Key Factors Research Articles

Magnetic Nanoparticles with Aspects of their Use in Cancer Therapy

Abstract: Cancers remain the leading cause of death worldwide, despite significant advances in their diagnosis and treatment. The inadequacy and ineffectiveness of standard treatments (chemotherapy, radiotherapy, and surgery), their severe side effects, and the resistance of tumor cells to chemotherapeutics have forced researchers to investigate alternative therapeutic strategies. Magnetic nanoparticles (MNPs) have been evaluated as one of the promising strategies in treating cancers, a major public health problem. Due to their intrinsic magnetic properties, MNPs are tools that can be designed to be multifunctional in medicine, including cancer therapy. Multifunctionality can be achieved with various drug/agent loadings, such as chemotherapeutic drugs, radionuclides, nucleic acids, and antibodies. This provides a multimodal theranostics platform for cancer diagnosis, monitoring, and therapy. These substances can then be delivered to the tumor tissue using an external magnetic field (EMF). Magnetic or photothermal applications kill cancer cells at the tumor site by inducing local hyperthermia, whereas photodynamic therapy kills them by producing reactive oxygen species. MNP applications also prevent drug resistance. In addition, alone or with different combination options, MNP applications provide synergistic effects and reduce side effects. Functionalized MNPs can be used to remove unwanted cells from blood, including circulating tumor cells (CTCs), which are key factors in the metastatic process and leukemia cells. Despite numerous successful studies, there are some unpredictable obstacles to be discovered in routine usage. This review focuses mainly on the application of MNPs in cancer treatment, covering future perspectives and challenges.

Obstacles and Threats for Developing Entrepreneurship Ecosystem in a Developing Country: Iran

Abstract: The development of entrepreneurship which is a requirement for the commercialization of academic findings in each society depends on many influencing factors. In this paper, these influencing variables on the entrepreneurial ecosystem in IRAN (in general and with a special focus on food technology) have been discussed. Furthermore, the ecosystem, and situations of the food industry in Iran as well as the barriers to the development of entrepreneurship have been described. After a review of the key success of succeeding countries, then, obstacles and approaches in Iran have been described. Also, the method and manner of ecosystem development, as well as effective components in the entrepreneurship ecosystem are introduced. Finally, the key success factors of the entrepreneurial ecosystem and evaluation criteria are described. Both academic and food industries may benefit from this study, especially start-ups, which want to start a business in this ecosystem and similar ones. Based on previous experiences a questionnaire has been recommended for the development of a new network, e.g. food technology network.

Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning

As the societal impact of Deep Neural Networks (DNNs) grows, the goals for advancing DNNs become more complex and diverse, ranging from improving a conventional model accuracy metric to infusing advanced human virtues such as fairness, accountability, transparency, and unbiasedness. Recently, techniques in Explainable Artificial Intelligence (XAI) have been attracting considerable attention and have tremendously helped Machine Learning (ML) engineers in understand AI models. However, at the same time, we started to witness the emerging need beyond XAI among AI communities; based on the insights learned from XAI, how can we better empower ML engineers in steering their DNNs so that the model’s reasonableness and performance can be improved as intended? This article provides a timely and extensive literature overview of the field Explanation-Guided Learning (EGL), a domain of techniques that steer the DNNs’ reasoning process by adding regularization, supervision, or intervention on model explanations. In doing so, we first provide a formal definition of EGL and its general learning paradigm. Second, an overview of the key factors for EGL evaluation, as well as summarization and categorization of existing evaluation procedures and metrics for EGL are provided. Finally, the current and potential future application areas and directions of EGL are discussed, and an extensive experimental study is presented aiming at providing comprehensive comparative studies among existing EGL models in various popular application domains, such as Computer Vision and Natural Language Processing domains. Additional resources related to event prediction are included in the article website: https://kugaoyang.github.io/EGL/

Single-cell chromatin accessibility analysis reveals the epigenetic basis and signature transcription factors for the molecular subtypes of colorectal cancers.

Colorectal cancer (CRC) is a highly heterogeneous disease, with well-characterized subtypes based on genome, DNA methylome, and transcriptome signatures. To chart the epigenetic landscape of CRCs, we generated a high-quality single-cell chromatin accessibility atlas of epithelial cells for 29 patients. Abnormal chromatin states acquired in adenomas were largely retained in CRCs, which were tightly accompanied by opposite changes of DNA methylation. Unsupervised analysis on malignant cells revealed two epigenetic subtypes, exactly matching iCMS classification, and key iCMS-specific transcription factors were identified, including HNF4A, PPARA for iCMS2 tumors, and FOXA3, MAFK for iCMS3 tumors. Notably, subtype-specific TFs bind to distinct target gene sets and contribute to both inter-patient similarities and diversities for both chromatin accessibilities and RNA expressions. Moreover, we identified CpG-island methylator phenotypes and pinpointed chromatin state signatures and TF regulators for CIMP-High subtype. Our work systematically revealed the epigenetic basis of the well-known iCMS and CIMP classifications of CRCs.

Microscale Structure Additive Manufacturing Control Method Using Localized Electrochemical Deposition

Micro‐nano scale 3D printing is attracting attention as an alternative manufacturing method for a variety of applications in electronic information, biomedical, and sensing devices. Localized electrochemical deposition (LECD) based on nanopipettes is naturally superior and economical for the manufacturing of high‐freedom, impurity‐free metal conductors. However, flexible printing sacrifices roughness and straightness. Therefore, the present study initially establishes a simulation model for LECD and subsequently analyzes the key factors that influence the quality and stability of the deposited structure. Furthermore, an effective solution is proposed to enhance the surface quality. Second, a constant deposition current control method based on fuzzy proportional–intergral–derivaite (PID) is proposed to effectively suppress the fluctuation and improve the stability and quality of the deposited structure. Finally, compared with the open‐loop control method, the proposed constant current control method can reduce the radial fluctuation of the copper pillar structure by 87%, and effectively improve the surface quality of the structure. The proposed method provides a new idea to carry out LCED‐based 3D printing with high resolution at the micro‐nano scale.

Reactive Case Detection and Treatment and Reactive Drug Administration for Reducing Malaria Transmission: A Systematic Review and Meta-Analysis.

Many countries pursuing malaria elimination implement "reactive" strategies targeting household members and neighbors of index cases to reduce transmission. These strategies include reactive case detection and treatment (RACDT; testing and treating those positive) and reactive drug administration (RDA; providing antimalarials without testing). We conducted systematic reviews of RACDT and RDA to assess their effect on reducing malaria transmission and gathered evidence about key contextual factors important to their implementation. Two reviewers screened titles/abstracts and full-text records using defined criteria (Patient = those in malaria-endemic/receptive areas; Intervention = RACDT or RDA; Comparison = standard of care; Outcome = malaria incidence/prevalence) and abstracted data for meta-analyses. The Grading of Recommendations, Assessment, Development, and Evaluations approach was used to rate certainty of evidence (CoE) for each outcome. Of 1,460 records screened, reviewers identified five RACDT studies (three cluster-randomized controlled trials [cRCTs] and two nonrandomized studies [NRS]) and seven RDA studies (six cRCTs and one NRS); three cRCTs comparing RDA to RACDT were included in both reviews. Compared with RDA, RACDT was associated with nonsignificantly higher parasite prevalence (odds ratio [OR] = 1.85; 95% CI: 0.96-3.57; one study) and malaria incidence (rate ratio [RR] = 1.30; 95% CI: 0.94-1.79; three studies), both very low CoE. Compared with control or RACDT, RDA was associated with non-significantly lower parasite incidence (RR = 0.73; 95% CI: 0.36-1.47; 2 studies, moderate CoE), prevalence (OR = 0.78; 95% CI: 0.52-1.17; 4 studies, low CoE), and malaria incidence (RR = 0.93; 95% CI: 0.82-1.05; six studies, moderate CoE). Evidence for reactive strategies' impact on malaria transmission is limited, especially for RACDT, but suggests RDA might be more effective.

103 A Bifurcation Model Predicts Intravascular Catheter Herniation When Using Transradial Access in Neuroendovascular Procedures

INTRODUCTION: The speed and safety of acute ischemic stroke interventions can be improved with catheter-based revascularization performed via the transradial access versus the traditional transfemoral access. A critical source of delay and procedural failure is a phenomenon known as herniation where the catheter system suddenly buckles and deviates from the intended endovascular pathway as the surgeon attempts to track one device over or through another around a tight bend. METHODS: Recent modeling work suggests that herniation is associated with a bifurcation in strain energy. We hypothesized that herniation could be predicted by modeling the strain energy stored in a catheter based on its flexural rigidity and the vascular anatomy. To test our hypothesis, we developed a computational model using finite element analysis and an experimental benchtop model using 3D-printed patient-specific aortic arches. Our mathematical model was validated in vivo using observational data derived from patient and porcine endovascular surgeries. RESULTS: Vascular geometry and flexural rigidity were used to derive the bifurcation condition and predict catheter stability versus instability (herniation). Catheter instability criterion was predictive of herniation in our computational model (sensitivity 100.0%, PPV 93.5%, NPV 100.0%); experimental ex vivo model (sensitivity 92.3%, PPV 89.6%, NPV 90.0%); patient in vivo model (sensitivity 100.0%, PPV 80.0%, NPV 100.0%); and porcine in vivo model (sensitivity 100%, PPV 100%, NPV 100%). CONCLUSIONS: We validated a predictive model of catheter herniation based upon the hypothesis that bifurcation in strain energy drive the phenomenon. Key factors in the model are the curvature of the vascular pathway and the flexural rigidity of the coaxial devices. Results suggest that strategic selection of catheters and wires based on their known flexural rigidity can be used to prevent the bifurcation in strain energy that causes herniation.

Ambulatory Robotic Colectomy: Factors Affecting and Affected by Postoperative Opioid Use.

The ongoing opioid crisis demands an investigation into the factors driving postoperative opioid use. Ambulatory robotic colectomies are an emerging concept in colorectal surgery, but concerns persist surrounding adequate pain control for these patients who are discharged very early. We sought to identify key factors affecting recovery room opioid use (ROU) and additional outpatient opioid prescriptions (AOP) after ambulatory robotic colectomies. This was a single-institution retrospective review of ambulatory robotic colon resections performed between 2019 and 2022. Patients were included if they discharged on the same day (SDD) or postoperative day 1 (POD1). Outcomes of interest included ROU [measured in parenteral morphine milligram equivalents (MMEs)], AOP (written between PODs 2 to 7), postoperative emergency department presentations, and readmissions. Two hundred nineteen cases were examined, 48 of which underwent SDD. The mean ROU was 29.4 MME, and 8.7% of patients required AOP. Between SDD and POD1 patients, there were no differences in postoperative emergency department presentations, readmissions, recovery opioid use, or additional outpatient opioid scripts. Older age was associated with a lower ROU (-0.54 MME for each additional year). Older age, a higher body mass index, and right-sided colectomies were also more likely to use zero ROU. Readmissions were strongly associated with lower ROU. Among SDD patients, lower ROU was also associated with higher rates of AOP. Ambulatory robotic colectomies and SDD can be performed with low opioid use and readmission rates. Notably, we found an association between low ROU and more readmission, and, in some cases, higher AOP. This suggests that adequate pain control during the postoperative recovery phase is a crucial component of reducing these negative outcomes.

Effects of heterogeneous complex-task sequencings on extraneous collective cognitive load, intrinsic motivation, and learning transfer in computer-supported collaborative learning

Computer-supported collaborative learning is an instructional technique to solve complex tasks. One of the key factors to enhance collaboration is increasing the level of interdependence among the collaborators. This study was conducted to examine if the heterogeneous knowledge held by each member promoted by heterogenous instructional sequencings enhances the level of interdependence during collaboration. A quasi-experiment was conducted with college seniors preparing for their careers in a Shinhan University located in Gyeonggi-do, South Korea. The experiment consisted of two phases: one was, where students gained prior knowledge using homogeneous or heterogeneous complex-task sequencing. The other was, where they collaborated with each other using a computer-supported tool. The results showed the statistically significant difference between the two groups in terms of extraneous collective cognitive load, intrinsic motivation, and learning transfer. The collaborative groups of members, which utilized heterogeneous instructional sequencings during the individual learning phase showed relatively lower extraneous collective cognitive load, and higher intrinsic motivation in three consecutive collaborative sessions except for the first. As well as groups of members had higher learning transfer results. Implications and limitations were further discussed on results.

Skin-derived precursor conditioned medium alleviated photoaging via early activation of TGF-β/Smad signaling pathway by thrombospondin1: In vitro and in vivo studies

Photoaging is one major exogenous factor of skin aging. Efficacy and safety of current anti-photoaging therapies remained to be improved. Our previous studies indicated that skin-derived precursors (SKPs) alleviated photodamage by early activation of TGF-β/Smad signaling pathway via thrombospondin1 (TSP1). However, the research concerning SKP conditioned medium (SKP-CM) has never been reported. In the current study, we aimed to explore the anti-photoaging effects of SKP-CM both in vitro and in vivo, and to elucidate the possible mechanisms. Mouse SKP-CM (mSKP-CM) collection was optimized by a comparative method. The concentration of protein and growth factors in mSKP-CM was detected using BCA protein assay kit and growth factor protein chip. The anti-photoaging effects of mSKP-CM and its regulation of key factors in the TGF-β/Smad signaling pathway were explored using UVA + UVB photoaged mouse fibroblasts (mFBs) and nude mice dorsal skin. The research revealed that mSKP-CM contained significantly higher-concentration of protein and growth factors than mouse mesenchymal stem cell conditioned medium (mDMSC-CM). mSKP-CM alleviated mFBs photoaging by restoring cell viability and relieving senescence and death. ELISA, qRT-PCR, and western blot results implied the potential mechanisms were associated with the early activation of TGF-β/Smad signaling pathway by TSP1. In vivo experiments demonstrated that compared with the topical intradermal mDMSC-CM injection and retinoic acid cream application, the photodamaged mice dorsal skin intradermally injected with mSKP-CM showed significantly better improvement. Consistent with the in vitro results, both western blot and immunohistochemistry results confirmed that protein expression of TSP1, smad2/3, p-smad2/3, TGF-β1, and collagen I increased, and matrix metalloproteinases decreased. In summary, both in vitro and in vivo experiments demonstrated that mSKP-CM alleviated photoaging through an early activation of TGF-β/Smad signaling pathway via TSP1. SKP-CM may serve as a novel and promising cell-free therapeutical approach for anti-photoaging treatment and regenerative medicine.

Exploring user satisfaction and improvement opportunities in public charging pile resources

The existing market of public charging pile services for electric vehicle (EV) users has occupied a particular market share. However, instead of solely focusing on pre-planning the construction of charging piles, it is crucial to address the shortcomings of the existing charging pile service and develop effective marketing strategies. This approach can help optimize the utilization of charging pile resources and minimize wastage. In this study, we explore EV users’ comments on the public charging pile service and adopt a natural language pre-training model to classify comments for extracting positive and negative comments. For these two types of comments respectively, we construct the text-to-knowledge to mine the keywords from multiple dimensions. We further excavate the words correlated with the keywords by utilizing dependency parsing to create relational dependency graphs. Taken together, we identify key factors influencing EV user satisfaction or dissatisfaction and uncover the relationships among these factors. These insights provide valuable information for charging pile operators to develop targeted marketing strategies and improvement plans for the existing public charging pile resources, ultimately enhancing the overall user experience.

Autonomy-Supportive, External-Focus Instructions Optimize Children’s Motor Learning in Physical Education

An external focus of attention and autonomy support are identified as key factors to optimize motor learning; however, research in children is limited. Moreover, research has failed to examine these factors in ecologically valid motor learning settings, like physical education. Therefore, the present study examined the effects of external focus of attention when delivered using autonomy-supportive or controlling instructional language on children’s motor learning. Thirty-three novice participants (10.30 ± 0.52 years) practiced a land-based curling task under supportive (external-focus instructions delivered with supportive language), controlling (external-focus instructions delivered with controlling language), or neutral (external instructions embedded in the task aim) conditions before completing a retention and transfer test. The supportive group produced higher positive affect after practice and greater accuracy in the retention test compared with the other groups. The findings provide support for the OPTIMAL (optimizing performance through intrinsic motivation and attention for learning) theory of motor learning that combining an external focus and autonomy support conditions improves motor learning.

Physical Activity Levels, Correlates, and All-Cause Mortality Risk in People Living With Different Health Conditions.

To better understand physical activity behavior and its health benefits in people living with health conditions, we studied people with and without 20 different self-reported health conditions with regard to (1) their physical activity levels, (2) factors correlated with these physical activity levels, and (3) the association between physical activity and all-cause mortality. We used a subsample (n = 88,659) of the Lifelines cohort study from the Netherlands. For people living with and without 20 different self-reported health conditions, we studied the aforementioned factors in relation to physical activity. Physical activity was assessed with the Short Questionnaire to Assess Health-Enhancing Physical Activity Questionnaire, and mortality data were obtained from the Dutch death register. People with a reported health condition were less likely to meet physical activity guidelines than people without a reported health condition (odds ratios ranging from 0.55 to 0.89). Higher body mass index and sitting time, and lower self-rated health, physical functioning, and education levels were associated with lower odds of meeting physical activity guidelines across most health conditions. Finally, we found a protective association between physical activity and all-cause mortality in both people living with and without different health conditions. People living with different health conditions are generally less physically active compared with people living without a health condition. Both people living with and without self-reported health conditions share a number of key factors associated with physical activity levels. We also observed the expected protective association between physical activity and all-cause mortality.

Enhancing Procurement Integrity: Key Factors Influencing Internal Audit Effectiveness in Tanzania Public Procurement

This paper analyses the effects of internal audit competence, independence, and procedures on internal audit effectiveness in the procurement process in the public sector of Tanzania. The study is quantitative, and data were collected through questionnaires from accounting officers, senior management officers, audit committees, and internal audit units in public sectors. A total of 318 responses were collected. A Partial Least Structural Equation Modelling (PLS-SEM) technique was applied using R-studio to analyse the collected data, assess the model and test hypotheses. The findings revealed that internal audit characteristics procedures, independence and competence influence internal audit effectiveness in procurement. The study findings provide useful insights for policymakers, academics, and internal audit practitioners on the effect of the characteristics of internal audits in improving the effectiveness of internal audits in procurement in Tanzania.

Dynamics of Population and Land Use towards Sustainable Development in Patna Planning Area

Abstract: This study examines the impact of population growth on the land use pattern of Patna Planning Area, in the context of urban geography. Patna, the capital city of Bihar state in India, has experienced significant population growth over the past few decades, leading to changes in its land use pattern. The objectives of this research include analyzing the historical population growth trends in Patna, identifying the key factors that have contributed to this growth, and assessing its impact on land use. The study takes into account various factors such as residential, industrial, commercial, and agricultural land use, as well as the infrastructural developments associated with population growth. To achieve these objectives, both primary and secondary data sources are utilized. Primary data is collected through surveys, interviews, and observations, while secondary data is obtained from existing literature, government reports, and demographic databases. The findings of this study reveal that the population growth in Patna has led to a changing land use pattern. The expansion of residential areas and the conversion of agricultural land into residential and commercial zones are noted as significant transformations. Additionally, industrial growth has resulted in the emergence of new industrial zones and the conversion of agricultural land into industrial areas in the suburbs. Furthermore, it is observed that population growth has put pressure on infrastructure such as transportation, sewage and water supply systems, leading to the need for their expansion and development. This study highlights the need for urban planning and policies to accommodate the growing population while ensuring sustainable land use.

Energy and exergy analysis of the cryogenic system for HTS magnets based on an open-cycle G-M/J-T cryocooler

High-field magnets have been developed for a broad range of research applications. High-temperature superconducting magnets have received considerable attention due to their potential use in high-field applications. The High Magnetic Field Laboratory of the Chinese Academy of Sciences (CHMFL) is currently designing and constructing high-temperature superconducting (HTS) magnets which need the cooling capacity about 5 W to 10 W at 4.5 K in order to ensure the stability of the system. To meet their operational requirements, a miniature cryogenic system based on the Gifford-McMahon/Joule-Thomson (G-M/J-T) cryocooler has been designed and analyzed. In this research, the performance of the cryogenic system for HTS magnets is investigated systematically by employing both energy analysis and entropy analysis techniques. The results highlight the importance of several key factors, including high pressures, precooling temperature at cooling stages, and J-T exchanger efficiency, for improving the cooling capacity of the cryogenic system. Lowering the precooling temperature can enhance the system cooling capacity and also cause an increase in the precooling capacity. As the pressure increases, the cooling capacity of the system reaches its maximum point at 11.31 bar The J-T heat exchanger accounts for the largest exergy loss rate, 35.2–43.7%. The findings provide technical guidelines for the subsequent experiments and performance optimization of cryogenic system.

Prognostic value and potential function of a novel heme-related LncRNAs signature in gastric cancer

Heme is a coordination complex formed by the binding of iron ions and porphyrin rings. Its metabolic processes are associated with various cancers, including gastric cancer (GC). In recent years, long non-coding RNAs (LncRNAs) have been identified as key regulatory factors in GC. However, the role of LncRNAs associated with heme metabolism in GC and their relationship with prognosis have not been reported. In this study, we constructed a novel LncRNAs signature related to heme metabolism (HMlncSig) and validated its prognostic value for predicting the survival of GC patients through training, test, and entire cohorts. Kaplan-Meier analysis demonstrated that patients in the high-risk group had shorter survival times. Univariate and multivariate Cox regression analysis showed that HMlncSig was an independent prognostic indicator for GC patients, regardless of other clinical pathological features. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis and gene set variation analysis pathways showed that the activation of these markers may be involved in tumor progression, influencing the survival of GC patients. The nomogram, based on HMlncSig score and clinical features, demonstrated the strong predictive ability of this signature. Additionally, significant differences were observed between the high-risk and low-risk groups in terms of immune cell subtypes, expression of immune checkpoint genes, and response to chemotherapy and immunotherapy. Through clinical validation, we found that the risk score and heme levels of GC patients were both significantly elevated and correlated with the degree of malignancy. Furthermore, we found that AP000692.1, a key gene in this signature, promoted the proliferation, migration, and invasion of GC cells. In conclusion, our HMlncSig model has significant predictive value for the prognosis of GC patients and can provide clinical guidance for personalized immunotherapy.

Applications of Autonomous Navigation Technologies for Unmanned Agricultural Tractors: A Review

The development of unmanned agricultural tractors (UAT) represents a significant step towards intelligent agricultural equipment. UAT technology is expected to lighten the workload of laborers and enhance the accuracy and efficiency of mechanized operations. Through the investigation of 123 relevant studies in the literature published in recent years, this article reviews three aspects of autonomous navigation technologies for UATs: perception, path planning and tracking, and motion control. The advantages and deficiencies of these technologies in the context of UATs are clarified by analyzing technical principles and the status of current research. We conduct summaries and analyses of existing unmanned navigation solutions for different application scenarios in order to identify current bottleneck issues. Based on the analysis of the applicability of autonomous navigation technologies in UATs, it can be seen that fruitful research progress has been achieved. The review also summarizes the common problems seen in current UAT technologies. The application of research to the sharing and integrating of multi-source data for autonomous navigation has so far been relatively weak. There is an urgent need for high-precision and high-stability sensing equipment. The universality of path planning methods and the efficiency and precision of path tracking need to be improved, and it is also necessary to develop highly reliable electrical control modules to enhance motion control performance. Overall, advanced sensors, high-performance intelligent algorithms, and reliable electrical control hardware are key factors in promoting the development of UAT technology.

Understanding the correlates of construction safety of high-rise buildings: A Bayesian perspective

Safety in high-rise building construction is a critical concern, particularly in the densely populated urban areas of Vietnam. Understanding the complex interplay of factors influencing safety on construction sites is essential for reducing accidents and enhancing overall project outcomes. This study aims to identify and analyze key factors impacting safety in high-rise construction projects. Utilizing Bayesian Poisson Regression, the research investigates the relationship between various safety-related factors and the occurrence of non-fatal accidents. The study adopts a comprehensive approach, selecting potential safety factors from the existing literature and developing a rating system validated by site safety managers. Data were collected from 48 high-rise buildingprojects in Vietnam, constructed between 2019 and 2022. Bayesian Poisson Regression was employed to analyze the impact of 15 variables on safety outcomes, including management commitment, worker participation,training programs, emergency preparedness, and safety inspections. The findings underscore the multifacetednature of construction safety and the need for a holistic approach that involves strong safety training, engagedmanagement and workers, protective measures, and proactive safety audits. This research provides actionableinsights for practitioners and contributes to the academic discourse on construction safety, emphasizing theutility of Bayesian methods in unraveling complex safety dynamics in high-rise construction.

Research on Renewable Energy Trading Strategies Based on Evolutionary Game Theory

The authors construct a tripartite evolutionary game model that considers renewable energy, traditional coal-fired power plants, and market users. We propose multiple income matrices under different strategies, conduct evolutionary stability analysis, and form a series of assumptions that meet the stability of the game. We also simulate and analyze the impact of key factors—such as assessment costs, different pricing behaviors of coal-fired power plants, electricity prices of renewable energy, and green electricity demand—on the stability of the game. In addition, the market equilibrium points that can be achieved by optimizing trading strategies and their optimization status in promoting renewable energy consumption are analyzed. Based on the operational characteristics of the Guangxi electricity market in China and the trading situation of renewable energy, an evolutionary game method is applied to conduct empirical research. The trading behavior and evolution of all parties in the market are fully analyzed and are then applied to the construction and mechanism improvement of the electricity market.