Dear Editor,This letter deals with the autonomous underwater vehicle(AUV)three dimensional(3D)trajectory tracking control chronically suffering from poor accuracy and efficiency in complex hydrodynamics.A state-of-the...Dear Editor,This letter deals with the autonomous underwater vehicle(AUV)three dimensional(3D)trajectory tracking control chronically suffering from poor accuracy and efficiency in complex hydrodynamics.A state-of-the-art predictive adaptive controller(PAC)is proposed with a distinct dual closed-loop structure.展开更多
Due to the complex structural hierarchy,with deeply nested associative relations between entities such as equipment,specifications,and business processes,intelligent power grid engineering is challenging.Meanwhile,lim...Due to the complex structural hierarchy,with deeply nested associative relations between entities such as equipment,specifications,and business processes,intelligent power grid engineering is challenging.Meanwhile,limited by the fragmented data and loss of contextual information,the generated reports are prone to the problems such as content redundancy and omission of critical information,failing to meet the demands of efficient decision-making and accurate management in modern power systems.To address these issues,this paper proposes a knowledge graph(KG)-enhanced framework to automatically generate electric power engineering reports.In the KG construction phase,a feature-fused entity recognition model named BERT-BiLSTM-CRF is adopted to improve the accuracy of entity recognition in scenarios involving power engineering professional terminology,thereby solving the problem of ambiguous entity boundaries in traditional models;then a BERT-attention relation extraction model is proposed to enhance the completeness of extracting complex hierarchical and implicit relations in power grid data.In the report generation phase,an improved Transformer architecture is adopted to accurately transform structured knowledge into natural language reports that comply with engineering specifications,addressing the issue of semantic inconsistency caused by the loss of structural information in existing models.By validating with real-world projects,the results show that the proposed framework significantly outperforms existing baseline models in entity recognition,confirming its superiority and applicability in practical engineering.展开更多
Objectives:The PACIFIC trial established the benefit of durvalumab following chemo-radiotherapy for stage III non-small cell lung cancer(NSCLC).However,the concurrent use of radiotherapy(RT)and durvalumab(PACIFIC-2 tr...Objectives:The PACIFIC trial established the benefit of durvalumab following chemo-radiotherapy for stage III non-small cell lung cancer(NSCLC).However,the concurrent use of radiotherapy(RT)and durvalumab(PACIFIC-2 trial)showed no additional advantage.The PD-RAD study was set up to understand the immunological effects of RT on the tumor microenvironment(TME)to aid in optimizing sequencing of combination therapies.Methods:The PD-RAD trial(ClinicalTrials.gov identifier:NCT03258788)aimed to enroll thirty NSCLC patients receiving radical-intent RT.Tumor biopsies and blood samples were collected pre-RT and at week 2 during RT and analyzed using multiplex immunohistochemistry(mIHC)and high-dimensional mass cytometry(CyTOF),respectively.Results:Paired biopsies were collected from only three patients(Pts 1,3&4)and blood from four patients(Pts 1-4)before the study was closed early during the COVID-19 pandemic.Programmed Death-Ligand 1(PD-L1)expression in the TME was raised in Patient 1,who responded well to treatment,and unaltered in two patients with progressive disease.CyTOF analysis revealed elevated circulating classical monocytes,highest in the patient with a good response.Conclusions:This study underscores the challenges of integrating advanced immune monitoring during RT delivery and did not meet its primary endpoint.The hypothesis-generating findings highlight PD-L1+macrophages in the TME and classical monocytes in the blood as potential immune biomarkers of RT response,but larger studies are needed to validate these observations and characterize the immune changes following curative-intent RT in patients with NSCLC.展开更多
基金supported by the National Natural Science Foundation of China(U24B20183)the Pioneer Leading Goose+X Science and Technology Program of Zhejiang Province(2025C02018)。
文摘Dear Editor,This letter deals with the autonomous underwater vehicle(AUV)three dimensional(3D)trajectory tracking control chronically suffering from poor accuracy and efficiency in complex hydrodynamics.A state-of-the-art predictive adaptive controller(PAC)is proposed with a distinct dual closed-loop structure.
基金supported by State Grid Shanghai Economic Research Institute under Grant No.SGTYHT/23-JS-004.
文摘Due to the complex structural hierarchy,with deeply nested associative relations between entities such as equipment,specifications,and business processes,intelligent power grid engineering is challenging.Meanwhile,limited by the fragmented data and loss of contextual information,the generated reports are prone to the problems such as content redundancy and omission of critical information,failing to meet the demands of efficient decision-making and accurate management in modern power systems.To address these issues,this paper proposes a knowledge graph(KG)-enhanced framework to automatically generate electric power engineering reports.In the KG construction phase,a feature-fused entity recognition model named BERT-BiLSTM-CRF is adopted to improve the accuracy of entity recognition in scenarios involving power engineering professional terminology,thereby solving the problem of ambiguous entity boundaries in traditional models;then a BERT-attention relation extraction model is proposed to enhance the completeness of extracting complex hierarchical and implicit relations in power grid data.In the report generation phase,an improved Transformer architecture is adopted to accurately transform structured knowledge into natural language reports that comply with engineering specifications,addressing the issue of semantic inconsistency caused by the loss of structural information in existing models.By validating with real-world projects,the results show that the proposed framework significantly outperforms existing baseline models in entity recognition,confirming its superiority and applicability in practical engineering.
基金the National Institute for Health and Care Research(NHR)Manchester Biomedical Research Centre(BRC)(NIHR203308,NIHR-BRC-1215-20007)Astra-Zeneca(ESR-14-10711)+2 种基金CRUK RadNet(C19941/A27801)TMI and CFF are the recipient of an NIHR Senior Investigator Award(NIHR205054 and NIHR205061)CTH is supported by the NIHR University College London Hospitals NHS Foundation Trust BRC,the City of London CRUK RadNet and the CRUK Lung Cancer Centre of Excellence.
文摘Objectives:The PACIFIC trial established the benefit of durvalumab following chemo-radiotherapy for stage III non-small cell lung cancer(NSCLC).However,the concurrent use of radiotherapy(RT)and durvalumab(PACIFIC-2 trial)showed no additional advantage.The PD-RAD study was set up to understand the immunological effects of RT on the tumor microenvironment(TME)to aid in optimizing sequencing of combination therapies.Methods:The PD-RAD trial(ClinicalTrials.gov identifier:NCT03258788)aimed to enroll thirty NSCLC patients receiving radical-intent RT.Tumor biopsies and blood samples were collected pre-RT and at week 2 during RT and analyzed using multiplex immunohistochemistry(mIHC)and high-dimensional mass cytometry(CyTOF),respectively.Results:Paired biopsies were collected from only three patients(Pts 1,3&4)and blood from four patients(Pts 1-4)before the study was closed early during the COVID-19 pandemic.Programmed Death-Ligand 1(PD-L1)expression in the TME was raised in Patient 1,who responded well to treatment,and unaltered in two patients with progressive disease.CyTOF analysis revealed elevated circulating classical monocytes,highest in the patient with a good response.Conclusions:This study underscores the challenges of integrating advanced immune monitoring during RT delivery and did not meet its primary endpoint.The hypothesis-generating findings highlight PD-L1+macrophages in the TME and classical monocytes in the blood as potential immune biomarkers of RT response,but larger studies are needed to validate these observations and characterize the immune changes following curative-intent RT in patients with NSCLC.
