Comprehensive Evaluation System Research Articles

Scenario-Based Green Infrastructure Installations for Building Urban Stormwater Resilience—A Case Study of Fengxi New City, China

Global climate change has precipitated a surge in urban flooding challenges, prompting the imperative role of green infrastructure (GI) as the linchpin of sponge city construction to enhance urban sustainability and resilience. But the evaluation of urban stormwater resilience faces challenges due to the lack of a comprehensive evaluation framework taking the intrinsic features of the resilience system into account and the insufficient coverage of alternative scenarios’ performance under multiple rainfall return periods. This study, focusing on Fengxi New City, China, evaluates the suitability of GI (i.e., green roofs, rain gardens, and permeable pavements) and constructs a stormwater management model (SWMM) for urban stormwater hydrological simulation. This study also establishes a comprehensive urban stormwater resilience evaluation system and uses quantitative methods to unify the performances of scenarios under different rainfall return periods. Our analytical findings elucidate that the suitability of GI is predominantly concentrated in the northern and western areas of the study area, with the smallest suitable area observed for permeable pavements. Divergent GIs exhibit disparate performances, with rain gardens emerging as particularly efficacious. Importantly, the combination of multiple GIs yields a synergistic enhancement in resilience, underscoring the strategic advantage of adopting a diverse and integrated approach to GI implementation. This study facilitates a deeper understanding of urban stormwater resilience and assists in informed planning decisions for GI and sponge cities.

Resisting the heat wave: Revealing inequalities in matching between heat exposure risk and healthcare services in a megacity

Climate warming and the growing urban heat island effect are exacerbating the unequal public health crisis in megacities, and thus it is important to assess the equity of matching relationship between the healthcare services and the heat exposure risk. We selected 255 census units in Tianjin city for the study, and calculated a heat exposure index based on the universal thermal climate index (UTCI) and constructed a comprehensive urban healthcare services evaluation system to measure the degree of mismatch between the two. The results showed the following. (1) The heat exposure risk and healthcare services followed an increasing pattern from the Outer suburb area (OSA) to the Metropolitan development area (MDA) and then to the Main urban area (MUA). (2) The overall imbalance in matching was low in the OSA, whereas the healthcare services were relatively insufficient in the MDA, and the heat exposure risk and healthcare services were relatively balanced in the MUA. (3) The degree of matching between the core and peripheral parts of the MUA was severely polarized, with an overall pattern of excess healthcare in the core area and a high risk of heat exposure in the peripheral areas. The results can provide effective guidance for rationalizing the allocation of healthcare resources from a heat exposure perspective, and provide a policy basis for risk management and fund investment.

The Integration of Dual Evaluation and Minimum Spanning Tree Clustering to Support Decision-Making in Territorial Spatial Planning

Spatial planning, a policy instrument for creating sustainable environments that meet the needs of the current and future generations, has been implemented extensively worldwide. However, it is difficult for urban planners to thoroughly determine the spatial value of a territory and make informed decisions regarding the efficient utilization of regional resources in the real world. This study proposes a novel methodological framework for spatial pattern optimization that can guide future land use by integrating Minimum Spanning Tree (MST) clustering with a comprehensive evaluation system (dual evaluation). Furthermore, the validity of this framework is demonstrated through a case study of territorial spatial planning in Deyang, China. The findings indicate that (1) the methodological framework presented in this study offers valuable guidance for the spatial arrangement of territorial resources, especially in practical projects; and (2) the combination of dual evaluation and MST clustering can facilitate automatic regionalization to identify spatial clusters exhibiting functional similarity in terms of land use. By focusing on methodological advancements, this study concludes that the integration of dual evaluation (DE) and MST clustering not only simplifies the identification of optimal land-use patterns but also promotes a more systematic and efficient approach to support spatial planning.

Reform and Innovation of College English Teaching Under the Background of Mobile Internet and Big Data

The rapid development of mobile Internet has brought new development opportunities to college education and teaching. Taking university English teaching as the research object, this paper analyses the characteristics of mobile Internet in the classroom, WeChat platform, English learning app and other forms of teaching, the changes and influence of mobile Internet on English teaching, and its application in university English teaching. According to the actual teaching situation, a comprehensive evaluation system based on the learning process and results was established. The results show that the university English teaching model based on mobile Internet and the innovative evaluation and examination system can effectively improve the teaching efficiency and students' independent and sustainable learning ability. Through the reform of university English teaching, students' academic performance and learning ability have been improved. The research results are of great practical significance for promoting the reform and innovative practice of university English teaching.

Assessment of the potential of salt mines for renewable energy peaking in China

Renewable energy sources, such as wind and solar, can reduce environmental pollution and promote the transformation of the energy structure. However, the intermittency and uncertainty of new energy sources such as wind and photovoltaics pose challenges to large-scale grid integration. Effective utilization of intermittent energy sources requires large-scale energy storage facilities. Salt rock is recognized as an excellent medium for underground large-scale energy storage with a wide range of applications. This paper identifies the potential of salt caverns to be used for large-scale energy storage by analyzing the distribution of wind and solar energy resources in China, taking into account the grid-connected infrastructure of the Chinese power grid and the geographic location of salt mines. The overlapping areas are identified for utilization in compressed air energy storage and hydrogen storage. Through meticulous categorization and analysis of the factors influencing salt cavern underground storage site selection, the AHP-EWM method is introduced to establish an objective hierarchy model for a comprehensive evaluation system of salt cavern underground storage site selection. The comprehensive planning of China's 20 major salt mines is conducted, and the research findings hold significant reference value for facilitating the low-carbon energy transition in China.

Material corrosion characteristics of heat-treated SLM-ed Hastelloy X in electrochemical machining process

Selective laser melting (SLM) technology and electrochemical machining (ECM) offer new methods for producing nickel-based superalloys with complex structures and high surface quality, including Hastelloy X parts. However, SLM-fabricated parts exhibit significant anisotropy, and there are no effective criteria for evaluating material corrosion characteristics in actual ECM due to the detachment of research and application, making the parameter selection challenging in actual ECM. To address this issue, this article proposes a comprehensive evaluation system based on the corrosion characteristics in the actual machining process and investigates the effect of heat treatment temperature on the corrosion characteristics of Hastelloy X in ECM. The results show that at a heat treatment temperature of 1000°C, machining efficiency, accuracy, and localization can all be achieved at a good level with good consistency in different directions at the expense of a certain machining accuracy. The 800℃ heat-treated specimen exhibits strong corrosion resistance, providing a significant advantage in machining localization and accuracy. When the heat treatment temperature exceeds the solid solution temperature (more than 1175℃), the mechanical properties and corrosion characteristics of the specimen are significantly degraded. The results of various material testing methods, including electrochemical testing, EBSD, XRD, and EDS indicate that changes in grain size due to recrystallization and the galvanic effect of precipitates are the primary causes of these changes.

Investigation of surrounding rock stability during proximal coal seams mining process and feasibility of ground control technology

The goaf formation of upper seam stope in proximity coal seams mining would influence the stability of the surrounding rock mass due to mining stress redistribution, which will seriously threaten the subsequent mining process and even ground environmental protection. Therefore, developing safe and efficient mining techniques, robust support strategies, and comprehensive safety evaluation systems is crucial for ensuring the overall safety of the mining process. Drawing upon on-site data, this study conducted a detailed feasibility analysis of the mechanized caving method. We developed a simulation model using similar materials, tailored for scenarios with overlying goaf, to demonstrate how lower seam mining was affected by the caving zone of the upper seam, leading to the progressive evolution of fracture networks. Furthermore, we employed numerical simulation models to juxtapose the simulated deformation areas with the actual potential deformation zones in the mining area. The mine seismic prediction (MSP) technique was utilized for the precise identification of unfavorable geological formations ahead of the working face, thereby preempting potential fractures or irregularities due to the presence of overlying goaf. In addition, a comprehensive support strategy was designed and implemented to bolster the stability of the roadways, thereby reinforcing the safety measures within the mining process. This study presents an integrated approach to investigate mining activities in the lower layers during stratified extraction, particularly how the overlying goaf of the upper seam affects the mining of the lower seam, leading to the progressive evolution of fracture networks. The findings and methodologies outlined in this work hold substantial practical significance, offering a pathway to enhance the reliability and safety of the mining process.

Evaluation of Air Traffic Control Ability Based on Fuzzy Theory and Multiple Evaluation Model

This paper constructs the structural model of the system of air traffic controllers' comprehensive ability evaluation. The use of analytic hierarchy process to determine the weight of various indicators should have weight values. The construction of the controller comprehensive capacity assessment model, fuzzy comprehensive evaluation method can be used to weigh matrix and membership matrix corresponding transformation, and then determine the comprehensive capacity of the controller to evaluate the value. In the assessment process, the advantages of various methods are combined, enabling the comprehensive evaluation of the comprehensive capacity of the controller, making the results tend to be reasonable. The research shows that the evaluation results made by this method can provide decision-making basis for aviation safety management at all levels. Using the multiple evaluation model, the controller’s comprehensive ability evaluation model is established to evaluate the comprehensive ability of the controller.

Temporal and Spatial Analysis of Coupling Coordination in Beijing–Tianjin–Hebei Urban Agglomeration: Ecology, Environment and Economy

With the rapid growth and development of urban areas, the economy has often been prioritized at the expense of the environment and ecological systems. However, it is essential to delve deeper into the relationship between the economy and the ecological environment. Therefore, this study introduces a comprehensive evaluation system that encompasses economic, ecological, and environmental factors in the Beijing–Tianjin–Hebei urban agglomeration in China. The Criteria Importance Through Inter-criteria Correlation (CRITIC) method is utilized to determine the weights of various indicators, and coupling as well as coupling coordination models are employed to investigate the spatiotemporal trends and interrelationships of the three factors. The results indicate that the economic development index has displayed a consistent uptrend since 2000, with the economic development index from 2015–2020 increasing by approximately four times compared to 2000–2005. The ecological status index has also increased in the last five years, with a rise of about 0.05 from 2015–2020 compared to 2000–2005. The environmental status index has fluctuated but generally increased, with a rise of approximately 5.6 times from 2015–2020 compared to 2000–2005. The coupling degree of the Beijing–Tianjin–Hebei urban agglomeration is relatively high, with intense coupling from 2005–2020, and moderate coupling from 2000–2005. Furthermore, the coupling coordination has continuously improved from mild maladjustment to barely coordinated from 2000 to 2020, indicating the enhancement of the coupling coordination of the three factors. It is crucial to acknowledge that there exists spatial heterogeneity in both the coupling degree and coupling coordination degree. This heterogeneity stems from the uneven progress in economic development, ecological conditions, and environmental status across various cities. Additional endeavors are required to foster the harmonized advancement of these factors across the entire region.

A Novel Strategy for Mixed Jam Evaluation: Apparent Indicator, Sensory, Metabolomic, and GC-IMS Analysis.

Jam is a popular traditional and modern food product for daily consumption. However, the benefits of mixed jams over single-fruit jams have not been thoroughly explored, with analyses limited to superficial indices. In this study, Xinjiang special Morus nigra L. and Prunus domestica L. were used as raw materials to prepare single-fruit and mixed jams, and their differences in antioxidants, organoleptic qualities, pH, texture, and color were analyzed. The dynamics of metabolites before and after thermal processing were assessed using untargeted metabolomics. The results indicate that the main metabolites were flavonoids, terpenoids, amino acids, phenolic acids, and carbohydrates. Flavonoid metabolites changed significantly after thermal processing, with 40 up-regulated and 13 down-regulated. During storage, polyphenols were the prominent differential metabolites, with fifty-four down-regulated and one up-regulated. Volatile aroma components were analyzed using gas chromatography-ion mobility spectrometry (GC-IMS); the aroma components E-2-hexenal, E-2-pentenal, 3-methylbutanal, 1-penten-3-ol, tetrahydro-linalool, 1-penten-3-one, hexyl propionate, isoamyl acetate, α-pinene, and propionic acid in mixed jam were significantly higher than in single-fruit jam. In this study, untargeted metabolomics and GC-IMS were used to provide a more comprehensive and in-depth evaluation system for jam analysis.

Design and rationale of the Comprehensive intelligent Hypertension managEment SyStem (CHESS) evaluation study: a cluster randomized controlled trial for hypertension management in primary care

BackgroundHypertension management in China is suboptimal with high prevalence and low control rate due to various barriers, including lack of self-management awareness of patients and inadequate capacity of physicians. Digital therapeutic interventions including mobile health and computational device algorithms such as clinical decision support systems (CDSS) are scalable with the potential to improve blood pressure (BP) management and strengthen the healthcare system in resource-constrained areas, yet their effectiveness remains to be tested. The aim of this report is to describe the protocol of the Comprehensive intelligent Hypertension managEment SyStem (CHESS) evaluation study assessing the effect of a multi-faceted hypertension management system for supporting patients and physicians on BP lowering in primary care settings. Materials and MethodsThe CHESS evaluation study is a parallel-group, cluster-randomized controlled trial conducted in primary care settings in China. 41 primary care sites from 3 counties of China are randomly assigned to either the usual care or the intervention group with the implementation of the CHESS system, more than 1600 patients aged 35-80 years with uncontrolled hypertension and access to a smartphone by themselves or relatives are recruited into the study and followed up for 12 months. In the intervention group, participants receive patient-tailored reminders and alerts via messages or intelligent voice calls triggered by uploaded home blood pressure monitoring data and participants’ characteristics, while physicians receive guideline-based prescription instructions according to updated individual data from each visit, and administrators receive auto-renewed feedback of hypertension management performance from the data analysis platform. The multiple components of the CHESS system can work synergistically and have undergone rigorous development and pilot evaluation using a theory-informed approach. The primary outcome is the mean change in 24-hour ambulatory systolic BP from baseline to 12-month. DiscussionThe CHESS trial will provide evidence and novel insight into the effectiveness and feasibility of an implementation strategy using a comprehensive digital BP management system for reducing hypertension burden in primary care settings. Trial registrationhttps://www.clinicaltrials.gov, NCT05605418

Green innovation and eco-efficiency: Interaction between society and environment of sustainable development demonstration belt in China

China has achieved remarkable results in sustainable development, particularly in integrating green innovation to enhance eco-efficiency. But why choose green innovation as the driver for urban eco-efficiency? How did it do? Based on ecological civilization demonstration zone in China (Yangtze River Economic Belt) city data from 2006 to 2019. This research developed comprehensive evaluation systems to measure both urban green innovation and ecoefficiency, making use of the SBM model with undesired output to gauge ecological efficiency of urban areas. On this basis, we extended analysis by applying a baseline regression model and a Spatial Durbin model to delve into the mechanisms of green innovation affects eco-efficiency. The results are as follows. (1) green innovation and urban eco-efficiency showed fluctuating upward trends but that regional heterogeneity existed among the three regions. Specifically, the lower reaches outperform in green innovation, closely followed by the middle and upper reaches. Concurrently, the eco-efficiency levels of the middle reaches surpass those of the lower and upper reaches. (2) Our findings confirmed that green innovation promotes eco-efficiency by pursuing economic growth while reducing externalities. Furthermore, green innovation and eco-efficiency exhibit a positive spatial correlation and benefits neighboring city’s’ eco-efficiency, revealing spatial spillover effect. (3) Technological progress and industrial restructuring, driven by green innovation practices, emerge as pivotal drivers for the improvement in eco-efficiency. The study's insights provide valuable guidance to policymakers and stakeholders seeking to leverage green innovation practices to promote long-term and healthy urban development.

Establishment of a human organoid-based evaluation system for assessing interspecies infection risk of animal-borne coronaviruses

ABSTRACT The COVID-19 pandemic presents a major threat to global public health. Several lines of evidence have shown that the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), along with two other highly pathogenic coronaviruses, SARS-CoV and Middle East Respiratory Syndrome (MERS-CoV) originated from bats. To prevent and control future coronavirus outbreaks, it is necessary to investigate the interspecies infection and pathogenicity risks of animal-related coronaviruses. Currently used infection models, including in vitro cell lines and in vivo animal models, fail to fully mimic the primary infection in human tissues. Here, we employed organoid technology as a promising new model for studying emerging pathogens and their pathogenic mechanisms. We investigated the key host-virus interaction patterns of five human coronaviruses (SARS-CoV-2 original strain, Omicron BA.1, MERS-CoV, HCoV-229E, and HCoV-OC43) in different human respiratory organoids. Five indicators, including cell tropism, invasion preference, replication activity, host response and virus-induced cell death, were developed to establish a comprehensive evaluation system to predict coronavirus interspecies infection and pathogenicity risks. Using this system, we further examined the pathogenicity and interspecies infection risks of three SARS-related coronaviruses (SARSr-CoV), including WIV1 and rRsSHC014S from bats, and MpCoV-GX from pangolins. Moreover, we found that cannabidiol, a non-psychoactive plant extract, exhibits significant inhibitory effects on various coronaviruses in human lung organoid. Cannabidiol significantly enhanced interferon-stimulated gene expression but reduced levels of inflammatory cytokines. In summary, our study established a reliable comprehensive evaluation system to analyse infection and pathogenicity patterns of zoonotic coronaviruses, which could aid in prevention and control of potentially emerging coronavirus diseases.

Abstract 6447: Development of a fully automated immunoassay system of serum pembrolizumab to forecast therapeutic effectiveness

Abstract Recently, immuno-oncology treatments utilizing immune checkpoint inhibitors including pembrolizumab have attracted attention. Such treatments demonstrate potential effectiveness against cancers resistant to existing drugs, while offering the benefit of reduced side effects. Nonetheless, there is a specific group of patients who do not experience adequate therapeutic benefits from pembrolizumab. Despite the issue, the development of a comprehensive evaluation system to forecast therapeutic effectiveness is still in development. A strategy to predict therapeutic effectiveness involves evaluating the trough level or the steady state plasma-concentration of a drug in the blood. Ohuchi, M. et al. (Lung Cancer, 2022) demonstrated that patients with lower trough levels have shorter overall survival and progression-free survival durations, according to LC-MS/MS measurement of pembrolizumab. Furthermore, Wang, N. et al (Lung Cancer, 2023) demonstrated that the optimization of the dosage interval, grounded on the steady state plasma-concentration (target concentration, 15 µg/mL) of pembrolizumab, extended the duration of progression-free survival. Despite the potential of LC-MS/MS measurements in predicting patient prognosis and the benefits of PK-guided therapy, their implementation in clinical settings is hindered by the complex and time-consuming pre-treatment process for samples. Consequently, there is a growing need for a practical and clinically feasible drug concentration measurement system. Aiming to construct a clinically applicable pembrolizumab measurement system, we have been dedicated to developing a fully automated immunoassay system using anti-pembrolizumab antibodies. We developed two measurement systems of pembrolizumab in serum using two different antibodies targeting pembrolizumab. Using less than 10 µl serum, these systems can quantify the concentration of pembrolizumab ranging from 0.125 to 500 µg/mL within an hour, thereby enabling PK-guided therapy in clinical settings. After developing the measurement systems, we performed a correlation analysis with the LC-MS/MS system, using 70 samples with varying pembrolizumab concentrations ranging from 1.80 to 85.0 µg/mL. The results demonstrated that our measurement systems have a good correlation with LC-MS/MS measurement. Furthermore, the two immunometric measurement systems demonstrated a significant correlation with each other, substantiating the accuracy of the newly developed measurement system in determining the levels of pembrolizumab in the serum. The fully automated immunoassay systems we developed can measure pembrolizumab in serum within an hour, potentially paving the way for personalized treatment based on the serum concentration of pembrolizumab in clinical practice. Citation Format: Naotaka Noda, Takuya Takahashi, Shigehiro Yagishita, Masahiro Miura, Yusuke Takahashi, Yasuhiro Irino, Masatoshi Yanagida, Akinobu Hamada. Development of a fully automated immunoassay system of serum pembrolizumab to forecast therapeutic effectiveness [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6447.

Analysis, distribution, and health evaluation of 8 biogenic amines in Chinese mackerel products by CoFe2O4/MEG solid phase extraction-HPLC

A CoFe2O4/MEG solid-phase extraction combined with high performance liquid chromatography was used for determination of 8 biogenic amines (Bas) in canned Spanish mackerel products. A new comprehensive evaluation system, including dietary exposure, food safety index, chemical quality index and biogenic amine index, was used for investigating the pollution distribution, exposure and health assessment of BAs in four sea areas/provinces of China. The pollution levels in the Yellow Sea-Jiangsu, Bohai Sea-Shandong, Yellow and Bohai Sea-Liaoning regions were equivalent, with ∑8BAs equalling 34.7–36.5 mg/kg, while in the South China Sea-Guangdong region ∑8BAs was lowest at 18.9 mg/kg. The concentration range of ∑8BAs and ∑4BAs were ND (not detected)-113 mg/kg and ND-80.8 mg/kg, respectively. All results showed that the main components of BAs were putrescine, histamine, and spermine, with detection rates ranging from 23.1% to 42.3%. The dietary exposure level range of 8 BAs was 85.8–266 μg∙kg−1∙d−1, IFSc was 0.00800–0.0248, CQI values range in the four regions was 1.21–3.93, with a mean CQI of 1.98. The total value of BAI ranges ND-0.840 mg/kg, with a mean BAI of 20.3 mg/kg. Statistical analysis showed that the overall health risk of BAs exhibits different trends in terms of gender, age, and region.

National innovation system: Measurement of overall effectiveness and analysis of influencing factors

China has made remarkable achievements in the construction of the National Innovation System (NIS), but the theoretical and empirical studies on the NIS's overall effectiveness have lagged behind the policy and management practice. From the perspective of system theory, this study defines the concept of NIS's overall effectiveness, and constructs a comprehensive evaluation system of NIS's overall effectiveness based on the panel data of China (mainland) from 2012 to 2020, using a combination assignment method and coupled coordination model for measurement and analysis. We also conducted a configuration analysis of the factors influencing the NIS's overall effectiveness using a fuzzy set qualitative comparative analysis approach (fsQCA). The results show that: First, from a temporal perspective, China's NIS's overall effectiveness has grown by leaps and bounds, with a 326.77% increase in 2020 compared to 2012. Second, from a spatial perspective, the top five regions in terms of the NIS's overall effectiveness from 2012 to 2020 are Guangdong Province, Jiangsu Province, Beijing, Shanghai, and Zhejiang Province, while the bottom five regions are Yunnan Province, Ningxia Province, Guizhou Province, Gansu Province, and Qinghai Province. The spatial distribution pattern of the NIS's overall effectiveness is "East > Central > West". Third, the factors driving the NIS's overall effectiveness are in three Configurations. The first type is a two-wheel drive of government innovation support and infrastructure construction, a typical case is Jiangsu Province. The second type is the two-wheeled government innovation support and digital economy, a typical case is Zhejiang Province. The third type is the three-legged government-infrastructure-digital economy support type, a typical case is Guangdong Province.

A GCN-based adaptive generative adversarial network model for short-term wind speed scenario prediction

Wind prediction is of great significance for wind energy utilization due to the stochastic nature of wind. To effectively facilitate various downstream decision-making tasks such as wind turbine control, predictive wind Scenario Generation (SG), which is capable of providing a set of deterministic instantiated wind prediction results, plays a critical role. In this paper, a novel Graph neural networks-based Adaptive Predictive Generative Adversarial Network (GAPGAN) model is proposed for accurate prediction of short-term future scenarios of a wind field. In GAPGAN, the original multivariate time series data are first reconstructed into the form of a graph, and spatiotemporal features are then extracted using Graph Convolutional Networks (GCNs). Next, a predictive generative adversarial network (PGAN) framework is proposed, which could generate different outputs corresponding to given historical observations as conditions. Finally, an adaptive PGAN training mechanism is introduced to stabilize the training process, and the best SG model is selected based on the proposed comprehensive evaluation system. Based on wind speed data collected from 11 wind turbines, computational experiments validate that the GAPGAN outperforms five benchmarking models in terms of point prediction accuracy, shape similarity, uncertainty prediction quality, and prediction scenario diversity.

Improving Madrasah Competitiveness Through Excellent Islamic Education Development Strategies

This study analyzes the development strategy of superior Islamic education at Madrasah Aliyah Unggulan Amanatul Ummah (MAU Amanatul Ummah) Mojokerto. This article uses case study research to reveal the comprehensive and integrative efforts made by MAU Amanatul Ummah to realize the vision of superior, intact, and noble Islamic education. The results showed that the development strategy implemented by MAU Amanatul Ummah includes institutional strengthening, improving the quality of human resources, developing a holistic curriculum, varying learning programs, implementing a comprehensive evaluation system, and strengthening networks and partnerships. The success of MAU Amanatul Ummah is inseparable from the visionary and transformative leadership of the Kiai, as well as the commitment of the entire academic community to continue to innovate and pursue excellence. Although still facing some challenges, the experience of MAU Amanatul Ummah can be an inspiration and reference for the development of Islamic education in Indonesia, especially in the context of pesantren-based education. This research contributes to the development of Islamic education discourse and practice in Indonesia and opens space for further study.

Supplier Evaluation in Supply Chain Environment Based on Radial Basis Function Neural Network

The comprehensive evaluation and selection of suppliers under the environment of supply chain management has become a key factor affecting the success of supply chain. How to select suppliers and the strategic partnership between suppliers under the environment of supply chain management has become an important challenge. To solve this problem, this paper takes the supplier evaluation and selection of Guangzhou Automobile Toyota Company as the research object, constructs the index system of supplier comprehensive evaluation and selection, uses the RBF neural network algorithm to establish the supplier evaluation and selection model, and makes an experimental study. The results show that radial basis function neural network is a local approximation network, which has a unique and definite solution to the problem, and there is no local minimum problem in BP network. It is a method that enables enterprises and suppliers to have a clear understanding and seek further promotion together. The research provides theoretical data support for enterprise managers to make decisions.

Research on the impact of Digital Economy Development on The Integration of The Two Industries

Based on data from 2010 to 2021 in 30 provinces of China, comprehensive evaluation systems for digital economy development, manufacturing, and service industry integration were constructed. Using a two-way fixed effects model with individual and time dimensions, empirical analysis conducted the impact of digital economy development on the integration of the two industries in each province. Additionally, a panel threshold model was employed to analyze the nonlinear relationship between digital economy development and the integration of the industries. The research findings indicate a significant promoting effect of digital economy development on the integration of the two industries. Robustness tests confirm the stability of the empirical results. In terms of heterogeneity, digital economy development in various regions significantly promotes the integration of the two industries, with the promotion effect in the central and western regions surpassing that in the eastern regions, and the optimal effect in regions with a moderate level of industrialization. Nonlinear reveals the evident nonlinear characteristics of the impact of digital economy on the integration of the two industries, with different effects at different stages of digital economy development. Based on these findings, policy recommendations are proposed, emphasizing the vigorous promotion of digital economy support for the integration of the two industries and the cultivation of digital talent.