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An artificialintelligence-based semi-quantitative diagnostic model for intraabdominal hemorrhage based on focused assessment with sonography for trauma:A large animal experimental study 认领 引用
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作者 Chang Liu Yang Li +11 位作者 Hao Tang Dong Han Yi Zhang Jiangyuan Lai Yusheng Zhang Yao Xiao Yingying Zhang Dongchu Zhao Tao Li Jingqin Fang Yinli Tian Lianyang Zhang 《Chinese Journal of Traumatology》 CAS CSCD 2026年第3期192-201,共10页
Purpose:To develop and validate an artificialintelligence model based on focused assessment with sonography for trauma(FAST)for the semi-quantitative grading of intra-abdominal hemorrhage resulting from blunt abdomina... Purpose:To develop and validate an artificialintelligence model based on focused assessment with sonography for trauma(FAST)for the semi-quantitative grading of intra-abdominal hemorrhage resulting from blunt abdominal trauma,particularly for use in prehospital or resource-limited settings.Methods:Nine Bama miniature pigs,mean weight(31.46±3.73)kg were enrolled.Graded hemorrhage from 0 to 1000 mL was simulated by infusing 100 mL of autologous arterial blood into the peritoneal cavity at each step.The hemorrhage volume was mapped to 3 grades based on total blood volume(estimated at 65 mL/kg):Grade Ⅰ(30%).FAST ultrasound videos were acquired from 6 standard sites:right upper quadrant-1,right upper quadrant-2,left upper quadrant-1,left upper quadrant-2,right pelvic cavity,and left pelvic cavity.The pixel area of hemorrhage was obtained by manually segmenting the frame with the largest fluidcollection using ITK-SNAP,and the corresponding scanning depth was recorded.A linear mixed-effects model was used to assess the impact of scanning depth on pixel area.A deep neural network,incorporating class weighting and dynamic probability threshold optimization,was constructed using a multimodal feature set including animal weight,pixel areas and scanning depths from each site,and the total pixel area.A 3-grade classificationwas performed.The model's performance was evaluated using leave-one-out cross-validation on an animal basis and compared with logistic regression,random forest,gradient boosting decision tree,and support vector machine.Results:A total of 797 raw videos were acquired,with 522 videos comprising 87 data groups(each covering 6 sites)included after screening.As hemorrhage volume increased,heart rate and shock index rose,while systolic blood pressure decreased;at 800 mL of hemorrhage,the shock index was 2.31±0.38.The mixed-effects model revealed a significantnegative correlation between scanning depth and pixel area(β=-2099.00,SE=1041.13,z=-2.02,p=0.044).The proposed model achieved an overall accuracy of 81.19%,outperforming support vector machine(73.77%),gradient boosting decision tree(70.63%),random forest(69.52%),and logistic regression(65.99%).Conclusion:In a porcine model of blunt abdominal trauma,a multimodal artificialintelligence approach based on FAST multi-site pixel area features,combined with a deep neural network optimized by class weighting and dynamic probability thresholds,can achieve semi-quantitative grading of intraabdominal hemorrhage. 展开更多
关键词 Artificialintelligence Trauma Focused assessment with sonography for trauma Intra-abdominal hemorrhage Semi-quantitative diagnosis
Artificial intelligence in scramjet research:Applications and future outlook 认领 引用
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作者 Ye TIAN Yitong ZHAO Jialing LE 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第4期1-3,共3页
1.Introduction Scramjet is pivotal for achieving hypersonic flight,enabling vehicles to operate at speeds exceeding Mach number 5.This engine is crucial for next-generation aerospace systems,including hypersonic missi... 1.Introduction Scramjet is pivotal for achieving hypersonic flight,enabling vehicles to operate at speeds exceeding Mach number 5.This engine is crucial for next-generation aerospace systems,including hypersonic missiles,spaceplanes,and high-speed aircraft.However,the development of scramjet is fraught with significant technical challenges,such as supersonic combustion,thermal management,and dynamic flow control. 展开更多
关键词 thermalmanagement hypersonic missilesspaceplanesand hypersonic flightenabling supersonic combustionthermal managementand dynamic flow control scramjet artificialintelligence hypersonicflight
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Explainable AI for predicting the strength of bio-cemented sands 认领 引用
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作者 Waleed El-Sekelly Muhammad Nouman Amjad Raja Tarek Abdoun 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2026年第2期1552-1569,共18页
The biological stabilization of soil using microbially induced carbonate precipitation(MICP)employs ureolytic bacteria to precipitate calcium carbonate(CaCO3),which binds soil particles,enhancing strength,stiffness,an... The biological stabilization of soil using microbially induced carbonate precipitation(MICP)employs ureolytic bacteria to precipitate calcium carbonate(CaCO3),which binds soil particles,enhancing strength,stiffness,and erosion resistance.The unconfinedcompressive strength(UCS),a key measure of soil strength,is critical in geotechnical engineering as it directly reflectsthe mechanical stability of treated soils.This study integrates explainable artificialintelligence(XAI)with geotechnical insights to model the UCS of MICP-treated sands.Using 517 experimental data points and a combination of various input variables—including median grain size(D50),coefficientof uniformity(Cu),void ratio(e),urea concentration(Mu),calcium concentration(Mc),optical density(OD)of bacterial solution,pH,and total injection volume(Vt)—fivemachine learning(ML)models,including eXtreme gradient boosting(XGBoost),Light gradient boosting machine(LightGBM),random forest(RF),gene expression programming(GEP),and multivariate adaptive regression splines(MARS),were developed and optimized.The ensemble models(XGBoost,LightGBM,and RF)were optimized using the Chernobyl disaster optimizer(CDO),a recently developed metaheuristic algorithm.Of these,LightGBM-CDO achieved the highest accuracy for UCS prediction.XAI techniques like feature importance analysis(FIA),SHapley additive exPlanations(SHAP),and partial dependence plots(PDPs)were also used to investigate the complex non-linear relationships between the input and output variables.The results obtained have demonstrated that the XAI-driven models can enhance the predictive accuracy and interpretability of MICP processes,offering a sustainable pathway for optimizing geotechnical applications. 展开更多
关键词 Microbially induced carbonate precipitation(MICP) Bio-cementation Unconfined compressive strength(UCS) Explainable artificialintelligence(XAI) Optimization
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How Al is revolutionizing the chemical engineering landscape 认领 引用
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作者 Guzhong Chen Zhen Song Zhiwen Qi 《ENGINEERING Chemical Engineering》 SCIE EI CAS CSCD 2026年第6期79-86,共8页
1 Introduction Artificial intelligence(Al)has rapidly emerged as a transformative force across the chemical engineering field.From academia to industry,chemical engineers are leveraging data-driven models and advanced... 1 Introduction Artificial intelligence(Al)has rapidly emerged as a transformative force across the chemical engineering field.From academia to industry,chemical engineers are leveraging data-driven models and advanced algorithms to optimize production,enhance safety,design novel processes and materials,and even generate new scientific insights.In recent years,the number of publications and projects applying machine learning(ML)and AI in process systems engineering(PSE),industrial data science,and chemical engineering more broadly has skyrocketed[1-3]. 展开更多
关键词 optimize productionenhance safetydesign novel processes materialsand process systems engineering pse industrial chemical eng generate new scientific insightsin artificial intelligence al machine learning ml advanced algorithms artificialintelligence
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Introduction to the Special Issue on Advanced Artificial Intelligence and Machine Learning Methods Applied to Energy Systems 认领 引用
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作者 Wei-Chiang Hong Yi Liang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第3期29-33,共5页
Diverse energy and power systems have been playing a significantly critical role in the revolution of sustainable energy supply for the future,which have a great impact on energy resources and efficiencies.Due to the ... Diverse energy and power systems have been playing a significantly critical role in the revolution of sustainable energy supply for the future,which have a great impact on energy resources and efficiencies.Due to the emerging artificial intelligence and machine learning,traditional modeling techniques in these energy systems have met challenges in still leveraging physics model and first principle-based approaches.Moreover,with the rapid development of hardware and computing techniques,new modeling approaches for energy systems have become more and more important for system design,integration,analysis,control,and management. 展开更多
关键词 energy power systems modeling techniques physics model energy resources machinelearning machine learningtraditional energy systems artificialintelligence
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Expert systems:Grounding cross-disciplinary LLMs in reality 认领 引用
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作者 Peng Zheng Guangwen Xu 《Resources Chemicals and Materials》 EI 2026年第1期97-99,共3页
The rapid advancement of artificial intelligence(AI)technologies,particularly the groundbreaking progress of large language models(LLMs)in the field of the natural language processing,has been profoundly reshaping the... The rapid advancement of artificial intelligence(AI)technologies,particularly the groundbreaking progress of large language models(LLMs)in the field of the natural language processing,has been profoundly reshaping the scientific research paradigms. 展开更多
关键词 natural language processinghas scientific research paradigms artificial intelligence ai technologiesparticularly large language models llms artificialintelligence
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Introduction to special issue on AI-empowered biomedical optical imaging:From image reconstruction to biomedical applications 认领 引用
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作者 Junle Qu 《Journal of Innovative Optical Health Sciences》 SCIE EI CSCD 2026年第4期1-3,共3页
The integration of artificial intelligence(AI)with biomedical optical imaging has emerged as one of the most transformative directions in modern biophotonics.From accelerating image reconstruction to enhancing quantit... The integration of artificial intelligence(AI)with biomedical optical imaging has emerged as one of the most transformative directions in modern biophotonics.From accelerating image reconstruction to enhancing quantitative analysis,AI-driven approaches are reshaping how we acquire,process,and interpret optical imaging data across scales—from subcellular structures to whole organisms.Deep learning,in particular,has demonstrated remarkable capacity to address long-standing challenges in computational imaging,including noise suppression,artifact correction,super-resolution reconstruction,and multi-modal data fusion. 展开更多
关键词 artificial intelligence ai optical imaging enhancing quantitative analysisai driven quantitativeanalysis artificialintelligence biomedicalopticalimaging imagerectification biomedical optical imaging
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Capturing hallmarks of cancer through the lens of artificial intelligence 认领 引用
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作者 Mengjiao Wei Bo Xu 《Intelligent Oncology》 CAS 2026年第2期1-2,共2页
The conceptual framework for the hallmarks of cancer,which was first proposed by Hanahan and Weinberg in 20001 and updated in 20112 and 2022,3 with a more recent version published in the spring of 2026,is the foundati... The conceptual framework for the hallmarks of cancer,which was first proposed by Hanahan and Weinberg in 20001 and updated in 20112 and 2022,3 with a more recent version published in the spring of 2026,is the foundational blueprint of modern cancer research.This latest review moves beyond a simple list of tumor traits to organize the immense complexity of cancer into four interconnected dimensions.4 The first dimension concerns acquired capabilities,which are the core functional capabilities cancer cells need to survive and spread. 展开更多
关键词 complexity hallmarksofcancer updateddimensions acquired capabilitieswhich artificialintelligence conceptual framework hallmarks cancerwhich acquiredcapabilities research
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Insights into standards in the Two Sessions 认领 引用
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作者 Jin Jili 《China Standardization》 2026年第3期28-35,共8页
During the Two Sessions,members of the CPPCC National Committee and deputies to the NPC discussed issues of common concern in the standardization field,such as artificial intelligence(AI)and digital technologies,vehic... During the Two Sessions,members of the CPPCC National Committee and deputies to the NPC discussed issues of common concern in the standardization field,such as artificial intelligence(AI)and digital technologies,vehicles and new energy,construction engineering,as well as food and agricultural products.Here,we summarize their insights into standards,to help standards play a bigger role in vigorously promoting the Chinese modernization. 展开更多
关键词 deputies npc foodandagriculturalproducts digitaltechnologies cppcc national committee artificial intelligence ai new energyconstruction constructionengineering artificialintelligence
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CHINA'S AI ACCELERATION:ECONOMIC GROWTH,GLOBAL INFLUENCE,AND THE ROAD AHEAD IN 2026 认领 引用
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作者 Antonio Alvarez 《China Report ASEAN》 2026年第2期62-63,共2页
As 2026 unfolds,the image of an autonomous port in Ningbo loading a U.S.-bound ship encapsulates the transformative power of China’s surge in artificial intelligence(AI).This automation marvel not only symbolizes Ch... As 2026 unfolds,the image of an autonomous port in Ningbo loading a U.S.-bound ship encapsulates the transformative power of China’s surge in artificial intelligence(AI).This automation marvel not only symbolizes China’s economic power but also demonstrates how deeply integrated AI has become into its global competition strategy.Once largely confined to academic research and pilot programs,AI is now embedded in China’s national strategy.The goal:drive productivity,modernize industries,and strengthen its competitive position in global technology markets. 展开更多
关键词 aiacceleration artificial intelligence ai productivity globalinfluence autonomous port economicgrowth artificialintelligence industriemodernization
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POLICIES 认领 引用
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《China's Foreign Trade》 2026年第3期4-5,共2页
China Issues Three-year Plan to Boost AI Integration With Information,Communications Sector China’s Ministry of Industry and Information Technology recent1y re1eased a three-year p1an to accelerate the integration of... China Issues Three-year Plan to Boost AI Integration With Information,Communications Sector China’s Ministry of Industry and Information Technology recent1y re1eased a three-year p1an to accelerate the integration of artificial intelligence(AI)with the country's infor mation and communications sector,setting targets for more autonomous networks. 展开更多
关键词 autonomousnetworks autonomous networks artificial intelligence ai integration informationcommunicationssector threeyearplan artificialintelligence
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From Solo to Symphony:China’s Answer to AI Governance 认领 引用
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作者 Zhang Hui 《China Today》 2026年第8期2-2,共1页
Seventy years ago,a handful of young scholars gathered at Dartmouth College in New Hampshire and first uttered the words“artificial intelligence.”Seven decades later,as algorithms begin to“think”and machines step ... Seventy years ago,a handful of young scholars gathered at Dartmouth College in New Hampshire and first uttered the words“artificial intelligence.”Seven decades later,as algorithms begin to“think”and machines step from the digital world into the physical one,the question is no longer whether AI will reshape human civilization,but who will write the score. 展开更多
关键词 human civilization artificialintelligence ai governance algorithm
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AI与艺术的共生之道 认领 引用
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作者 宋鹭 《疯狂英语（新悦读）》 2026年第3期44-46,78,共3页
主题群:AI与艺术篇幅:317词建议用时:6分钟.1 Reflecting on a favorite piece of art—whether a painting,song,novel or film—often brings about deeply personal connections rooted in emotion,meaning and human experience.Now... 主题群:AI与艺术篇幅:317词建议用时:6分钟.1 Reflecting on a favorite piece of art—whether a painting,song,novel or film—often brings about deeply personal connections rooted in emotion,meaning and human experience.Now,imagine that same work was generated by artificial intelligence.This situation is increasingly likely as AI rapidly evolves to produce works across creative fields like writing,visual art,music and choreography(编舞艺术).A recent survey sought to understand public views on this shift. 展开更多
关键词 art creativefields artificial intelligencethis survey evolution artificialintelligence publicview emotionalconnection
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Jeanologia launches billy,the first artificial intelligence for denim design 认领 引用
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《China Textile》 2026年第2期55-56,共2页
Over 25 years ago,Jeanologia revolutionized the denim industry by introducing laser technology for jean finishing,a solution that replaced manual processes with high impact on both workers’health and the environment,... Over 25 years ago,Jeanologia revolutionized the denim industry by introducing laser technology for jean finishing,a solution that replaced manual processes with high impact on both workers’health and the environment,marking the beginning of a new era in denim production.Today,the Spanish company is once again transforming the sector with the launch of BILLY,the first artificial intelligence developed specifically for the denim industry,capable of extracting precise designs directly from a picture.With this launch,Jeanologia brings AI into one of the most creative and complex phases of denim development:design. 展开更多
关键词 lasertechnology manual processes denimfinishing denimdesign laser technology workershealth artificialintelligence artificial intelligence
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人工智能艺术:平衡技术与创造力 认领 引用
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作者 袁艳丽 《疯狂英语（新悦读）》 2026年第6期55-57,79,共3页
1 Artificial intelligence(AI)has become a debated creative tool in todays art world.When it comes to AI in art,it is essential to examine different types and uses separately.Generative AI,which creates animated digita... 1 Artificial intelligence(AI)has become a debated creative tool in todays art world.When it comes to AI in art,it is essential to examine different types and uses separately.Generative AI,which creates animated digital artworks,deserves special attention.2 Using AI to create art raises important ethical questions that both creators and viewers must consider carefully.One major concern involves intellectual property—who owns the artwork created by AI systems,especially when these systems learn from existing copyrighted works?Another critical issue is bias in training data.If AI learns from biased information,the generated art may strengthen unfair ideas about certain groups or fail to represent them fairly. 展开更多
关键词 ethicalquestions intellectualproperty generativeai bias intellectual property who artificial intelligence ai learn existing co artificialintelligence
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Artificial Intelligence,Real Emotion 认领 引用
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作者 GE LIJUN 《ChinAfrica》 2026年第4期35-35,共1页
Trainers are shaping AI to respond with empathy,gentleness and emotional understanding “AI is my best friend,”24-yearold Yu Yang from the private training sector shared on social media.With its constant availability... Trainers are shaping AI to respond with empathy,gentleness and emotional understanding “AI is my best friend,”24-yearold Yu Yang from the private training sector shared on social media.With its constant availability,efficiency and rationality,AI has become a true source of emotional support for certain users. 展开更多
关键词 AIemotionalsupport empathy emotionalunderstanding gentleness artificialintelligence
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Intelligent multi-channel classificationof microseismic events upon TBM excavation 认领 引用
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作者 Xin Yin Feng Gao +3 位作者 Zitao Chen Yucong Pan Quansheng Liu Shouye Cheng 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2025年第11期7056-7077,共22页
In recent years,tunnel boring machines(TBMs)have been widely used in tunnel construction.Rockbursts,as a dynamic geological disaster,pose a serious threat to the safety and efficienttunneling of TBMs.The microseismic ... In recent years,tunnel boring machines(TBMs)have been widely used in tunnel construction.Rockbursts,as a dynamic geological disaster,pose a serious threat to the safety and efficienttunneling of TBMs.The microseismic monitoring technique provides an effective solution for rockburst warning.However,due to the complexity and variability of the TBM excavation environment,microseismic events induced by rock fracture are often accompanied by interference events,such as electrical noise,TBM vibration,and mechanical knock.This study proposes a multi-channel intelligent classification approach for microseismic events in TBM excavation scenarios,based on double-layer stacking learning,to identify rock fractures.In this approach,decision tree is used as the base classifieron each microseismic channel,while extreme learning machine is employed as the meta-classifierto aggregate all base classifiers.Additionally,mind evolutionary computation is integrated to optimize the built-in hyperparameters of various classifiers.Meanwhile,a comprehensive preprocessing and augmentation flowfor microseismic data has been developed,encompassing feature extraction,dimensionality reduction,outlier detection,and outlier substitution.The results reveal that the multi-channel stacking model,which combines classificationand regression tree and extreme learning machine,achieves optimal global and local generalization performance compared to other multi-channel stacking models and traditional single-channel models.The accuracy,Hamming loss,and Cohen’s kappa are 96.75%,0.0325,and 0.9148,respectively,and the F1-score and AUC on rock fracture events are 0.9366 and 0.9818,respectively.Finally,a generative artificialintelligence-based scheme is invented to enhance the robustness of the model for signal-mixing events. 展开更多
关键词 Tunnel boring machine(TBM) Microseismic monitoring Microseismic classification Stacking learning Generative artificialintelligence Generative adversarial network
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Artificial Intelligence for Power Systems with Renewable Energy 认领 引用
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作者 Luolin Xiong Yang Tang +1 位作者 Kankar Bhattacharya Feng Qian 《Engineering》 SCIE EI CSCD 2025年第9期25-28,共4页
1.Introduction Engineers,policymakers,and governments are currently facing the pressing global challenges of climate change and the energy crisis.To address the continuously increasing demand for energy and mitigate e... 1.Introduction Engineers,policymakers,and governments are currently facing the pressing global challenges of climate change and the energy crisis.To address the continuously increasing demand for energy and mitigate environmental damage,energy conservation and emissions reduction have become strategic priorities for sustainable development[1].Nations worldwide have reached a consensus on reducing carbon emissions and have introduced various policies and actions,such as the carbon peak and carbon neutrality targets proposed by China[2,3]. 展开更多
关键词 sustainable development nations policies actionssuch carbon peak carbon neutrality ta reducing carbon emissions power systems artificialintelligence climate change
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Design and optimization of microalgae photobioreactors for treatment of nitrogen and phosphorus in wastewater 认领 引用
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作者 Shanyu Xie Yuanpeng Wang Qingbiao Li 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2025年第10期222-232,共11页
The use of microalgae to recover nitrogen and phosphorus from wastewater has garnered significant attention,positioning it as one of the most promising and sustainable strategies in modern wastewater treatment.While v... The use of microalgae to recover nitrogen and phosphorus from wastewater has garnered significant attention,positioning it as one of the most promising and sustainable strategies in modern wastewater treatment.While various photobioreactors(PBRs)configurations have been widely applied for microalgae cultivation,limited research has focused on optimizing PBR design specificallyto enhance nitrogen and phosphorus removal efficiency.The high operational costs of wastewater treatment,combined with the inherent variability of microalgal growth,have prompted the search for advanced solutions that improve nitrogen and phosphorus removal while minimizing resource consumption and enabling predictive process control.Recently,the integration of PBR systems with artificialintelligence and machine learning(AI/ML)modeling has emerged as a transformative approach to enhancing nutrient removal,particularly for nitrogen and phosphorus.This study firstsummarizes existing PBR designs tailored for diverse applications,then outlines strategies for system enhancement through the optimization of mixing methods,construction materials,light intensity,and light source configuration.Furthermore,computational fluiddynamics(CFD)and AI/ML modeling are presented as tools to guide the structural design and operational optimization of microalgae-based nitrogen and phosphorus removal processes.Finally,future research directions and key challenges are discussed. 展开更多
关键词 Microalgae Photobioreactor Design Optimization Nitrogen phosphorus removal Artificialintelligence
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Inaugural Statement on the First Issue of SmartSys 认领 引用 被引量：1
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作者 Zhong Lin Wang 《SmartSys》 2025年第1期28-29,共2页
Artificial intelligence has the potential to stand as the cornerstone of human society,which could drive our civilization forward and emerge as a pivotal frontier in the ongoing technological revolution and industrial... Artificial intelligence has the potential to stand as the cornerstone of human society,which could drive our civilization forward and emerge as a pivotal frontier in the ongoing technological revolution and industrial transformation.Amidst profound shifts in the global technological landscape,smart materials,smart devices,and smart systems have become the defining pillars of our era,which will catalyze paradigm shifts in engineering science and reshape the trajectory of modern technology. 展开更多
关键词 technological revolution smartmaterials our civilization smart systems smartdevices industrial transformationamidst artificialintelligence artificial intelligence
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