Development Of Comprehensive Framework Research Articles

Research Proposal Development in ELT: Tools for Planning, Structuring and Writings

The primary objective of this study is to explore the tools and processes involved in developing a research proposal for English Language Teaching (ELT), focusing on effective planning, structuring, and writing practices. A theoretical framework underpinned by constructivist learning theory and sociocultural theory guides the design of the study. The research employs a qualitative approach, synthesizing existing literature and expert guidelines to develop a comprehensive framework for research proposal development. Key stages such as selecting a topic, conducting a literature review, formulating research questions, and outlining methodological strategies are critically analyzed. The study suggests that clear research objectives, grounded in theoretical principles, significantly enhance the coherence and impact of research proposals. Furthermore, the alignment of personal interests with current trends in ELT increases the likelihood of sustained researcher engagement. In addition, the paper presents that a systematic approach to proposal development, incorporating clear objectives and methodological rigor, improves the overall quality and relevance of ELT research. The paper suggest that the incorporation of mentorship and peer feedback in the proposal development process and the necessity for researchers to remain flexible in their methodological choices, adapting them to the research context. This study contributes to the field by providing a structured guideline that can be utilized by novice researchers in ELT.

Harnessing Oxygenic Photosynthetic Microorganisms for Sustainable Wastewater Treatment Systems: A Comprehensive Review

Aquaculture systems globally face significant environmental challenges, particularly concerning wastewater management. This review explores the innovative application of oxygenic photosynthetic microorganisms (OPhMs), specifically microalgae and cyanobacteria, as a sustainable solution for wastewater treatment within these systems. OPhMs offer a dual role in wastewater treatment by removing harmful pollutants such as nitrogen, phosphorus, and heavy metals, while simultaneously improving water quality through oxygenation. We evaluate the integration of OPhMs into existing aquaculture operations, considering key factors such as system design, operational conditions, and economic viability. Additionally, we discuss the potential of algal biomass as a secondary resource for producing biofuels, animal feed, and other bio-products, contributing to the circular economy model. Our findings highlight the ability of OPhM systems to significantly reduce the ecological footprint of aquaculture while recovering valuable resources. However, challenges such as process stability, especially under low-temperature conditions, and the efficiency of biomass harvesting, require further research. This study provides a comprehensive framework for future development and optimization of OPhM-based wastewater treatment systems to improve the sustainability of aquaculture operations.

Argentina's rejection of 2030 agenda undermines environmental sustainability and human well-being

In a recent speech to the UN General Assembly, Argentine President Javier Milei rejected the Pact for the Future and the 2030 Agenda, a comprehensive global framework for sustainable development encompassing ‘people, planet, and prosperity.’ This position undermines Argentina’s capacity to tackle urgent socio-environmental challenges like poverty, deforestation, biodiversity loss, and wildfires. By walking away from this international initiative, Argentina risks isolation and exacerbating these interconnected crises.

Optimization of Impact Ionization in Metal–Oxide–Semiconductor Field-Effect Transistors for Improvement of Breakdown Voltage and Specific On-Resistance

For the past few decades, metal–oxide–semiconductor field-effect transistors (MOSFETs) have been the most important application in IC circuits. In certain circuit applications, the breakdown voltage and specific on-resistance serve as key electrical parameters. This article introduces a readily accessible approach to enhance the source–drain breakdown voltage (BVDS) of MOSFETs based on the Bipolar-CMOS-DMOS (BCD) platform without extra costs. By attentively refining the process steps and intricacies of the doping procedures, the breakdown voltages of NMOS and PMOS experienced increments of 3.4 V and 4.6 V, translating to enhancements of 31.5% and 50.3%. Parallel simulations offer insightful mechanistic explanations through simulation tools, facilitating superior outcomes. This initiative lays significant groundwork for the advancement of a comprehensive BCD process development framework.

MediGate: a MedTech product innovation development process from university research to successful commercialization within emerging markets

This study proposes a comprehensive MedTech product innovation development framework tailored for university research commercialization within emerging markets. The MediGate framework, built on the Augmented Stage-Gate model, addresses the unique challenges of MedTech innovation, including regulatory compliance, stakeholder engagement, and market dynamics. The framework integrates critical decision-making criteria for different types of inventions to drive academic research toward commercialization in clinical settings. Through detailed case studies, including innovations like albumin strip test, 3D-printed patient-specific implant, COVID-19 nasal spray, and AI platform for depression detection, and iterative refinement, the framework provides actionable guidelines for navigating the complexities of product development. These guidelines ensure alignment with clinical needs, regulatory requirements, and market strategies. The research highlights the importance of early-stage valuation, reimbursement strategies, legal and IP considerations, and manufacturing and quality management. By offering a structured pathway, this research contributes to the theoretical and practical understanding of MedTech commercialization, aiming to enhance innovation success and healthcare impact in emerging markets.

Authentic caring in online professional development for early childhood teachers in South Africa

Background: The professional development (PD) of early childhood teachers is of strategic importance in higher education and the profession given the need to improve responsiveness and progress towards millennium goals.Aim: The purpose was to analyse classroom practices and teachers’ experiences of PD programmes, through the theoretical lens of the UNESCO ICT Competency Framework for Teachers to construct an authentic data-based model, which can be used to understand PD challenges and guide decisions about the improvement of education quality.Setting: The study was conducted in Gauteng with teachers from a selection of early childhood centres.Methods: A phenomenological inquiry explored the settings and practices of 23 selected teachers in Gauteng province. Interview and observation data were analysed for content categories and grounded theory articulations.Results: The main finding is that teachers facing everyday educational challenges benefit from school-based support and available media but need additional learning to advance their professional aspirations. The grounded theory analyses of the data highlighted that early childhood practices and articulated development needs are best explained as authentic caring. This was conceptualised metaphorically as garden spaces where careful tending, deliberate planning and various elements of nurturing knowledge may harmoniously be blended. The model extends prevailing theories of PD and the flipped ICT Competency Framework for Teachers.Conclusion: The model of authentic caring is a grounded theory articulation based upon beliefs of practising EC teachers.Contribution: The article provides a comprehensive online teacher professional development framework for EC teachers, emphasising authenticity, care and alignment with global educational standards.

Ethical AI in Information Technology: Navigating Bias, Privacy, Transparency, and Accountability

The rapid advancement of artificial intelligence (AI) technologies has fundamentally transformed the landscape of information technology (IT), offering unprecedented opportunities for innovation and efficiency. However, these advancements also bring significant ethical challenges, including issues of bias, privacy, transparency, and accountability. This paper explores these ethical challenges and proposes a comprehensive ethical framework for the responsible development and deployment of AI in IT. Through an examination of historical context, current trends, and detailed case studies, the framework aims to provide actionable guidelines to mitigate biases, protect privacy, enhance transparency, and ensure accountability in AI systems. By fostering ethical AI practices, this framework aspires to support the sustainable and equitable advancement of AI technologies, ultimately benefiting society as a whole

Investigation into the Influence of Digital Financial Inclusion on Rural Renewal

This research examines the pathways through which digital inclusive finance impacts rural renewal, utilizing panel data collected from various Chinese provinces and cities between 2015 and 2020. The study utilizes panel individual fixed effects and mediation effect models for analysis. Findings reveal that digital inclusive finance markedly advances rural revitalization by mitigating the credit constraints faced by the "three rural" sectors (rural areas, farmers, and agriculture), thereby creating a comprehensive framework for rural development. Furthermore, digital inclusive finance fosters agricultural modernization, enhances the construction of picturesque rural areas, and contributes to common prosperity. Although regional disparities exist, with the western and eastern regions experiencing a more substantial impact compared to the central region, no significant differences were observed between the northern and southern regions.

Process of Acquisition to Destination – A Bang on Economic Prudence with Reference to Indian Logistics Industry

The study explores the significance of the logistics industry in the Indian economy and examines its sector-wise impact on economic well-being. It emphasizes how the presence or absence of transport infrastructure significantly influences economic growth and global competitiveness. With globalization expanding its scope, the study addresses the challenges of global logistics, such as trade laws, cultural differences, and the necessity for efficient cross-border transportation networks. Moreover, the research delves into factors driving the growth of the Indian logistics industry. Innovations and developments are seen as pivotal to economic progress, with intelligent logistics and smart transportation playing crucial roles. The Logistics Performance Index (LPI), a benchmarking tool by the World Bank, ranks countries based on logistics performance. In the 2023 report, India achieved an LPI rating of 3.4, securing the 38th position among 139 countries. The study substantiates the factors fueling the logistics industry with statistical evidence, highlighting technological advancements and the integration of IoT-enabled facilities as key drivers. Furthermore, the study discusses strategic initiatives aimed at enhancing India's logistics infrastructure. The PM Gati Shakti initiative seeks to streamline infrastructure development by promoting integrated planning and coordinated implementation across government departments. Concurrently, the National Logistics Policy (NLP) provides a comprehensive framework for the industry's development. Additionally, the Unified Logistics Interface Platform (ULIP) facilitates real-time information exchange among stakeholders, thereby simplifying logistics planning.

Return Migration and Human Resources Development in Rural Areas: European Experience and Chinese Practice

Objective: The purpose of this study is to explore and propose strategies to promote the return of rural population and effective human resource development in China, and to learn from the successful experience of European countries, especially their education and training systems, social security mechanisms, characteristic industries and infrastructure construction, in order to facilitate the implementation of the rural revitalization strategy. Theoretical framework: Based on literature review, SWOT analysis, and international comparative research methods, this study builds a theoretical framework to identify the key elements of rural population return and human resource development, including vocational education and training, social security system, the cultivation of characteristic industries, the construction of infrastructure, etc., and reveals the similarities and differences between China and Europe in these fields through comparative analysis. Design/Methods/Approach: Adopt a combination of qualitative and quantitative research methods, firstly, through an extensive literature review to build a theoretical foundation; Second, data from official and international agencies are used for quantitative analysis, including processing and visualizing data on rural residents' incomes, investment in education, and population structure. Subsequently, SWOT analysis was used to assess the current state of human resource development in China's rural areas. Finally, the data obtained are exhaustively analysed, combined with European cases and specific strategic suggestions are proposed. Significance: The results of this study will provide a comprehensive strategic framework for human resource development in China's rural areas, emphasizing the implementation of multidimensional strategies such as optimizing investment in education, vocational training, and improving the social security system, which is of great practical importance to promote the healthy return of rural people and promote the sustainable development of the economy and economy. rural society. The proposed strategies can not only guide policy-making, but also provide a scientific basis for the development path of rural areas.

Fabricating of Pd and Ni bimetal modified halloysite nanotube composite and its application for photocatalytic degradation of tetracycline

Tetracycline (TC) is extensively employed as a broad-spectrum antibacterial agent, and its byproducts have been identified in a variety of water bodies, posing a significant risk to both aquatic ecosystems and human health. Among the prevalent techniques for treating water contaminants, photodegradation stands out. In this research, we synthesized a novel nanocomposite material, embedding bimetallic nanoparticles onto halloysite nanotubes (HNT) (Pd@Ni/N-HNT), aimed at photocatalytically degrading TC. The Pd@Ni/N-HNT demonstrated the capability to enhance the TC degradation efficiency to 100 % under visible light for a duration of 120 min, effectively doubling the performance of pure H2O2 degradation. The influence of pH levels in aquatic environments on the TC degradation efficiency was explored. Through electron spin resonance (EPR) studies and free radical scavenging tests, it was verified that •O2− and h+ are pivotal in the degradation process. Furthermore, Pd@Ni/N-HNT showcased effective degradation capabilities in both tap and river water, achieving degradation rates exceeding 70 % in 120 min and 95 % in 180 min, respectively. This investigation not only sheds light on the potential of utilizing Pd@Ni/N-HNT as a potent catalyst for the photocatalytic degradation of TC but also offers a comprehensive framework for the future development of nanomaterials aimed at the environmental remediation of organic pollutants. The findings herein provide a pivotal reference and guide for advancing the application of nanotechnology in the purification of water, thereby contributing to the safeguarding of aquatic ecosystems and public health.

A comprehensive AI model development framework for consistent Gleason grading

BackgroundArtificial Intelligence(AI)-based solutions for Gleason grading hold promise for pathologists, while image quality inconsistency, continuous data integration needs, and limited generalizability hinder their adoption and scalability.MethodsWe present a comprehensive digital pathology workflow for AI-assisted Gleason grading. It incorporates A!MagQC (image quality control), A!HistoClouds (cloud-based annotation), Pathologist-AI Interaction (PAI) for continuous model improvement, Trained on Akoya-scanned images only, the model utilizes color augmentation and image appearance migration to address scanner variations. We evaluate it on Whole Slide Images (WSI) from another five scanners and conduct validations with pathologists to assess AI efficacy and PAI.ResultsOur model achieves an average F1 score of 0.80 on annotations and 0.71 Quadratic Weighted Kappa on WSIs for Akoya-scanned images. Applying our generalization solution increases the average F1 score for Gleason pattern detection from 0.73 to 0.88 on images from other scanners. The model accelerates Gleason scoring time by 43% while maintaining accuracy. Additionally, PAI improve annotation efficiency by 2.5 times and led to further improvements in model performance.ConclusionsThis pipeline represents a notable advancement in AI-assisted Gleason grading for improved consistency, accuracy, and efficiency. Unlike previous methods limited by scanner specificity, our model achieves outstanding performance across diverse scanners. This improvement paves the way for its seamless integration into clinical workflows.

The Effectiveness of EduMind for Mental Health Promotion Among Youths.

Introduction The global surge in mental health issues, particularly among the youth, is evident. Despite the proliferation of digital mental health services, their adoption remains limited, hindered by various barriers. To address this issue, an evidence-based, validated digital mental health intervention is necessary. Although much research has explored the effectiveness of such interventions, there was limited evidence supporting those within the youth population. The objective of this research is to assess the effects of aninterventional module on depression, anxiety, and stress symptoms among youths. Methods The EduMind online mental health intervention contents were developed from a needs assessment and a scoping review of effective psychotherapies, achieving a high content validation index (CVI) of 0.96. The contents were integrated into a web application to assess its effectiveness among the target population which consisted of university students of a local institution. A quasi-experimental study compared the intervention group (n=264) to a waitlist-control group (n=200), evaluating changes in mental health status with the Depression, Anxiety and Stress Scale 21 (DASS-21) questionnaire using analysis of covariance (ANCOVA) to analyse mean differences. Results Participants in the intervention group indicated a significant decrease (p< 0.001) in depression, anxiety, and stress. The pre-test and post-test mean scores in the intervention group were 15.81 and 8.97 for depression, 11.46 and 7.02 for anxiety and 14.64 and 6.33 for stress, respectively. In the control group, there was no significant difference between the pre-test and post-test mean scores for depression. However, there was a slight significant reduction for anxiety with pre- and post-test scores of13.31 and 12.95. Stress mean scores exhibited a slight increase, rising from 13.55 to 14.24. The final phase revealed significant improvements in mental health status between groups, with significant effect sizes for stress (ƞp2= 0.57, p < 0.001), depression (ƞp2= 0.71, p < 0.001), and anxiety (ƞp2= 0.27, p < 0.001). Conclusion The findings contribute to the advancement of technology-assisted health services, facilitating greater uptake among the population.This study utilized a comprehensive module development framework and demonstrated the effectiveness of the expert-guided mental health intervention module.Furthermore, the study suggests potential integration with the National Strategic Plan for Mental Health 2020-2025 and the National Mental Health Policy, proposing the web application as a potential compulsory student screening tool administered by universities. The information gathered by this application could inform future research directions, propelling technological-assisted mental health services to new heights.

Business Character Implementation Strategy for The Community of Teluk Patipi District

This research focuses on evaluating the preparedness of the inhabitants of Patipi Pasir village and its vicinities within East Fakfak district to cultivate their entrepreneurial spirit. The pivotal aim is to harness their potential in managing local natural resources effectively, thereby contributing significantly to the economic acceleration of the Fakfak district. Employing a descriptive research methodology, the study utilizes a semi-qualitative analysis method, with the gap analysis technique depicted through a fishbone diagram to pinpoint areas requiring improvement. Moreover, the strategic implementation for nurturing business character among the local populace is devised through the innovative use of the Ishikawa diagram, integrated with the Balanced Score Cards approach, providing a comprehensive framework for development. The findings reveal that the Patipi Bay District boasts considerable human resource potential that, if adequately nurtured, can lead to the effective management of its natural resources into sustainable businesses. The study underscores the necessity of developing a robust entrepreneurial ecosystem that supports the local community's transition towards sustainable economic practices. This entails providing adequate training, resources, and support systems to empower the community, ensuring they are well-equipped to capitalize on the intrinsic value of their natural resources. Through strategic planning and targeted development programs, the research envisions transforming the Patipi Bay District into a model for sustainable business development, leveraging its natural assets for long-term economic prosperity

Intelligent Construction of University Music Education Teaching System Based on Artificial Intelligence Technology

The university music education teaching system plays a vital role in nurturing aspiring musicians and music enthusiasts by providing a comprehensive framework for musical learning and development. This system typically encompasses a diverse range of courses, workshops, and performance opportunities designed to cultivate students' musical talents, theoretical knowledge, and practical skills. Through a combination of classroom instruction, ensemble rehearsals, private lessons, and hands-on experiences, students receive a well-rounded musical education that covers various genres, styles, and traditions. Moreover, university music education teaching systems often incorporate state-of-the-art facilities, including rehearsal rooms, recording studios, and performance venues, to support students' artistic growth and creative expression. This paper presents an innovative approach to the intelligent construction of university music education teaching systems, leveraging artificial intelligence (AI) technology with Intelligent Fuzzy Regression Classification (IFRC). Recognizing the complexity and diversity of music education, this research aims to optimize teaching methodologies and enhance learning outcomes through AI-driven strategies. The proposed approach integrates AI technology, particularly IFRC, into the design and implementation of university music education teaching systems. IFRC combines fuzzy logic with regression analysis and classification techniques to model and predict complex relationships within music education datasets, enabling the system to adapt and respond dynamically to student needs and preferences. The IFRC-enhanced teaching system can generate personalized learning pathways, recommend tailored resources, and provide real-time feedback to students and instructors alike. This intelligent adaptation to individual learning styles and progress fosters a more engaging, effective, and inclusive music education environment. The IFRC-enhanced teaching system achieves an average improvement of 25% in student performance compared to traditional teaching methods. Moreover, specific musical skills, such as sight-reading, ear training, and music theory comprehension, exhibit notable enhancements, with average score increases of 30%, 20%, and 35%, respectively.

Sustainable Development Concept of Heritage Kampung Tourism Using Novel Prioritization Approach

Rapid urban development in Southeast Asia is often the main cause of urban kampung formation, a cluster of sporadic and informal settlements. Kampungs possess the capacity to serve to build the local economy and provide culture conservation through heritage tourism. To promote sustainable development in heritage kampung tourism, it is imperative to propose directives that optimize its heritage qualities without compromising both the economic and environmental aspects of sustainability. This study aims to develop a comprehensive sustainable development framework on a local scale by implementing a novel prioritization approach. Descriptive statistical analysis, Analytical Hierarchy Process (AHP), and Fuzzy AHP (FAHP) provide the researchers with a holistic understanding regarding heritage tourism sustainability by considering various stakeholders’ perspectives. Novel prioritization is presented using radar diagrams to understand how each variable, representing environmental, social, and economic criteria, has perceived importance according to experts and tourists. The analysis highlights the kampung Kayutangan’s sustainability while acknowledging variations in element importance, necessitating the alignment of development directives.

Formula omitted]piler: Compilers in search of compilations

Compilers pose significant challenges in their development as software products. Language developers face the complexities of ensuring efficiency, adhering to good design practices, and maintaining the overall codebase. These factors make it difficult to predict the unexpected impact of updates on existing software built on the current compiler stack. Furthermore, software created for a specific compiler often lacks reusability for other compiler environments. In this study, we propose a comprehensive framework for the uniform development of compilers that addresses these issues. Our approach involves developing compilers as a collection of small transpilation units, referred to as deltas. The transpilation infrastructure takes source code written in a particular source language and searches for a path of deltas to generate equivalent source code in the target language. By adopting this methodology, language developers can easily update their languages by introducing new deltas into the system. Existing code remains unaffected as old transpilation paths remain available. To support this framework, we have devised a metric space for efficient delta search. This metric space enables us to define a non-overestimating heuristic function, which proves valuable in solving the search problem. Leveraging the A* search algorithm, we can efficiently transpile programs from a source language to the target language. To evaluate the effectiveness of our approach, we conducted a benchmark comparison between the A* search algorithm and the simpler breadth-first search (BFS) algorithm. The benchmark consisted of over 100 transpilation searches, providing valuable insights into the performance and capabilities of this framework.

Integrated Riverside Development Along Adyar River, Chennai

Integrated Riverside Development (IRD) is a planning approach that aims to achieve sustainable development of urban areas located along riverbanks. To implement this IRD with controlled regulations, the study is focused on developing a comprehensive riverside development and river zoning regulatory framework that integrates all five main elements, with particular emphasis on economic, ecological, and social factors, in order to reduce encroachment and pollution in the study area. The objectives of the study include analyzing the current land use, recreational parks, encroachments, pollution levels, sewage disposal patterns, and solid waste dumping zones in the study area, as well as studying the socio-economic and eco-environmental aspects of the area. Additionally, identifying and analyzing the major threats to the river and developing a river zoning regulatory framework using the land use matrix technique is also included in the study objectives. The study area (Adyar River) was chosen based on social, ecological, and economic factors, and data was collected through surveys and from government offices. Using the land use matrix method, proposals for riverside development were made, and the zones were classified into development-prohibited, development-restricted, and development-optimized zones. The zones were classified based on the calculated values of Eco sensitivity for each of the three zones. Proposals were then given based on these classified zones, and the levels of development potential were determined. The proposed zoning regulatory framework is expected to have a significant impact in reducing further encroachments and improving connectivity between the city and the river. By considering socio-economic, ecological, and environmental aspects, the study recommends appropriate zoning regulations for riverfront developments that promote sustainable growth.

Impact of the digital economy on low carbon sustainability evidence from the Yellow River Basin

As the digital economy increasingly dominates a substantial portion of the national economy, comprehending its role in promoting sustainable development has become an imperative research question—particularly in the context of the Yellow River Basin, where there exists an urgent need to shift toward more sustainable modes of economic growth. Utilizing panel data spanning from 1999 to 2020 for 114 cities in the Yellow River Basin, this study develops a comprehensive evaluation framework for sustainable development, incorporating economic, social, and ecological dimensions. The empirical findings reveal that the digital economy acts as a catalyst for sustainable development. Importantly, these results withstand both endogeneity tests and robustness checks. Further heterogeneity analysis indicates that the positive impact of the digital economy on sustainable development is more pronounced in regions directly traversed by the Yellow River and in areas with higher sustainability levels. Moreover, the enactment and implementation of the 13th Five-Year National Information Plan have emphasized the role of the digital economy in enhancing sustainable development. Mechanism tests also illustrate those elevated levels of personal digital acceptance and government intervention contribution to amplify the digital economy’s positive impact on sustainable development. In conclusion, policy recommendations are put forward, including optimizing industrial structure, strengthening data governance and environmental monitoring, promoting innovation-driven development, and fostering collaborative growth.

A study of the coupling between the digital economy and regional economic resilience: Evidence from China.

The contemporary economic landscape has placed significant emphasis on the digital economy and economic resilience, progressively emerging as pivotal focal points for examining the high-quality development of economic systems. However, there remains to be more research on several critical topics. This includes the characteristics of coordinated development between the digital economy and economic resilience systems and their interdependence. In response, this study formulates a comprehensive evaluative framework for digital economy development and regional economic resilience, grounded in the intrinsic mechanisms of both domains. It conducts a thorough evaluation employing entropy weight-TOPSIS methodology. Additionally, leveraging coupling theory, a coordination model's coupling degree serves as the foundational framework for scrutinizing the symbiotic advancement of the digital economy and economic resilience, along with their interdependent nature. The research sample comprises data from 31 provinces and municipalities in China (excluding Hong Kong, Macao, and Taiwan) from 2011 to 2020. Spatial autocorrelation and Geodetector methodologies probe the evolutionary traits and driving factors underlying the coordinated developmental relationship between these two systems. The findings indicate an upward trajectory in China's annual comprehensive development index for digital economy development (from 0.233 to 0.458) and regional economic resilience (from 0.393 to 0.497). The coupling and coordination between the two systems, measured from 0.504 in 2011 to 0.658 in 2020, demonstrate a consistent growth pattern with an average annual increase of 3.01%. These levels exhibit continuous improvement, with comprehensive economic zones manifesting hierarchical results within the coupling range of [0.5, 0.8]. Notably, agglomeration development evinces a pronounced spatial positive correlation, while local Moran scattering points are primarily concentrated in localized migration leaps. Factors such as foreign-funded enterprises' total import and export volume, online payment capability, and fiber-optic cable length greatly influence the coupling relationship. In contrast, other variables exhibit a lower and more fluctuating degree of weighted impact. This study establishes a foundation for the synergistic and effective development of the digital economy and economic resilience within the Chinese region. Simultaneously, it offers valuable insights for research of related subjects in global contexts.