Quantitative Evaluation Model Research Articles

Assessment of the Interconnection for Multi-Transfer Facilities: A Perspective from Coupling Coordination

Transfer terminals with a high integration level could provide favorable support to Mobility-as-a-Service, which is essential to sustainable transportation. The interconnection of multiple transfer facilities in terminals would affect travelers’ transfer choices during their trips. Existing research on intermodality lacks an efficient multi-dimension indicator system regarding transfer facilities. To date, the selection of representative indicator systems and the construction of quantitative evaluation models based on these indicators that can reflect the coupling relationship between transfer facilities effectively and comprehensively are still challenging. Aiming at this challenge, this study conducts the work in the following three ways. First, the concept of the degree of coupling coordination of multiple transfer facilities (DCC-MTF) is proposed to evaluate the interaction among multiple transfer facilities. Second, indicators of diversity, selectivity, accessibility, and continuity are designed and used to establish the model by using the entropy weight method. Third, the spatial distribution characteristics of DCC-MTF for each transfer facility are geo-visualized and clustered. Field observation is conducted at Lelylaan Station in the city of Amsterdam, and the indicator analysis derived from the collected data is discussed. Overall, the quantitative evaluation model presented in this study, which is universal and can be applied to similar scenarios, is directly valuable for planners and designers who aim to improve the integration level of transfer terminals.

Ecological and environmental damage assessment of water resources protection mining in the mining area of Western China

The application of water resources protection mining has alleviated greatly the deterioration of ecological environment in the ecologically fragile mining areas of Western China. To quantitatively evaluate the improvement effect of this technology on the ecological environment of the mining area, the evaluation index system of ecological environment in the mining area was proposed based on the water-preserved mining techniques of water resources protection mining. The entropy weight method and the Decision-making Trial and Evaluation Laboratory were selected as the subjective and objective weight method, and the cloud model theory was used as the modeling basis, then a quantitative evaluation model of ecological environment of water-preserved mining was constructed. Besides, the Halagou coal mine in Shendong Group was taken as an example, and the ecological environment of this mining area was quantitatively assessed to verify the rationality of the proposed evaluation model. The results show that the ecological environment level of the Halagou mining area is between Excellent and Good (generally at a good level), which is consistent with the actual ecological environment situation of the Halagou mining area. Thus, the rationality of the proposed evaluation model is verified. Through the evaluation cloud map, the evaluation results are biased towards the evaluation level of Good, indicating that there is still room for improvement in the ecological environment of the Halagou coal mine. Combined with the analysis results, suggestions for the sustainable improvement of the ecological environment of the mining area are given: Halagou coal mine should focus on the restoration of subsidence area and the control of mine water inflow.

Study on evaluation method of fracture forming ability of shale oil reservoirs in Fengcheng Formation, Mahu sag

In order to effectively evaluate the complex fracture network forming ability of Fengcheng Formation shale oil reservoirs in Mahu sag, the core in a vertical well of Fengcheng Formation in Mahu sag was considered as the research object. Through coring sampling, indoor experimental testing, combined with logging data and comprehensive interpretation, the rock mechanical properties and in-situ stress profile of the reservoir are systematically obtained. The results show that the shale oil reservoir of Fengcheng Formation in Mahu sag has deep burial depth, large absolute value of in-situ stress, high compressive strength and elastic modulus, good brittleness, low development degree of reservoir bedding, but relatively developed natural fractures. Among these features, brittleness, natural fractures, compressive strength and in-situ stress are the main controlling factors affecting the reservoir fracture propagation. The acoustic emission b value during the process of rock fracture can characterize the ability to form complex fracture network. By evaluating the correlation coefficient between each main control factor and acoustic emission b value for the first time, the weight value of each factor on fracture forming ability is determined. So as to establish the quantitative evaluation model of reservoir fracture forming ability, and quantitatively evaluate the fracture forming ability of the reservoir section. Applying the quantitative evaluation model of fracture forming ability to the logging data of the well. The evaluation results of the whole well section are consistent with the liquid production profile of the well, which shows that the research model established by this method is reliable. That also provides a guidance for the fracturing transformation and horizon optimization of horizontal wells in Fengcheng Formation shale oil reservoir in Mahu sag in the later stage.

Quantitative Evaluation of Small Intestinal Hemorrhage Using Energy Spectrum CT Iodine-Water Map.

The objective of this research is to analyze the quantitative evaluation of human small intestinal bleeding by observing and analyzing animal experiments of small intestinal hemorrhage in rabbit models for the convenience of understanding the role of energy spectrum CT iodine-water diagram in animal experimental research of quantitative evaluation of small intestinal bleeding in rabbit models. Compared with the energy spectrum of iodine-water graph of a rabbit CT model, the present study studied the quantitative evaluation of small intestinal bleeding by using a rabbit model instead of human. According to the method mentioned above and the analysis of experimental data, the role of energy spectrum CT iodine-water map and the quantitative evaluation of human small intestinal bleeding have been understood. It was found that the energy spectrum CT iodine-water map replaces humans in the rabbit model for quantitative evaluation of small intestinal bleeding in animal experiments, which is important in the present study. Besides, based upon the combination of theoretical and experimental data, the ten flow rates set on the base material iodine (water) maps of the arterial phase and the portal phase can be analyzed to detect the leakage of contrast agent. The yield was 100%. The research results showed that the animal experiment of quantitative assessment of small intestinal bleeding by replacing the human body with the rabbit model in the energy spectrum CT iodine-water diagram is critical to humans in the study of small intestinal hemorrhagic diseases. In addition, it can be used to adjust the treatment plan timely according to the amount of bleeding to prevent shock or heavy bleeding that threatens patients' lives.

Quantitative Evaluation System of Wrist Motor Function for Stroke Patients Based on Force Feedback.

Motor function evaluation is a significant part of post-stroke rehabilitation protocols, and the evaluation of wrist motor function helps provide patients with individualized rehabilitation training programs. However, traditional assessment is coarsely graded, lacks quantitative analysis, and relies heavily on clinical experience. In order to objectively quantify wrist motor dysfunction in stroke patients, a novel quantitative evaluation system based on force feedback and machine learning algorithm was proposed. Sensors embedded in the force-feedback robot record the kinematic and movement data of the subject, and the rehabilitation doctor used an evaluation scale to score the wrist function of the subject. The quantitative evaluation models of wrist motion function based on random forest (RF), support vector machine regression (SVR), k-nearest neighbor (KNN), and back propagation neural network (BPNN) were established, respectively. To verify the effectiveness of the proposed quantitative evaluation system, 25 stroke patients and 10 healthy volunteers were recruited in this study. Experimental results show that the evaluation accuracy of the four models is all above 88%. The accuracy of BPNN model is 94.26%, and the Pearson correlation coefficient between model prediction and clinician scores is 0.964, indicating that the BPNN model can accurately evaluate the wrist motor function for stroke patients. In addition, there was a significant correlation between the prediction score of the quantitative assessment system and the physician scale score (p < 0.05). The proposed system enables quantitative and refined assessment of wrist motor function in stroke patients and has the feasibility of helping rehabilitation physicians in evaluating patients’ motor function clinically.

Monosodium Glutamate-Induced Mouse Model With Unique Diabetic Retinal Neuropathy Features and Artificial Intelligence Techniques for Quantitative Evaluation.

ObjectiveTo establish an artificial intelligence-based method to quantitatively evaluate subtle pathological changes in retinal nerve cells and synapses in monosodium glutamate (MSG) mice and provide an effective animal model and technique for quantitative evaluation of retinal neurocytopathies.MethodsICR mice were subcutaneously injected with MSG to establish a model of metabolic syndrome. We then established a mouse model of type 1 diabetes, type 2 diabetes, and KKAy mouse model as control. The HE sections of the retina were visualized using an optical microscope. AI technology was used for quantitative evaluation of the retinal lesions in each group of rats. The surface area custom parameters of the retinal nerve fiber layer (RNFL), inner plexiform layer (IPL), inner nuclear layer (INL), and outer plexiform layer (OPL) were defined as SR, SIPL, SINL, and SOPL, respectively. Their heights were defined as HR, HIPL, HINL, and HOPL, and the number of ganglion cells was defined as A. Then, the attention-augmented fully convolutional Unet network was used to segment the retinal HE images, and AI technology to identify retinal neurocytopathies quantitatively.ResultsThe attention-augmented fully convolutional Unet network increased PA and IOU parameters for INL, OPL, RNFL, and ganglion cells and was superior in recognizing fine structures. A quantitative AI identification of the height of each layer of the retina showed that the heights of the IPL and INL of the MSG model were significantly less than those of the control groups; the retinas of the other diabetic models did not exhibit this pathological feature. The RNFLs of type 2 diabetes were thinner, and the characteristics of retinopathy were not obvious in the other animal models. The pathological changes seen on HE images were consistent with the results of the quantitative AI evaluation. Immunohistochemistry results showed that NMDAR2A, GluR2, and NRG1 were significantly downregulated in the retina of MSG mice.ConclusionsThe MSG retinopathy model is closely associated with neurotransmitter abnormalities and exhibits important characteristics of retinal neurodegeneration, making it suitable for studying retinal neurocytopathies. The AI recognition technology for retinal images established in the present study can be used for the quantitative and objective evaluation of drug efficacy.

Assessment of recoverable oil and gas resources by in-situ conversion of shale—Case study of extracting the Chang 73 shale in the Ordos Basin

The purpose of this study is to investigate the entire evolution process of shales with various total organic contents (TOC) in order to build models for quantitative evaluation of oil and gas yields and establish methods for assessing recoverable oil and gas resources from in-situ conversion of organic matters in shale. Thermal simulation experiments under in-situ conversion conditions were conducted on Chang 73 shales from the Ordos Basin in a semi-open system with large capacity. The results showed that TOC and Ro were the key factors affecting the in-situ transformation potential of shale. The remaining oil and gas yields increased linearly with TOC but inconsistently with Ro. Ro ranged 0.75%–1.25% and 1.05%–2.3%, respectively, corresponding to the main oil generation stage and gas generation stage of shale in-situ transformation. Thus a model to evaluate the remaining oil/gas yield with TOC and Ro was obtained. The TOC of shale suitable for in-situ conversion should be greater than 6%, whereas its Ro should be less than 1.0%. Shales with 0.75% (Ro) could obtain the best economic benefit. The results provided a theoretical basis and evaluation methodology for predicting the hydrocarbon resources from in-situ conversion of shale and for the identification of the optimum “sweet spots”. The assessment of the Chang 73 shale in the Ordos Basin indicated that the recoverable oil and gas resources from in-situ conversion of organic matters in shale are substantial, with oil and gas resources reaching approximately 450 × 108 t and 30 × 1012 m3, respectively, from an area of 4.27 × 104 km2.

Optimization of Bed Demand for Elderly Care Services Based on Leslie Matrix

With the deepening of the aging process and the weakening of the family’s ability to care for the aged, urban residents will have an increasing demand for elderly care service institutions in the future. Therefore, it is necessary to optimize the prediction of the demand for elderly service beds. In the paper, an optimization method of Leslie matrix is proposed to predict the future trend of the total population and aging by comprehensively considering factors such as birth rate and mortality rate, and analyze and predict the demand scale of elderly service beds according to the distribution of urban and rural areas and economic divisions. Based on the AHP model, the business opportunities for elderly service beds will be transformed into a quantitative evaluation model to analyzing the return rate of pension service investment in different regions. The simulation experiment shows that increasing the total number of elderly care institutions and improving them can effectively solve the insufficient number of elderly service beds.

A Nomogram Based on Molecular Biomarkers and Radiomics to Predict Lymph Node Metastasis in Breast Cancer.

BackgroundThe aim of this study was to explore the feasibility and efficacy of a non-invasive quantitative imaging evaluation model to assess the lymphatic metastasis of breast cancer based on a radiomics signature constructed using conventional T1-weighted image (T1WI) enhanced MRI and molecular biomarkers.MethodsPatients with breast cancer diagnosed via lymph biopsies between June 2015 and June 2019 were selected for the study. All patients underwent T1WI contrast-enhancement before treatment; lymph biopsy after surgery; and simultaneous Ki-67, COX-2, PR, Her2 and proliferating cell nuclear antigen detection. All images were imported into ITK-SNAP for whole tumor delineation, and AK software was used for radiomics feature extraction. Next, the radiomics signature Rad-score was constructed after reduction of specific radiomic features. A multiple regression logistic model was built by combining the Rad-score and molecular biomarkers based on the minimum AIC.ResultsIn all, 100 patients were enrolled in this study, including 45 with non-lymph node (LN) metastasis and 55 with LN metastasis. A total of 1,051 texture feature parameters were extracted, and LASSO was used to reduce the dimensionality of the radiomics features. The log(λ) was set to 0.002786, and 19 parameters were retained for the construction of the radiomics tag Rad-score. ROC was used to evaluate the diagnostic efficiency of Rad-score: the area under the ROC curve (AUC) of the Rad-score for identifying non-lymphatic and lymphatic metastases was 0.891 in the training cohort and 0.744 in the validation cohort. With the incorporation of tumor molecular markers, the AUCs of the training cohort and validation cohort of the nomogram were 0.936 and 0.793, respectively, which were notably higher than the AUCs of the clinical parameters in the training and validation cohorts (0.719 and 0.588, respectively).ConclusionThe combined model constructed using the Rad-score and molecular biomarkers can be used as an effective non-invasive method to assess LN metastasis of breast cancer. Furthermore, it can be used to quantitatively evaluate the risk of breast cancer LN metastasis before surgery.

Combined Model of Quantitative Evaluation of Chest Computed Tomography and Laboratory Values for Assessing the Prognosis ofCoronavirus Disease 2019.

To assess the prognostic power of quantitative analysis of chest CT, laboratory values, and their combination in COVID-19 pneumonia. Retrospective analysis of patients with PCR-confirmed COVID-19 pneumonia and chest CT performed between March 07 and November 13, 2020. Volume and percentage (PO) of lung opacifications and mean HU of the whole lung were quantified using prototype software. 13laboratory values were collected. Negative outcome was defined as death, ICU admittance, mechanical ventilation, or extracorporeal membrane oxygenation. Positive outcome was defined as care in the regular ward or discharge. Logistic regression was performed to evaluate the prognostic value of CT parameters and laboratory values. Independent predictors were combined to establish a scoring system for prediction of prognosis. This score was validated on a separate validation cohort. 89 patients were included for model development between March 07 and April 27, 2020 (mean age: 60.3 years). 38 patients experienced a negative outcome. In univariate regression analysis, all quantitative CT parameters as well as C-reactive protein (CRP), relative lymphocyte count (RLC), troponin, and LDH were associated with a negative outcome. In a multivariate regression analysis, PO, CRP, and RLC were independent predictors of a negative outcome. Combination of these three values showed a strong predictive value with a C-index of 0.87. A scoring system was established which categorized patients into 4 groups with a risk of 7 %, 30 %, 67 %, or 100 % for a negative outcome. The validation cohort consisted of 28 patients between May 5 and November 13, 2020. A negative outcome occurred in 6 % of patients with a score of 0, 50 % with a score of 1, and 100 % with a score of 2 or 3. The combination of PO, CRP, and RLC showed a high predictive value for a negative outcome. A 4-point scoring system based on these findings allows easy risk stratification in the clinical routine and performed exceptionally in the validation cohort. · A high PO is associated with an unfavorable outcome in COVID-19. · PO, CRP, and RLC are independent predictors of an unfavorable outcome, and their combination has strong predictive power. · A 4-point scoring system based on these values allows quick risk stratification in a clinical setting. · Scharf G, Meiler S, Zeman F et al. Combined Model of Quantitative Evaluation of Chest Computed Tomography and Laboratory Values for Assessing the Prognosis of Coronavirus Disease 2019. Fortschr Röntgenstr 2022; 194: 737 - 746.

Content Coverage and Readability of Science Textbooks in Use in Nigerian Secondary Schools

This study evaluated the content coverage and readability of science textbooks in use in Nigerian secondary schools. The study utilized an evaluation design. The study was limited to the core sciences studied at both the junior and senior secondary schools. They are Physics, Chemistry, Biology and Basic Science. A total of one thousand eight hundred and forty-eight research subjects comprising one thousand eight hundred students and forty-eight science teachers were used for the study. Two research questions and one null hypothesis guided the study. The research questions were answered using the quantitative model for textbook evaluation developed by Emerole (2008) while the hypothesis was tested at 0.05 level of significance using Chi-square test of goodness of fit. The finding revealed that all the science textbooks evaluated covered the contents of the core curriculum. The result of data analysis revealed that three out of four evaluated textbooks in biology are readable. Modern Biology for Senior Secondary Schools had readability mean score of 38.41%, Essential Biology for Senior Secondary Schools had 72.4%, College Biology for Senior Secondary Schools had 66.29% while Comprehensive Biology for Senior Secondary Schools had readability index of 60.1%. The data on readability for physics, chemistry and basic science indicate that they are readable. Based on the findings the researchers made specific recommendations with respect to the textbooks recommended for use in the four subject areas in Nigerian secondary schools. This will provide a template and guide for ministry of education in recommendation of science textbooks for secondary schools. In addition, it will serve as a basis and guide for review of science textbooks in use in both junior and senior secondary schools. Keywords: content coverage, readability, science textbooks, secondary schools DOI: 10.7176/JEP/13-7-06 Publication date: March 31 st 2022

Construction of a Fundamental Quantitative Evaluation Model of the A-Share Listed Companies Based on the BP Neural Network.

Quantitative investment has attracted much attention, along with the vigorous development of Fintech. Fundamentals are one of the most important reference factors for investment. Before quantitative trading, evaluation of fundamentals may have been more dependent on personal experience. While artificial intelligence evaluation models can provide good investment suggestions and select stocks with better fundamentals. From the four angles of solvency, growth ability, operation ability, and profitability, this research selects 13 financial indicators to build a fundamental evaluation system through correlation coefficient analysis. The corporate life cycle assessment indicator is innovatively added so that the fundamental improvement expectation is put into the evaluation system. Four different kinds of scoring methods are applied to obtain a more rational and comprehensive evaluation of indicators. Then, grey relational analysis is adopted to determine the initial weight to calculate the expected output. Finally, BP neural network (back propagation) is used for training and testing to realize weight optimization. It is concluded that the model is suitable for quantitative scoring of the fundamentals of listed companies and can effectively reflect their value of them.

Evaluation Model of Teachers' Teaching Ability Based on Improved Random Forest with Grey Relation Projection

The development and improvement of teachers' teaching ability is the guarantee to continuously improve the overall teaching ability and school running level of universities. Therefore, it is of great significance to scientifically evaluate teachers' teaching ability. Aiming at the problems of traditional algorithms, such as weak generalization performance and difficult determination of parameters and model structure, a random forest algorithm is introduced into the field of teaching ability prediction. At an equal time, the ordinary grey correlation algorithm is accelerated through the usage of the projection principle, and instructor instructing capacity assessment mannequin based totally on grey projection expanded random woodland algorithm is proposed. The grey correlation degree judgment matrix is used to represent the correlation between historical samples and influencing factors, and the weight of influencing factors is established by the direct weight method to weight the judgment matrix. The random woodland algorithm is used to set up the prediction model, the grey projection is used to display screen the pattern set education model, and ultimately, the characteristic vector is entered to whole the prediction. The experimental results show that the new method has high prediction accuracy, robustness, and effectiveness. It not only enriches the evaluation methods of teachers' teaching ability but also provides a quantitative evaluation model reference for teachers' teaching ability evaluation.

Quantitative Evaluation System of Upper Limb Motor Function of Stroke Patients Based on Desktop Rehabilitation Robot.

Rehabilitation training and movement evaluation after stroke have become a research hotspot as stroke has become a very common and harmful disease. However, traditional rehabilitation training and evaluation are mainly conducted under the guidance of rehabilitation doctors. The evaluation process is time-consuming and the evaluation results are greatly influenced by doctors. In this study, a desktop upper limb rehabilitation robot was designed and a quantitative evaluation system of upper limb motor function for stroke patients was proposed. The kinematics and dynamics data of stroke patients during active training were collected by sensors. Combined with the scores of patients’ upper limb motor function by rehabilitation doctors using the Wolf Motor Function Test (WMFT) scale, three different quantitative evaluation models of upper limb motor function based on Back Propagation Neural Network (BPNN), K-Nearest Neighbors (KNN), and Support Vector Regression (SVR) algorithms were established. To verify the effectiveness of the quantitative evaluation system, 10 healthy subjects and 21 stroke patients were recruited for experiments. The experimental results show that the BPNN model has the best evaluation performance among the three quantitative evaluation models. The scoring accuracy of the BPNN model reached up to 87.1%. Moreover, there was a significant correlation between the models′ scores and the doctors′ scores. The proposed system can help doctors to quantitatively evaluate the upper limb motor function of stroke patients and accurately master the rehabilitation progress of patients.

Model-Based Anticancer Effect of Botulinum Neurotoxin Type A1 on Syngeneic Melanoma Mice

In recent, Botulinum Neurotoxin A1 (BoNT/A1) has been suggested as a potential anticancer agent due to neuronal innervation in tumor cells. Although potential BoNT/A1’s mechanism of action for the tumor suppression has been gradually revealed so far, there were no reports to figure out the exposure-response relationships because of the difficulty of its quantitation in the biological matrix. The main objectives of this study were to measure the anticancer effect of BoNT/A1 using a syngeneic mouse model transplanted with melanoma cells (B16-F10) and developed a kinetic-pharmacodynamic (K-PD) model for quantitative exposure-response evaluation. To overcome the lack of exposure information, the K-PD model was implemented by the virtual pharmacokinetic compartment link to the pharmacodynamic compartment of Simeoni’s tumor growth inhibition model and evaluated using curve-fitting for the tumor growth-time profile after intratumoral injection of BoNT/A1. The final K-PD model was adequately explained for a pattern of tumor growth depending on represented exposure parameters and simulation studies were conducted to determine the optimal dose under various scenarios considering dose strength and frequency. The optimal dose range and regimen of ≥13.8 units kg−1 once a week or once every 3 days was predicted using the final model in B16-F10 syngeneic model and it was demonstrated with an extra in-vivo experiment. In conclusion, the K-PD model of BoNT/A1 was well developed to optimize the dosing regimen for evaluation of anticancer effect and this approach could be expandable to figure out quantitative interpretation of BoNT/A1’s efficacy in various xenograft and/or syngeneic models.

Construction method of quantitative evaluation model for the maturity of Korla fragrant pear

The maturity variation laws of Korla fragrant pears were explored for a quantitative evaluation of harvest maturity to solve the reasonable matching between harvest maturity of Korla fragrant pears and market quality demands. Korla fragrant pears from different harvesting periods were chosen as the research objects. Some quality indexes were chosen as the evaluation indexes per industry standards, including hardness, soluble solid content (SSC), single-fruit weight, fruit longitudinal diameter, fruit equatorial diameter, pericarp color parameters (L*, a*, and b*), and titratable acid. Variation data of these quality indexes with accumulated temperature were collected. Scores of several quality indexes were gained through principal component analysis. A mathematical model of scores and accumulated temperatures was constructed. On this basis, a quantitative maturity model of Korla fragrant pears was constructed. Results demonstrate that SSC, single-fruit weight, fruit longitudinal diameter, fruit equatorial diameter, L*, a*, and b* are significantly and positively correlated with the accumulated temperature. Meanwhile, hardness and titratable acid showed significant negative correlations with the accumulated temperature. Relations between scores of principal components and accumulated temperature conform to the Sigmoidal model. The constructed quantitative maturity model of Korla fragrant pears can quantify the maturity of pears. Research conclusions can provide insight into the harvest periods, evaluate Korla fragrant pears’ maturity, and lay a theoretical foundation for quantitative research on fruit maturity. Keywords: Korla fragrant pear, quantitative evaluation, maturity, principal component analysis, model construction DOI: 10.25165/j.ijabe.20221504.6653 Citation: Yu S H, Tang Y R, Lan H P, Li X L, Zhang H, Zeng Y, et al. Construction method of quantitative evaluation model for maturity of Korla fragrant pear. Int J Agric & Biol Eng, 2022; 15(4): 243–250.

快速城镇化过程中的城市蔓延与生态保护冲突空间识别与量化评估——以长三角生态绿色一体化发展示范区为例

PDF HTML阅读 XML下载 导出引用 引用提醒 快速城镇化过程中的城市蔓延与生态保护冲突空间识别与量化评估——以长三角生态绿色一体化发展示范区为例 DOI: 10.5846/stxb202102070402 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家重点研发计划项目(2016YFC0502702) Spatial identification and quantitative evaluation of conflict space between urban sprawl and ecological protection in the process of rapid urbanization: A case study of the Yangtze River Delta Eco-Green Integrated Development Demonstration Zone Author: Affiliation: Fund Project: National Key Research and Development Program(2016YFC0502702) 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:如何解决社会经济发展与生态环境保护之间的矛盾是实现区域和城市可持续发展的首要问题, 表现在空间上就是城市无序蔓延与生态环境保护用地的冲突, 本质上是建成区与非建成区的生态系统之间的冲突。以长三角生态绿色一体化发展示范区为例, 基于自然环境因子和社会经济因子构建城市蔓延风险空间量化评估模型, 得到城市蔓延风险空间分布并提取城市蔓延严重风险区；利用生态侵蚀度指数识别评估生态保护压力空间并提取生态保护压力高值区。根据城市蔓延严重风险区与生态保护压力高值区的重合空间, 对城市无序蔓延与生态保护的冲突程度进行分析, 进而探讨快速城镇化发展过程中二者的协调关系, 为城市国土空间规划与区域生态保护决策提供科技支撑。长三角生态绿色一体化发展示范区案例研究结果表明：(1)城市蔓延的严重风险区与生态保护压力高值区的重合面积达到583.83km2；其中较高风险区与侵蚀度高的地区重合面积为311.73km2, 冲突度为53.39%；高风险区与侵蚀度高的地区重合面积为47.70 km2, 冲突度为8.17%。(2)示范区内各类生态系统中, 耕地生态系统受城市蔓延冲突程度均为最高, 其在较高和高风险区的占比分别为91.58%、8.42%；其次是草地生态系统。为协调城市蔓延与生态保护空间的关系, 保障示范区生态绿色一体化发展。进一步识别了示范区内生态预警区和城市蔓延重点关注区, 其中生态预警区内需要充分的生态修复, 降低生态保护压力；城市蔓延重点关注区在建设时要注意保护原有生态保护压力大的区域, 加强生态工程建设, 管控建设用地规模, 保障蓝绿空间占比。 Abstract:How to solve the contradiction between the social economy and the ecological environmental protection is a basic problem to understand the regional and urban sustainable development, which is manifested in the conflict space between urban sprawl and ecological protection. It's an essential conflict between the ecosystem of built-up and unbuilt-up areas. This article selects the Yangtze River Delta Eco-Green Integrated Development Demonstration Zone as the research area. Based on natural environment and socio-economic factors, we constructed a spatially quantitative evaluation model for urban sprawl risks to generate the spatial distribution of several risk areas and extract the serious risk areas of urban sprawl. Moreover, the ecological erosion index was used to identify and evaluate the ecological protection pressure space and extract the high value areas of ecological protection pressure. According to the overlapping space between the serious risk area of urban sprawl and the high value area of ecological protection pressure, the conflict degree between urban sprawl and ecological protection was analyzed for the coordinated relationship between the urban sprawl and ecological protection in the process of rapid urbanization. We aim to provide scientific and technological support for urban territorially spatial planning and regionally ecological protection decision-making. The results showed that: (1) the overlap space between the serious risk area of urban sprawl and the high value area of ecological protection pressure reached 583.83 km2. The overlap area between the areas with higher urban sprawl risk and the areas with higher ecological erosion degree was 311.73 km2 and the conflict degree was 53.39%. The overlap area of the highest risk area and the highest erosion area was 47.70 km2, and the conflict degree was 8.17%. (2) In the demonstration area, the cultivated land ecosystem suffered the highest degree of urban sprawl conflict, accounting for 91.58% and 8.42% in the higher and the highest risk areas, respectively, followed by the grassland ecosystem. In order to coordinate the balance between urban sprawl and ecological protection, and ensure the sustainable development of the Demonstration Zone, this article further identified the ecological early warning area and key concern area in the demonstration area of integrated development of ecological green in the Demonstration Zone. In the construction of the key areas of urban sprawl, attention should be paid to the protection of the original areas under great ecological protection pressure, the ecological engineering construction should be strengthened, the scale of construction land should be controlled, and the proportion of blue and green space should be guaranteed. 参考文献 相似文献 引证文献

Port Capability Evaluation from the Perspective of Supply Chain

Today’s ports have become an important node in the global supply chain. It is particularly important to make a scientific assessment of the comprehensive capabilities of the port and to provide a reference for the long-term development of the port. From the perspective of the supply chain, this article first selects the evaluation indicators that affect the port’s capabilities from four aspects of port resource ownership, control management, comprehensive services, and innovation-driven aspect. Secondly, we use the expert scoring method to judge the importance of the evaluation indicators and build a scientific and independent port capacity evaluation system from the perspective of the supply chain. Then, this paper uses the analytic hierarchy process to determine the weight coefficients of each evaluation index and uses the gray cluster analysis method of the triangular whitening weight function based on the center point to establish a qualitative and quantitative port capacity evaluation model from the perspective of the supply chain. Finally, we take a port in Northeast Asia as an example to conduct an empirical analysis to verify the feasibility of the port capacity evaluation system and model from the perspective of the supply chain constructed in this paper. The research results of this article can well analyze the port’s resource ownership, control and management capabilities, comprehensive service capabilities, and innovation-driven capabilities and provide a practical and effective theoretical basis for the port’s key development directions.

Evaluating the Effectiveness of Regional Ecological Civilization Policy: Evidence from Jiangsu Province, China.

Evaluating the effectiveness of ecological civilization policies is the basis from which policymakers can optimize policies. From the perspective of the overall effectiveness of regional policies, and taking Jiangsu Province as an example, this study constructed a quantitative evaluation model of eco-civilization policy text and an eco-civilization evaluation index system. Using these tools, this paper evaluates the effectiveness of 53 ecological civilization policies issued by Jiangsu Province during 2004–2019 to promote the construction of ecological civilization in the four fields of resource utilization, environmental protection, economic development, and social life. There are three key findings. (1) During the period of 2004–2019, the effectiveness of the textual content of ecological civilization policies in Jiangsu Province generally showed a fluctuating upward trend. (2) The construction effectiveness indexes of the four fields of eco-civilization all showed a growth trend, but the construction effect varied greatly. The index of economic development had grown rapidly, while environmental protection had grown slowly. (3) Ecological civilization policies in Jiangsu Province were effective in promoting the construction of ecological civilization. However, the effects of different policy dimensions on ecological civilization development in the four fields were significantly different. Finally, based on these results, powerful recommendations are provided for the optimization of eco-civilization policies in Jiangsu Province. Moreover, Jiangsu is the first province in China to launch a provincial-level ecological civilization construction plan. Its policy optimization to promote ecological civilization construction can also provide an example and realistic basis for reference for the construction of eco-civilization in other provinces in China.

Insights into the pore structure and oil mobility in fine-grained sedimentary rocks: The Lucaogou Formation in Jimusar Sag, Junggar Basin, China

Unconventional shale/tight oil resources in fine-grained sedimentary rocks play essential roles in global energy structure. Fine-grained sedimentary rocks are characterized by complex pore assemblage and connectivity. Insights into the links between pore structure and movable oil are important for exploration and production of tight/shale oil or gas in fine-grained sedimentary rocks. A series of analyses including thin sections, mercury injection capillary pressure (MICP), and nuclear magnetic resonance (NMR) were carried out to unravel the linkage between pore structure and oil movability. Various centrifugation speeds were used in the NMR tests to remove the movable oil to obtain the movable oil saturation corresponding to various centrifugation speed. Fractal dimension is calculated from NMR T2 spectrum. Then four types of pore structures were divided according to the parameters derived from the MICP and NMR results, and the characteristics of various pore structure are summarized. From type Ⅰ to type Ⅳ, the threshold pressure, irreducible water saturation (Swi), and the fractal dimension increased while the SHgmax, rapex, T2gm, porosity, permeability, and movable oil saturation decreased. Then the key factors controlling the movable oil saturation were investigated, including permeability, porosity, T2gm, rapex, and mineral composition of the rocks. The movable oil saturation is dominated by porosity, T2gm, fractal dimension, and rapex. Then a quantitative evaluation model of the movable oil saturation was established. In addition, the NMR logs and the derived parameters were utilized to evaluate the reservoir quality and pore structures in a single well. At last the T2 value of 25 ms (the ratio of the T2 components >25 ms to the total T2 components) was used to calculate the movable oil saturation in the upper member of the Lucaogou Formation, and the T2 value of 28 ms was used for the lower member of the Lucaogou Formation in the Jimusar Sag. The results are testified by the high-speed (10000 r/min) centrifugation NMR measurements. The results above help improve understanding of tight/shale oil enrichment and provide a new model for calculating the movable oil saturation in fine-grained sedimentary rocks.