Enhancing Autonomy Capability in Regional Power Grids:A Strategic Planning Approach with Multiple Autonomous Evaluation Indexes

After the integration of large-scale DistributedGeneration(DG)into the distribution network,the randomness and volatility of its output result in a reduction of spatiotemporal alignment between power generation and demand in the distribution network,exacerbating the phenomenon of wind and solar power wastage.As a novel power system model,the fundamental concept of Regional Autonomous Power Grids(RAPGs)is to achieve localized management and energy autonomy,thereby facilitating the effective consumption of DGs.Therefore,this paper proposes a distributed resource planning strategy that enhances the autonomy capabilities of regional power grids by considering multiple evaluation indexes for autonomy.First,a regional Energy Storage(ES)configuration strategy is proposed.This strategy can select a suitable reference value for the upper limit of ES configuration based on the regional load andDGoutput to maximize the elimination of source load deviations in the region as the upper limit constraint of ES capacity.Then,a control strategy for regional ES is proposed,the charging and discharging reference line of ES is set,and multiple autonomy and economic indexes are used as objective functions to select different proportions of ES to control the distributed resources of the regional power grid and establish evaluation indexes of the internal regional generation and load power ratio,the proportion of power supply matching hours,new energy consumption rate and tie line power imbalance outside the region to evaluate changes in the regional autonomy capabilities.The final simulation results showthat in the real regional grid example,the planning method in the planning year in the region of the overall power supply matching hour ratio and new energy consumption rate increased by 3.9%and 4.8%on average,and the power imbalance of the tie line decreased by 7.8%on average.The proposed planning approach enables the maximization of regional autonomy while effectively smoothing the fluctuation of power exchange between the regional grid and the higher-level grid.This presents a rational and effective planning solution for the regional grid,facilitating the coordinated development between the region and the distribution network.

Spectral purification improves monitoring accuracy of the comprehensive growth evaluation index for film-mulched winter wheat

In order to further improve the utility of unmanned aerial vehicle(UAV)remote-sensing for quickly and accurately monitoring the growth of winter wheat under film mulching, this study examined the treatments of ridge mulching,ridge–furrow full mulching, and flat cropping full mulching in winter wheat.Based on the fuzzy comprehensive evaluation (FCE) method, four agronomic parameters (leaf area index, above-ground biomass, plant height, and leaf chlorophyll content) were used to calculate the comprehensive growth evaluation index (CGEI) of the winter wheat, and 14 visible and near-infrared spectral indices were calculated using spectral purification technology to process the remote-sensing image data of winter wheat obtained by multispectral UAV.Four machine learning algorithms, partial least squares, support vector machines, random forests, and artificial neural network networks(ANN), were used to build the winter wheat growth monitoring model under film mulching, and accuracy evaluation and mapping of the spatial and temporal distribution of winter wheat growth status were carried out.The results showed that the CGEI of winter wheat under film mulching constructed using the FCE method could objectively and comprehensively evaluate the crop growth status.The accuracy of remote-sensing inversion of the CGEI based on the ANN model was higher than for the individual agronomic parameters, with a coefficient of determination of 0.75,a root mean square error of 8.40, and a mean absolute value error of 6.53.Spectral purification could eliminate the interference of background effects caused by mulching and soil, effectively improving the accuracy of the remotesensing inversion of winter wheat under film mulching, with the best inversion effect achieved on the ridge–furrow full mulching area after spectral purification.The results of this study provide a theoretical reference for the use of UAV remote-sensing to monitor the growth status of winter wheat with film mulching.

Developments in the study of Chinese herbal medicine's assessment index and action mechanism for diabetes mellitus

In traditional Chinese medicine(TCM),based on various pathogenic symptoms and the‘golden chamber’medical text,Huangdi Neijing,diabetes mellitus falls under the category‘collateral disease’.TCM,with its wealth of experience,has been treating diabetes for over two millennia.Different antidiabetic Chinese herbal medicines re-duce blood sugar,with their effective ingredients exerting unique advantages.As well as a glucose lowering effect,TCM also regulates bodily functions to prevent diabetes associated complications,with reduced side effects compared to western synthetic drugs.Chinese herbal medicine is usually composed of polysaccharides,saponins,al-kaloids,flavonoids,and terpenoids.These active ingredients reduce blood sugar via various mechanism of actions that include boosting endogenous insulin secretion,enhancing insulin sensitivity and adjusting key enzyme activity and scavenging free radicals.These actions regulate glycolipid metabolism in the body,eventually achiev-ing the goal of normalizing blood glucose.Using different animal models,a number of molecular markers are available for the detection of diabetes induction and the molecular pathology of the disease is becoming clearer.Nonetheless,there is a dearth of scientific data about the pharmacology,dose-effect relationship,and structure-activity relationship of TCM and its constituents.Further research into the efficacy,toxicity and mode of action of TCM,using different metabolic and molecular markers,is key to developing novel TCM antidiabetic formulations.

I-DCGAN and TOPSIS-IFP:A simulation generation model for radiographic flaw detection images in light alloy castings and an algorithm for quality evaluation of generated images

The intelligent detection technology driven by X-ray images and deep learning represents the forefront of advanced techniques and development trends in flaw detection and automated evaluation of light alloy castings.However,the efficacy of deep learning models hinges upon a substantial abundance of flaw samples.The existing research on X-ray image augmentation for flaw detection suffers from shortcomings such as poor diversity of flaw samples and low reliability of quality evaluation.To this end,a novel approach was put forward,which involves the creation of the Interpolation-Deep Convolutional Generative Adversarial Network(I-DCGAN)for flaw detection image generation and a comprehensive evaluation algorithm named TOPSIS-IFP.I-DCGAN enables the generation of high-resolution,diverse simulated images with multiple appearances,achieving an improvement in sample diversity and quality while maintaining a relatively lower computational complexity.TOPSIS-IFP facilitates multi-dimensional quality evaluation,including aspects such as diversity,authenticity,image distribution difference,and image distortion degree.The results indicate that the X-ray radiographic images of magnesium and aluminum alloy castings achieve optimal performance when trained up to the 800th and 600th epochs,respectively.The TOPSIS-IFP value reaches 78.7%and 73.8%similarity to the ideal solution,respectively.Compared to single index evaluation,the TOPSIS-IFP algorithm achieves higher-quality simulated images at the optimal training epoch.This approach successfully mitigates the issue of unreliable quality associated with single index evaluation.The image generation and comprehensive quality evaluation method developed in this paper provides a novel approach for image augmentation in flaw recognition,holding significant importance for enhancing the robustness of subsequent flaw recognition networks.

A preliminary site selection system for underground hydrogen storage in salt caverns and its application in Pingdingshan,China

Large‐scale underground hydrogen storage(UHS)provides a promising method for increasing the role of hydrogen in the process of carbon neutrality and energy transition.Of all the existing storage deposits,salt caverns are recognized as ideal sites for pure hydrogen storage.Evaluation and optimization of site selection for hydrogen storage facilities in salt caverns have become significant issues.In this article,the software CiteSpace is used to analyze and filter hot topics in published research.Based on a detailed classification and analysis,a“four‐factor”model for the site selection of salt cavern hydrogen storage is proposed,encompassing the dynamic demands of hydrogen energy,geological,hydrological,and ground factors of salt mines.Subsequently,20 basic indicators for comprehensive suitability grading of the target site were screened using the analytic hierarchy process and expert survey methods were adopted,which provided a preliminary site selection system for salt cavern hydrogen storage.Ultimately,the developed system was applied for the evaluation of salt cavern hydrogen storage sites in the salt mines of Pingdingshan City,Henan Province,thereby confirming its rationality and effectiveness.This research provides a feasible method and theoretical basis for the site selection of UHS in salt caverns in China.

Coupling coordination analysis of Mazu culture,socio-economy and ecological environment of Meizhou Island

Taking the pilgrimage,tourism and cultural island of Meizhou Island as an example,the evaluation index system of the coupling and coordinated development of“Mazu culture,socio-economy,eco-environment”(MSE)compound system was constructed.The index weights were determined by AHP-entropy method,and the coupling degree,coordinated degree,comprehensive evaluation index and grey correlation degree of MSE system of Mazu Island from 2012 to 2022 were measure.The results showed that:(1)the comprehensive evaluation indexes of the three subsystems was on the rise in general,but the evaluation index of the ecological subsystems increased relatively slowly.(2)The coupling degree was only in the running-in stage in 2012,and the other years were in the coordinated coupling stage.(3)The coupling coordination degree increased from 0.35 in 2012 to 0.82 in 2022,the coupling coordination level was changed from mild imbalance to good coordination.(4)Through the comparison of grey correlation degree,the 24 indexes in the evaluation index system had great influence on the coupling coordination degree of MSE system.The coupling coordination degree was closely related to the development of socio-economy and the spread of Mazu culture.With the rapid development of tourism brought about by the spread of Mazu culture,the pressure on the ecological environment will be increasing.Compared with the rapid growth of tourism and economy,it is equally important to strengthen environmental protection and pay attention to the quality of ecological environment development.

Exploration and Research on Textbook Quality Evaluation Index System Based on Engineering Major in Higher Education

The report of the Chinese 20th National Congress put forward“strengthening the construction and management of textbooks”for the first time,which indicates the importance of textbook construction and highlights the vital position of textbooks in the overall development of the country.From the perspective of textbook quality,and based on the research and analysis of the policy requirements and current evaluation indicators of higher education textbooks,this paper establishes the textbook quality evaluation index system composed of basic indicators and evaluation indicators.This system is based on the principles of science,comprehensiveness,operability,and target-oriented approach.It provides a relatively scientific,objective,and fair reference system for the management and evaluation of textbooks.

Construction of an Evaluation Index System for Innovation and Entrepreneurship Education in Vocational Colleges from Students’Perspective

Innovation and entrepreneurship education is an essential content in the current teaching of colleges and universities and an important driving force to promote students’employment.Currently,colleges and universities continue to strengthen the innovation of innovation and entrepreneurship teaching,and the construction of the evaluation system of innovation and entrepreneurship education is lagging.The evaluation system is an important evaluation standard for innovation and entrepreneurship teaching and the basis for educational innovation,which is also a critical part of teaching that requires attention.This paper takes the construction of the evaluation index system of innovation and entrepreneurship education in vocational colleges as the research goal and understands the function of innovation and entrepreneurship evaluation as well as the evaluation principle through the literature analysis method.It also analyzes the evaluation index system of innovation and entrepreneurship teaching from students’perspective to provide an effective reference for the implementation of innovation and entrepreneurship education in higher vocational colleges.

Development of an Information-Based Leadership Evaluation Index System for School Management Teams:A Comprehensive Approach

In the context of educational informatization reform,there are many uncertain factors in the process of education development.To optimize the educational environment so that it can be effectively combined with information technology,teachers need to change their teaching ideas,strengthen the school’s own adaptability to informatization,and promote the development of informatization construction in schools.As a branch of information leadership,the management team should establish an evaluation index system for information leadership in order to ensure the construction of school informatization,so as to provide a boost for the integration of school resources and information technology.Based on the overview and connotation of information-based leadership of the management team,this paper explores the construction of an evaluation index system of information-based leadership of the school management team,aiming to provide references for the research of relevant personnel in the future.

Current Status of the Application of Surgical Specialty Nursing Quality Evaluation Indicators

This paper reviews the current status of the application of surgical specialty nursing quality evaluation indicators both domestically and internationally.It covers the related concepts,theoretical foundations,construction methods,construction fields,application research,and existing shortcomings of these indicators.It suggests that scholars and researchers in the nursing field in China should base their work on mature theories,use scientific research methods,and construct a quality indicator system that aligns with China’s surgical development,is practical,unified,suitable for the local context,and beneficial for the development of the surgical nursing discipline.

Application of traditional indexes and adverse events in the ophthalmologic perioperative medical quality evaluation during 2010-2012

AIM: To evaluate the medical quality of ophthalmologic perioperative period during 2010-2012 in our hospital. METHODS: The relevant data of perioperative period were collected in our hospital during 2010-2012, and the medical quality of perioperative period was evaluated by using the traditional evaluation indexes and adverse events. Whereby, the traditional indicators include vision changes, improving of intraocular pressure, diagnostic accordance rate before and after operation, cure improvement rate, successful rescue rate, and incidence of surgical complications, etc Adverse events are associated with ophthalmologic perioperative events including pressure sores, postoperative wound infection, drug adverse events, and equipment related adverse events. RESULTS: There were 1483, 1662 and 1931 ophthalmic operations in our hospital in the year 2010, 2011 and 2012, respectively. From traditional index analysis, the proportions of vision improvement for each year were 96.43%, 96.76% and 97.32%, respectively; the rates of intraocular pressure improvement were 87.50%, 85.72% and 90.17%, respectively ( P <0.05); the diagnostic accordance rates before and after operation were 99.86%, 99.94% and 99.90%, respectively; cure improvement rates were 99.73%, 99.93% and 99.84%, respectively; the successful rescue rates were 82.98%, 81.46% and 76.66%, respectively; the complications incidence rates were 18.44%, 17.52% and 17.97%, respectively. The negative factor analysis results showed that: among all the patients of ophthalmic surgeries in our hospital during 2010 and 2012, only one case of postoperative wound infection was found in 2011, and also only one case of tumbling in 2010. The adverse drug events for each year were 1 case (0.07%), 2 cases (0.12%), and 4 cases (0.21%), respectively; the medical device adverse events for each year were 3 cases (0.20%), 5 cases (0.30%), and 6 cases (0.31%), respectively. Noticeably, only one case with postoperative infection of endophthalmitis was found in 2011. Moreover, no pulmonary infection or pulmonary embolism occurred during the three years. The perioperative adverse event rates for each year were 0.34% (5/1483), 0.48% (8/1662) and 0.52% (10/1931), respectively. Though incidence was rising during the three years, no statistical significance was observed (P>0.05). It is the same case with drugs and medical devices adverse events (P>0.05). CONCLUSION: Traditional indicators reflect an excellent operation of the perioperative ophthalmologic quality, whereas adverse events analysis indicates some underlying problems. Compared with the traditional indexes for medical quality evaluation, the index of adverse events is more reasonable and easier to make an objective evaluation for medical quality of ophthalmologic perioperation, facilitating further refine analysis. Reasonable application of the adverse events indicators helps hospital to make the detailed quality control measures.

A Full-Scale Optimization of a Crop Spatial Planting Structure and its Associated Effects

Driven by the concept of agricultural sustainable development,crop planting structure optimization(CPSO)has become an effective measure to reduce regional crop water demand,ensure food security,and protect the environment.However,traditional optimization of crop planting structures often ignores the impact on regional food supply–demand relations and interprovincial food trading.Therefore,using a system analysis concept and taking virtual water output as the connecting point,this study proposes a theoretical CPSO framework based on a multi-aspect and full-scale evaluation index system.To this end,a water footprint(WF)simulation module denoted as soil and water assessment tool–water footprint(SWAT-WF)is constructed to simulate the amount and components of regional crop WFs.A multi-objective spatial CPSO model with the objectives of maximizing the regional economic water productivity(EWP),minimizing the blue water dependency(BWFrate),and minimizing the grey water footprint(GWFgrey)is established to achieve an optimal planting layout.Considering various benefits,a fullscale evaluation index system based on region,province,and country scales is constructed.Through an entropy weight technique for order preference by similarity to an ideal solution(TOPSIS)comprehensive evaluation model,the optimal plan is selected from a variety of CPSO plans.The proposed framework is then verified through a case study of the upper–middle reaches of the Heihe River Basin in Gansu province,China.By combining the theory of virtual water trading with system analysis,the optimal planting structure is found.While sacrificing reasonable regional economic benefits,the optimization of the planting structure significantly improves the regional water resource benefits and ecological benefits at different scales.

Visualization for Explanation of Deep Learning-Based Defect Detection Model Using Class Activation Map

Recently,convolutional neural network(CNN)-based visual inspec-tion has been developed to detect defects on building surfaces automatically.The CNN model demonstrates remarkable accuracy in image data analysis;however,the predicted results have uncertainty in providing accurate informa-tion to users because of the“black box”problem in the deep learning model.Therefore,this study proposes a visual explanation method to overcome the uncertainty limitation of CNN-based defect identification.The visual repre-sentative gradient-weights class activation mapping(Grad-CAM)method is adopted to provide visually explainable information.A visualizing evaluation index is proposed to quantitatively analyze visual representations;this index reflects a rough estimate of the concordance rate between the visualized heat map and intended defects.In addition,an ablation study,adopting three-branch combinations with the VGG16,is implemented to identify perfor-mance variations by visualizing predicted results.Experiments reveal that the proposed model,combined with hybrid pooling,batch normalization,and multi-attention modules,achieves the best performance with an accuracy of 97.77%,corresponding to an improvement of 2.49%compared with the baseline model.Consequently,this study demonstrates that reliable results from an automatic defect classification model can be provided to an inspector through the visual representation of the predicted results using CNN models.

Ecological evaluation of marine macroalgal communities on five islands of Korea in the Yellow Sea

Macroalgae have long been used as biological indicators of marine ecosystem health worldwide due to their ecological importance and sensitivity to environmental stress.A number of previous studies have utilized macroalgal communities in monitoring surveys of environmental conditions.This study examined the characteristics and patterns of marine macroalgal communities in the Yellow Sea off the western coast of Korea.Macroalgae were analyzed for the number of species,biomass,and coverage ratio by macroalgal type.During the study period,82 macroalgal species(10 green algae,17 brown algae,and 55 red algae)were identified at the five study sites,with the highest number of species found at Gwanrido and Uido(both containing 41 species)and the lowest at Daeijakdo(27 species).The average biomass(via dry weight)was 98.63 g/m^(2),consisting of green algae(8.39 g/m^(2)),brown algae(35.08 g/m^(2)),and red algae(55.16 g/m^(2)).The dominant macroalgae species in terms of biomass were Corallina pilulifera,Sargassum thunbergii,and Ulva australis in the intertidal zones,and Botryocladia wrightii and Gelidium elegans in the subtidal zones.Richness,evenness,and diversity indices based on the biomass of abundant species were 5.08,0.65,and 2.30,respectively,over the entire study area.Based on the evaluation of the environmental states by the community indices,overall,the Ecological Evaluation Index of macroalgae communities in the study area was marked as“Good-Moderate”,but was determined as“ModerateLow”at several sites during summer.The results can be a direct approach in the assessment of coastal habitats in which anthropogenic as well as climate change influences persist.

Evaluation method for assessing the auxiliary service transaction mechanism in regional power markets

Accurate and seamless auxiliary services in the power market can guarantee smooth and continuous power system operation. China’s new round of power system reform has entered a critical period, and reform implementation requires comprehensive improvements in the maturity of the supporting auxiliary service market. This study reviews the development status and evolution path of the European unified power market and the US regional power market, provides experience for the development of China’s regional power market, then identifies the key influencing factors of auxiliary service trading mechanism design in regional power markets. To analyze the rationality of the auxiliary service trading evaluation index, this paper established an evaluation model for assessing regional power markets. Using combined weight optimization, the gray correlation TOPSIS method was applied to comprehensively evaluate auxiliary service trading in the regional power market. Finally, the application of the proposed evaluation method was briefly analyzed to examine four regional power markets in China and evaluate the effectiveness of current market construction in different regions and provide suggestions for future market construction.

An evaluation model for smart grids in support of smart cities based on the Hierarchy of Needs Theory

Smart cities depend highly on an intelligent electrical networks to provide a reliable,safe,and clean power supplies.A smart grid achieves such aforementioned power supply by ensuring resilient energy delivery,which presents opportunities to improve the cost-effectiveness of power supply and minimize environmental impacts.A systematic evaluation of the comprehensive benefits brought by smart grid to smart cities can provide necessary theoretical fundamentals for urban planning and construction towards a sustainable energy future.However,most of the present methods of assessing smart cities do not fully take into account the benefits expected from the smart grid.To comprehensively evaluate the development levels of smart cities while revealing the supporting roles of smart grids,this article proposes a model of smart city development needs from the perspective of residents’needs based on Maslow’s Hierarchy of Needs theory,which serves the primary purpose of building a smart city.By classifying and reintegrating the needs,an evaluation index system of smart grids supporting smart cities was further constructed.A case analysis concluded that smart grids,as an essential foundation and objective requirement for smart cities,are important in promoting scientific urban management,intelligent infrastructure,refined public services,efficient energy utilization,and industrial development and modernization.Further optimization suggestions were given to the city analyzed in the case include strengthening urban management and infrastructure constructions,such as electric vehicle charging facilities and wireless coverage.

Fuzzy pattern recognition model of geological sweetspot for coalbed methane development

From the perspective of geological zone selection for coalbed methane(CBM) development, the evaluation parameters(covering geological conditions and production conditions) of geological sweetspot for CBM development are determined, and the evaluation index system of geological sweetspot for CBM development is established. On this basis, the fuzzy pattern recognition(FPR) model of geological sweetspot for CBM development is built. The model is applied to evaluate four units of No.3 Coal Seam in the Fanzhuang Block, southern Qinshui Basin, China. The evaluation results are consistent with the actual development effect and the existing research results, which verifies the rationality and reliability of the FPR model. The research shows that the proposed FPR model of geological sweetspot for CBM development does not involve parameter weighting which leads to uncertainties in the results of the conventional models such as analytic hierarchy process and multi-level fuzzy synthesis judgment, and features a simple computation without the construction of multi-level judgment matrix. The FPR model provides reliable results to support the efficient development of CBM.

Common Species Distribution Models in Biodiversity Analysis and Their Challenges and Prospects in Application

Species distribution models have been widely used to explore suitable habitats of species,the impact of climate change on the distribution of suitable habitats of species,and the construction of ecological reserves.This paper introduced species distribution models commonly used in biodiversity analysis,as well as model performance evaluation indexes,challenges in the application of species distribution models,and finally prospected the development trend of research on species distribution models.

Remote Sensing Landslide Monitoring Based on Machine Learning Method

The susceptibility evaluation of landslides has become one of the key environmental issues that people are concerned about. This study took the land-slides in Xishuangbanna, Yunnan Province as the study object, and selected 10 evaluation factors such as digital elevation model (DEM), slope aspect, precipitation, land use, water system, roads, population density, lithology, faults, and NDVI. Different machine learning methods were compared and studied, and the ROC (receiver operating characteristics) curve verification revealed that the accuracy of the random forest evaluation model was high. In the prediction and evaluation of the susceptibility of landslides, five risk levels were divided. After the superimposed analysis, 87.26% of the disaster points fell in the first and second susceptibility areas. The spot analysis found that the distribution of hot spots is consistent with the distribution of disaster spots. In a word, the results of this study can provide better technical support for the evaluation and early warning of landslides in Southwest China.

Research on the Construction of Evaluation Model for the Development of Biopharmaceutical Park in China

Objective To study the influencing factors on the development of biopharmaceutical park,and to construct an evaluation model of the influencing factors for biopharmaceutical park in China.Methods By analyzing various factors affecting biopharmaceutical parks,an evaluation index system of biopharmaceutical parks and an evaluation model of influencing factors of biopharmaceutical park development based on fuzzy group decision making were established.Results and Conclusion Factors such as research and development(R&D)funding investment,incentive for transformation of scientific and technological achievements,and industrial clusters have a greater impact on the development of biopharmaceutical industrial parks in China.Local governments should increase the investment in R&D funding.Besides,they should pay attention to the incentive of transformation of scientific and technological achievements to improve the innovation ability of enterprises.Meanwhile,they should promote the clustering of high-tech enterprises to comprehensively enhance the healthy development of biopharmaceutical parks in China.