In this study, we investigate Quantum Long Short-Term Memory and Quantum Gated Recurrent Unit integrated with Variational Quantum Circuits in modeling complex dynamical systems, including the Van der Pol oscillator, coupled oscillators, and the Lorenz system. We implement these advanced quantum machine learning techniques and compare their performance with traditional Long Short-Term Memory and Gated Recurrent Unit models. The results of our study reveal that the quantum-based models deliver superior precision and more stable loss metrics throughout 100 epochs for both the Van der Pol oscillator and coupled harmonic oscillators, and 20 epochs for the Lorenz system. The Quantum Gated Recurrent Unit outperforms competing models, showcasing notable performance metrics. For the Van der Pol oscillator, it reports MAE 0.0902 and RMSE 0.1031 for variable x and MAE 0.1500 and RMSE 0.1943 for y; for coupled oscillators, Oscillator 1 shows MAE 0.2411 and RMSE 0.2701 and Oscillator 2 MAE is 0.0482 and RMSE 0.0602; and for the Lorenz system, the results are MAE 0.4864 and RMSE 0.4971 for x, MAE 0.4723 and RMSE 0.4846 for y, and MAE 0.4555 and RMSE 0.4745 for z. These outcomes mark a significant advancement in the field of quantum machine learning. Full article

The research conducted at the Shanxi Agricultural University’s Quinoa Experimental Model Base in Jinzhong, Shanxi Province, aimed to assess agronomic traits and their correlation with yield across 32 quinoa varieties. Three distinct yield categories emerged: low (≤1500 kg ha⁻¹), middle (1500–2500 kg⁻¹), and high (>2500 kg ha⁻¹). High-yielding varieties demonstrated notable characteristics, including decreased plant height and increased leaf area per plant at maturity compared to low- and middle-yielding varieties. Moreover, the decline in leaf area per plant and root traits from flowering to maturity was less pronounced in the high-yielding varieties. The high-yielding varieties had a higher hardness of the stem base and middle stem by 12–13.7% and 6.3–11.5% compared to the medium- and low-yield varieties. Furthermore, high-yielding varieties indicated improvements in dry matter accumulation, decreased effective branch number, and increased main ear length and 1000-grain weight. Correlation analysis highlighted significant relationships between grain weight, yield, post-flowering senescence, and root and leaf characteristics. Structural equation model analysis revealed the negative impact of certain root and leaf traits on grain weight and yield, suggesting their importance in determining productivity. Notably, high-yielding varieties exhibited traits conducive to increased grain weight, including shorter plant height, slower root senescence, and enhanced post-flowering leaf resilience. These findings showed that understanding the relationship between agronomic traits and yield potential is crucial for optimizing quinoa production and promoting the sustainable development of this essential crop. Full article

To study the influence of coal mining on the water richness overlying strata in the mining area using time-lapse electrical monitoring technology, four dataset acquisitions were completed with the same acquisition method, equipment, parameters, and processing flow. According to the characteristics of the data, major problems such as topographic correction, high-precision denoising, spatial and temporal normalization, and resistivity data inversion have been solved. Precise tomographic imaging was achieved through high-precision data processing and difference inversion. The results show that the electrical stratification characteristics of the overlying soil and rock layers are clear, the resistivity from the surface down gradually increases, and the electrical layers are not uniform locally. During mining, the overlying strata are affected by mining, the electrical resistivity of the underlying aquifers increased to varying degrees, and the fluctuation of electrical resistivity increased while the aquifer’s water content decreased. After mining, the overlying aquifer has the phenomenon of ‘reduced resistivity and water recovery’. After a period of time, the overlying soil disturbance and overlying rock failure zone will gradually tend to be stable. Meanwhile, the aquifer structure and water content will also gradually recover. Our results could provide guidance for water resources protection in this region. Full article

The targeted delivery of a hydrophilic Tripeptide-3 to the skin using microemulsions or nanoemulsions for facial oil reduction was the focus of this study. The impact factors affecting oil/water transparent dispersion formation, such as the surfactant system, HLB value, and co-solvent, were identified through the water titration method and pseudoternary phase diagram plots. The interfacial tension between caprylic/capric triglyceride (CCT oil) and water was significantly reduced by the surfactant/co-surfactant combination (S_mix) of Cremophore^® RH40 and a double-tails co-surfactant, polyglycerol-3-diisostearate, at an HLB of 13 together with a water-to-co-solvent (PG) ratio of 1:1. A two-level full factorial design of experiment (FFD-DoE) emphasized the independent variables of the HLB value, co-solvent, and CCT oil contents affecting the optimal compositions for micro- or nanoemulsion formation. The low-energy spontaneous emulsification of the optimized combination at a low S_mix content (10%) yielded the translucent oil-in-water Tripeptide-3 nanoemulsions with an internal droplet size of 25.7 ± 1.20 nm, a narrow polydispersity index of 0.237 ± 0.129, and 70.6 ± 0.58% transmittance. The in vitro skin permeation study revealed a significantly higher skin penetration and retention of the Tripeptide-3 nanoemulsions compared to the high surfactant microemulsions and coarse emulsions. Skin irritation and oil control efficacy were evaluated in healthy volunteers before and after product application for 28 days. The obtained nanoemulsions not only decreased sebum production but also enhanced skin moisture levels. In conclusion, the meticulously designed nanoemulsions, incorporating suitable excipients, show a promising delivery system for hydrophilic peptides to control sebum overproduction in oily facial skin. Full article

Nonalcoholic fatty liver disease (NAFLD) is the liver component of a cluster of conditions, while its subtype, nonalcoholic steatohepatitis (NASH), emerges as a potentially progressive liver disorder that harbors the risk of evolving into cirrhosis and culminating in hepatocellular carcinoma (HCC). NASH and cardiovascular disease (CVD) have common risk factors, but compared to liver-related causes, the most common cause of death in NASH patients is CVD. Within the pharmacological armamentarium, statins, celebrated for their lipid-modulating prowess, have now garnered attention for their expansive therapeutic potential in NASH. Evidence from a plethora of studies suggests that statins not only manifest anti-inflammatory and antifibrotic properties but also impart a multifaceted beneficial impact on hepatic health. In this review, we used “statin”, “NAFLD”, “NASH”, and “CVD” as the major keywords and conducted a literature search using the PubMed and Web of Science databases to determine the safety and efficacy of statins in patients and animals with NASH and NAFLD, and the mechanism of statin therapy for NASH. Simultaneously, we reviewed the important role of the intestinal microbiota in statin therapy for NASH, as it is hoped that statins will provide new insights into modulating the harmful inflammatory microbiota in the gut and reducing systemic inflammation in NASH patients. Full article

Experimental autoimmune orchitis (EAO) is a well-established rodent model of organ-specific autoimmunity associated with infertility in which the testis immunohistopathology has been extensively studied. In contrast, analysis of testis biopsies from infertile patients associated with inflammation has been more limited. In this work, testicular biopsies from patients with idiopathic non-obstructive azoospermia diagnosed with hypospermatogenesis (HypoSp) [mild: n = 9, and severe: n = 11], with obstructive azoospermia and complete Sp (spermatogenesis) (control group, C, n = 9), and from Sertoli cell-only syndrome (SCOS, n = 9) were analyzed for the presence of immune cells, spermatogonia and Sertoli cell (SCs) alterations, and reproductive hormones levels. These parameters were compared with those obtained in rats with EAO. The presence of increased CD45+ cells in the seminiferous tubules (STs) wall and lumen in severe HypoSp is associated with increased numbers of apoptotic meiotic germ cells and decreased populations of undifferentiated and differentiated spermatogonia. The SCs showed an immature profile with the highest expression of AMH in patients with SCOS and severe HypoSp. In SCOS patients, the amount of SCs/ST and Ki67+ SCs/ST increased and correlated with high serum FSH levels and CD45+ cells. In the severe phase of EAO, immune cell infiltration and apoptosis of meiotic germ cells increased and the number of undifferentiated and differentiated spermatogonia was lowest, as previously reported. Here, we found that orchitis leads to reduced sperm number, viability, and motility. SCs were mature (AMH-) but increased in number, with Ki67+ observed in severely damaged STs and associated with the highest levels of FSH and inflammatory cells. Our findings demonstrate that in a scenario where a chronic inflammatory process is underway, FSH levels, immune cell infiltration, and immature phenotypes of SCs are associated with severe changes in spermatogenesis, leading to azoospermia. Furthermore, AMH and Ki67 expression in SCs is a distinctive marker of severe alterations of STs in human orchitis. Full article

Cloud providers offer various purchasing options to enable users to tailor their costs according to their specific requirements, including on-demand, reserved instances, and spot instances. On-demand and spot instances satisfy short-term workloads, whereas reserved instances fulfill long-term instances. However, there are workloads that fall outside of either long-term or short-term categories. Consequently, there is a notable absence of services specifically tailored for medium-term workloads. On-demand services, while offering flexibility, often come with high costs. Spot instances, though cost-effective, carry the risk of termination. Reserved instances, while stable and less expensive, may have a remaining period that extends beyond the duration of users’ tasks. This gap underscores the need for solutions that address the unique requirements and challenges associated with medium-term workloads in the cloud computing landscape. This paper introduces a new cloud broker that introduces IaaS services for medium-term workloads. On one hand, this broker strategically reserves resources from providers, and on the other hand, it interacts with users. Its interaction with users is twofold. It collects users’ preferences regarding commitment term for medium-term workloads and then transforms the leased resources based on commitment term, aligning with the requirements of most users. To ensure profitability, the broker sells these services utilizing an auction algorithm. Hence, in this paper, an auction algorithm is introduced and developed, which treats cloud services as virtual assets and integrates the depreciation over time. The findings affirm the lack of services that fulfill medium workloads while ensuring the financial viabilty and profitability of the broker, given that the estimated return on investment (ROI) is acceptable. Full article

With the introduction of numerous technologies and equipment, the volume of data in smart substations has undergone exponential growth. In order to enhance the intelligent management level of substations and promote their efficient and sustainable development, the one-key sequential control system of smart substations is being renovated. In this study, firstly, the intelligent substation is defined and compared with the traditional substation. The one-key sequential control system is introduced, and the main issues existing in the system are analyzed. Secondly, experiments are conducted on the winding temperature, insulation oil temperature, and ambient temperature of power transformers in the primary equipment. Combining data fusion technology and transformer neural network models, a Power Transformer-Transformer Neural Network (PT-TNNet) model based on data fusion is proposed. Subsequently, comparative experiments are conducted with multiple algorithms to validate the high accuracy, precision, recall, and F1 score of the PT-TNNet model for equipment state monitoring and fault diagnosis. Finally, using the efficient PT-TNNet, Random Forest, and Extra Trees models, the cross-validation of the accuracy of winding temperature and insulation oil temperature of transformers is performed, confirming the superiority of the PT-TNNet model based on transformer neural networks for power transformer state monitoring and fault diagnosis, its feasibility for application in one-key sequential control systems, and the optimization of one-key sequential control system performance. Full article

Although endometriosis is a benign disease, it is associated with cancer-related gene mutations, such as KRAS or PIK3CA. Endometriosis is associated with elevated levels of inflammatory factors that cause severe pain. In a previous study, we demonstrated that KRAS or PIK3CA mutations are associated with the activation of cell proliferation, migration, and invasion in a patient-derived immortalized endometriotic cell line, HMOsisEC10. In this study, we investigated the effects of these mutations on progesterone resistance. Since the HMOsisEC10 had suppressed progesterone receptor (PR) expression, we transduced PR-B to HMOsisEc10 cell lines including KRAS mutant and PIK3CA mutant cell lines. We conducted a migration assay, invasion assay, and MTT assay using dienogest and medroxyprogestrone acetate. All cell lines showed progesterone sensitivity with or without mutations. Regarding inflammatory factors, real-time quantitative RT-PCR revealed that the KRAS mutation cell line exhibited no suppression of Cox-2 and mPGES-1 on progesterone treatment, whereas IL-6, MCP-1, VEGF, and CYP19A1 were significantly suppressed by progesterone in both mutated cell lines. Our results suggest that KRAS mutation and PIK3CA mutation in endometriotic cells may not be associated with progesterone resistance in terms of aggressiveness. However, KRAS mutations may be associated with progesterone resistance in the context of pain. Full article

Polycaprolactone (PCL) scaffolds have demonstrated an effectiveness in articular cartilage regeneration due to their biomechanical properties. On the other hand, alginate hydrogels generate a 3D environment with great chondrogenic potential. Our aim is to generate a mixed PCL/alginate scaffold that combines the chondrogenic properties of the two biomaterials. Porous PCL scaffolds were manufactured using a modified salt-leaching method and embedded in a culture medium or alginate in the presence or absence of chondrocytes. The chondrogenic capacity was studied in vitro. Type II collagen and aggrecan were measured by immunofluorescence, cell morphology by F-actin fluorescence staining and gene expression of COL1A1, COL2A1, ACAN, COL10A1, VEGF, RUNX1 and SOX6 by reverse transcription polymerase chain reaction (RT-PCR). The biocompatibility of the scaffolds was determined in vivo using athymic nude mice and assessed by histopathological and morphometric analysis. Alginate improved the chondrogenic potential of PCL in vitro by increasing the expression of type II collagen and aggrecan, as well as other markers related to chondrogenesis. All scaffolds showed good biocompatibility in the in vivo model. The presence of cells in the scaffolds induced an increase in vascularization of the PCL/alginate scaffolds. The results presented here reinforce the benefits of the combined use of PCL and alginate for the regeneration of articular cartilage. Full article

Genetic biomarkers have played a pivotal role in the classification, prognostication, and guidance of clinical cancer therapies. Large-scale and multi-dimensional analyses of entire cancer genomes, as exemplified by projects like The Cancer Genome Atlas (TCGA), have yielded an extensive repository of data that holds the potential to unveil the underlying biology of these malignancies. Mutations stand out as the principal catalysts of cellular transformation. Nonetheless, other global genomic processes, such as alterations in gene expression and chromosomal re-arrangements, also play crucial roles in conferring cellular immortality. The incorporation of multi-omics data specific to cancer has demonstrated the capacity to enhance our comprehension of the molecular mechanisms underpinning carcinogenesis. This report elucidates how the integration of comprehensive data on methylation, gene expression, and copy number variations can effectively facilitate the unsupervised clustering of cancer samples. We have identified regressors that can effectively classify tumor and normal samples with an optimal integration of RNA sequencing, DNA methylation, and copy number variation while also achieving significant $p$-values. Further, these regressors were trained using linear and logistic regression with $k$-means clustering. For comparison, we employed autoencoder- and stacking-based omics integration and computed silhouette scores to evaluate the clusters. The proof of concept is illustrated using liver cancer data. Our analysis serves to underscore the feasibility of unsupervised cancer classification by considering genetic markers beyond mutations, thereby emphasizing the clinical relevance of additional global cellular parameters that contribute to the transformative process in cells. This work is clinically relevant because changes in gene expression and genomic re-arrangements have been shown to be signatures of cellular transformation across cancers, as well as in liver cancers. Full article

A recent measure was developed to assess the Quality of Life (QoL) of young people with advanced cancer and is available for parents and professionals (Advance QoL). The present study aimed to elaborate self-reported versions for children and adolescents with advanced cancer. We adopted a four-phase research plan: (1) to elaborate the Advance QoL questionnaire for youth (8–12 and 13–18 years old) with a team of young research partners; (2) to evaluate the understandability of these versions in a sample of 12 young patients from the target population using cognitive interviews; (3) to assess social validity in the same group using a questionnaire and the content validity index (CVI); and (4) to refine the questionnaires according to these results. Four major themes were identified: (1) issues affecting the understanding of the tool; (2) issues that did not affect the understanding of the tool; (3) modifications to improve the tool; and (4) positive features of the tool. Advance QoL was well received, and feedback was positive. Adjustments were made according to young people’s comments and two self-reported versions are now available. It is essential to measure the key domains of QoL in advanced cancer. Advance QoL self-report versions will help target the specific needs of young people with this condition and their families. Full article

Background: Surgeons have limited knowledge of the lumbar intervertebral foramina. This study aimed to classify osteophytes in the lumbar intervertebral foramen and to determine their pathoanatomical characteristics, discuss their potential biomechanical effects, and contribute to developing surgical methods. Methods: We conducted a retrospective, non-randomized, single-center study involving 1224 patients. The gender, age, and anatomical location of the osteophytes in the lumbar intervertebral foramina of the patients were recorded. Results: Two hundred and forty-nine (20.34%) patients had one or more osteophytes in their lumbar 4 and 5 foramina. Of the 4896 foramina, 337 (6.88%) contained different types of osteophytes. Moreover, four anatomical types of osteophytes were found: mixed osteophytes in 181 (3.69%) foramina, osteophytes from the lower endplate of the superior vertebrae in 91 (1.85%) foramina, osteophytes from the junction of the pedicle and lamina of the upper vertebrae in 39 foramina (0.79%), and osteophytes from the upper endplate of the lower vertebrae in 26 (0.53%) foramina. The L4 foramen contained a significantly higher number of osteophytes than the L5 foramen. Osteophyte development increased significantly with age, with no difference between males and females. Conclusions: The findings show that osteophytic extrusions, which alter the natural anatomical structure of the lumbar intervertebral foramina, are common and can narrow the foramen. Full article

Although current policies discourage the use of corporal punishment (CP), its use is still widespread in the US. The objective of this study was to assess the proportion of parents who used CP during the pandemic and identify related risk and protective factors. We analyzed results of a nationwide cross-sectional internet panel survey of 9000 US caregivers who responded in three waves from November 2020 to July 2021. One in six respondents reported having spanked their child in the past week. Spanking was associated with intimate partner violence and the use of multiple discipline strategies and not significantly associated with region or racial self-identification. Parents who spanked sought out more kinds of support, suggesting an opportunity to reduce spanking through more effective parenting resources. Additionally, these results suggest that parents who report using CP may be at risk for concurrent domestic violence. Full article

We investigated the experiences of Brazilian gay men with HIV, focusing on the moment of diagnosis and its potential biopsychosocial impacts. This clinical–qualitative study involved 15 participants interviewed online and synchronously by a clinical psychologist in 2021. Thematic analysis was employed to analyze the data. Interpretations were grounded in Minority Stress Theory. Four thematic axes emerged, including “Diagnostic Revelation”, “Social and Internalized Stigma”, “Biopsychosocial Effects of Living with HIV”, and “Gratitude for Treatment Advances and the Brazilian Health System”. The diagnosis was often experienced as traumatic, exacerbated by the absence of empathy and emotional support from healthcare providers. Participants commonly reported guilt, fear upon learning of their HIV status, social isolation, loneliness, lack of social support, and damage to affective-sexual relationships. Many also noted a decline in mental health, even those without HIV-related medical complications. Despite over 40 years since the HIV epidemic began, the prevalence of homophobia and serophobia among gay men remains widespread, including within the multidisciplinary teams of specialized services. This indicates that the stigma associated with homosexuality and HIV persists, despite significant biomedical progress in the diagnosis and treatment of the infection, particularly in Brazil. Full article

This research investigates the application of deep learning in sentiment analysis of Canadian maritime case law. It offers a framework for improving maritime law and legal analytic policy-making procedures. The automation of legal document extraction takes center stage, underscoring the vital role sentiment analysis plays at the document level. Therefore, this study introduces a novel strategy for sentiment analysis in Canadian maritime case law, combining sentiment case law approaches with state-of-the-art deep learning techniques. The overarching goal is to systematically unearth hidden biases within case law and investigate their impact on legal outcomes. Employing Convolutional Neural Network (CNN)- and long short-term memory (LSTM)-based models, this research achieves a remarkable accuracy of 98.05% for categorizing instances. In contrast, conventional machine learning techniques such as support vector machine (SVM) yield an accuracy rate of 52.57%, naïve Bayes at 57.44%, and logistic regression at 61.86%. The superior accuracy of the CNN and STM model combination underscores its usefulness in legal sentiment analysis, offering promising future applications in diverse fields like legal analytics and policy design. These findings mark a significant choice for AI-powered legal tools, presenting more sophisticated and sentiment-aware options for the legal profession. Full article

In the context of autonomous driving, the fusion of LiDAR and camera sensors is essential for robust obstacle detection and distance estimation. However, accurately estimating the transformation matrix between cost-effective low-resolution LiDAR and cameras presents challenges due to the generation of uncertain points by low-resolution LiDAR. In the present work, a new calibration technique is developed to accurately transform low-resolution 2D LiDAR points into camera pixels by utilizing both static and dynamic calibration patterns. Initially, the key corresponding points are identified at the intersection of 2D LiDAR points and calibration patterns. Subsequently, interpolation is applied to generate additional corresponding points for estimating the homography matrix. The homography matrix is then optimized using the Levenberg–Marquardt algorithm to minimize the rotation error, followed by a Procrustes analysis to minimize the translation error. The accuracy of the developed calibration technique is validated through various experiments (varying distances and orientations). The experimental findings demonstrate that the developed calibration technique significantly reduces the mean reprojection error by 0.45 pixels, rotation error by 65.08%, and distance error by 71.93% compared to the standard homography technique. Thus, the developed calibration technique promises the accurate transformation of low-resolution LiDAR points into camera pixels, thereby contributing to improved obstacle perception in intelligent autonomous driving systems. Full article

Television plays a significant role in shaping the beliefs, perceptions, and attitudes of young individuals. Understanding the factors that influence these beliefs is essential for comprehending the impact of television programming on the youth population. This paper aims to investigate the correlations in beliefs regarding television programming among Greek youths aged 15–18 with their demographic characteristics, parental educational levels, school performance, and daily television viewing habits. To study the above, a structured questionnaire was electronically distributed to 204 Greek teenagers after obtaining parental consent. By identifying the factors associated with variations in beliefs, this study contributes to the existing literature on media influence and youth development. The findings indicate youth’s moderate levels of reflection regarding different aspects of television shows, including their presentation to the public and their influence on perceptions and attitudes. What is more, the youth audience haslow trust in TV news, and they moderately believe that the content of news is greatly influenced by governments and political elite agendas, while they consider TV as a major influential media type in shaping people’s political opinions. Notably, youngsters who considered themselves high-achieving students, as well as those who engaged in more frequent television viewing, including documentaries, news, and talk shows, exhibit increased concern and skepticism regarding the information presented in the television programs they watch. This is an important finding, because despite the low trust in TV as a medium, it continues to attract the attention of young people. Full article

Significant research endeavors have focused on microbial fuel cell (MFC) systems within wastewater treatment protocols owing to their unique capacity to convert chemical energy from waste into electricity while maintaining minimal nutrient concentrations in the effluent. While prior studies predominantly relied on empirical investigations, there remains a need to explore modeling and simulation approaches. Assessing MFC systems’ performance and power generation based on real wastewater data is pivotal for their practical implementation. To address this, a MATLAB model is developed to elucidate how MFC parameters and constraints influence system performance and enhance wastewater treatment efficiency. Leveraging actual wastewater data from a municipal plant in Guelph, Canada, six sets of MFC models are employed to examine the relationship between power generation and six distinct parameters (inflow velocity, membrane thickness, internal resistance, anode surface area, feed concentration, and hydraulic retention time). Based on these analyses, the final model projects a total power generation of 50,515.16 kW for the entire wastewater treatment plant in a day, capable of supporting approximately 2530 one-person households. Furthermore, the model demonstrates a notably higher chemical oxygen demand (COD) removal rate (75%) compared to the Guelph WWTP. This comprehensive model serves as a valuable tool for future simulations in similar wastewater treatment plants, providing insights for optimizing performance and aiding in practical applications. Full article

Per- and polyfluoroalkyl substances (PFASs) are carbon–fluorine compounds with widespread industrial and domestic use, posing potential toxicological risks to humans and ecosystems. Several analytical methods have been developed to assess the occurrence of PFASs in the environment, but a standardized method, applicable to all matrices, is still lacking. This paper reviews the extraction and chromatographic detection methods for PFAS assessment in environmental samples, considering parameters such as the LOD, LOQ, and recoveries. Solid phase extraction (SPE) is commonly used, showing high recovery rates for water, soil, and sediment samples using HBL and WAX polymeric sorbents (85–100% and 93–111.5%, respectively). LC-MS has demonstrated low LODs and LOQs in seawater (0.01–0.08 ng L⁻¹; 0.03–0.24 ng L⁻¹), marine sediment (0.002–0.018 ng g⁻¹; 0.004–0.054 ng g⁻¹), and dust (0.08–0.68 pg g⁻¹; 0.26–2.25 pg g⁻¹), indicating its sensitivity when detecting trace PFAS levels. Evaluating PFASs is crucial for the development of future removal strategies and risk assessments. Potential solutions including the use of PFAS substitutes and innovative adsorption techniques for their adsorption could present promise in reducing their environmental presence. Full article

In order to evaluate the damage to tunnel cables caused by fire caused by leakage of transformer oil into a cable channel, the fire characteristics of different volumes of transformer oil flowing into a cable channel were analyzed by numerical simulation. The results show that when the total leakage of transformer oil is less than or equal to 3 L, the fire will end within 120 s, and when the total leakage is greater than or equal to 5 L, the fire duration will exceed 900 s. When the leakage amount is 1 L, the cable only burns slightly, and when the leakage amount is 3~12 L, the cable burns obviously. The combustion of the cable is mainly concentrated between 15 s and 75 s, and the overall combustion rate of the cable increases first and then decreases. When the total leakage is greater than or equal to 8 L, the damage distance of the middle and lower layer cable is the smallest. When the total leakage is less than or equal to 5 L, the damage distance of the lower layer cable is the smallest, and the damage distance of the lower layer cable, middle and lower layer cable, and middle and upper layer cable is less than half of the length of the cable channel. Full article