Journal of Radiation Research and Applied Sciences最新文献

{"title":"Thermo-solutal convective flow of nanofluid with Marangoni convection: An artificial neural network study considering thermophoresis and thermal radiation effects","authors":"Mouloud Aoudia ,&nbsp;Munawar Abbas ,&nbsp;Ibtehal Alazman ,&nbsp;Ilyas Khan","doi":"10.1016/j.jrras.2025.101612","DOIUrl":"10.1016/j.jrras.2025.101612","url":null,"abstract":"<div><div>A neural network backpropagation approach combined with the AI-integrated Levenberg-Marquardt algorithm provides a comprehensive analysis of the thermal radiation on thermos-solutal Marangoni convective flow of nanofluid with thermophoresis influenced by Lorentz force effects. In order to explain mass and heat transmission and fluid flow, non-linear, coupled PDE (partial differential equations) are transformed into ODE (ordinary differential equations) with similarity scaling. The Bvp4c method is then used to resolve these equations numerically. The suggested model has important uses in many industrial and technical processes where mass transfer and heat are important factors. It is used in sophisticated material processing, cooling systems, and microfluidic devices where accurate thermal control is crucial. The research holds special significance for cooling mechanisms based on nanotechnology, including nuclear reactor safety and semiconductor chip cooling. Furthermore, the model's incorporation of Marangoni convection, thermophoresis, and thermal radiation effects renders it applicable to solar energy harvesting, biomedical engineering, and aerospace technology, all of which depend on effective heat dissipation and fluid stability. The concentration profile decreases as increase the thermophoretic parameter rise.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 3","pages":"Article 101612"},"PeriodicalIF":1.7,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144070671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of cell junctions in radiation-induced injury to normal tissue","authors":"Lin Ma ,&nbsp;Ge Xu ,&nbsp;Xiaoran Shi ,&nbsp;Jiahui Wu ,&nbsp;Yanhe Li ,&nbsp;Xiu Zhao ,&nbsp;Qi Liu","doi":"10.1016/j.jrras.2025.101616","DOIUrl":"10.1016/j.jrras.2025.101616","url":null,"abstract":"<div><div>Normal tissue faces the risk of ionizing radiation (IR) exposure during radiological examination or radiotherapy, and growing evidence indicates an elevated risk of radiation-induced normal tissue dysfunction via disrupted cell junctions. However, the mechanisms underlying this type of damage are not well understood. IR may induce tissue inflammation, but there is a paucity of evidence to support this theory. In this review, we summarize the literature to illustrate the role of cell junctions in radiation-induced normal tissue injury. Targeting cell junction proteins after IR may lead to new methods of normal tissue protection during radiotherapy or radiological examination.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 3","pages":"Article 101616"},"PeriodicalIF":1.7,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144072671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances in bioconvection of Casson nanofluids over a stretching sheet: Influence of thermal radiation and activation energy","authors":"Farkhanda Afzal ,&nbsp;Tahir Kamran ,&nbsp;Muhammad Bilal Riaz","doi":"10.1016/j.jrras.2025.101598","DOIUrl":"10.1016/j.jrras.2025.101598","url":null,"abstract":"<div><h3>Background</h3><div>Nanofluids possess enhanced thermal properties, making them highly effective in improving heat transfer performance within thermal systems. Owing to their distinctive thermophysical characteristics, nanofluids have attracted considerable interest across various engineering applications.</div></div><div><h3>Purpose</h3><div>This study investigates the magnetohydrodynamic (MHD) flow of Casson nanofluids over a stretching sheet, accounting for the effects of thermal radiation, activation energy, bioconvection, and motile microorganisms. The roles of Brownian motion and thermophoresis in heat and mass transfer are also analyzed.</div></div><div><h3>Method</h3><div><em>ology</em>: The governing nonlinear partial differential equations (PDEs) are reduced to a system of nonlinear ordinary differential equations (ODEs) through similarity transformations. These equations, along with the corresponding boundary conditions, are numerically solved using the bvp4c solver in MATLAB.</div></div><div><h3>Results</h3><div>The analysis demonstrates that an increase in the Brownian motion parameter promotes thermal energy diffusion, whereas a higher Lewis number inhibits mass transfer. The Casson fluid parameter reduces the velocity boundary layer thickness, resulting in a 12.4 % rise in shear stress. Additionally, a higher Prandtl number leads to a 21.7 % decrease in thermal boundary layer thickness, thereby enhancing heat dissipation. The thermophoretic parameter exerts a pronounced effect on nanoparticle concentration, yielding a 15.3 % increase in concentration gradients. These results offer valuable insights into optimizing heat and mass transfer in nanofluid-based thermal systems.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 3","pages":"Article 101598"},"PeriodicalIF":1.7,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144069641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of ultrasound-guided needle knife combined with platelet-rich plasma infusion on lumbar muscle strain and prognostic evaluation","authors":"Binbin Zhao ,&nbsp;Hongli Jia ,&nbsp;Subing Zhang ,&nbsp;Yuzi Yang ,&nbsp;Bing Li ,&nbsp;Pei Shi ,&nbsp;Gongxi Fang","doi":"10.1016/j.jrras.2025.101562","DOIUrl":"10.1016/j.jrras.2025.101562","url":null,"abstract":"<div><div>The study evaluated the effectiveness of ultrasound-guided needle knife (UGNK) combined with platelet-rich plasma (PRP) infusion in treating chronic lumbar muscle strain (CLMS). Ninety-two patients with CLMS treated from January 2023 to January 2024 were randomly divided into a control group (CG, n = 46, simple local injection) and an observation group (OG, n = 46, UGNK with PRP infusion). The study compared treatment outcomes, lumbar range of motion, ultrasound findings, pain levels, lumbar function, serum inflammatory factors, and quality of life (QOL) before and after treatment. The effective rate in the OG (97.83 %) was significantly higher than in the CG (78.26 %, P &lt; 0.05). After treatment, the OG showed a reduced lumbar range of motion, smaller hypoechoic areas, and lower pain scores (Present Pain Intensity [PPI], Visual Analog Scale [VAS], and Pain Rating Index [PRI]) compared to the CG (P &lt; 0.05). The OG also had higher Japanese Orthopaedic Association (JOA) scores and lower Oswestry Disability Index (ODI) scores, indicating improved lumbar function (P &lt; 0.05). Serum levels of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and C-reactive protein (CRP) were lower in the OG, demonstrating reduced inflammation (P &lt; 0.05). Additionally, QOL scores in the physiology, social relations, psychology, and environment domains were higher in the OG (P &lt; 0.05). In conclusion, UGNK combined with PRP infusion effectively improves clinical symptoms, lumbar function, pain relief, inflammation reduction, and QOL in CLMS patients, suggesting a promising therapeutic approach.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 3","pages":"Article 101562"},"PeriodicalIF":1.7,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144069640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On estimating the finite population mean using improved estimators in adaptive cluster sampling design","authors":"Rohan Mishra ,&nbsp;Diaa S. Metwally ,&nbsp;Rajesh Singh ,&nbsp;Nitesh Kumar Adichwal","doi":"10.1016/j.jrras.2025.101593","DOIUrl":"10.1016/j.jrras.2025.101593","url":null,"abstract":"<div><div>This article introduces a generalized class of estimators tailored for estimating the finite population mean within the framework of Adaptive Cluster Sampling (ACS) design. The proposed class is designed to encompass numerous existing estimators as its particular cases while also introducing several new novel estimators. It should be noted that the existing estimators which are presented in Section 3 are members of the proposed log type generalized class <span><math><mrow><msub><mi>T</mi><mi>g</mi></msub></mrow></math></span>. From the proposed log type generalized class <span><math><mrow><msub><mi>T</mi><mi>g</mi></msub></mrow></math></span>, four new log type estimators are developed. We derive the expressions for bias and mean square error (MSE) up to the first order of approximation. Through simulation studies and a real data application, we compare the performance of the new estimators derived from this proposed class with existing ones, demonstrating that the newly developed estimators outperform their existing counterparts. For the better understanding of the performances of our suggested class of estimators, we present the numerical results graphically.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 3","pages":"Article 101593"},"PeriodicalIF":1.7,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143943706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The modified sign test under indeterminacy with application to COVID-19 data","authors":"Qamer Abbas ,&nbsp;L.S. Diab ,&nbsp;Safar M. Alghamdi ,&nbsp;Farrukh Jamal","doi":"10.1016/j.jrras.2025.101583","DOIUrl":"10.1016/j.jrras.2025.101583","url":null,"abstract":"<div><div>The sign test is a non-parametric method for assessing median differences in paired observations, especially when parametric assumptions (e.g., normality for paired t-tests) are violated. However, its conventional form is limited to exact categorical data (binary/ordinal) and cannot handle interval-valued data (measurements expressed as ranges), restricting its use in cases of imprecise, vague, or indeterminate observations. To address this gap, we propose a modified neutrosophic sign test that incorporates indeterminacy, enabling analysis of interval-valued data for both one-sample and two-sample hypothesis testing under uncertainty. We validate its efficacy through two real-world case studies: (1) assessing COVID-19 reproduction rates to evaluate transmission dynamics and (2) analyzing daily ICU occupancy trends for COVID-19-positive patients in Pakistan. These applications highlight its adaptability in public health scenarios with data variability. Results confirm that the neutrosophic sign test effectively resolves nonparametric decision-making problems involving interval data, providing robust statistical insights in fields like engineering, biological sciences, and public health—where indeterminate data are common. By accommodating imprecision, this approach enhances the traditional sign test's versatility, making it a practical tool for modern statistical analysis in complex, uncertain environments.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 3","pages":"Article 101583"},"PeriodicalIF":1.7,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143943709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning estimation of heat and mass transfer attributes of thermal radiative Williamson nanofluid flow via nonlinear stretchable surface","authors":"Syed M. Hussain ,&nbsp;Dilawar Nawaz ,&nbsp;Bushra Attique ,&nbsp;Muhammad Haroon ,&nbsp;Wasim Jamshed ,&nbsp;Kamel Guedri ,&nbsp;Basim M. Makhdoum ,&nbsp;Abdulrazak H. Almaliki","doi":"10.1016/j.jrras.2025.101581","DOIUrl":"10.1016/j.jrras.2025.101581","url":null,"abstract":"<div><div>Nanomaterials exhibit remarkable thermal properties and have promising utilization in areas such as thermal energy transmission, biopharmaceuticals, the food industry, solar power generation and electric cooling systems. The significant applications of nanoparticles inspired the development of a mathematical model to analyze mass and heat transfer in magnetically influenced Williamson nanoliquid flow across an exponentially extendable surface by incorporating physical factors of Brownian motion and thermophoresis effects along with Arrhenius activation energy and convective boundary constraints. The fundamental equations describing the mathematical structure are designed in the sense of a highly nonlinear coupled partial differential setup. A set of similar variables is utilized to transmute the differential setup into a non-dimensional ordinary system. The attained ODEs are resolved with the implementation of a shooting algorithm in conjunction with the RK-4 technique. Afterwards, a machine learning algorithm based on the backpropagated Leven-berg Marquardt paradigm is also utilized to forecast the numerical outcomes of the quantities of engineering. The impact of relevant flow factors on the associated flow distributions and the quantities of engineering interest are presented via graphical and tabular format. The numerical outcomes signify that momentum distribution dominates by inducing mono nanoparticles as compared to hybrid particles. Enhancement in thermal distribution is perceived by intensifying Brownian motion and thermophoresis effects, whereas contrary aspects are observed for associated flux. In addition, the trained ANN models shows that the best validation performance of Model-A is 1.15e-5 that happens at 565 epochs, while the best validation performance for Model-B is 3.38e-5 at 641 epochs. Small estimations guarantee that model training completed properly. Nusselt number elevates by 29 % for mono and 25 % for hybrid nanoliquid flow when <span><math><mrow><mo>(</mo><mrow><mi>R</mi><mi>d</mi></mrow><mo>)</mo></mrow></math></span> varies from 0.2 to 0.6, while depreciates up to 1.5 % by elevating <span><math><mrow><mrow><mo>(</mo><mrow><mi>N</mi><mi>t</mi></mrow><mo>)</mo></mrow><mtext>.</mtext></mrow></math></span></div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 3","pages":"Article 101581"},"PeriodicalIF":1.7,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143937013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the impact of thermal radiation, induced magnetic force, and convective boundary condition on MHD nanofluid flows","authors":"G. Venkata Ramana Reddy ,&nbsp;Charankumar Ganteda ,&nbsp;Maria Naseem ,&nbsp;Muhammad Amer Qureshi ,&nbsp;Wasim Jamshed ,&nbsp;Mohamed R. Eid ,&nbsp;Syed M. Hussain ,&nbsp;Abdulrazak H. Almaliki","doi":"10.1016/j.jrras.2025.101572","DOIUrl":"10.1016/j.jrras.2025.101572","url":null,"abstract":"<div><div>A numerical model is developed to investigate the heat and mass transfer characteristics of a two-dimensional Maxwell nanofluid flow over an expanding/shrinking surface under the influence of thermal radiation and an induced magnetized force. The governing nonlinear differential equations, which account for magnetohydrodynamic (MHD) effects and viscoelastic fluid behavior, are solved numerically using the Runge-Kutta-Fehlberg (RKF45) method. The study aims to obtain detailed profiles for velocity, temperature, and concentration distributions under varying physical parameters.</div><div>The results indicate that the Deborah number significantly enhances the flow velocity due to the elastic nature of the Maxwell fluid. An increase in the magnetic parameter (M) leads to a suppression of the velocity field as a result of the Lorentz force while simultaneously strengthening the induced magnetic field. The thermal radiation parameter (Nr) positively impacts the temperature distribution, thereby increasing the thermal boundary layer thickness. Furthermore, the Lewis number (<em>Le</em>) is found to reduce concentration levels, indicating dominant thermal over mass diffusivity.</div><div>Overall, the study provides new insights into the coupled effects of magnetic induction, radiative heat transfer, and fluid elasticity on nanofluid transport behaviour, which has practical implications in material processing, energy systems, and biomedical engineering applications.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 3","pages":"Article 101572"},"PeriodicalIF":1.7,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143937014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient energy utilization in LTE networks with intelligent handover mechanisms","authors":"Umar Danjuma Maiwada ,&nbsp;Gaber Sallam Salem Abdalla ,&nbsp;Narinderjit Singh Sawaran Singh ,&nbsp;Anas A. Salameh","doi":"10.1016/j.jrras.2025.101599","DOIUrl":"10.1016/j.jrras.2025.101599","url":null,"abstract":"<div><div>As mobile data traffic surges and the number of connected devices rises, energy efficiency has become a critical concern in Long-Term Evolution (LTE) networks. Traditional handover algorithms in LTE systems prioritize metrics such as signal strength and load balancing, often overlooking the impact on energy consumption. This study addresses that gap by proposing an intelligent, data-driven handover optimization framework designed to reduce energy usage in heterogeneous LTE environments. The core objective is to enhance network sustainability without significantly compromising Quality of Service (QoS). To achieve this, we introduce a machine learning-based handover decision mechanism that integrates user behavior prediction and workload balancing. Thus, analyzing both user mobility patterns and network conditions, the proposed system identifies optimal timing and target cells for handovers. This proactive strategy minimizes unnecessary signaling and handover attempts, which are common sources of energy waste in traditional approaches. The framework includes a Mobility Load Balancing (MLB) algorithm that extends beyond conventional metrics, incorporating energy-awareness as a key factor in decision-making. Simulations demonstrate that our intelligent handover mechanism delivers substantial energy savings while maintaining service quality at acceptable levels. Specifically, it outperforms standard LTE handover methods by significantly reducing redundant handovers and base station power usage. This research not only contributes to the theoretical understanding of energy-efficient radio network (RN) management but also provides a practical solution for telecom operators aiming to deploy greener LTE infrastructures. Also, leveraging machine learning techniques, the proposed model supports more sustainable operations and helps networks better manage the increasing data demands of the Internet of Things (IoT) era. In summary, our work introduces a novel, intelligent approach to LTE handover management that aligns energy efficiency with service performance. The findings suggest that intelligent, predictive algorithms can play a pivotal role in creating more sustainable and cost-effective wireless networks.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 3","pages":"Article 101599"},"PeriodicalIF":1.7,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143931372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DE-UNeXt: Dual encoder UNeXt for intracranial hemorrhage segmentation on a novel HBU CH dataset","authors":"Jun Wang ,&nbsp;Tiegang Jia ,&nbsp;Lei Liu ,&nbsp;Shuai Wang ,&nbsp;Zhaoqi Wang ,&nbsp;Shanshan Chu","doi":"10.1016/j.jrras.2025.101551","DOIUrl":"10.1016/j.jrras.2025.101551","url":null,"abstract":"<div><h3>Objective:</h3><div>Intracranial hemorrhage(ICH) is one of the highly fatal diseases. Clinically, CT scans are key for doctors to assess the extent of hemorrhage and develop treatment plans. However, there are currently few publicly available pixel-level ICH datasets, which limits the improvement of CT image segmentation performance for intracranial hemorrhage. To address this problem, this paper proposes a new intracranial hemorrhage image dataset, HBU CH, which aims to provide rich, diverse, and realistic intracranial hemorrhage cases. Meanwhile, an end-to-end intracranial hemorrhage segmentation network, DE-UNeXt, is proposed to improve the segmentation accuracy of the lesion parts.</div></div><div><h3>Methods:</h3><div>First, a Dual Encoder Structure (DE) is proposed, where both the original image and its inverted counterpart are input into two parallel encoders. This approach captures object features from two complementary perspectives, enabling the learning of a richer feature representation. Next, a Dual Feature Compensation (DFC) Module is proposed, which combines traditional convolutional methods with contextual Transformers to process and fuse the features extracted from the DE structure in parallel. The DFC module accounts for both local spatial information and global semantic context, thereby enhancing segmentation accuracy and refining lesion boundaries.</div></div><div><h3>Results:</h3><div>Experiments conducted on the proposed HBU CH dataset, as well as two widely used datasets – BCIHM and BHSD – demonstrate that the proposed DE-UNeXt, built on a lightweight network, outperforms the baseline method. Specifically, the Intersection over Union (IoU) and F1 score of DE-UNeXt show improvements of approximately 3.06% and 2.01%, respectively. The code and dataset are available at <span><span>https://github.com/davidsmithwj/DE-UNeXt</span><svg><path></path></svg></span> for further research.</div></div>","PeriodicalId":16920,"journal":{"name":"Journal of Radiation Research and Applied Sciences","volume":"18 3","pages":"Article 101551"},"PeriodicalIF":1.7,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143928573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}