Results Of Comprehensive Evaluation Research Articles

Integrity assessment of shale gas wells in Changning Block based on hierarchical analysis method

AbstractThe integrity of shale gas wells is crucial in ensuring safety and efficiency throughout the development process. Such integrity spans the entire process of drilling and fracturing horizontal wells and is an essential indicator for ensuring safe and stable production throughout the lifespan of the well. This study investigates methods for assessing the integrity of shale gas wells by employing the analytic hierarchy process combined with experimental data to establish evaluation criteria and weights. The assessment is carried out specifically on shale gas wells in Changning Block. Results indicate that the integrity of these shale gas wells is influenced by various factors, such as drilling and fracturing processes. Moreover, the integrity assessment of indicators such as oil layer casing/technical casing, liquid carrying capacity, and tube column deformation is relatively low, indicating a need for enhanced monitoring and management. The comprehensive evaluation results indicate that, overall, the integrity rating of shale gas wells is generally considered “common,” but some potential safety hazards still remain that require timely attention and resolution. Case analysis reveals varying levels of integrity risks in shale gas wells. Case 1’s score of 93.51 warrants attention but is still deemed generally safe. However, Case 2’s score of 73.89 indicates a disaster level, emphasizing urgent intervention needs. Critical factors such as pressure, cementation quality, and corrosion demand proactive management for safe, sustainable operations.

Evaluation methods of BDS-3 ground-segment defensive capability oriented to satellite navigation countermeasures

Owing to intentional interference and destructions during satellite navigation countermeasures, the security application of global navigation satellite systems (GNSS) faces immense challenges. To ensure the safe application of the GNSS in complex electromagnetic environment, the system-level defensive capability need be assessed, which can make for maintaining GNSS normal service during countering and further realizing the optimal decision. Therefore, this study used the ground control segment in the GNSS as the evaluation object, the bottom indices related to the criterion layers including service performance and station function as the key evaluation indices, and the technical requirement of each index under a secure situation as the standard, to propose the evaluation system including index system and evaluation methods for the ground-segment defensive capability. As BeiDou navigation satellite system III (BDS-3) is a global navigation satellite system independently built and operated by China, it was taken as a case for method verification. Then, BDS-3 two-way observation data between the satellite and the ground and between stations, which was collected from Beijing flight Control Center, from March 5 to 12 (2022) were selected during tests, and the results were compared with the existing standards contained in BDS open service performance standard to evaluate the system-level defensive capability. Evaluation Results of positioning accuracy and error correction ability for the BDS-3's ground stations determined through seven damage experiments with different interference strength show that: Corresponding horizontal and vertical positioning accuracy of stations under test did not exceed 1 m in the statistical period and their convergence time did not exceed the limit (30 min); thus, the ground segment of the BDS-3 has a good defensive capability. Compared to comprehensive evaluation results of the BDS-3, based on the theoretical threshold (the ground-segment threshold ≤48.40 % and the space-segment threshold ≤51.60 %), we know that its ground-segment defense (14.06 %) was worse than GPS ground-segment defense (14.43 %), whereas the ground-segment defense of the BDS/GPS integrated system (15.29 %) was best and its capability evaluation grade was strong. They indicate system's future improvements should focus more on enhancing the development scale and service efficiency of the BDS-3's ground stations in the Western Hemisphere, and reasonably promote system compatibility and interoperability while considering facility cost and operating efficiency.

ACSICS: Joint Distribution Mode Integrating Agricultural Industry Chain Logistics Under the Background of Artificial Intelligence

The purpose is to study the new application of artificial intelligence (AI) technology in the Agro logistics industry distribution modes. This work summarizes the problems in agricultural logistics by investigating the current situation of the logistics distribution modes (LDMs) of Agro products and establishes a joint LDM integrating logistics and agricultural industry chain (AIC). An intelligent virtual center is established for the joint LDM according to the specific situation of Xi’an. Experts are invited to evaluate the proposed LDM. The results show that the existing third-party logistics (3PL), agricultural supermarket docking LDM, and company+farmer shared LDM have respective advantages and disadvantages. The virtual center for the proposed joint LDM multiplies the weight matrix [Formula: see text] and fuzzy evaluation matrix A to obtain a comprehensive fuzzy evaluation result. It evaluates the result according to the maximum membership criterion. Most experts have a relatively good evaluation of the joint LDM. In the comprehensive fuzzy evaluation results, the comprehensive “excellent” score is 0.3755, and the comprehensive “good” score is 0.2678. According to the principle of maximum subordination, the AIC logistics integrating Agro products logistics has an excellent performance, and the overall satisfaction level of performance has exceeded 85%. In addition, Yonghui supermarket adopts the joint LDM, and the price of fruits and vegetables is lower than that of other LDMs. Therefore, the proposed AI-based joint LDM can optimize the distribution route, improve distribution efficiency, and save logistics costs to a great extent.

Design of an online education student learning status evaluation model based on dual-improved neural networks

With the continuous development of network technology, online education has become an important form of education. However, in the online education model, it is difficult for educators to effectively evaluate students' learning status, and using a learning status evaluation model can effectively solve this problem. The main goal of this model is to comprehensively evaluate students' learning behavior, progress, and outcomes, in order to understand their learning status, provide effective teaching feedback to teachers, help students improve learning methods, and improve learning efficiency. The current automatic evaluation model for student learning status has certain limitations in terms of applicability and accuracy. A student learning state evaluation model based on Multi task Cascaded Convolutional Networks (MTCNN) is proposed to address the effectiveness of online education student learning state evaluation. Use the facial image acquisition function to extract students' facial features, process each feature through label classification, and then analyze the students' attention and learning emotions. Finally, analyze the effectiveness of the research method application. The results showed that the train_loss value of the learning state evaluation model proposed in the study can be reduced to about 0.1; the train_acc value can reach more than 95 %, and the overall volatility is small; the overall evaluation accuracy of facial expressions can reach 74.71 %, which is significantly better than cpc, VGG19 and other evaluation methods; compared with the comprehensive evaluation results and multi-modal analysis methods, only two evaluations at the critical value are different. The experimental results show that the online education students’ learning status evaluation model designed by the research has a high accuracy rate and has a certain application potential in the field of online education.

Study on Supply Shain Financing Scheme of A Vietnamese Coffee Company in China

This paper takes G7 Coffee, a Vietnamese coffee company, as an example to design a supply chain financing scheme suitable for the company. First of all, on the basis of explaining the concept of supply chain, supply chain financing and other related concepts, supply chain management theory, supply chain financing model, fuzzy comprehensive evaluation model and other theoretical foundations, based on the financing situation of a Vietnamese coffee company G7 coffee in China, combined with the financing problems of the company and the company's capital needs, The feasibility of supply chain financing of G7 Coffee in China for a Vietnamese coffee company is proposed. Secondly, this paper introduces the evaluation method of supply chain financing scheme of G7 Coffee in China of a Vietnamese coffee company. Finally, on the basis of clear objectives and principles of financing scheme design, an evaluation system of supply chain financing mode of a Vietnamese coffee company based on AHP is constructed. The applicability of accounts receivable supply chain financing, inventory supply chain financing and prepayment supply chain financing adopted by the company is further analyzed by fuzzy comprehensive evaluation method. The fuzzy comprehensive evaluation results show that The accounts receivable financing model is the best financing model for the supply chain financing of G7 Coffee in China of a Vietnamese coffee company. In order to ensure the smooth implementation of the supply chain financing plan of a Vietnamese coffee company G7 Coffee in China, this paper proposes to strengthen the guarantee from three aspects: financial system, credit management and risk control.

Assessment of Intelligent Unmanned Maintenance Construction for Asphalt Pavement Based on Fuzzy Comprehensive Evaluation and Analytical Hierarchy Process

Conventional human-involved maintenance methods for asphalt pavement pose significant challenges when applied to high-traffic road sections, often leading to congestion and safety risks, as well as reduced maintenance efficiency. In recent years, explorations into unmanned construction technology for newly constructed expressways have yielded beneficial and encouraging results. However, its application in road maintenance in more complex environments still needs to be expanded. In this study, an intelligent unmanned maintenance technology for asphalt pavement was applied to the Lilong Highway in Zhejiang Province, China, and the compactability, thickness, surface smoothness, permeability coefficient, and constructure depth of maintenance road sections were measured. Then, based on fuzzy comprehensive mathematics and the analytic hierarchy process, a comprehensive evaluation was performed on the intelligent unmanned maintenance technology, considering the aspects of road quality, safety, application, and socio-economic benefits. The results show that the road quality of intelligent unmanned maintenance technology can meet the road specification requirements. In addition, the membership degree of unmanned maintenance technology in the excellent grade is the highest, reaching 0.805, and the quantified value for the overall evaluation of the application effectiveness of unmanned maintenance technology is 92.10. This means that the final comprehensive evaluation result of unmanned maintenance technology is rated as excellent. The research findings provide decision-makers with valuable insights into the unmanned automation maintenance challenges faced by asphalt pavement, enabling them to implement appropriate measures to elevate the maintenance standards of road transportation.

Evaluation of Urban Quality Improvement Based on the MABAC Method and VIKOR Method: A Case Study of Shandong Province, China

In the current stage of urbanization in China, urban construction has gradually shifted from incremental construction dominated by real estate to stock transformation based on improving urban quality. The evaluation of urban renewal projects is crucial for decision-making and resource allocation. However, there is no consensus on the evaluation indicators and methods. This study evaluates the current status of urban quality using the MABAC method based on numerical indicators. It evaluates the improvement of urban quality using the VIKOR method based on public satisfaction indicators. It is found that the comprehensive weights and subjective weights of the five first-level indicators in the evaluation index system of urban quality improvement in Shandong Province, namely blue–green space improvement, air cleanliness improvement, road traffic improvement, life service improvement, and governance capacity improvement, are quite different. The weight distribution of these indicators needs to be adjusted and optimized, especially for improving living services, as well as secondary indicators such as black and odorous water treatment, urban clean heating, the number of public vehicles per 10,000 people in the city, the 15 min living circle, the renovation of old residential areas, and the construction of urban intelligent management platforms. Based on the comprehensive evaluation results, an attempt is made to propose a more scientific evaluation index system, providing valuable references for urban renewal management.

Current Controller Design of Grid-Connected Inverter with Incomplete Observation Considering L-/LC-Type Grid Impedance

This paper presents a current control design for stabilizing an inductive-capacitive-inductive (LCL)-filtered grid-connected inverter (GCI) system under uncertain grid impedance and distorted grid environment. To deal with the negative impact of grid impedance, LC-type grid impedance is considered in both the system model derivation and controller design process of an LCL-filtered GCI system. In addition, the integral and resonant control terms are also augmented into the system model in the synchronous reference frame to guarantee the reference tracking of zero steady-state error and good harmonic disturbance compensation of the grid-injected currents from GCI. By considering the effect of grid impedance on the control design process, an incomplete state feedback controller will be designed based on the linear-quadratic regulator (LQR) without damaging the asymptotic stabilization and robustness of the GCI system under uncertain grid impedance. By means of the closed-loop pole map evaluation, the asymptotic stability, robustness, and resonance-damping capability of the proposed current control scheme are confirmed even when all the system states are not available. In order to reduce the number of required sensors for the realization of the controller, a discrete-time current-type full-state observer is employed in this paper to estimate the system state variables with high precision. The feasibility and effectiveness of the proposed control scheme are demonstrated by the PSIM simulations and experiments by using a three-phase GCI prototype system under adverse grid conditions. The comprehensive evaluation results show that the designed control scheme maintains the stability and robustness of the LCL-filtered GCI when connecting to unexpected grids, such as harmonic distortion and L-type and LC-type grid impedances. As a result, the proposed control scheme successfully stabilizes the entire GCI system with high-quality grid-injected currents even when the GCI faces severe grid distortions and an extra grid dynamic caused by the L-type or LC-type grid impedance. Furthermore, low-order distortion harmonics come from the background grid voltages and are maintained as acceptable limits according to the IEEE Std. 1547-2003. Comparative test result with the conventional one also confirms the effectiveness of the proposed control scheme under LC-type grid impedance thanks to the consideration of LC grid impedance in the design process.

Evaluation method for the impact of digital finance on the environmental performance of manufacturing industry

ABSTRACT A new evaluation method for the impact of digital finance on the environmental performance of the manufacturing industry is proposed to improve the accuracy of evaluation results and provide reliable data for enterprise development. Establish a scientific and comprehensive evaluation index system that includes environment, cost-effectiveness, life cycle, and sustainable development. Collect sample data through indirect measurement and direct measurement methods through questionnaire surveys and standardize each data through the measurement of digital economy development level to eliminate differences between different indicators. Based on the constructed evaluation indicator system and sample data collection results, the weights of each evaluation indicator are determined by establishing a projection pursuit model. The fuzzy comprehensive evaluation method and the analytic hierarchy process are used to obtain the fuzzy comprehensive evaluation results of environmental performance based on the projection pursuit model to evaluate the impact of digital finance on the environmental performance of the manufacturing industry. The experimental results show that compared with traditional business models, digital business models can effectively reduce energy consumption, operating costs, and logistics transportation costs of enterprises, improve resource utilization efficiency, and outperform traditional methods in evaluation accuracy, recall rate, and efficiency, verifying the effectiveness of this method.

Comparative Study on Financial Services Trade Competitiveness in the Belt and Road Countries — Taking the Banking Sector as an Example

Based on the comprehensive evaluation results of entropy weight TOPSIS method, this paper conducted a comparative analysis on the financial services trade competitiveness in the Belt and Road Initiative countries, taking the banking sector as an example. The main findings are as follows: most Belt and Road Initiative countries lack competitiveness in financial services trade across borders and the gap is obvious when they are compared with Japan and other developed Western countries. China’s financial services trade competitiveness is ranked highly among the Belt and Road Initiative countries; the financial services trade competitiveness in East Asia and Central and Eastern Europe is stronger than that of other regions with South Asia being the weakest. Based on Diamond Model, this study analyzed the reasons for the gap between the Belt and Road Initiative countries and developed Western countries, and found that the gap between them is obvious in most aspects. Finally, countermeasures are proposed to improve China’s financial services trade competitiveness based on the analysis.

The correlation between drivers’ road familiarity and glance behavior using real vehicle experimental data and mathematical models

Objective Road familiarity is an important factor affecting drivers’ visual features. Analyzing the quantitative correlation between drivers’ road familiarity and visual features in complex environment is of great help to improve driving safety. However, there are few relevant studies. This paper takes urban plane intersection as the environmental object to explore the correlation between drivers’ glance behavior and road familiarity, and conducts research on the quantitative evaluation model of road familiarity based on this correlation. Method First, a real vehicle experiment was carried out to record the eye movement data of 24 drivers with different road familiarity. The driver’s visual field plane was divided into 10 areas of interest (AOIs) based on the driver’s perspective. Three measures, including average glance duration, number of glances, and fixation transition probabilities between AOIs at urban plane intersections, were extracted. Finally, based on the experimental results, the driver road familiarity evaluation model was constructed using the factor analysis method. Results There are significant differences between unfamiliar and familiar drivers regarding the average glance duration toward the forward (FW) area, the left window (LW) area, the left rearview mirror (LVM) area and the left forward (LF) area, the number of glances toward the other (OT) area, and the fixation transition probabilities of LW→RF (right forward), LF→LF, LF→FW, FW→LW, FW→FW, FW→RVM (right rearview mirror). The comprehensive evaluation results show that the accuracy rate of the driver road familiarity evaluation model reached 83%. Conclusions This paper revealed that there is a strong correlation between drivers’ road familiarity and drivers’ glance behavior. Based on this correlation, we can include road familiarity as a part of drivers’ working status and establish a high accuracy evaluation model of driver road familiarity. The conclusion of this paper can provide some reference for the humanized design and improvement of advanced driving assistance system, which is of great significance for reducing the driving workload of drivers and improving the driving safety.

Comprehensive Assessment and Empirical Research on Green and Low-Carbon Technologies in the Steel Industry

The iron and steel industry is the leading industry supporting China’s industrial sector. Currently, there is less assessment work on green and low-carbon technologies for the iron and steel industry. This study clarifies the overall strategy of technology assessment by researching the relevant theories and methods of technology assessment. The study further establishes a scientific and reasonable comprehensive assessment index system of green and low-carbon technologies for the iron and steel industry from the aspects of technology index, economy and promotion, and application, including factors such as 11 indexes, the amount of energy saving, carbon dioxide emission reduction, and the resource recovery rate by utilising analytical and comprehensive methods and combining with the characteristics of the technologies. By analysing and comparing the advantages and disadvantages of the commonly used assessment methods, the entropy weighting method, grey correlation analysis method, and TOPSIS (technique for order preference by similarity to an ideal solution) method are combined and optimised to construct a comprehensive assessment model. The Latin hypercube sampling method is also introduced to analyse the technical parameters in combination with the evaluation model. Finally, fourteen iron and steel green and low-carbon technologies were selected for case assessment and uncertainty analysis of technical parameters, and it was found that the comprehensive assessment result of gas combined cycle power generation technology was optimal. After determining the weights of each assessment indicator through the entropy weighting method, it is concluded that the technical performance indicator > economic indicator > promotional indicator. A comparative analysis of the results under the three preference decisions concludes that technical performance is the main obstacle to improving the comprehensive assessment score of the technology, followed by the economics of the technology. Finally, the uncertainty analysis of the technical parameters shows that the fluctuation of the technical parameters not only affects the performance of the technology, but also affects the weights of the indicators and the comprehensive evaluation results of the technology.

Power quality interval grading evaluation method of AC/DC distribution network considering source-load weighting and voltage coupling

In the context of the ‘dual carbon’ goal, the integration of renewable energy sources has a significant impact on distribution systems, while the substantial integration of DC loads and photovoltaic power has led to a progressive transition of conventional distribution networks towards hybrid AC-DC distribution networks in the field of electrical engineering. However, this shift has brought about more formidable power quality challenges within the power industry. To address these emerging power quality issues, we propose a novel power quality interval grading evaluation method for AC/DC distribution networks considering source-load weighting and voltage coupling. Firstly, the voltage acquisition data is meticulously decoupled to disentangle the interdependencies. Secondly, the power quality evaluation system of the AC/DC distribution network is established. Considering the influence of different access source-load types on each node, the subjective weight is determined by source load weighted two-tuple linguistic analytic hierarchy process (AHP), the objective weight is determined by the entropy weight method, and the idea of using game equilibrium algorithm to obtain comprehensive weight to balance the error of single weight on evaluation result is put forward. Then, the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) of interval number improvement is used to classify and evaluate the power quality index to make up for the shortcomings of the single-point sampling method. Finally, a more accurate and comprehensive power quality evaluation result is obtained based on a practical example.

Spatial and temporal assessment of sustainable development indicators for the China-Pakistan transportation corridor

ABSTRACT The China-Pakistan Transportation Corridor (CPTC) has long faced great challenges in natural disasters and sustainable development. This study develops a localised indicator evaluation system for the CPTC sustainable development. It contains 27 Tier I and 8 Tier II indicators, covering 11 sustainable development goals. Based on this evaluation system, a single-goal, multidimensional, and comprehensive evaluation of the CPTC sustainable development level is conducted for 2015, 2017 and 2020. The results show that, in terms of single goals, Xinjiang has the highest sustainable development level. Khyber Pakhtunkhwa has the poorest level of sustainable development. The Islamabad Capital Territory is better developed for all goals, especially in SDG5, SDG8 and SDG9. Besides these three goals, SDG6, and SDG11 are more prominent in Punjab, whereas SDG2 and SDG3 performed worst. From a multidimensional evaluation, the CPTC sustainable development level has been steadily increasing. However, the social and environmental dimensions of Khyber Pakhtunkhwa have experienced a ‘regression’. The comprehensive evaluation results show that the level of sustainable development in all provinces of the CPTC increase, except for Khyber Pakhtunkhwa. This study identifies CPTC sustainability issues and proposes targeted recommendations for sustainable development.

A comprehensive assessment method for manned confined space layouts taking into account operational posture comfort supported by artificial intelligence algorithm

Given its specialized design application, the layout design of confined spaces for human occupancy has a significant impact on the efficiency of operators, especially in the design processes aimed at aviation, aerospace, navigation, and other significant engineering fields. The influence of operational posture on layout comfort is crucial, yet existing assessment methods have limited considerations for the impact of operational posture on layout comfort. Therefore, this study proposes a layout decision support method that integrates posture recognition, simulation, and simulation-based comfort comprehensive assessment. By combining intelligent recognition technology, simulation technology, and comprehensive evaluation methods, it aims to provide a highly reliable comprehensive evaluation result for layout design and decision recommendations. To validate the effectiveness of the method, we conducted a comfort experimental evaluation involving seven individuals in the layout design of human-occupied confined spaces at Northwestern Polytechnical University. The results indicate that the proposed method offers a more objective and comprehensive means for layout design and optimization. This Improvement method not only addresses the deficiencies in existing spatial layout evaluation methods and provides a theoretical basis for architectural layout planning evaluation but also offers new perspectives and methodological support for scientific layout design and planning.

A general framework for qualitative analysis of Raman spectroscopy based on deep learning

Deep learning has become the prevailing method for qualitative analysis of Raman spectroscopy. However, for researchers and engineers without a background in computer science or artificial intelligence, the knowledge required can be challenging. This includes the underlying principles of deep learning and the features of frameworks such as PyTorch, TensorFlow, and Keras. To address this challenge, we summarize the Raman spectroscopy analysis process and design a suitable deep learning framework, including dataset creation, data preprocessing, data augmentation, deep learning model development, model training, model evaluation, model visualization analysis, and model deployment. We use four open-source Raman spectroscopy datasets, including binary classification and multi-classification examples, to explain the framework’s components and operation and provide comprehensive evaluation results. This framework has the potential to improve work efficiency and accelerate the research process.

Regional population and social welfare from the perspective of sustainability: Evaluation indicator, level measurement, and interaction mechanism.

Key to regional sustainable development are the development and interplay of population dynamics and social welfare, each playing a significant role. As a representative region with demographic characteristics such as negative population growth and large labor outflow, the development and interaction between population and social welfare in Nanchong deserve in-depth exploration. This article takes the development of population and social welfare in Nanchong as the research object, and constructs an evaluation indicator system of population and social welfare through research backtracking, and uses entropy method and coupling coordination model to measure the development level and interactive effect of population and social welfare in Nanchong from 2010 to 2021. The research results show that: Firstly, the comprehensive evaluation results of population in Nanchong shows a linear upward trend, which indicates the stable positive effect of population structure and distribution, the gradual improvement effect of population quality effectively compensate for the weakening effect of population quantity, thus achieving the positive development of population. Secondly, the comprehensive evaluation results of social welfare in Nanchong shows an exponential upward trend, which indicates the social welfare has maintained a rapid growth momentum in various dimensions and the long-term positive effects have completely absorbed the negative effects, thus achieving the positive development of social welfare. Thirdly, during the sample period, the population and social welfare in Nanchong consistently maintained a high level of interaction strength, with factors diffusing and integrating. On this basis, the diffusion theory is used as an empirical reference to construct three interactive mechanisms between the population and social welfare in Nanchong and the implications are inferred from the empirical results.

Analysis of Outstanding Problems and Countermeasures in the Reform of Fine Arts Teaching in China’s Colleges and Universities Based on the VAR Model

Abstract With the development of society, the artistic cultivation requirements for talents are increasing. This paper discusses in depth the main problems in the current reform of art teaching and puts forward targeted solution strategies, aiming to improve the overall quality of art teaching. In the study, the key factors affecting the quality of art teaching in colleges and universities were analyzed using the VAR model, and a multimodal art education knowledge map was constructed using the Viterbi method. Through the ALKPT knowledge tracking model, this paper assessed and scored students’ mastery of art knowledge and incorporated the results into the art classroom quality evaluation module. Based on the scoring data, the art classroom quality features were standardized, and the comprehensive evaluation results were derived through feature fusion dynamic weight assignment. Impulse response analysis showed that the number of returnees who studied abroad to learn about art positively impacted art teaching. The empirical results showed that after the reform of art teaching, the students’ art theory scores increased by 5 points on average, the scores were distributed between 10 and 20 points, and the achievement gap between students was reduced. This study provides a robust strategy and evaluation tool for optimizing art teaching, improving teaching quality and promoting students’ artistic literacy.

Research on the reform and effect evaluation of three-dimensional motion animation blended teaching based on fuzzy evaluation model

Abstract This paper combines the teaching of a 3D animation course with the blended teaching mode and constructs a framework for the design of 3D animation blended teaching reform. Based on the fuzzy comprehensive evaluation algorithm, we adopt qualitative and quantitative methods to determine the evaluation index system of teaching reform, divide the course teaching objectives, teaching content, learning resources, online learning and teaching design and classroom organization into five first-level indexes, establish the weights of the evaluation index system, and complete the construction of the fuzzy comprehensive evaluation system of 3D animation blended teaching. Examine the design and teaching effects of 3D animation that blends learning from different dimensions, and examine the correlation between learners’ multidimensional recognition of teaching reform and its learning impact. By combining the weights of each index, the fuzzy comprehensive evaluation results are obtained by determining the affiliation degree of each index using the fuzzy statistical method. The operation results show that the fuzzy comprehensive evaluation scores of the five first-level indicators of teaching reform are 0.754546, 0.69943, 0.638926, 0.66888, and 0.5966. It can be seen that the comprehensive evaluation results of the five aspects have achieved good results. The evaluation of teaching reform’s effects can be targeted and feasible using a fuzzy comprehensive evaluation model.

Clinicopathologic assessment of secondary syphilis avoids misdiagnosis: results of comprehensive evaluation of 114 cases.

Secondary syphilis is well-known for its protean cutaneous manifestations and therefore very easy to be misdiagnosed. The current study was to observe the frequency of histopathological features characterizing secondary syphilis, and summarize the diseases most likely to be misdiagnosed. In this study a total of 129 pathological specimens from 114 patients with biopsy-proven secondary syphilis were retrospectively analysed and categorized according to clinicopathologic characteristics. The frequency of histopathological features characterizing secondary syphilis were analysed by comparison with clinical features. We found that in a single sample there is at least one feature or at most 13 features exist concurrently, and most demonstrated between 5 and 9 diagnostic features. Plasma cells (97.6% overall vs. 94.0% ≤ 6 features), endothelial swelling (86.8% vs. 74.0%), epidermis hyperplasia (73.6% vs. 62.0%) especially irregular acanthosis, lymphocytes infiltration (71.3% vs. 52.0%) and interstitial patterns (69% vs. 72.0%) were the most common findings in all cases as well as in cases with ≤ 6 features. Granulomatous inflammation is an uncommon histopathologic pattern in secondary syphilis (12.4%). The rash morphologies of our biopsies mainly manifesting as macules and maculopapules were more likely to have 6 or fewer features, which were not only easily misdiagnosed for pityriasis rosea, tinea and erythema multiforme, but also mostly taken from the trunk and genitalia. Atypical morphologies can be combined with plasma cell infiltration and T. pallidum immunohistochemical stain to confirm the diagnosis. In this study plasma cells from superficial and deep perivascular distribution to nodular infiltration were a crucial clue for diagnosis of secondary syphilis.