Background:Giant cell arteritis(GCA),the most common systemic vasculitis affecting elderly individuals,currently lacks specific therapies.This study aimed to systematically identify therapeutic targets for GCA through...Background:Giant cell arteritis(GCA),the most common systemic vasculitis affecting elderly individuals,currently lacks specific therapies.This study aimed to systematically identify therapeutic targets for GCA through integration of large-scale multi-omics datasets.Methods:We constructed a multi-stage analytical framework encompassing 32 proteomic datasets(covering 2914 unique plasma proteins)and 6 transcriptomic datasets.Multi-omics integration strategies,including two-sample Mendelian randomization,colocalization analysis,and functional enrichment analysis,were employed to identify and validate causal relationships between candidate targets and GCA risk across 4 independent European-ancestry GCA cohorts.Single-cell RNA sequencing analysis of peripheral blood mononuclear cells from untreated GCA patients was performed to characterize hub gene-immune cell relationships.Results:We identified 43 plasma proteins causally associated with GCA[false discovery rate(FDR)<0.05],with 17 representing novel therapeutic targets.Through dual validation using proteome-wide association studies and transcriptome-wide association studies,we identified 13 high-confidence candidate targets with distinct tissue-specific expression patterns.Unc-51 like kinase 3(ULK3)emerged as the strongest protective factor(odds ratio=0.47,95%confidence interval:0.37–0.71)through autophagy regulation,while SLAMF7 represents an immediate drug repositioning opportunity as the target of food and drug administration-approved elotuzumab.Five targets have existing approved drugs(SLAMF7,ICAM1,IL18,IL6ST,CTSS).Single-cell analysis revealed profound disruption of hub gene-immune cell relationships in untreated GCA patients,with cell-type-specific alterations in inflammatory gene expression,and TYMP as the most critical hub gene.Conclusions:This study provides a clinically-actionable atlas of 43 potential therapeutic targets in GCA,identifying novel mechanisms including autophagy modulation and metabolic reprogramming,with immediate drug repositioning opportunities and precision medicine strategies based on tissue-specific and cell-type-specific expression patterns.These findings require experimental validation before clinical translation.展开更多
In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order relia...In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order reliability methods exhibit limited accuracy in highly nonlinear scenarios.To overcome these challenges,a novel reliability analysis strategy based on a multimodal differential evolution algorithm and a hypersphere integration method is proposed.Initially,the penalty function method is employed to reformulate the MPP search problem as a conditionally constrained optimization task.Subsequently,a differential evolution algorithm incorporating a population delineation strategy is utilized to identify all MPPs.Finally,a paraboloid equation is constructed based on the curvature of the limit-state function at the MPPs,and the failure probability of the structure is calculated by using the hypersphere integration method.The localization effectiveness of the MPPs is compared through multiple numerical cases and two engineering examples,with accuracy comparisons of failure probabilities against the first-order reliability method(FORM)and the secondorder reliability method(SORM).The results indicate that the method effectively identifies existing MPPs and achieves higher solution precision.展开更多
Objective To systematically characterize the developmental trajectory and interdisciplinary integration of intelligent diagnosis in traditional Chinese medicine(TCM)through quantitative topic evolution analysis,we add...Objective To systematically characterize the developmental trajectory and interdisciplinary integration of intelligent diagnosis in traditional Chinese medicine(TCM)through quantitative topic evolution analysis,we addressed the fragmentation of existing research and clarified the long-term research structure and evolutionary patterns of the field.Methods A topic evolution analysis was performed on Chinese-language literature pertaining to intelligent diagnosis in TCM.Publications were retrieved from the China National Knowledge Infrastructure(CNKI),Wanfang Data,and China Science and Technology Journal Database(VIP),covering the period from database inception to July 3,2025.A hybrid segmentation approach,based on cumulative publication growth trends and inflection point detection,was applied to divide the research timeline into distinct stages.Subsequently,the latent Dirichlet allocation(LDA)model was used to extract research topics,followed by alignment and evolutionary analysis of topics across different stages.Results A total of 3919 publications published between 2003 and 2025 were included,and the research trajectory was divided into five stages based on data-driven breakpoint detection.The field exhibited a clear evolutionary shift from early rule-based systems and tonguepulse image and signal analysis(2006–2010),to machine-learning-based syndrome and prescription modeling(2011–2015),followed by deep-learning-driven pattern recognition and formula association(2016–2020).Since 2021,research has increasingly emphasized knowledge-graph construction,multimodal integration,and intelligent clinical decision-support systems,with recent studies(2024–2025)showing the emergence of large language models and agent-based diagnostic frameworks.Topic evolution analysis further revealed sustained cross-stage continuity in syndrome modeling and prescription association analysis,alongside the progressive consolidation of integrated intelligent diagnostic platforms.Conclusion By identifying key technological transitions and persistent core research themes,our findings offer a structured reference framework for the design of intelligent diagnostic systems,the construction of knowledge-driven clinical decision-support tools,and the alignment of AI models with TCM diagnostic logic.Importantly,the stage-based evolutionary insights derived from this analysis can inform future methodological choices,improve model interpretability and clinical applicability,and support the translation of intelligent TCM diagnosis from experimental research to real-world clinical practice.展开更多
[Objective]This study aims to investigate the multi-body hydrodynamic interaction mechanisms during offshore lifting operations of aquaculture net cages in wind-fishery integration systems.By integrating numerical sim...[Objective]This study aims to investigate the multi-body hydrodynamic interaction mechanisms during offshore lifting operations of aquaculture net cages in wind-fishery integration systems.By integrating numerical simulations and dynamic analysis methods,this study systematically investigates the coupled dynamic response characteristics during the cage-carrier vessel separation process to reveal its dynamic evolution patterns and key influence mechanisms.[Method]Based on potential flow theory,a fully coupled dynamic analysis model of crane vessel-net cage-semi-submersible barge was established for a marine ranch project in Guangdong.The complete lifting process was dynamically simulated using SESAM software.Five typical operating sea states were configured to investigate the influence of wave parameters on the system's motion response under combined wave-current-wind actions.[Result]The results demonstrate that wave period dominates the system stability.Under short-period conditions,the system maintains stable motion with relatively small horizontal relative displacements,while long-period conditions excite low-frequency resonance,leading to significant slow-drift motions.Vertical response analysis reveals that long-period waves cause severe relative displacement fluctuations between the cage and semi-submersible vessel,with actual displacement amplitudes doubling the preset safety target of 2.045 m.Quantitative analysis further indicates that when significant wave height increases from 1.0 m to 1.5 m,the actual displacement amplitude increases by approximately 20%relative to the target displacement of 2.045 m,demonstrating that its influence is significantly weaker than the displacement variations induced by wave period changes.The complete dynamic simulation successfully captures the continuous dynamic response characteristics during the lifting process.[Conclusion]This research clarifies the influence mechanisms of wave parameters on the cage lifting process,identifying wave period as the crucial factor for operational safety.An operation window assessment method incorporating multi-body coupling effects is established,proposing a safety criterion with peak period not exceeding six seconds as the core requirement.The findings provide theoretical foundation for safe installation of marine ranch net cages and offer valuable references for similar offshore lifting operations.展开更多
To achieve efficient and refined thermal environment simulations for single-phase and two-phase flows in aircraft cabins,we propose an integrated analysis method.This approach enables rapid coupled heat transfer calcu...To achieve efficient and refined thermal environment simulations for single-phase and two-phase flows in aircraft cabins,we propose an integrated analysis method.This approach enables rapid coupled heat transfer calculations among single-phase flow,two-phase flow,and solids within a single time step.For single-phase fluid and solid equipment,a fast numerical algorithm for natural convection is developed using a loosely coupled strategy,dividing the single-phase flow into developmental stages for efficient temperature field computation.For two-phase flow and the fuel tank wall,a transient heat transfer model is constructed at the gas-liquid-solid boundary,facilitating fast thermal analysis.These methods are unified for integrated simulation of the cabin’s thermal environment.Validation based on two-dimensional models demonstrates a speedup by a factor of 7.9,while maintaining an average temperature error of less than 1%at two-phase nodes.The method’s robustness is confirmed under various high-temperature boundary conditions.展开更多
The 13-node quadrilateral and 39-node hexahedral cubic serendipity elements produce nodally integrated positive-definite lumped heat capacity matrices in higher-order finite element analysis.However,these elements dis...The 13-node quadrilateral and 39-node hexahedral cubic serendipity elements produce nodally integrated positive-definite lumped heat capacity matrices in higher-order finite element analysis.However,these elements display severe convergence deterioration in explicit transient heat conduction analysis with lumped heat ca-pacity matrices.This convergence decay is due to the violation of variational integration consistency by the standard Galerkin formulation with lumped heat capacity matrices.This issue is resolved by introducing the boundary-enhanced Galerkin weak form that incorporates the elemental boundary contribution in the discrete finite element formulation.Subsequently,it is theoretically proven that a direct nodal integration identically fulfills the variational integration consistency in the context of the boundary-enhanced Galerkin weak form.The proposed variationally consistent nodal integration therefore enables optimal convergence for explicit transient heat conduction analysis with lumped heat capacity matrices.The efficacy of the proposed variationally con-sistent nodal integration formulation for the 13-node quadrilateral and 39-node hexahedral cubic elements is thoroughly demonstrated via numerical examples.展开更多
The integration of multi-omic liquid biopsies with artificial intelligence(AI)represents a rapidly evolving frontier in early cancer detection,offering the potential to enhance personalized medicine and improve patien...The integration of multi-omic liquid biopsies with artificial intelligence(AI)represents a rapidly evolving frontier in early cancer detection,offering the potential to enhance personalized medicine and improve patient outcomes.This review explores the current state and emerging directions of this approach,focusing on the synergistic value of combining genomics,epigenomics,transcriptomics,proteomics,and metabolomics with AIdriven analytics.We discuss advances in multi-analyte blood tests such as CancerSEEK,which have demonstrated promising multi-cancer detection capabilities in early studies,as well as efforts to integrate liquid biopsy data with imaging modalities to improve diagnostic performance.The review also highlights ongoing challenges,including the need for greater analytical sensitivity,improved specificity for early-stage disease,standardization of workflows,and harmonization with existing screening modalities.We outline the prospective—but still largely investigational—impact of these technologies on cancer management,including early detection,treatment monitoring,and minimal residual disease assessment,along with their potential economic implications.Ultimately,we envision a future in which multi-omic liquid biopsies integrated with AI may contribute to more effective,noninvasive cancer detection strategies,while recognizing that substantial validation,regulatory approval,and health-system integration are required before widespread clinical adoption can occur.展开更多
Mango(Mangifera indica L.)is one of the main economic crops in Hainan,China,prized for its distinctive flavor and high nutritional value.It is also rich in health-promoting antioxidants such as vitamin C and flavonoid...Mango(Mangifera indica L.)is one of the main economic crops in Hainan,China,prized for its distinctive flavor and high nutritional value.It is also rich in health-promoting antioxidants such as vitamin C and flavonoids.Enhanced ultraviolet-B(UV—B)radiation,a growing global environmental concern,alters plant antioxidant systems,with increased flavonoid accumulation as a common adaptive response.However,its effects on mango fruit remain largely unexplored.To investigate the antioxidant responses of mango to enhanced UV-B radiation and identify key responsive flavonoid compounds and regulatory genes,we exposed‘Tainong 1’mango fruits growing under natural light to 96 kJ·m^(-2)·d^(-1)of UV-B radiation to simulate high UV-B conditions.Treated fruits were smaller in size and had a pulp of a more intense yellow colour.Further,malondialdehyde content in treated fruits was higher during the phase of rapid fruit enlargement.Additionally,treated fruits showed increased sugar-acid ratios,total phenol,total flavonoid,carotenoid,and ascorbic acid contents.Furthermore,they showed significantly enhanced antioxidant activity,as measured by the FRAP,ABTS,and DPPH assays.Extensive targeted metabolomic-analysis identified flavonoids as the largest category of compounds differentially expressed in treated and control groups.Quantitative metabolomics of flavonoids identified hyperoside,quercimeritrin,and(-)-catechin gallate as the key flavonoid metabolites responsive to UV-B treatment.Transcriptome analysis revealed an enrichment of the flavonoid biosynthesis pathway,with most associated differentially expressed genes showing upregulation.Furthermore,qRT-PCR analysis confirmed that the expression of the genes MiCHS7,MiCHI1,MiCHI2,MiFLS,MiF3H2,and MiF3H3 correlated with changes in key flavonoid metabolites.Indeed,correlation analysis indicated that MiCHS7,MiCHI1,MiFLS,and MiF3H3 are potential key genes involved in flavonoid accumulation under UV-B treatment.Thus,our study provides a theoretical basis for breeding for new resilient varieties and developing UV-B-resistant mango cultivation techniques.展开更多
The rapid growth of biomedical data,particularly multi-omics data including genomes,transcriptomics,proteomics,metabolomics,and epigenomics,medical research and clinical decision-making confront both new opportunities...The rapid growth of biomedical data,particularly multi-omics data including genomes,transcriptomics,proteomics,metabolomics,and epigenomics,medical research and clinical decision-making confront both new opportunities and obstacles.The huge and diversified nature of these datasets cannot always be managed using traditional data analysis methods.As a consequence,deep learning has emerged as a strong tool for analysing numerous omics data due to its ability to handle complex and non-linear relationships.This paper explores the fundamental concepts of deep learning and how they are used in multi-omics medical data mining.We demonstrate how autoencoders,variational autoencoders,multimodal models,attention mechanisms,transformers,and graph neural networks enable pattern analysis and recognition across all omics data.Deep learning has been found to be effective in illness classification,biomarker identification,gene network learning,and therapeutic efficacy prediction.We also consider critical problems like as data quality,model explainability,whether findings can be repeated,and computational power requirements.We now consider future elements of combining omics with clinical and imaging data,explainable AI,federated learning,and real-time diagnostics.Overall,this study emphasises the need of collaborating across disciplines to advance deep learning-based multi-omics research for precision medicine and comprehending complicated disorders.展开更多
In the structural reliability analysis,the first-order reliability method(FORM)often yields significant errors when addressing nonlinear problems.Although the second-order reliability method(SORM)can provide higher ac...In the structural reliability analysis,the first-order reliability method(FORM)often yields significant errors when addressing nonlinear problems.Although the second-order reliability method(SORM)can provide higher accuracy,the additional computation of the Hessian matrix leads to lower computational efficiency.Additionally,when the dimensionality of the random variables is high,the approximation formula of SORM can result in larger errors.To address these issues,a structural reliability analysis method based on Kriging and spherical cap area integral is proposed.Firstly,this method integrates FORM with the quasi-Newton algorithm Broyden-Fletcher-Goldfarb-Shanno(BFGS),trains the Kriging model by using sample points from the algorithm’s iteration process,and combines the Kriging model with gradient information to approximate the Hessian matrix.Then,the failure surface is approximated as a rotating paraboloid,utilizing the spherical cap to replace the complex surface.For the n-dimensional case,the hyperspherical cap area expression is combined with the integral method to calculate the failure probability.Finally,the method is validated through three examples,demonstrating improved computational accuracy and efficiency compared to traditional methods.展开更多
This paper presents an improved precise integration algorithm fortransient analysis of heat transfer and some other problems. Theoriginal precise integration method is improved by means of the inve-rse accuracy analys...This paper presents an improved precise integration algorithm fortransient analysis of heat transfer and some other problems. Theoriginal precise integration method is improved by means of the inve-rse accuracy analysis so that the parameter N, which has been takenas a constant and an independent pa- rameter without consideration ofthe problems in the original method, can be generated automaticallyby the algorithm itself.展开更多
In this study,an improved integrated radial basis function with nonuniform shape parameter is introduced.The proposed shape parameter varies in each support domain and is defined byθ=1/d_(max),where d_(max)is the max...In this study,an improved integrated radial basis function with nonuniform shape parameter is introduced.The proposed shape parameter varies in each support domain and is defined byθ=1/d_(max),where d_(max)is the maximum distance of any pair of nodes in the support domain.The proposed method is verified and shows good performance.The results are stable and accurate with any number of nodes and an arbitrary nodal distribution.Notably,the support domain should be large enough to obtain accurate results.This method is then applied for transient analysis of curved shell structures made from functionally graded materials with complex geometries.Through several numerical examples,the accuracy of the proposed approach is demonstrated and discussed.Additionally,the influence of various factors on the dynamic behavior of the structures,including the power-law index,different materials,loading conditions,and geometrical parameters of the structures,was investigated.展开更多
This paper studies the sensing base station(SBS)that has great potential to improve the safety of vehicles and pedestrians on roads.SBS can detect the targets on the road with communication signals using the integrate...This paper studies the sensing base station(SBS)that has great potential to improve the safety of vehicles and pedestrians on roads.SBS can detect the targets on the road with communication signals using the integrated sensing and communication(ISAC)technique.Compared with vehicle-mounted radar,SBS has a better sensing field due to its higher deployment position,which can help solve the problem of sensing blind areas.In this paper,key technologies of SBS are studied,including the beamforming algorithm,beam scanning scheme,and interference cancellation algorithm.To transmit and receive ISAC signals simultaneously,a double-coupling antenna array is applied.The free detection beam and directional communication beam are proposed for joint communication and sensing to meet the requirements of beamwidth and pointing directions.The joint timespace-frequency domain division multiple access algorithm is proposed to cancel the interference of SBS,including multiuser interference and duplex interference between sensing and communication.Finally,the sensing and communication performance of SBS under the industrial scientific medical power limitation is analyzed and simulated.Simulation results show that the communication rate of SBS can reach over 100 Mbps and the range of sensing and communication can reach about 500 m.展开更多
A non-negative latent factor(NLF)model is able to be built efficiently via a single latent factor-dependent,non-negative and multiplicative update(SLF-NMU)algorithm for performing precise representation to high-dimens...A non-negative latent factor(NLF)model is able to be built efficiently via a single latent factor-dependent,non-negative and multiplicative update(SLF-NMU)algorithm for performing precise representation to high-dimensional and incomplete(HDI)matrix from many kinds of big-data-related applications.However,an SLF-NMU algorithm updates a latent factor relying on the current update increment only without considering past learning information,making a resultant model suffer from slow convergence.To address this issue,this study proposes a proportional integral(PI)controller-enhanced NLF(PI-NLF)model with two-fold ideas:1)Designing an increment refinement(IR)mechanism,which formulates the current and past update increments as the proportional and integral terms of a PI controller,thereby assimilating the past update information into the learning scheme smoothly with high efficiency;2)Deriving an IR-based SLF-NMU(ISN)algorithm,which updates a latent factor following the principle of an IR mechanism,thus significantly accelerating an NLF model's convergence rate.The simulation results on eight HDI matrices collected by real applications validate that a PI-NLF model outstrips several leading-edge models in both computational efficiency and accuracy when estimating missing data within an HDI matrix.The proposed PI-NLF model can be effectively applied to applications involving HDI matrix like e-commerce system,social network,and cloud service system.The code is available at https://github.com/yuanyeswu/PINLF/blob/mainIPINLF-code.zip.展开更多
This paper presents an isogeometric boundary element method(IGABEM)for transient heat conduction analysis.The Non-Uniform Rational B-spline(NURBS)basis functions,which are used to construct the geometry of the structu...This paper presents an isogeometric boundary element method(IGABEM)for transient heat conduction analysis.The Non-Uniform Rational B-spline(NURBS)basis functions,which are used to construct the geometry of the structures,are employed to discretize the physical unknowns in the boundary integral formulations of the governing equations.Bezier extraction technique is employed to accelerate the evaluation of NURBS basis functions.We adopt a radial integration method to address the additional domain integrals.The numerical examples demonstrate the advantage of IGABEM in dimension reduction and the seamless connection between CAD and numerical analysis.展开更多
Simulated photo-degradation of fluorescent dissolved organic matter(FDOM) in Lake Baihua(BH) and Lake Hongfeng(HF) was investigated with three-dimensional excitationemission matrix(3 DEEM) fluorescence combined with t...Simulated photo-degradation of fluorescent dissolved organic matter(FDOM) in Lake Baihua(BH) and Lake Hongfeng(HF) was investigated with three-dimensional excitationemission matrix(3 DEEM) fluorescence combined with the fluorescence regional integration(FRI),parallel factor(PARAFAC) analysis,and multi-order kinetic models.In the FRI analysis,fulvic-like and humic-like materials were the main constituents for both BH-FDOM and HF-FDOM.Four individual components were identified by use of PARAFAC analysis as humic-like components(C1),fulvic-like components(C2),protein-like components(C3) and unidentified components(C4).The maximum 3 DEEM fluorescence intensity of PARAFAC components C1-C3 decreased by about 60%,70% and 90%,respectively after photo-degradation.The multi-order kinetic model was acceptable to represent the photo-degradation of FDOM with correlation coefficient(Radj2)(0.963-0.998).The photo-degradation rate constants(kn) showed differences of three orders of magnitude,from 1.09 × 10-6 to 4.02 × 10-4 min-1,and half-life of multi-order model(T1/2n)ranged from 5.26 to 64.01 min.The decreased values of fluorescence index(FI) and biogenic index(BI),the fact that of percent fluorescence response parameter of Region I(PⅠ,n) showed the greatest change ratio,followed by percent fluorescence response parameter of Region II(PⅡ,n,while the largest decrease ratio was found for C3 components,and the lowest T1/2n was observed for C3,indicated preferential degradation of protein-like materials/components derived from biological sources during photodegradation.This research on the degradation of FDOM by 3 DEEM/FRI-PARAFAC would be beneficial to understanding the photo-degradation of FD OM in natural environments and accurately predicting the environmental behaviors of contaminants in the presence of FDOM.展开更多
At 0.12 mmol/L γ-glutamyl p-nitroaniline(GGPNA),an improved integrated method was developed for kinetic analysis of γ-glutamyltransferase(GGT) reaction process and the integration with the classical initial rate met...At 0.12 mmol/L γ-glutamyl p-nitroaniline(GGPNA),an improved integrated method was developed for kinetic analysis of γ-glutamyltransferase(GGT) reaction process and the integration with the classical initial rate method to measure serum GGT.For the improved integrated method,an integrated rate equation,which used the predictor variable of reaction time and considered inhibitions by both GGPNA and products,was nonlinearly fit to GGT reaction processes.For the integration strategy,classical initial rates were estimated when GGPNA consumption percentages were below 50%;otherwise,maximal reaction rates of GGT were estimated by the improved integrated method and converted into initial rates according to the differential rate equation at 0.11 mmol/L GGPNA.The inte-gration strategy was validated using optimized GGT kinetic parameters and 10-s intervals to record reaction curves within 8.0 min.By the integration strategy,there was a linear response from 0.9 to 32.0 U/L GGT,coefficients of variation were below 3.5%for GGT from 8.0 to 32.0 U/L(n=5) ,and GGT activities in clinical sera responded linearly to their classical initial rates at 2.00 mmol/L GGPNA with an expected slope.Therefore,the integration strategy was successful in measuring GGT at 0.12 mmol/L GGPNA.展开更多
We propose a new approach to reuse the basis function evaluations in the numerical integration of isogeometric analysis.The concept of reusability of the basis functions is introduced according to their symmetrical,tr...We propose a new approach to reuse the basis function evaluations in the numerical integration of isogeometric analysis.The concept of reusability of the basis functions is introduced according to their symmetrical,translational and proportional features on both the coarse and refined levels.Based on these features and the parametric domain regularity of each basis,we classify the bases on the original level and then reuse them on the refined level,which can reduce the time for basis calculations at integration nodes.By using the sum factorization method and the mean value theorem for the integrals,a new integration method with high integral efficiency is proposed.We validate the proposed method by some structural analysis problems in domains with different dimensionality.Comparing the numerical result accuracy and the time cost of the proposed integration method with the full Gauss integration quadrature,it turns out to be very promising.展开更多
The paper applied the isogeometric boundary element method(IGABEM)to thermoelastic problems.The Non-Uniform Rational B-splines(NURBS)used to construct geometric models are employed to discretize the boundary integral ...The paper applied the isogeometric boundary element method(IGABEM)to thermoelastic problems.The Non-Uniform Rational B-splines(NURBS)used to construct geometric models are employed to discretize the boundary integral formulation of the governing equation.Due to the existence of thermal stress,the domain integral term appears in the boundary integral equation.We resolve this problem by incorporating radial integration method into IGABEM which converts the domain integral to the boundary integral.In this way,IGABEM can maintain its advantages in dimensionality reduction and more importantly,seamless integration of CAD and numerical analysis based on boundary representation.The algorithm is verified by numerical examples.展开更多
In order to improve the detection accuracy of Doppler asymmetric spatial heterodyne(DASH)interferometer in harsh temperatures,an opto-mechanical-thermal integration analysis is carried out.Firstly,the correlation betw...In order to improve the detection accuracy of Doppler asymmetric spatial heterodyne(DASH)interferometer in harsh temperatures,an opto-mechanical-thermal integration analysis is carried out.Firstly,the correlation between the interference phase and temperature is established according to the working principle and the phase algorithm of the interferometer.Secondly,the optical mechanical thermal analysis model and thermal deformation data acquisition model are designed.The deformation data of the interference module and the imaging optical system at different temperatures are given by temperature load simulation analysis,and the phase error caused by thermal deformation is obtained by fitting.Finally,based on the wind speed error caused by thermal deformation of each component,a reasonable temperature control scheme is proposed.The results show that the interference module occupies the main cause,the temperature must be controlled within(20±0.05)℃,and the temperature control should be carried out for the temperature sensitive parts,and the wind speed error caused by the part is 3.8 m/s.The thermal drift between the magnification of the imaging optical system and the thermal drift of the relative position between the imaging optical system and the detector should occupy the secondary cause,which should be controlled within(20±2)℃,and the wind speed error caused by the part is 3.05 m/s.In summary,the wind measurement error caused by interference module,imaging optical system,and the relative position between the imaging optical system and the detector can be controlled within 6.85 m/s.The analysis and temperature control schemes presented in this paper can provide theoretical basis for DASH interferometer engineering applications.展开更多
基金supported by grants from the Fundamental Research Funds for the Central Universities(No.2025ZFJH03)the Central Guidance Fund for Local Science and Technology Development(No.2024ZY01054)the CAMS Innovation Fund for Medical Sciences(No.2019-I2M-5-045).
文摘Background:Giant cell arteritis(GCA),the most common systemic vasculitis affecting elderly individuals,currently lacks specific therapies.This study aimed to systematically identify therapeutic targets for GCA through integration of large-scale multi-omics datasets.Methods:We constructed a multi-stage analytical framework encompassing 32 proteomic datasets(covering 2914 unique plasma proteins)and 6 transcriptomic datasets.Multi-omics integration strategies,including two-sample Mendelian randomization,colocalization analysis,and functional enrichment analysis,were employed to identify and validate causal relationships between candidate targets and GCA risk across 4 independent European-ancestry GCA cohorts.Single-cell RNA sequencing analysis of peripheral blood mononuclear cells from untreated GCA patients was performed to characterize hub gene-immune cell relationships.Results:We identified 43 plasma proteins causally associated with GCA[false discovery rate(FDR)<0.05],with 17 representing novel therapeutic targets.Through dual validation using proteome-wide association studies and transcriptome-wide association studies,we identified 13 high-confidence candidate targets with distinct tissue-specific expression patterns.Unc-51 like kinase 3(ULK3)emerged as the strongest protective factor(odds ratio=0.47,95%confidence interval:0.37–0.71)through autophagy regulation,while SLAMF7 represents an immediate drug repositioning opportunity as the target of food and drug administration-approved elotuzumab.Five targets have existing approved drugs(SLAMF7,ICAM1,IL18,IL6ST,CTSS).Single-cell analysis revealed profound disruption of hub gene-immune cell relationships in untreated GCA patients,with cell-type-specific alterations in inflammatory gene expression,and TYMP as the most critical hub gene.Conclusions:This study provides a clinically-actionable atlas of 43 potential therapeutic targets in GCA,identifying novel mechanisms including autophagy modulation and metabolic reprogramming,with immediate drug repositioning opportunities and precision medicine strategies based on tissue-specific and cell-type-specific expression patterns.These findings require experimental validation before clinical translation.
基金National Natural Science Foundation of China(No.52375236)Fundamental Research Funds for the Central Universities of China(No.23D110316)。
文摘In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order reliability methods exhibit limited accuracy in highly nonlinear scenarios.To overcome these challenges,a novel reliability analysis strategy based on a multimodal differential evolution algorithm and a hypersphere integration method is proposed.Initially,the penalty function method is employed to reformulate the MPP search problem as a conditionally constrained optimization task.Subsequently,a differential evolution algorithm incorporating a population delineation strategy is utilized to identify all MPPs.Finally,a paraboloid equation is constructed based on the curvature of the limit-state function at the MPPs,and the failure probability of the structure is calculated by using the hypersphere integration method.The localization effectiveness of the MPPs is compared through multiple numerical cases and two engineering examples,with accuracy comparisons of failure probabilities against the first-order reliability method(FORM)and the secondorder reliability method(SORM).The results indicate that the method effectively identifies existing MPPs and achieves higher solution precision.
基金Grants of National Natural Science Foundation of China(82274685).
文摘Objective To systematically characterize the developmental trajectory and interdisciplinary integration of intelligent diagnosis in traditional Chinese medicine(TCM)through quantitative topic evolution analysis,we addressed the fragmentation of existing research and clarified the long-term research structure and evolutionary patterns of the field.Methods A topic evolution analysis was performed on Chinese-language literature pertaining to intelligent diagnosis in TCM.Publications were retrieved from the China National Knowledge Infrastructure(CNKI),Wanfang Data,and China Science and Technology Journal Database(VIP),covering the period from database inception to July 3,2025.A hybrid segmentation approach,based on cumulative publication growth trends and inflection point detection,was applied to divide the research timeline into distinct stages.Subsequently,the latent Dirichlet allocation(LDA)model was used to extract research topics,followed by alignment and evolutionary analysis of topics across different stages.Results A total of 3919 publications published between 2003 and 2025 were included,and the research trajectory was divided into five stages based on data-driven breakpoint detection.The field exhibited a clear evolutionary shift from early rule-based systems and tonguepulse image and signal analysis(2006–2010),to machine-learning-based syndrome and prescription modeling(2011–2015),followed by deep-learning-driven pattern recognition and formula association(2016–2020).Since 2021,research has increasingly emphasized knowledge-graph construction,multimodal integration,and intelligent clinical decision-support systems,with recent studies(2024–2025)showing the emergence of large language models and agent-based diagnostic frameworks.Topic evolution analysis further revealed sustained cross-stage continuity in syndrome modeling and prescription association analysis,alongside the progressive consolidation of integrated intelligent diagnostic platforms.Conclusion By identifying key technological transitions and persistent core research themes,our findings offer a structured reference framework for the design of intelligent diagnostic systems,the construction of knowledge-driven clinical decision-support tools,and the alignment of AI models with TCM diagnostic logic.Importantly,the stage-based evolutionary insights derived from this analysis can inform future methodological choices,improve model interpretability and clinical applicability,and support the translation of intelligent TCM diagnosis from experimental research to real-world clinical practice.
文摘[Objective]This study aims to investigate the multi-body hydrodynamic interaction mechanisms during offshore lifting operations of aquaculture net cages in wind-fishery integration systems.By integrating numerical simulations and dynamic analysis methods,this study systematically investigates the coupled dynamic response characteristics during the cage-carrier vessel separation process to reveal its dynamic evolution patterns and key influence mechanisms.[Method]Based on potential flow theory,a fully coupled dynamic analysis model of crane vessel-net cage-semi-submersible barge was established for a marine ranch project in Guangdong.The complete lifting process was dynamically simulated using SESAM software.Five typical operating sea states were configured to investigate the influence of wave parameters on the system's motion response under combined wave-current-wind actions.[Result]The results demonstrate that wave period dominates the system stability.Under short-period conditions,the system maintains stable motion with relatively small horizontal relative displacements,while long-period conditions excite low-frequency resonance,leading to significant slow-drift motions.Vertical response analysis reveals that long-period waves cause severe relative displacement fluctuations between the cage and semi-submersible vessel,with actual displacement amplitudes doubling the preset safety target of 2.045 m.Quantitative analysis further indicates that when significant wave height increases from 1.0 m to 1.5 m,the actual displacement amplitude increases by approximately 20%relative to the target displacement of 2.045 m,demonstrating that its influence is significantly weaker than the displacement variations induced by wave period changes.The complete dynamic simulation successfully captures the continuous dynamic response characteristics during the lifting process.[Conclusion]This research clarifies the influence mechanisms of wave parameters on the cage lifting process,identifying wave period as the crucial factor for operational safety.An operation window assessment method incorporating multi-body coupling effects is established,proposing a safety criterion with peak period not exceeding six seconds as the core requirement.The findings provide theoretical foundation for safe installation of marine ranch net cages and offer valuable references for similar offshore lifting operations.
文摘To achieve efficient and refined thermal environment simulations for single-phase and two-phase flows in aircraft cabins,we propose an integrated analysis method.This approach enables rapid coupled heat transfer calculations among single-phase flow,two-phase flow,and solids within a single time step.For single-phase fluid and solid equipment,a fast numerical algorithm for natural convection is developed using a loosely coupled strategy,dividing the single-phase flow into developmental stages for efficient temperature field computation.For two-phase flow and the fuel tank wall,a transient heat transfer model is constructed at the gas-liquid-solid boundary,facilitating fast thermal analysis.These methods are unified for integrated simulation of the cabin’s thermal environment.Validation based on two-dimensional models demonstrates a speedup by a factor of 7.9,while maintaining an average temperature error of less than 1%at two-phase nodes.The method’s robustness is confirmed under various high-temperature boundary conditions.
基金supported by the National Natural Science Foundation of China(Grant Nos.12372201 and 12072302).
文摘The 13-node quadrilateral and 39-node hexahedral cubic serendipity elements produce nodally integrated positive-definite lumped heat capacity matrices in higher-order finite element analysis.However,these elements display severe convergence deterioration in explicit transient heat conduction analysis with lumped heat ca-pacity matrices.This convergence decay is due to the violation of variational integration consistency by the standard Galerkin formulation with lumped heat capacity matrices.This issue is resolved by introducing the boundary-enhanced Galerkin weak form that incorporates the elemental boundary contribution in the discrete finite element formulation.Subsequently,it is theoretically proven that a direct nodal integration identically fulfills the variational integration consistency in the context of the boundary-enhanced Galerkin weak form.The proposed variationally consistent nodal integration therefore enables optimal convergence for explicit transient heat conduction analysis with lumped heat capacity matrices.The efficacy of the proposed variationally con-sistent nodal integration formulation for the 13-node quadrilateral and 39-node hexahedral cubic elements is thoroughly demonstrated via numerical examples.
文摘The integration of multi-omic liquid biopsies with artificial intelligence(AI)represents a rapidly evolving frontier in early cancer detection,offering the potential to enhance personalized medicine and improve patient outcomes.This review explores the current state and emerging directions of this approach,focusing on the synergistic value of combining genomics,epigenomics,transcriptomics,proteomics,and metabolomics with AIdriven analytics.We discuss advances in multi-analyte blood tests such as CancerSEEK,which have demonstrated promising multi-cancer detection capabilities in early studies,as well as efforts to integrate liquid biopsy data with imaging modalities to improve diagnostic performance.The review also highlights ongoing challenges,including the need for greater analytical sensitivity,improved specificity for early-stage disease,standardization of workflows,and harmonization with existing screening modalities.We outline the prospective—but still largely investigational—impact of these technologies on cancer management,including early detection,treatment monitoring,and minimal residual disease assessment,along with their potential economic implications.Ultimately,we envision a future in which multi-omic liquid biopsies integrated with AI may contribute to more effective,noninvasive cancer detection strategies,while recognizing that substantial validation,regulatory approval,and health-system integration are required before widespread clinical adoption can occur.
基金financially supported by the National Natural Science Foundation of China(Grant No.32160677)the Hainan University Mango Research System.
文摘Mango(Mangifera indica L.)is one of the main economic crops in Hainan,China,prized for its distinctive flavor and high nutritional value.It is also rich in health-promoting antioxidants such as vitamin C and flavonoids.Enhanced ultraviolet-B(UV—B)radiation,a growing global environmental concern,alters plant antioxidant systems,with increased flavonoid accumulation as a common adaptive response.However,its effects on mango fruit remain largely unexplored.To investigate the antioxidant responses of mango to enhanced UV-B radiation and identify key responsive flavonoid compounds and regulatory genes,we exposed‘Tainong 1’mango fruits growing under natural light to 96 kJ·m^(-2)·d^(-1)of UV-B radiation to simulate high UV-B conditions.Treated fruits were smaller in size and had a pulp of a more intense yellow colour.Further,malondialdehyde content in treated fruits was higher during the phase of rapid fruit enlargement.Additionally,treated fruits showed increased sugar-acid ratios,total phenol,total flavonoid,carotenoid,and ascorbic acid contents.Furthermore,they showed significantly enhanced antioxidant activity,as measured by the FRAP,ABTS,and DPPH assays.Extensive targeted metabolomic-analysis identified flavonoids as the largest category of compounds differentially expressed in treated and control groups.Quantitative metabolomics of flavonoids identified hyperoside,quercimeritrin,and(-)-catechin gallate as the key flavonoid metabolites responsive to UV-B treatment.Transcriptome analysis revealed an enrichment of the flavonoid biosynthesis pathway,with most associated differentially expressed genes showing upregulation.Furthermore,qRT-PCR analysis confirmed that the expression of the genes MiCHS7,MiCHI1,MiCHI2,MiFLS,MiF3H2,and MiF3H3 correlated with changes in key flavonoid metabolites.Indeed,correlation analysis indicated that MiCHS7,MiCHI1,MiFLS,and MiF3H3 are potential key genes involved in flavonoid accumulation under UV-B treatment.Thus,our study provides a theoretical basis for breeding for new resilient varieties and developing UV-B-resistant mango cultivation techniques.
文摘The rapid growth of biomedical data,particularly multi-omics data including genomes,transcriptomics,proteomics,metabolomics,and epigenomics,medical research and clinical decision-making confront both new opportunities and obstacles.The huge and diversified nature of these datasets cannot always be managed using traditional data analysis methods.As a consequence,deep learning has emerged as a strong tool for analysing numerous omics data due to its ability to handle complex and non-linear relationships.This paper explores the fundamental concepts of deep learning and how they are used in multi-omics medical data mining.We demonstrate how autoencoders,variational autoencoders,multimodal models,attention mechanisms,transformers,and graph neural networks enable pattern analysis and recognition across all omics data.Deep learning has been found to be effective in illness classification,biomarker identification,gene network learning,and therapeutic efficacy prediction.We also consider critical problems like as data quality,model explainability,whether findings can be repeated,and computational power requirements.We now consider future elements of combining omics with clinical and imaging data,explainable AI,federated learning,and real-time diagnostics.Overall,this study emphasises the need of collaborating across disciplines to advance deep learning-based multi-omics research for precision medicine and comprehending complicated disorders.
基金National Natural Science Foundation of China(No.52375236)Fundamental Research Funds for the Central Universities,China(No.23D110316)。
文摘In the structural reliability analysis,the first-order reliability method(FORM)often yields significant errors when addressing nonlinear problems.Although the second-order reliability method(SORM)can provide higher accuracy,the additional computation of the Hessian matrix leads to lower computational efficiency.Additionally,when the dimensionality of the random variables is high,the approximation formula of SORM can result in larger errors.To address these issues,a structural reliability analysis method based on Kriging and spherical cap area integral is proposed.Firstly,this method integrates FORM with the quasi-Newton algorithm Broyden-Fletcher-Goldfarb-Shanno(BFGS),trains the Kriging model by using sample points from the algorithm’s iteration process,and combines the Kriging model with gradient information to approximate the Hessian matrix.Then,the failure surface is approximated as a rotating paraboloid,utilizing the spherical cap to replace the complex surface.For the n-dimensional case,the hyperspherical cap area expression is combined with the integral method to calculate the failure probability.Finally,the method is validated through three examples,demonstrating improved computational accuracy and efficiency compared to traditional methods.
基金the National Natural Science Foundation of China (No.19872016,19872017)the National Key Basic Research Special Foundation (G1999032805)the Foundation for University Key Teachers by the Ministry of Education of China
文摘This paper presents an improved precise integration algorithm fortransient analysis of heat transfer and some other problems. Theoriginal precise integration method is improved by means of the inve-rse accuracy analysis so that the parameter N, which has been takenas a constant and an independent pa- rameter without consideration ofthe problems in the original method, can be generated automaticallyby the algorithm itself.
基金Ho Chi Minh City University of Technology (HCMUT), VNU-HCM for supporting this study
文摘In this study,an improved integrated radial basis function with nonuniform shape parameter is introduced.The proposed shape parameter varies in each support domain and is defined byθ=1/d_(max),where d_(max)is the maximum distance of any pair of nodes in the support domain.The proposed method is verified and shows good performance.The results are stable and accurate with any number of nodes and an arbitrary nodal distribution.Notably,the support domain should be large enough to obtain accurate results.This method is then applied for transient analysis of curved shell structures made from functionally graded materials with complex geometries.Through several numerical examples,the accuracy of the proposed approach is demonstrated and discussed.Additionally,the influence of various factors on the dynamic behavior of the structures,including the power-law index,different materials,loading conditions,and geometrical parameters of the structures,was investigated.
基金supported in part by the National Natural Science Foundation of China under Grant U21B2014,Grant 92267202,and Grant 62271081.
文摘This paper studies the sensing base station(SBS)that has great potential to improve the safety of vehicles and pedestrians on roads.SBS can detect the targets on the road with communication signals using the integrated sensing and communication(ISAC)technique.Compared with vehicle-mounted radar,SBS has a better sensing field due to its higher deployment position,which can help solve the problem of sensing blind areas.In this paper,key technologies of SBS are studied,including the beamforming algorithm,beam scanning scheme,and interference cancellation algorithm.To transmit and receive ISAC signals simultaneously,a double-coupling antenna array is applied.The free detection beam and directional communication beam are proposed for joint communication and sensing to meet the requirements of beamwidth and pointing directions.The joint timespace-frequency domain division multiple access algorithm is proposed to cancel the interference of SBS,including multiuser interference and duplex interference between sensing and communication.Finally,the sensing and communication performance of SBS under the industrial scientific medical power limitation is analyzed and simulated.Simulation results show that the communication rate of SBS can reach over 100 Mbps and the range of sensing and communication can reach about 500 m.
基金supported in part by the National Natural Science Foundation of China(62372385,62272078)the Chongqing Natural Science Foundation(CSTB2023NSCQ-LZX0069).
文摘A non-negative latent factor(NLF)model is able to be built efficiently via a single latent factor-dependent,non-negative and multiplicative update(SLF-NMU)algorithm for performing precise representation to high-dimensional and incomplete(HDI)matrix from many kinds of big-data-related applications.However,an SLF-NMU algorithm updates a latent factor relying on the current update increment only without considering past learning information,making a resultant model suffer from slow convergence.To address this issue,this study proposes a proportional integral(PI)controller-enhanced NLF(PI-NLF)model with two-fold ideas:1)Designing an increment refinement(IR)mechanism,which formulates the current and past update increments as the proportional and integral terms of a PI controller,thereby assimilating the past update information into the learning scheme smoothly with high efficiency;2)Deriving an IR-based SLF-NMU(ISN)algorithm,which updates a latent factor following the principle of an IR mechanism,thus significantly accelerating an NLF model's convergence rate.The simulation results on eight HDI matrices collected by real applications validate that a PI-NLF model outstrips several leading-edge models in both computational efficiency and accuracy when estimating missing data within an HDI matrix.The proposed PI-NLF model can be effectively applied to applications involving HDI matrix like e-commerce system,social network,and cloud service system.The code is available at https://github.com/yuanyeswu/PINLF/blob/mainIPINLF-code.zip.
基金funded by National Natural Science Foundation of China(NSFC)under Grant Nos.11702238,51904202,and 11902212Nanhu Scholars Program for Young Scholars of XYNU.
文摘This paper presents an isogeometric boundary element method(IGABEM)for transient heat conduction analysis.The Non-Uniform Rational B-spline(NURBS)basis functions,which are used to construct the geometry of the structures,are employed to discretize the physical unknowns in the boundary integral formulations of the governing equations.Bezier extraction technique is employed to accelerate the evaluation of NURBS basis functions.We adopt a radial integration method to address the additional domain integrals.The numerical examples demonstrate the advantage of IGABEM in dimension reduction and the seamless connection between CAD and numerical analysis.
基金financially supported by the National Natural Science Foundation of China(No.41573130)BNU Interdisciplinary Research Foundation for First-Year Doctoral Candidates(No.BNUXKJC1802)
文摘Simulated photo-degradation of fluorescent dissolved organic matter(FDOM) in Lake Baihua(BH) and Lake Hongfeng(HF) was investigated with three-dimensional excitationemission matrix(3 DEEM) fluorescence combined with the fluorescence regional integration(FRI),parallel factor(PARAFAC) analysis,and multi-order kinetic models.In the FRI analysis,fulvic-like and humic-like materials were the main constituents for both BH-FDOM and HF-FDOM.Four individual components were identified by use of PARAFAC analysis as humic-like components(C1),fulvic-like components(C2),protein-like components(C3) and unidentified components(C4).The maximum 3 DEEM fluorescence intensity of PARAFAC components C1-C3 decreased by about 60%,70% and 90%,respectively after photo-degradation.The multi-order kinetic model was acceptable to represent the photo-degradation of FDOM with correlation coefficient(Radj2)(0.963-0.998).The photo-degradation rate constants(kn) showed differences of three orders of magnitude,from 1.09 × 10-6 to 4.02 × 10-4 min-1,and half-life of multi-order model(T1/2n)ranged from 5.26 to 64.01 min.The decreased values of fluorescence index(FI) and biogenic index(BI),the fact that of percent fluorescence response parameter of Region I(PⅠ,n) showed the greatest change ratio,followed by percent fluorescence response parameter of Region II(PⅡ,n,while the largest decrease ratio was found for C3 components,and the lowest T1/2n was observed for C3,indicated preferential degradation of protein-like materials/components derived from biological sources during photodegradation.This research on the degradation of FDOM by 3 DEEM/FRI-PARAFAC would be beneficial to understanding the photo-degradation of FD OM in natural environments and accurately predicting the environmental behaviors of contaminants in the presence of FDOM.
基金Project supported by the National Natural Science Foundation of China (No.30200266)the Program for New Century Excellent Talents in University of Ministry of Education of China(No.NCET-09-928)
文摘At 0.12 mmol/L γ-glutamyl p-nitroaniline(GGPNA),an improved integrated method was developed for kinetic analysis of γ-glutamyltransferase(GGT) reaction process and the integration with the classical initial rate method to measure serum GGT.For the improved integrated method,an integrated rate equation,which used the predictor variable of reaction time and considered inhibitions by both GGPNA and products,was nonlinearly fit to GGT reaction processes.For the integration strategy,classical initial rates were estimated when GGPNA consumption percentages were below 50%;otherwise,maximal reaction rates of GGT were estimated by the improved integrated method and converted into initial rates according to the differential rate equation at 0.11 mmol/L GGPNA.The inte-gration strategy was validated using optimized GGT kinetic parameters and 10-s intervals to record reaction curves within 8.0 min.By the integration strategy,there was a linear response from 0.9 to 32.0 U/L GGT,coefficients of variation were below 3.5%for GGT from 8.0 to 32.0 U/L(n=5) ,and GGT activities in clinical sera responded linearly to their classical initial rates at 2.00 mmol/L GGPNA with an expected slope.Therefore,the integration strategy was successful in measuring GGT at 0.12 mmol/L GGPNA.
基金National Natural Science Foundation of China(Grant Nos.#51675197,#51805190).
文摘We propose a new approach to reuse the basis function evaluations in the numerical integration of isogeometric analysis.The concept of reusability of the basis functions is introduced according to their symmetrical,translational and proportional features on both the coarse and refined levels.Based on these features and the parametric domain regularity of each basis,we classify the bases on the original level and then reuse them on the refined level,which can reduce the time for basis calculations at integration nodes.By using the sum factorization method and the mean value theorem for the integrals,a new integration method with high integral efficiency is proposed.We validate the proposed method by some structural analysis problems in domains with different dimensionality.Comparing the numerical result accuracy and the time cost of the proposed integration method with the full Gauss integration quadrature,it turns out to be very promising.
基金This study was funded by the National Natural Science Foundation of China(NSFC)(Grant Nos.11702238,51904202 and 11902212)and Nanhu Scholars Program for Young Scholars of XYNU.
文摘The paper applied the isogeometric boundary element method(IGABEM)to thermoelastic problems.The Non-Uniform Rational B-splines(NURBS)used to construct geometric models are employed to discretize the boundary integral formulation of the governing equation.Due to the existence of thermal stress,the domain integral term appears in the boundary integral equation.We resolve this problem by incorporating radial integration method into IGABEM which converts the domain integral to the boundary integral.In this way,IGABEM can maintain its advantages in dimensionality reduction and more importantly,seamless integration of CAD and numerical analysis based on boundary representation.The algorithm is verified by numerical examples.
文摘In order to improve the detection accuracy of Doppler asymmetric spatial heterodyne(DASH)interferometer in harsh temperatures,an opto-mechanical-thermal integration analysis is carried out.Firstly,the correlation between the interference phase and temperature is established according to the working principle and the phase algorithm of the interferometer.Secondly,the optical mechanical thermal analysis model and thermal deformation data acquisition model are designed.The deformation data of the interference module and the imaging optical system at different temperatures are given by temperature load simulation analysis,and the phase error caused by thermal deformation is obtained by fitting.Finally,based on the wind speed error caused by thermal deformation of each component,a reasonable temperature control scheme is proposed.The results show that the interference module occupies the main cause,the temperature must be controlled within(20±0.05)℃,and the temperature control should be carried out for the temperature sensitive parts,and the wind speed error caused by the part is 3.8 m/s.The thermal drift between the magnification of the imaging optical system and the thermal drift of the relative position between the imaging optical system and the detector should occupy the secondary cause,which should be controlled within(20±2)℃,and the wind speed error caused by the part is 3.05 m/s.In summary,the wind measurement error caused by interference module,imaging optical system,and the relative position between the imaging optical system and the detector can be controlled within 6.85 m/s.The analysis and temperature control schemes presented in this paper can provide theoretical basis for DASH interferometer engineering applications.
