To accomplish the reliability analyses of the correlation of multi-analytical objectives,an innovative framework of Dimensional Synchronous Modeling(DSM)and correlation analysis is developed based on the stepwise mode...To accomplish the reliability analyses of the correlation of multi-analytical objectives,an innovative framework of Dimensional Synchronous Modeling(DSM)and correlation analysis is developed based on the stepwise modeling strategy,cell array operation principle,and Copula theory.Under this framework,we propose a DSM-based Enhanced Kriging(DSMEK)algorithm to synchronously derive the modeling of multi-objective,and explore an adaptive Copula function approach to analyze the correlation among multiple objectives and to assess the synthetical reliability level.In the proposed DSMEK and adaptive Copula methods,the Kriging model is treated as the basis function of DSMEK model,the Multi-Objective Snake Optimizer(MOSO)algorithm is used to search the optimal values of hyperparameters of basis functions,the cell array operation principle is adopted to establish a whole model of multiple objectives,the goodness of fit is utilized to determine the forms of Copula functions,and the determined Copula functions are employed to perform the reliability analyses of the correlation of multi-analytical objectives.Furthermore,three examples,including multi-objective complex function approximation,aeroengine turbine bladeddisc multi-failure mode reliability analyses and aircraft landing gear system brake temperature reliability analyses,are performed to verify the effectiveness of the proposed methods,from the viewpoints of mathematics and engineering.The results show that the DSMEK and adaptive Copula approaches hold obvious advantages in terms of modeling features and simulation performance.The efforts of this work provide a useful way for the modeling of multi-analytical objectives and synthetical reliability analyses of complex structure/system with multi-output responses.展开更多
Panax notoginseng(P.notoginseng),a valuable traditional Chinese medicine,is the dried root of plants in Acanthopanax gracilistylus family,with the effect of dispersing blood stasis,eliminating swelling and relieving p...Panax notoginseng(P.notoginseng),a valuable traditional Chinese medicine,is the dried root of plants in Acanthopanax gracilistylus family,with the effect of dispersing blood stasis,eliminating swelling and relieving pain.With the development of modern medicine,the active ingredients and mechanisms of P.notoginseng have been gradually revealed.The present paper systematically reviews the chemical composition and biological activities of P.nologinseng,to provide a scientific basis and reference for detailed research on P.nologinseng.展开更多
Based on thermodynamic calculations and continuous rheological extrusion(CRE)technology,Al-Ti-V-B master alloys were designed and prepared.The morphology and the distribution of the refined phases in the master alloys...Based on thermodynamic calculations and continuous rheological extrusion(CRE)technology,Al-Ti-V-B master alloys were designed and prepared.The morphology and the distribution of the refined phases in the master alloys were analyzed by XRD,SEM,and TEM.The effects of master alloy addition and holding time on the microstructure and mechanical properties of A356 alloy were investigated.Under the optimum refiner addition of 0.3wt.%and the holding time of 20 min,the average grain size of the refined A356 alloy is 151.8±9.11μm,89.62%lower than that of original A356 alloy.The tensile strength and elongation of as-cast A356refined alloy are 196.11 MPa and 5.75%,respectively.After T6 treatment,the tensile strength and elongation of A356 refined alloy are 290.1 MPa and 3.09%,respectively.The fracture morphology is characterized by a predominance of along-crystal fracture with a small amount of through-crystal fracture,attributed to the refined grains.Finer grains promote crack path deflection and localized plastic deformation,enhancing energy dissipation and reducing the tendency for brittle fracture.This study provides a novel approach to improving the mechanical properties of A356 alloy through grain refinement using CRE Al-Ti-V-B master alloy.展开更多
BACKGROUND Bile leakage is a common complication following laparoscopic common bile duct exploration(LCBDE)with primary duct closure(PDC).Identifying and analyzing the risk factors associated with bile leakage is cruc...BACKGROUND Bile leakage is a common complication following laparoscopic common bile duct exploration(LCBDE)with primary duct closure(PDC).Identifying and analyzing the risk factors associated with bile leakage is crucial for improving surgical outcomes.AIM To explore the value analysis of common risk factors for bile leakage after LCBDE and PDC,with a focus on strict adherence to indications.METHODS Clinical data of 106 cases undergoing LCBDE+PDC in the Hepatobiliary and Pancreatic Surgery Department(Division 1)of Chuzhou First People’s Hospital from April 2019 to March 2024 were collected.Retrospective and multiple factor regression analysis were conducted on common risk factors for bile leakage.The change in surgical time was analyzed using the cumulative summation(CUSUM)method,and the minimum number of cases required to complete the learning curve for PDC was obtained based on the proposed fitting curve by identifying the CUSUM maximum value.RESULTS Multifactor logistic regression analysis showed that fibrinous inflammation and direct bilirubin/indirect bilirubin were significant independent high-risk factors for postoperative bile leakage(P<0.05).The time to drain removal and length of hospital stay in cases without bile leakage were significantly shorter than in cases with bile leakage(P<0.05),with statistical significance.The CUSUM method indicated that a minimum of 51 cases were required for the surgeon to complete the learning curve(P=0.023).CONCLUSION With a good assessment of duodenal papilla sphincter function,unobstructed bile-pancreatic duct convergence,exact stone clearance,and sufficient surgical experience to complete the learning curve,PDC remains the preferred method for bile duct closure and is worthy of clinical promotion.展开更多
AIM：To evaluate the structural injure patterns in peripapillary retinal fiber layer （pRNFL）, retinal ganglion cell layer （RGCL） and their correlations to visual function in various mitochondrial optic neuropathi...AIM：To evaluate the structural injure patterns in peripapillary retinal fiber layer （pRNFL）, retinal ganglion cell layer （RGCL） and their correlations to visual function in various mitochondrial optic neuropathies （MON） to offer help to their differential diagnosis.METHODS：Totally 32 MON patients （60 eyes） were recruited within 6mo after clinical onsets, including 20 Leber hereditary optic neuropathy （LHON） patients （37eyes）, 12 ethambutol-induced optic neuropathy （EON）patients （23 eyes）, and 41 age-gender matched healthy controls （HC, 82 eyes）. All subjects had pRNFL and RGCL examinations with optic coherence tomography （OCT） and visual function tests.RESULTS：In the early stages of MON, the temporal pRNFL thickness decreased （66.09±22.57μm）, but increased in other quadrants, compared to HC （76.95±14.81μm）. The other quadrants remaining stable for LHON and EON patients besides the second hour sector of pRNFL thickness reduced and the temporal pRNFL decreased （56.78±15.87μm） for EON. Total macular thickness in MON reduced remarkably（279.25±18.90μm; P=0.015）, which mainly occurring in the inner circle （3 mm diameter of circle） and the nasal temporal sectors in the outer circle （5.5 mm diameter of circle）, in contrast to those in HC. RGCL thickness reduced in each sector of the macula （61.90±8.73μm; P≤0.001）. It strongly showed the correlationship of best corrected visual acuity （R=0.50, P=0.0003） and visual field injury （R=0.54,P=0.0002） in MON patients.CONCLUSION：OCT is a potential tool for detecting structural alterations in the optic nerves of various MON. Different types of MON may have different damage patterns.展开更多
Turbine blisks are assembled using blades,disks and casings.They can endure complex loads at a high temperature,high pressure and high speed.The safe operation of assembled structures depends on the reliability of eac...Turbine blisks are assembled using blades,disks and casings.They can endure complex loads at a high temperature,high pressure and high speed.The safe operation of assembled structures depends on the reliability of each component.Monte Carlo(MC)simulation is commonly used to analyze structural reliability,but this method needs to run thousands of computations.In order to assess the clearance reliability of assembled structures in an efficient and precise manner,the novel Kriging-based decomposed-coordinated(DC)(DCNK)approach is proposed by integrating the DC strategy,the Kriging model and the importance sampling-based Markov chain(MCIS)technique.In this method,the DC strategy is used to decompose a multi-objective problem into many single-objective problems.The relationships between these many single-objectives and the overall objective are then coordinated.The Kriging model is applied to establish the limit state functions of the single-objectives and multi-objective problems,while the MCIS method is used to assess the structural assembled clearance reliability.Moreover,a highly nonlinear complex compound function is first utilized to verify the DCNK model from a mathematical perspective.Then,the reliability of an aeroengine high-pressure turbine(HPT)blade-tip radial running clearance(BTRRC)is analyzed to validate the DCNK approach by considering thermo-structural interaction.The analytical results show that the reliability is 0.9976 when the allowance value of the BTTRC is 1.7650×10^(−3)m.Compared with different methodologies(including direct simulation,the classical Kriging model,and the weighted response surface method(WRSM)),the proposed method holds obvious advantages in computing time and precision,as well as simulation efficiency and precision.The efforts of this paper provide a useful approach to analyzing assembled clearance reliability and contribute to the development of structural reliability theory.展开更多
To improve the computational efficiency and accuracy of multi-objective reliability estimation for aerospace engineering structural systems,the Intelligent Vectorial Surrogate Modeling(IVSM)concept is presented by fus...To improve the computational efficiency and accuracy of multi-objective reliability estimation for aerospace engineering structural systems,the Intelligent Vectorial Surrogate Modeling(IVSM)concept is presented by fusing the compact support region,surrogate modeling methods,matrix theory,and Bayesian optimization strategy.In this concept,the compact support region is employed to select effective modeling samples;the surrogate modeling methods are employed to establish a functional relationship between input variables and output responses;the matrix theory is adopted to establish the vector and cell arrays of modeling parameters and synchronously determine multi-objective limit state functions;the Bayesian optimization strategy is utilized to search for the optimal hyperparameters for modeling.Under this concept,the Intelligent Vectorial Neural Network(IVNN)method is proposed based on deep neural network to realize the reliability analysis of multi-objective aerospace engineering structural systems synchronously.The multioutput response function approximation problem and two engineering application cases(i.e.,landing gear brake system temperature and aeroengine turbine blisk multi-failures)are used to verify the applicability of IVNN method.The results indicate that the proposed approach holds advantages in modeling properties and simulation performances.The efforts of this paper can offer a valuable reference for the improvement of multi-objective reliability assessment theory.展开更多
T-cell receptor(TCR)γδ-expressing cells are conserved lymphocytes of innate immunity involved in first-line defense and immune surveillance.TCRγδrecognizes protein/nonprotein ligands without the help of the major ...T-cell receptor(TCR)γδ-expressing cells are conserved lymphocytes of innate immunity involved in first-line defense and immune surveillance.TCRγδrecognizes protein/nonprotein ligands without the help of the major histocompatibility complex(MHC),especially via direct binding to protein ligands,which is dependent primarily on theδchain complementary determining region 3(CDR3δ).However,the mechanism of protein‒antigen recognition by humanγδTCRs remains poorly defined.We hypothesize thatγδTCRs recognize self-proteins expressed ectopically on the cell membrane that are derived from intracellular components under stress.Here,we mapped 16 intercellular self-proteins among 21,000 proteins with a huProteinChip as putative ligands for Vδ1/Vδ2 TCRs,13 for Vδ1 TCRs and 3 for Vδ2 TCRs.Functional tests confirmed that ectopic nucleolin(NCL)is a ligand for the Vδ1 TCR,whereas protein-glutamineγ-glutamyltransferase K(TGM1)is a ligand for the Vδ2 TCR.In the context of radiation exposure,the ectopic expression of intracellular proteins on the tumor cell surface is related to the increased antitumor cytotoxicity ofγδT cells both in vitro and in vivo.In conclusion,the recognition of intracellular proteins that are ectopically expressed on somatic cells by humanγδTCRs is a basic interaction mechanism that enables new types of immune pattern recognition and a novelγδTCR-ligandbased strategy for tumor immunotherapy.展开更多
Phase recovery from intensity-only measurements forms the heart of coherent imaging techniques and holography.In this study,we demonstrate that a neural network can learn to perform phase recovery and holographic imag...Phase recovery from intensity-only measurements forms the heart of coherent imaging techniques and holography.In this study,we demonstrate that a neural network can learn to perform phase recovery and holographic image reconstruction after appropriate training.This deep learning-based approach provides an entirely new framework to conduct holographic imaging by rapidly eliminating twin-image and self-interference-related spatial artifacts.This neural network-based method is fast to compute and reconstructs phase and amplitude images of the objects using only one hologram,requiring fewer measurements in addition to being computationally faster.We validated this method by reconstructing the phase and amplitude images of various samples,including blood and Pap smears and tissue sections.These results highlight that challenging problems in imaging science can be overcome through machine learning,providing new avenues to design powerful computational imaging systems.展开更多
This paper examines the effects of ownership types on firms＇ R＆D intensity and innovation performance, using a sample of 357,857 Chinese firms from 2005-2007. This study finds considerable divergence among Chinese d...This paper examines the effects of ownership types on firms＇ R＆D intensity and innovation performance, using a sample of 357,857 Chinese firms from 2005-2007. This study finds considerable divergence among Chinese domestic enterprises in terms of R＆D intensity and innovation performance. Firms owned by the central government are the key drivers for firms＇ R＆D activities, while local government, private and foreign ownerships are negatively related to both R＆D intensity and innovation performance. Significant divergence within government ownership category and argues that China＇s institutional changes generate varied government ownership groups with different levels of resource endowment, which in turn influence firms＇ R＆D activities.展开更多
γδT cells function as sentinels in early host responses to infections and malignancies.Specifically,γδT cells recognize tumor-associated stress antigens via T-cell receptor(TCR)γδand play important roles in the ...γδT cells function as sentinels in early host responses to infections and malignancies.Specifically,γδT cells recognize tumor-associated stress antigens via T-cell receptor(TCR)γδand play important roles in the antitumor immune response.In this study,we characterized the pattern of the human TCRγδcomplementary determinant region 3(CDR3)repertoire in patients with lung carcinoma(LC)via high-throughput sequencing.The results showed that the diversity of CDR3δwas significantly reduced,and that of CDR3γwas unchanged in LC patients compared with healthy individuals;in addition,LC patients shared significantly more CDR3δsequences with each other than healthy individuals.The CDR3 length distribution and N-addition length distribution did not significantly differ between LC patients and healthy individuals.In addition,the CDR3 repertoire tended to use more Vδ2 and fewer Vδ1 germline gene fragments among LC patients.Moreover,we found a combination of four TCRγδrepertoire features that focus on CDR3δand can be used as a biomarker for LC diagnosis.Our research suggests that the TCRγδCDR3 repertoire changed in LC patients due to the antitumor immune response byγδT cells in vivo,and these changes primarily focus on the amplification of certain tumor-specific CDR3δclones among patients.This study demonstrates the role ofγδT cells from the TCRγδCDR3 repertoire in tumor immunity and lays the foundation for elucidating the mechanism underlying the function ofγδT cells in antitumor immunity.展开更多
Charmonium dissociation is an important probe of the quark–gluon plasma medium in heavy-ion collisions.The magnetic field produced in non-central collisions can affect the charmonia and their dissociation.We study th...Charmonium dissociation is an important probe of the quark–gluon plasma medium in heavy-ion collisions.The magnetic field produced in non-central collisions can affect the charmonia and their dissociation.We study the cc bound state in magnetic field and at finite temperature using the Schrodinger equation.We find that below the dissociation temperature,both the magnetic field and momentum of the charmonia affect the formation or dissociation of the bound state,forming a non-trivial structure.展开更多
Deep neural networks have achieved state-of-the-art performance on many object recognition tasks,but they are vulnerable to small adversarial perturbations.In this paper,several extensions of generative stochastic net...Deep neural networks have achieved state-of-the-art performance on many object recognition tasks,but they are vulnerable to small adversarial perturbations.In this paper,several extensions of generative stochastic networks(GSNs)are proposed to improve the robustness of neural networks to random noise and adversarial perturbations.Experimental results show that compared to normal GSN method,the extensions using adversarial examples,lateral connections and feedforward networks can improve the performance of GSNs by making the models more resistant to overfitting and noise.展开更多
The original restricted Boltzmann machines(RBMs)are extended by replacing the binary visible and hidden variables with clusters of binary units,and a new learning algorithm for training deep Boltzmann machine of this ...The original restricted Boltzmann machines(RBMs)are extended by replacing the binary visible and hidden variables with clusters of binary units,and a new learning algorithm for training deep Boltzmann machine of this new variant is proposed.The sum of binary units of each cluster is approximated by a Gaussian distribution.Experiments demonstrate that the proposed Boltzmann machines can achieve good performance in the MNIST handwritten digital recognition task.展开更多
基金co-supported by the National Natural Science Foundation of China(Nos.52405293,52375237)China Postdoctoral Science Foundation(No.2024M754219)Shaanxi Province Postdoctoral Research Project Funding,China。
文摘To accomplish the reliability analyses of the correlation of multi-analytical objectives,an innovative framework of Dimensional Synchronous Modeling(DSM)and correlation analysis is developed based on the stepwise modeling strategy,cell array operation principle,and Copula theory.Under this framework,we propose a DSM-based Enhanced Kriging(DSMEK)algorithm to synchronously derive the modeling of multi-objective,and explore an adaptive Copula function approach to analyze the correlation among multiple objectives and to assess the synthetical reliability level.In the proposed DSMEK and adaptive Copula methods,the Kriging model is treated as the basis function of DSMEK model,the Multi-Objective Snake Optimizer(MOSO)algorithm is used to search the optimal values of hyperparameters of basis functions,the cell array operation principle is adopted to establish a whole model of multiple objectives,the goodness of fit is utilized to determine the forms of Copula functions,and the determined Copula functions are employed to perform the reliability analyses of the correlation of multi-analytical objectives.Furthermore,three examples,including multi-objective complex function approximation,aeroengine turbine bladeddisc multi-failure mode reliability analyses and aircraft landing gear system brake temperature reliability analyses,are performed to verify the effectiveness of the proposed methods,from the viewpoints of mathematics and engineering.The results show that the DSMEK and adaptive Copula approaches hold obvious advantages in terms of modeling features and simulation performance.The efforts of this work provide a useful way for the modeling of multi-analytical objectives and synthetical reliability analyses of complex structure/system with multi-output responses.
文摘Panax notoginseng(P.notoginseng),a valuable traditional Chinese medicine,is the dried root of plants in Acanthopanax gracilistylus family,with the effect of dispersing blood stasis,eliminating swelling and relieving pain.With the development of modern medicine,the active ingredients and mechanisms of P.notoginseng have been gradually revealed.The present paper systematically reviews the chemical composition and biological activities of P.nologinseng,to provide a scientific basis and reference for detailed research on P.nologinseng.
基金supported by the National Key Research and Development Program of China (Grant No.2022YFB3706801)the National Natural Science Foundation of China (Grant Nos.U2341253,52371019,U2241232)+2 种基金the Dalian High-level Talents Innovation Support Program (Grant No.2021RD06)the Applied Basic Research Program of Liaoning Province (Grant No.2022JH2/101300003)the Natural Science Foundation of Liaoning Province (Grant Nos.2022-BS-262,JYTMS20230031)。
文摘Based on thermodynamic calculations and continuous rheological extrusion(CRE)technology,Al-Ti-V-B master alloys were designed and prepared.The morphology and the distribution of the refined phases in the master alloys were analyzed by XRD,SEM,and TEM.The effects of master alloy addition and holding time on the microstructure and mechanical properties of A356 alloy were investigated.Under the optimum refiner addition of 0.3wt.%and the holding time of 20 min,the average grain size of the refined A356 alloy is 151.8±9.11μm,89.62%lower than that of original A356 alloy.The tensile strength and elongation of as-cast A356refined alloy are 196.11 MPa and 5.75%,respectively.After T6 treatment,the tensile strength and elongation of A356 refined alloy are 290.1 MPa and 3.09%,respectively.The fracture morphology is characterized by a predominance of along-crystal fracture with a small amount of through-crystal fracture,attributed to the refined grains.Finer grains promote crack path deflection and localized plastic deformation,enhancing energy dissipation and reducing the tendency for brittle fracture.This study provides a novel approach to improving the mechanical properties of A356 alloy through grain refinement using CRE Al-Ti-V-B master alloy.
基金Supported by the Wannan Medical College Teaching Hospital Special Application for Scientific Research,No.WK2023JXYY036the Anhui Provincial Translational Clinical Medical Research Special Application,No.202204295107020062.
文摘BACKGROUND Bile leakage is a common complication following laparoscopic common bile duct exploration(LCBDE)with primary duct closure(PDC).Identifying and analyzing the risk factors associated with bile leakage is crucial for improving surgical outcomes.AIM To explore the value analysis of common risk factors for bile leakage after LCBDE and PDC,with a focus on strict adherence to indications.METHODS Clinical data of 106 cases undergoing LCBDE+PDC in the Hepatobiliary and Pancreatic Surgery Department(Division 1)of Chuzhou First People’s Hospital from April 2019 to March 2024 were collected.Retrospective and multiple factor regression analysis were conducted on common risk factors for bile leakage.The change in surgical time was analyzed using the cumulative summation(CUSUM)method,and the minimum number of cases required to complete the learning curve for PDC was obtained based on the proposed fitting curve by identifying the CUSUM maximum value.RESULTS Multifactor logistic regression analysis showed that fibrinous inflammation and direct bilirubin/indirect bilirubin were significant independent high-risk factors for postoperative bile leakage(P<0.05).The time to drain removal and length of hospital stay in cases without bile leakage were significantly shorter than in cases with bile leakage(P<0.05),with statistical significance.The CUSUM method indicated that a minimum of 51 cases were required for the surgeon to complete the learning curve(P=0.023).CONCLUSION With a good assessment of duodenal papilla sphincter function,unobstructed bile-pancreatic duct convergence,exact stone clearance,and sufficient surgical experience to complete the learning curve,PDC remains the preferred method for bile duct closure and is worthy of clinical promotion.
基金Supported by the National High Technology Research and Development Program of China(863 Program,No.2015AA020511)
文摘AIM：To evaluate the structural injure patterns in peripapillary retinal fiber layer （pRNFL）, retinal ganglion cell layer （RGCL） and their correlations to visual function in various mitochondrial optic neuropathies （MON） to offer help to their differential diagnosis.METHODS：Totally 32 MON patients （60 eyes） were recruited within 6mo after clinical onsets, including 20 Leber hereditary optic neuropathy （LHON） patients （37eyes）, 12 ethambutol-induced optic neuropathy （EON）patients （23 eyes）, and 41 age-gender matched healthy controls （HC, 82 eyes）. All subjects had pRNFL and RGCL examinations with optic coherence tomography （OCT） and visual function tests.RESULTS：In the early stages of MON, the temporal pRNFL thickness decreased （66.09±22.57μm）, but increased in other quadrants, compared to HC （76.95±14.81μm）. The other quadrants remaining stable for LHON and EON patients besides the second hour sector of pRNFL thickness reduced and the temporal pRNFL decreased （56.78±15.87μm） for EON. Total macular thickness in MON reduced remarkably（279.25±18.90μm; P=0.015）, which mainly occurring in the inner circle （3 mm diameter of circle） and the nasal temporal sectors in the outer circle （5.5 mm diameter of circle）, in contrast to those in HC. RGCL thickness reduced in each sector of the macula （61.90±8.73μm; P≤0.001）. It strongly showed the correlationship of best corrected visual acuity （R=0.50, P=0.0003） and visual field injury （R=0.54,P=0.0002） in MON patients.CONCLUSION：OCT is a potential tool for detecting structural alterations in the optic nerves of various MON. Different types of MON may have different damage patterns.
基金This paper is supported by the National Natural Science Foundation of China(51875465)the Civil Aircraft Scientific Research Project.The authors would like to thank their generous supports.
文摘Turbine blisks are assembled using blades,disks and casings.They can endure complex loads at a high temperature,high pressure and high speed.The safe operation of assembled structures depends on the reliability of each component.Monte Carlo(MC)simulation is commonly used to analyze structural reliability,but this method needs to run thousands of computations.In order to assess the clearance reliability of assembled structures in an efficient and precise manner,the novel Kriging-based decomposed-coordinated(DC)(DCNK)approach is proposed by integrating the DC strategy,the Kriging model and the importance sampling-based Markov chain(MCIS)technique.In this method,the DC strategy is used to decompose a multi-objective problem into many single-objective problems.The relationships between these many single-objectives and the overall objective are then coordinated.The Kriging model is applied to establish the limit state functions of the single-objectives and multi-objective problems,while the MCIS method is used to assess the structural assembled clearance reliability.Moreover,a highly nonlinear complex compound function is first utilized to verify the DCNK model from a mathematical perspective.Then,the reliability of an aeroengine high-pressure turbine(HPT)blade-tip radial running clearance(BTRRC)is analyzed to validate the DCNK approach by considering thermo-structural interaction.The analytical results show that the reliability is 0.9976 when the allowance value of the BTTRC is 1.7650×10^(−3)m.Compared with different methodologies(including direct simulation,the classical Kriging model,and the weighted response surface method(WRSM)),the proposed method holds obvious advantages in computing time and precision,as well as simulation efficiency and precision.The efforts of this paper provide a useful approach to analyzing assembled clearance reliability and contribute to the development of structural reliability theory.
基金supported by the National Natural Science Foundation of China(No.51875465)the Shaanxi Province Postdoctoral Research Project Funding,Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University(No.CX2023002)+1 种基金the Civil Aircraft Scientific Research Projectthe Fund of Shanghai Engineering Research Center of Civil Aircraft Health Monitoring(No.GCZX-2022-01).
文摘To improve the computational efficiency and accuracy of multi-objective reliability estimation for aerospace engineering structural systems,the Intelligent Vectorial Surrogate Modeling(IVSM)concept is presented by fusing the compact support region,surrogate modeling methods,matrix theory,and Bayesian optimization strategy.In this concept,the compact support region is employed to select effective modeling samples;the surrogate modeling methods are employed to establish a functional relationship between input variables and output responses;the matrix theory is adopted to establish the vector and cell arrays of modeling parameters and synchronously determine multi-objective limit state functions;the Bayesian optimization strategy is utilized to search for the optimal hyperparameters for modeling.Under this concept,the Intelligent Vectorial Neural Network(IVNN)method is proposed based on deep neural network to realize the reliability analysis of multi-objective aerospace engineering structural systems synchronously.The multioutput response function approximation problem and two engineering application cases(i.e.,landing gear brake system temperature and aeroengine turbine blisk multi-failures)are used to verify the applicability of IVNN method.The results indicate that the proposed approach holds advantages in modeling properties and simulation performances.The efforts of this paper can offer a valuable reference for the improvement of multi-objective reliability assessment theory.
基金supported by the CAMS Initiative for Innovative Medicine(2021-I2M-1-035 and 2021-I2M-1-005)the National Natural Science Foundation of China(32270915,U20A20374,82071791,82103319 and 32300745)+2 种基金the Beijing Municipal Commission of Science and Technology Fund for Innovative Drugs(Z221100007922040)the National Key Research and Development Program of China(2022YFC3602004)the Changzhou Sci&Tech Program(CJ20220185)。
文摘T-cell receptor(TCR)γδ-expressing cells are conserved lymphocytes of innate immunity involved in first-line defense and immune surveillance.TCRγδrecognizes protein/nonprotein ligands without the help of the major histocompatibility complex(MHC),especially via direct binding to protein ligands,which is dependent primarily on theδchain complementary determining region 3(CDR3δ).However,the mechanism of protein‒antigen recognition by humanγδTCRs remains poorly defined.We hypothesize thatγδTCRs recognize self-proteins expressed ectopically on the cell membrane that are derived from intracellular components under stress.Here,we mapped 16 intercellular self-proteins among 21,000 proteins with a huProteinChip as putative ligands for Vδ1/Vδ2 TCRs,13 for Vδ1 TCRs and 3 for Vδ2 TCRs.Functional tests confirmed that ectopic nucleolin(NCL)is a ligand for the Vδ1 TCR,whereas protein-glutamineγ-glutamyltransferase K(TGM1)is a ligand for the Vδ2 TCR.In the context of radiation exposure,the ectopic expression of intracellular proteins on the tumor cell surface is related to the increased antitumor cytotoxicity ofγδT cells both in vitro and in vivo.In conclusion,the recognition of intracellular proteins that are ectopically expressed on somatic cells by humanγδTCRs is a basic interaction mechanism that enables new types of immune pattern recognition and a novelγδTCR-ligandbased strategy for tumor immunotherapy.
文摘Phase recovery from intensity-only measurements forms the heart of coherent imaging techniques and holography.In this study,we demonstrate that a neural network can learn to perform phase recovery and holographic image reconstruction after appropriate training.This deep learning-based approach provides an entirely new framework to conduct holographic imaging by rapidly eliminating twin-image and self-interference-related spatial artifacts.This neural network-based method is fast to compute and reconstructs phase and amplitude images of the objects using only one hologram,requiring fewer measurements in addition to being computationally faster.We validated this method by reconstructing the phase and amplitude images of various samples,including blood and Pap smears and tissue sections.These results highlight that challenging problems in imaging science can be overcome through machine learning,providing new avenues to design powerful computational imaging systems.
基金This research is supported by National Natural Science Foundation of China （No. 71373010）.
文摘This paper examines the effects of ownership types on firms＇ R＆D intensity and innovation performance, using a sample of 357,857 Chinese firms from 2005-2007. This study finds considerable divergence among Chinese domestic enterprises in terms of R＆D intensity and innovation performance. Firms owned by the central government are the key drivers for firms＇ R＆D activities, while local government, private and foreign ownerships are negatively related to both R＆D intensity and innovation performance. Significant divergence within government ownership category and argues that China＇s institutional changes generate varied government ownership groups with different levels of resource endowment, which in turn influence firms＇ R＆D activities.
基金by the National Natural Science Foundation of China(31500725,81673010,91542117,81471574,31471016)CAMS Central Public Welfare Scientific Research Institute Basal Research Expenses(2016ZX310180-5 and 2017PT31004)+2 种基金the CAMS Initiative for Innovative Medicine(2016-I2M-1-008)the National Key Research and Development Program of China(2016YFA0101001,2016YFC0903900)Peking Union Medical College Foundation(No.3332015111).
文摘γδT cells function as sentinels in early host responses to infections and malignancies.Specifically,γδT cells recognize tumor-associated stress antigens via T-cell receptor(TCR)γδand play important roles in the antitumor immune response.In this study,we characterized the pattern of the human TCRγδcomplementary determinant region 3(CDR3)repertoire in patients with lung carcinoma(LC)via high-throughput sequencing.The results showed that the diversity of CDR3δwas significantly reduced,and that of CDR3γwas unchanged in LC patients compared with healthy individuals;in addition,LC patients shared significantly more CDR3δsequences with each other than healthy individuals.The CDR3 length distribution and N-addition length distribution did not significantly differ between LC patients and healthy individuals.In addition,the CDR3 repertoire tended to use more Vδ2 and fewer Vδ1 germline gene fragments among LC patients.Moreover,we found a combination of four TCRγδrepertoire features that focus on CDR3δand can be used as a biomarker for LC diagnosis.Our research suggests that the TCRγδCDR3 repertoire changed in LC patients due to the antitumor immune response byγδT cells in vivo,and these changes primarily focus on the amplification of certain tumor-specific CDR3δclones among patients.This study demonstrates the role ofγδT cells from the TCRγδCDR3 repertoire in tumor immunity and lays the foundation for elucidating the mechanism underlying the function ofγδT cells in antitumor immunity.
基金Supported by Guangdong Major Project of Basic and Applied Basic Research (2020B0301030008)NSFC (11905006, 12035007)
文摘Charmonium dissociation is an important probe of the quark–gluon plasma medium in heavy-ion collisions.The magnetic field produced in non-central collisions can affect the charmonia and their dissociation.We study the cc bound state in magnetic field and at finite temperature using the Schrodinger equation.We find that below the dissociation temperature,both the magnetic field and momentum of the charmonia affect the formation or dissociation of the bound state,forming a non-trivial structure.
文摘Deep neural networks have achieved state-of-the-art performance on many object recognition tasks,but they are vulnerable to small adversarial perturbations.In this paper,several extensions of generative stochastic networks(GSNs)are proposed to improve the robustness of neural networks to random noise and adversarial perturbations.Experimental results show that compared to normal GSN method,the extensions using adversarial examples,lateral connections and feedforward networks can improve the performance of GSNs by making the models more resistant to overfitting and noise.
文摘The original restricted Boltzmann machines(RBMs)are extended by replacing the binary visible and hidden variables with clusters of binary units,and a new learning algorithm for training deep Boltzmann machine of this new variant is proposed.The sum of binary units of each cluster is approximated by a Gaussian distribution.Experiments demonstrate that the proposed Boltzmann machines can achieve good performance in the MNIST handwritten digital recognition task.
