROM AUTHOR]

The high-precision regional geoid model provides important fundamental geospatial information for developing and applying many disciplines. Deterministic and stochastic modifications are applied to Stokes's and Hotine's formulas of geoid modeling to reduce errors. Based on the Experimental Geopotential Model 2019 (XGM2019), this paper used Stokes's and Hotine's formulas to analyze the variation of global root mean square error (RMSE) with modification parameters for two deterministic (Wong and Gore; and Vaníček and Kleusberg) and three stochastic modifications (biased, unbiased, and optimum). Taking the quasigeoid refinement of Jilin Province as an example, the global RMSE, approximate geoid undulation, and additive corrections were calculated. The parameter analysis and the global RMSE calculation showed that the variation of the modification limits and the terrestrial gravity data error variance had a centimeter-level effect on the global RMSE. In contrast, the impact of the integration radius was relatively small. The stochastic modifications were better than the deterministic ones in calculating the global RMSE. The global RMSE of Hotine's formula was smaller than that of Stokes's, and its unbiased and optimum modifications reached the minimum value of 12.9 mm. The validation of XGM2019 and the refined quasigeoid based on the high accuracy GPS/leveling points showed that the standard deviation (STD) of XGM2019 was 5.8 cm in Jilin Province, and the refined optimal quasigeoid model was 2.9 cm. Stokes's and Hotine's formulas provided the same accuracy in the study area. In the western plain area, the accuracy of the deterministic modifications was 2.0 cm, which was about 0.4 cm higher than that of the stochastic modifications. In the eastern mountainous area, the stochastic modifications were better than the deterministic ones, and the accuracy was about 3.2 cm. Stokes's and Hotine's formulas based on deterministic and stochastic modifications significantly improve the accuracy of the XGM2019. The deterministic and stochastic modifications show millimeter-level differences in plain and mountainous areas. [ABSTRACT FROM AUTHOR]

The Erdaopuzi section in the Baishan area of Jilin Province, northeast China, contains abundant late Tremadoc graptolites. However, there are some taxonomic controversies regarding the characters of the hand specimens that are difficult to identify. In this paper, we present our restudy of isolated graptolites from acid residue and discuss the taxonomic problems of the subgenus Clonograptus (Neoclonograptus) Zhao and Zhang. Four genera and six species were identified, including Adelograptus tenellus (Linnarsson), Ancoragraptus gracilis (Zhao and Zhang), Dictyonema sp., Psigraptus jacksoni Rickards and Stait, Psigraptus lenzi Jackson, Psigraptus arcticus Jackson. According to the significant evolution of morphological characters, two graptolite zones (from bottom to top) can be identified in ascending order in the study area, i.e. Adelograptus Zone and the Psigraptus Zone. [ABSTRACT FROM AUTHOR]

In this paper, a novel fingerprint method was established for the quality control of Rana chensinensis eggs (RE) by high-performance liquid chromatography (HPLC). Cluster analysis and principal component analysis were performed. Besides, the antitussive effect of RE was explored. The analysis was achieved on a Kromasil 100-5C18 (4.6 mm × 250 mm, 5 μm) column by gradient elution using methanol-0.1% phosphoric acid solution as the mobile phase. The influence of RE on cough latent periods and cough times of mice was investigated via an ammonia cough-inducing experiment. The validated HPLC method was precise, reproducible, and stable. The HPLC fingerprints of 10 batches of RE samples displayed 31 well-resolved common peaks in the chromatogram. Three of these peaks were identified and assigned to 1-methyl hydantoin, estradiol, and 4-cholestene-3-one. The similarities of 10 batches of samples were more than 0.95. RE from different origins could be classified into three groups via SPSS 23.0 software, suggesting RE samples from various provinces (Jilin, Liaoning, and Heilongjiang) can be well distinguished via the established method. High dose and middle dose of the RE group can significantly prolong the cough latent periods of mice (P < 0.05 or P < 0.01) and inhibit the cough times of mice (P < 0.01), indicating RE had a good antitussive effect. HPLC fingerprint combined with multicomponent determination can be an efficient and useful method for monitoring the quality of RE. This study also provided a more comprehensive strategy for the quality evaluation of RE. [ABSTRACT FROM AUTHOR]

Physalins, active ingredients from the Physalis alkekengi L. var. franchetii (P. alkekengi) plant, have shown anti-inflammatory, antioxidant and anticancer activities. Whereas the bioactivity of physalins have been confirmed, their biosynthetic pathways, and those of quite a few derivatives, remain unknown. In this paper, biosynthesis and structure modification-related genes of physalins were mined through transcriptomic and metabolomic profiling. Firstly, we rapidly and conveniently analyzed physalins by UPLC-Q-TOFMS/MS utilizing mass accuracy, diagnostic fragment ions, and common neutral losses. In all, 58 different physalin metabolites were isolated from P. alkekengi calyxes and berries. In an analysis of the physalin biosynthesis pathway, we determined that withanolides and withaphysalins may represent a crucial intermediate between lanosterol and physalins. and those steps were decanted according to previous reports. Our results provide valuable information on the physalin metabolites and the candidate enzymes involved in the physalins biosynthesis pathways of P. alkekengi. In addition, we further analyzed differential metabolites collected from calyxes in the Jilin (Daodi of P. alkekengi) and others. Among them, 20 physalin metabolites may represent herb quality biomarkers for Daodi P. alkekengi, providing an essential role in directing the quality control index of P. alkekengi. [ABSTRACT FROM AUTHOR]

As the first‐wave COVID‐19 has passed in 2020, people's awareness of self‐protection began to decline gradually. How to prevent and control the second‐wave COVID‐19 has become an important issue in many countries and regions. By analyzing the transmission of the second‐wave COVID‐19 caused by an imported case in Tonghua City, Jilin Province, China, in January 2021, we establish a new mathematical COVID‐19 model to simulate the transmission characteristics of the second‐wave COVID‐19. First, we analyze the basic properties of the model, prove the existence of the equilibrium point, and obtain the expression of the basic reproduction number with important biological significance. Secondly, we use the weighted nonlinear least square estimation method to fit the cases in Tonghua City of Jilin Province in January 2021, and get the estimated value of the parameters. The basic reproduction number of the second‐wave COVID‐19 in Tonghua City is R0=1.0695, which is much smaller than that of the first‐wave COVID‐19 in Wuhan in 2020. Finally, in the optimal control part, we consider two control methods (keeping social distance and nucleic acid detection of all people in the city) to simulate the control of the disease. The results show that the control intensity of the two control methods needs to be dynamically changed and adjusted, so that the cost can be minimized with the least infection. The results of this paper can not only provide suggestions for health management departments, but also provide a reference for the analysis of the second‐wave COVID‐19 in other countries or regions. [ABSTRACT FROM AUTHOR]

The Longgang volcanic field (LVF) is one of the largest intraplate monogenetic volcanic regions in China, and eruption lasted from the early Pleistocene to the Holocene. Previous research shows that the LVF is not only experiencing rapid surface uplift but also significant seismic activity. The magmatic system under the LVF poses a hazard of potential eruption. The three‐dimensional electrical resistivity model developed by magnetotelluric data shows that the upper crust of the LVF and the surrounding areas hosts a high‐resistivity body composed of volcanic rocks produced by massive eruptions during past volcanic episodes. There are two main high‐conductivity structures below the depth of 10 km in the southwest and northeast of the LVF. The two structures merge in the lower crust and extend to the mantle. We interpret these high‐conductivity structures to be magmatic channels (the resistivity of C1 is 20–50 and C2 is 5–20 Ωm). Magmatic channel upwelling along the C1 may have caused the eruption of the Jinlongdingzi volcano 1,700 years ago. The C2 magmatic channel in the northeast of the LVF is larger and lower resistivity than C1. The modern surface uplift and seismicity in the LVF is a result of upwelling and intrusion along C2 magmatic channel. The Hunjiang fault passing through the LVF may also influence the upwelling of material along the C2 magmatic channel, posing a hazard of future eruption in the LVF. The high‐conductivity structures in the LVF pass through the Moho and extend to the upper mantle and are connected from the top to bottom. Combined with geochemical data, we speculate that the magmatic system in the LVF may directly come from the upper mantle and the magma has experienced rapid ascent with limited crustal internal evolution. Plain Language Summary: The Longgang volcanic field (LVF) is one of the main active volcanic regions in Jilin Province, northeast China. It is densely populated and economically developed, and it is also the most important food production place and tourist region in China. Therefore, the risk of volcanic and seismic activity in this area has always been the focus of attention and research. Through a geophysical method called Magnetotellurics, we develop a three‐dimensional electrical resistivity model of the LVF. The model reveals two crustal and mantle scale magmatic channels C1 and C2. The modern crustal uplift and seismicity are result of upwelling and intrusion of the C2 magmatic channel, posing a hazard of future eruption in the LVF. The results of this paper can provide deep geophysical basis for the prediction of volcanic magma system and eruption risk. Key Points: Broadband magnetotelluric data were used to generate a three‐dimensional electrical structure of the Longgang volcanic field (LVF) and adjacent areasThe modern crustal uplift and seismicity in the LVF is a result of upwelling and intrusion of the electrically conductive zone interpreted as a magmatic channelThe magmatic system in the LVF is sourced from the deep mantle and has experienced rapid uplift and limited crustal internal evolution [ABSTRACT FROM AUTHOR]

The increasing scarcity of cultivated land resources necessitates the continuous change in cultivated land functions. Cultivated land has gradually changed from being used for a single function to multiple functions. The use of cultivated land for multiple functions has become an important way to achieve the sustainable use, management, and protection of cultivated land. In this, the development of different functions of cultivated land must be coordinated. Thus, clarifying the evolution trend of the use of cultivated land for various functions, calculating the coupling and coordination degrees of these multiple functions, and identifying the driving factors in these uses play important roles in realizing the orderly development of cultivated land multifunctionality. This paper defined multifunctioning cultivated land as containing a production function, a social function, and an ecological function. Based on the socioeconomic panel data and geospatial data of Heilongjiang, Jilin, and Liaoning, which are the major grain-producing areas of northeast China, in the years 2005, 2010, 2015, and 2020 we calculated the multiple function coupling coordination degree of cultivated land using the Coupling Coordination Degree Model and identified the driving forces in the evolution of the spatial-temporal pattern of cultivated land multifunctionality using Geodetector. The results show that from 2005 to 2020, there were significant regional differences in terms of the production, social, and ecological functions of cultivated land in the research areas. The multifunctional coupling coordination degree of cultivated land in the study areas was gradually improved. The spatial-temporal evolution of the multifunctional coupling coordination degree of cultivated land was found to mainly be influenced by the level of agricultural development, such as the level of per capita disposable income and the rate of effective irrigation of cultivated land. The government should attempt to guarantee the comparative benefits of agricultural production to increase the income level of farmers; increase investment in agricultural infrastructure construction to improve the level of agriculture development; and implement a strict farmland protection policy to achieve the continuous improvement of the productivity of cultivated land, realize the ordered development of coupling, and improve the coordination of the use of cultivated land for multiple functions. The results of this study are applicable not only to northeast China but also to other major grain-producing areas that are under pressure to protect their cultivated land and achieve the suitable use of cultivated land. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

How to explore the allocation and green utilization level of urban construction land resources has an important role in the sustainable development of the city. Taking 47 counties and cities in Jilin Province as an example, this paper evaluates the green utilization efficiency of urban construction land (GUEUCL) in 2011 and 2015 by using the unexpected output super-SBM model and explores the spatial-temporal differentiation characteristics and influencing factors of GUEUCL by using GIS and machine learning methods. The results show that (1) the GUEUCL in Jilin Province is low, mainly distributed in small- and medium-sized areas, with significant positive spatial correlation. The L-L concentration area is mainly distributed in the eastern region, but the degree of spatial concentration is small, the spatial structure characteristics of the two periods are different, and the spatial heterogeneity is large; (2) the internal factor decomposition shows the impact of pure technical efficiency on the comprehensive efficiency and the restriction ability is stronger than the scale efficiency, that is to say, the factors such as management and technology have a greater impact on the comprehensive efficiency; (3) the relative importance of external factors has always been ranked as socioeconomic factors, urban development factors, and natural science and technology factors. This paper focuses on the temporal and spatial characteristics of each county and city and the influencing factors, which provides a certain value reference for the pilot of ecological construction and the development of ecoenvironmental benefit economic system in Jilin Province. [ABSTRACT FROM AUTHOR]

As an important river in the central part of Jilin Province, the Yinma River plays a crucial role in the daily lives of the people in Jilin Province. In this paper, 15 cross sections were selected in the Yinma River basin. Based on the water quality monitoring data from 2012 to 2021, referring to the Environmental Quality Standards for Surface Water (GB 3838 - 2002) and historical monitoring data of the river, dissolved oxygen (DO), five-day biochemical oxygen demand (BODS), permanganate index (CODMn), chemical oxygen demand (COD), ammonia nitrogen (NH4-N), total phosphorus (TP), and total nitrogen (TN) were determined as 7 evaluation indicators, and the water quality of 15 cross sections in the Yinma River basin was comprehensively evaluated. A characteristic analysis was conducted on the water quality of the Yinma River, and its pollution sources were identified. Based on the conclusions, constructive control measures were proposed. [ABSTRACT FROM AUTHOR]

This paper develops a regional new energy industry (NEI) competitiveness evaluation index system based on the theoretical framework of the "diamond model" and the unique characteristics of the new energy industry and made an empirical analysis of Jilin province with analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method. The analysis results show that the new energy industry in Jilin Province has a good foundation, and the government's role, talent support, technological innovation, and market factors are acceptable. However, due to location factors and resource endowments, regional GDP and per capita consumption expenditure are low. The lack of intrinsic motivation of industrial competitive advantage has resulted in the poor overall competitiveness of the new energy industry in Jilin Province. Then, it is advised to take targeted measures to work closely with national NEI development strategy, optimize the industrial technology innovation ability and the talent support, actively guide social capital flows and new energy consumption, optimize regional energy consumption structure and industrial structure by creating a complete NEI chain, and revitalize the whole economy. [ABSTRACT FROM AUTHOR]

In the era of economic globalization, the competitiveness of products on a global scale is increasingly achieved through effective and sustainable strategies for brand development by the leaders. This paper conducts an empirical study on regional brand competitiveness (BC) influencing factors. A research model was proposed and tested by employing structural equation modeling. Data analysis was conducted using 214 valid questionnaires from two major producing areas in Jilin Province, China. Research results show that Brand Market (BM) and Government Guidance (GG) directly and positively impact the regional BC. Regional Resource (RR) and industrial development (ID) indirectly impact the regional BC through the mediating role of BM and GG. BM is the most important factor affecting the regional BC. Based on this, the path to improve the competitiveness of traditional agricultural products under economic globalization is determined, and targeted countermeasures and suggestions are formulated for the existing problems. [ABSTRACT FROM AUTHOR]

The summer monsoon–affected area is a suitable area for agricultural production in China. Against the background of climate warming, the activity of the summer monsoon is changing significantly. The drought and flood disasters in this region are becoming more and more frequent and have a greater and more serious impact on agricultural production. Therefore, based on observational data from meteorological stations and yield loss data in agriculture caused by drought and flood disasters in summer monsoon–affected areas, this paper studied the characteristics of the hazard of disaster-causing factors, the risk of losses to agriculture caused by droughts and floods, and their correlation. Moreover, it compared and analyzed the variability of drought and flood hazard and risk to agriculture before and after a temperature rise. The results showed that the precipitation in summer monsoon–affected areas is obviously affected by monsoon activities, and there is an overall though non-significant positive correlation between annual average standardized precipitation evapotranspiration index (SPEI) and the summer monsoon activity index (MI). The drought disaster comprehensive loss rate (DCLR) was generally higher than the flood disaster comprehensive loss rate (FCLR). This shows that the impact of drought on agriculture production is significantly greater than that of floods in this area. The high hazard and risk areas for drought were mainly distributed along the edge of the summer monsoon area and in its vicinity, whereas the high hazard and risk areas for flooding were mainly distributed in the lower reach of the Yangtze, Songhua, and Liaohe Rivers. Among them, Liaoning, Jilin and Heilongjiang are high-risk superposition areas of drought and flood disasters. The hazards of drought and flood dominate the risk of disaster loss. Climate warming has significantly expanded the high-hazard and high-risk ranges in China for drought and flood disasters and has also changed their spatial distribution patterns. The high-hazard area for drought has shifted to the monsoon edge area, the high-risk area for drought has moved northward, and both the high-hazard and the high-risk areas for floods have clearly moved southward. The impact of climate warming on drought was more significant than on floods. This study provides important scientific guidance for formulating drought and flood disaster prevention planning and agricultural production development patterns in China. [ABSTRACT FROM AUTHOR]

Cultivated-land multi-functionality has become an important way to achieve sustainable cultivated-land protection, and it has become a hot spot in the field of land-management policy. Taking the cultivated black soils in the grain-producing area of Jilin Province, Northeast China, as a case study, this paper assessed the multi-functions of cultivated land over the past 30 years by applying the improved TOPSIS model. Furthermore, the key limiting factors and influencing factors of the multi-functions of cultivated land were identified through the obstacle-degree model and the Geo-detector. The results show that the level of multi-functionality rose from 1990 to 2020, but an increase in both economic and social functions hindered improvements in the ecological function of cultivated land. There were obvious spatial differences in the functions of cultivated land in different counties, with ecological functions showing the highest degree of differentiation, followed by social and economic functions. The per capita agricultural output, the degree of agricultural mechanization, the average output from cultivated land, and the agricultural-labor productivity had the most restrictive effects on the functions of cultivated land, with barrier-degree values of 15.90, 13.90, 11.76, and 10.30, respectively. Coupling–coordination in the multi-functions and sub-functions of cultivated land showed an upward trend, from "low coupling coordination–antagonistic coupling coordination" to "high coupling coordination-optimal coupling coordination". The government should include the level of multi-functional utilization in future policies for the management and utilization of cultivated land and take measures to reduce the differences in the functions of cultivated land among regions. Quantifying the multi-functional value of cultivated land and subsidizing land cultivation should encourage farmers to protect the land and help to strengthen multi-functional planning and functional design, improve ecological utilization, and promote the sustainable use of cultivated land. [ABSTRACT FROM AUTHOR]

Parameter sensitivity analysis can determine the influence of the input parameters on the model output. Identification and calibration of critical parameters are the crucial points of the process model optimization. Based on the Extended Fourier Amplitude Sensitivity Test (EFAST) and the Morris method, this paper analyzes and compares the parameter sensitivity of the annual mean net primary productivity (NPP) of Larix olgensis Henry forests in Jilin Province simulated by the Lund–Potsdam–Jena dynamic global vegetation model (LPJ model) in 2009–2014 and 2000–2019, and deeply examines the sensitivity and influence of the two methods to each parameter and their respective influence on the model's output. Moreover, it optimizes some selected parameters and re-simulates the NPP of Larix olgensis forests in Jilin Province from 2010 to 2019. The conclusions are the following: (1) For the LPJ model, the sensitive and non-influential parameters could be identified, which could guide the optimization order of the model and was valuable for model area applications. (2) The results of the two methods were similar but not identical. The sensitivity parameters were significantly correlated (p < 0.05); parameter krp was the most sensitive parameter, followed by parameters αm, αa and gm. These sensitive parameters were mainly found in the photosynthesis, water balance, and allometric growth modules. (3) The EFAST method had a higher precision than the Morris method, which could calculate quantitatively the contribution rate of each parameter to the variances of the model results; however, the Morris method involved fewer model running times and higher efficiency. (4) The mean relative error (MRE) and mean absolute error (MAE) of the simulated value of LPJ model after parameter optimization decreases. The optimized annual mean value of NPP from 2010 to 2019 was 580 g C m−2 a−1, with a mean annual growth rate of 2.13%, exhibiting a fluctuating growth trend. The MAE of the simulated value of LPJ model after parameter optimization decreases. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering Management / Gongcheng Guanli Xuebao is the property of Journal of Engineering Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The green and sustainable development of fisheries is a crucial way to safeguard the environment, guarantee food security, and promote social and economic development. In the rapidly evolving era of digitalization, how to fully leverage the advantages of digitalization to motivate fishery sustainable development has become a worthy research question. Based on combing the development stage and characteristics of Chinese fishery digitalization, this paper selects six fishery digitalization factors from the perspective of configuration based on the technology-organization-environment (TOE) theoretical framework, and uses the panel fuzzy-set qualitative comparative analysis (fsQCA) method to explore the configurational path of how digitalization empowered the sustainable development of fisheries in China from 2011 to 2021. This paper found that: (1) Fishery digitalization can significantly enhance the level of fishery sustainable development, but individual elements of fishery digitalization are not necessary conditions for realizing a high degree of fishery sustainable development. However, strengthening digitalization talent support plays a more universal role. (2) Four types of fishery digital ecology can generate a high level of fishery sustainable development, demonstrating the multiple paths and complex mechanisms of fishery digitalization empowering fishery sustainable development. (3) In underdeveloped areas such as Jilin, Hunan, and Qinghai, the empowering effect of digitalization on the sustainable development of fisheries is relatively limited. The research findings open the "black box" of how digitalization empowers the sustainable development of fisheries, providing theoretical reference for various types of provinces to utilize digitalization to drive the sustainable development of fisheries. [Display omitted] • Theoretical framework is based on the configuration perspective and TOE framework. • We use the panel fsQCA method to explore fishery digitalization empowerment pathways. • Four types of fishery digital ecology can generate high fishery sustainability. • Digital talent support plays a more general role in fishery sustainable development. • The empowering effect of digitalization is relatively limited in underdeveloped areas. [ABSTRACT FROM AUTHOR]

Because of the particularity of energy being non-renewable, the development of energy-intensive cities must consider its follow-up development issues in advance, especially for newly developed energy-intensive cities like Songyuan in the midwest of Jilin Province. It is necessary to summarize the experience from other energy-intensive cities and recognize the problems existing in its own development, so that the development of the city will not perish due to the exhaustion of energy. At present, the sustainable development of energy-intensive cities is the focus of attention at home and abroad. Energy-intensive cities have made great contributions to the national and regional economy but also paid a considerable price. Making the city continue to prosper and develop steadily without causing the city to decline due to the exhaustion of energy is the main problem facing the country, the government, and experts and scholars. Taking Songyuan City in Northeast China as an example, this paper adopts a combination of breakthroughs from the surface and breakthroughs, supplemented by theoretical analysis and empirical evaluation, and uses mathematical model simulation and expert consultation and decision-making methods. Starting from the theoretical height of man-land harmony and sustainable development, we construct an evaluation model of rural development status in energy-enriched poverty-stricken areas, evaluate the evolution trend of rural development status, and propose leading models and development strategies for rural transformation and development in energy-enriched poverty-stricken areas. It provides theoretical reference and decision-making basis for the sustainable development of rural Songyuan City. [ABSTRACT FROM AUTHOR]

In the past few years, the increasing amount of space debris has triggered the demand for distributed surveillance systems. Long exposure time can effectively improve the target detection capability of the wide-area surveillance system. Problems that also cause difficulties in space-target detection include large amounts of data, countless star points, and discontinuous or nonlinear targets. In response to these problems, this paper proposes a high-precision space-target detection and tracking pipeline that aims to automatically detect debris data in space. First, a guided filter is used to effectively remove the stars and noise, then Hough transform is used to detect space debris, and finally Kalman filter is applied to track the space debris target. All experimental images are from Jilin Observatory, and the telescope is in star-tracking mode. Our method is practical and effective. The results show that the proposed automatic extraction channel of space debris can accurately detect and track space targets in a complex background. [ABSTRACT FROM AUTHOR]

Using the hourly monitoring data of pollutants from 16 automatic atmospheric monitoring stations in eastern Jilin Province from 2015 to 2020, this paper analyzed the temporal and spatial distribution laws of CO, SO2, NO2, PM10, PM2.5, and O3 in eastern Jilin Province. At the same time, the regional transport pathways of pollutants were analyzed using the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model; the potential source contribution function (PSCF) analyzed the potential source area of PM2.5. Finally, the "weekend effect" of CO, NO2, PM2.5, and O3 was analyzed. The results showed that the six pollutants showed a downward trend year by year. The concentrations of O3, PM10, and PM2.5 were higher in northwest Jilin, and the concentrations of SO2 and CO were higher in southwest Jilin. Except for CO, the seasonal variation of pollutants was pronounced. Except for O3, most pollutants had the highest concentration in winter. Hourly variation analysis described that SO2 and O3 had only one peak in a day, and the other four pollutants showed "double peak" hourly variation characteristics. The study area was mainly affected by the airflow pathway from northwest and southwest. The weight potential source contribution function (WPSCF) high-value area of PM2.5 was northwest and southwest. O3 showed a "negative weekend effect", and NO2 and CO showed a "positive weekend effect". [ABSTRACT FROM AUTHOR]

With regard to environmental facilities, blindness and the subjectivity of site selection lead to serious economic, engineering and social problems. A proper siting proposal often poses a challenge to local governments, as multiple factors should be considered, such as costs, construction conditions and social impact. How to make the optimal siting decision has become a topical issue in academic circles. In order to enrich the framework of site selection models, this study combined GIS, AHP and Remote Sensing (RS) technologies to conduct siting suitability analysis of sewage treatment plants, and it was first applied in the Liao River basin in Jilin Province in China. The enriched model is able to reveal blindness in the former site selection of sewage treatment plants and explore optimal siting areas, involving an effective quantification method for summer dominant wind direction and urban stream direction. In a case study, it was found that local governments need to be cautious of the distance of sites from rivers and residential areas and the impact of these sites on downwind and downstream residents. Additionally, siting suitability has obvious regional characteristics, and its distribution varies significantly between towns. Huaide Town shows the largest optimal siting areas and can be given priority for the construction of new sewage treatment plants. This paper developed a more scientific approach to site selection, and the outcome can provide a robust reference for local governments. [ABSTRACT FROM AUTHOR]

National nature reserves are an important part of classification management on ecological protection in China. Taking the national nature reserves of Jilin Province as examples, this paper introduced the stability index by referring to the intensity model of land-use and land-cover change (LUCC), and analyzed the overall stability of land-use and land-cover (LULC) in the study area from the time interval level and land category level. The stability of LULC in different types of nature reserves was tracked and identified by extracting land-use change trajectory, and the land-use change trajectory was divided into three types: stable type, sub-stable type and unstable type. The impact of LUCC on regional ecosystem services was studied by using hotspot analysis and gravity center analysis. The results showed that: 1) The LULC in the study area was stable on the whole, and the proportion of stable land area reached 86.08%. The intensity of LUCC showed an increasing trend in recent 20 years, and the conversion of cultivated land and construction land was active in continuous time interval. 2) The stability of LULC in forest ecological reserves and wildlife reserves in the eastern part of Jilin Province was the highest, while that in inland wetland reserves and geological relic reserves in the central and western part of Jilin Province was lower. 3) The LUCC in national nature reserves not only changed the value of its own ecosystem service function, but also affected the ecosystem service function of the whole region. The combination of intensity analysis and land-use change trajectory was used to identify the characteristics of stability of LULC in nature reserves, which was conducive to deeply understand the process of LUCC in national nature reserves and provided reasonable suggestions for regional ecological protection. [ABSTRACT FROM AUTHOR]

As the global ecosystem has been severely disturbed by an increasing number of human activities at different scales, remote sensing technology, as an effective quantitative measure of environmental quality, has been widely used. The remote sensing ecological index (RSEI) is one of the most popular and comprehensive ecological quality assessment indices based on the remote sensing data. However, the RSEI model exhibits that the ecological environment under natural conditions is not limited by the spatial scales. In addition, the model has major shortcomings in index selection and eigenvector, which greatly limit the application of RSEI. In this paper, the RSEI model is improved and a remote sensing ecological index optimized by the regional scale (RO-RSEI) is proposed. The result of the study, conducted in Shuangyang District, Changchun City, Jilin Province, shows that the RO-RSEI model has regional ecological significance after the introduction of the scale theory of landscape ecology; the index is preferred to solve problems like the RSEI model applied mechanization and baseless index selection. Meanwhile, due to the optimization of the eigenvector contribution of the optimal index, it solves the problems like non-unique model calculation result caused by principal component analysis or even antipodal calculation result. Compared with the RSEI model, the monitoring result of RO-RSEI model can better reflect the regional ecological changes. The improved model offers the possibility of monitoring ecological environment quality with remote sensing big data and provides a scientific basis for future scholars' batch computing. [ABSTRACT FROM AUTHOR]

Taurine is an amino acid, and product rich in taurine is widely used in the field of functional foods and medicines. There are many wild mussel resources which is inexpensive in the Songhua River Basin of Jilin Province. The wild mussel contains abundant taurine, but its processing utilization rate is low. In this paper, taurine was extracted by using a pulsed electric field (PEF) assisted enzymatic from mussel meat, and the single‐factor test and response surface methodology were used to optimize the extraction process by using a central composite design (CCD). When a PEF assisted enzymatic was applied to the mussel meat, the cells ruptured, and substances such as taurine flowed out. A three‐dimensional graphical surface and a two‐dimensional contour map were constructed based on the RSM test results, which could intuitively reflect the influence of various factors and their interaction on the extraction of taurine. We could see that the results were consistent with the initial single‐factor experiment. The optimal extraction conditions were the electric field strength of 25 kV/cm, the number of pulses of 10, and the enzymolysis time of 2.95 hr. The maximum taurine yield was achieved of 13.77 mg/g. Compared with enzymatic method; the taurine yield was significantly increased by 28.21% with the PEF‐assisted enzymatic extraction process. Taurine could be effectively separated and purified by cation exchange and crystallization and recrystallization. Novelty impact statement: PEF‐assisted enzymatic method was used to extract taurine from mussel meat, and the taurine yield was 13.77 mg/g under the best conditions. The single‐factor test and response surface methodology were used to optimize the extraction process by using a central composite design. Taurine could be effectively separated and purified by cation exchange chromatography and crystallization and recrystallization to obtain better purity and yield. [ABSTRACT FROM AUTHOR]