A 3D crustal model was constructed using a combination of cutting-edge techniques,which were integrated to provide a density model for Egypt and address the sporadic distribution of seismic data.These techniques inclu...A 3D crustal model was constructed using a combination of cutting-edge techniques,which were integrated to provide a density model for Egypt and address the sporadic distribution of seismic data.These techniques include obtaining gravity data from the Gravity Field and Steady-State Ocean Circulation Explorer(GOCE),creating seismic profiles,analyzing the receiver functions of seismic data,obtaining information from boreholes,and providing geological interpretations.GOCE satellite gravity data were processed to construct a preliminary model based on nonlinear inversions of the data.A regional crustal thickness model was developed using receiver functions,seismic refraction profiles,and geological insights.The inverted model was validated using borehole data and compared with seismic estimates.The model exhibited strong consistency and revealed a correlation between crustal thickness,geology,and tectonics of Egypt.It showed that the shallowest depths of the Moho are located in the north along the Mediterranean Sea and in the eastern part along the Red Sea,reflecting an oceanic plate with a thin,high-density crust.The deepest Moho depths are located in the southwestern part of Egypt,Red Sea coastal mountains,and Sinai Peninsula.The obtained 3D model of crustal thickness provided finely detailed Moho depth estimates that aligned closely with geology and tectonic characteristics of Egypt,contributing valuable insights into the subsurface structure and tectonic processes of region.展开更多
Unsteady aerodynamic characteristics at high angles of attack are of great importance to the design and development of advanced fighter aircraft, which are characterized by post-stall maneuverability with multiple Deg...Unsteady aerodynamic characteristics at high angles of attack are of great importance to the design and development of advanced fighter aircraft, which are characterized by post-stall maneuverability with multiple Degrees-of-Freedom(multi-DOF) and complex flow field structure.In this paper, a special kind of cable-driven parallel mechanism is firstly utilized as a new suspension method to conduct unsteady dynamic wind tunnel tests at high angles of attack, thereby providing experimental aerodynamic data. These tests include a wide range of multi-DOF coupled oscillatory motions with various amplitudes and frequencies. Then, for aerodynamic modeling and analysis, a novel data-driven Feature-Level Attention Recurrent neural network(FLAR) is proposed. This model incorporates a specially designed feature-level attention module that focuses on the state variables affecting the aerodynamic coefficients, thereby enhancing the physical interpretability of the aerodynamic model. Subsequently, spin maneuver simulations, using a mathematical model as the baseline, are conducted to validate the effectiveness of the FLAR. Finally, the results on wind tunnel data reveal that the FLAR accurately predicts aerodynamic coefficients, and observations through the visualization of attention scores identify the key state variables that affect the aerodynamic coefficients. It is concluded that the proposed FLAR enhances the interpretability of the aerodynamic model while achieving good prediction accuracy and generalization capability for multi-DOF coupling motion at high angles of attack.展开更多
The average stiffness performance indices throughout the workspace are commonly used as global stiffness performance indices to evaluate the overall stiffness performance of parallel mechanisms,which involves an analy...The average stiffness performance indices throughout the workspace are commonly used as global stiffness performance indices to evaluate the overall stiffness performance of parallel mechanisms,which involves an analysis of the stiffness performance of numerous discrete points in the workspace.This necessitates time-consuming and inefficient calculation,which is particularly pronounced in the optimization design stage of the mechanism,where the variations in the global stiffness performance indices versus various dimensional and structural parameters need to be analyzed.This paper presents a semi-analytical approach for stiffness modeling of the novel(R(RPS&RP))&2-UPS parallel mechanism(referred to as the Trifree mechanism)and proposes“local”stiffness performance indices as alternatives to global indices.Drawing on the screw theory,the Cartesian stiffness matrix of the Trifree mechanism is formulated explicitly by considering the compliances of all elastic elements and the over-constraint characteristics inherent in the mechanism.Based on the spherical motion pattern of the Trifree mechanism,four special reference configurations are extracted within the workspace.This yields“local”stiffness performance indices capable of accurately evaluating the overall stiffness performance of the mechanism and effectively improving the computational efficiency.The variations in global and“local”stiffness performance indices versus key design parameters are investigated.Furthermore,the proposed indices are applied to the Tricept and Trimule mechanisms.The results demonstrate that the proposed indices exhibit excellent computational accuracy and efficiency in evaluating the overall stiffness performance of these spherical parallel mechanisms.Moreover,the stiffness performance of the novel parallel mechanism investigated in this study closely resembles that of the well-known Tricept and Trimule mechanisms.This research proposes a semi-analytic stiffness model of the Trifree mechanism and“local”stiffness performance indices to evaluate the overall stiffness performance,thereby substantially improving the computational efficiency without sacrificing accuracy.展开更多
Embedding optical fiber sensors into composite materials offers the advantage of real-time structural monitoring.However,there is an order-of-magnitude difference in diameter between optical fibers and reinforcing fib...Embedding optical fiber sensors into composite materials offers the advantage of real-time structural monitoring.However,there is an order-of-magnitude difference in diameter between optical fibers and reinforcing fibers,and the detailed mechanism of how embedded optical fibers affect the micromechanical behavior and damage failure processes within composite materials remains unclear.This paper presents a micromechanical simulation analysis of composite materials embedded with optical fibers.By constructing representative volume elements(RVEs)with randomly distributed reinforcing fibers,the optical fiber,the matrix,and the interface phase,the micromechanical behavior and damage evolution under transverse tensile and compressive loads are explored.The study finds that the presence of embedded optical fibers significantly influences the initiation and propagation of microscopic damage within the composites.Under transverse tension,the fiber-matrix interface cracks first,followed by plastic cracking in the matrix surrounding the fibers,forming micro-cracks.Eventually,these cracks connect with the debonded areas at the fiber-matrix interface to form a dominant crack that spans the entire model.Under transverse compression,plastic cracking first occurs in the resin surrounding the optical fibers,connecting with the interface debonding areas between the optical fibers and the matrix to form two parallel shear bands.Additionally,it is observed that the strength of the interface between the optical fiber and the matrix critically affects the simulation results.The simulated damage morphologies align closely with those observed using scanning electron microscopy(SEM).These findings offer theoretical insights that can inform the design and fabrication of smart composite materials with embedded optical fiber sensors for advanced structural health monitoring.展开更多
The acetylpolyamine oxidase(APAO),spermine oxidase(SMO),and spermidine/spermine N1-acetyltransferase(SSAT)are pivotal enzymes in polyamine metabolism,exerting direct influence on polyamine homeostasis regulation.Dysfu...The acetylpolyamine oxidase(APAO),spermine oxidase(SMO),and spermidine/spermine N1-acetyltransferase(SSAT)are pivotal enzymes in polyamine metabolism,exerting direct influence on polyamine homeostasis regulation.Dysfunctions in these enzymes are intricately linked to inflammatory diseases and cancers.Establishing their three-dimensional structures is essential for exploring enzymatic catalytic mechanisms and designing inhibitors at the atomic level.This article primarily assesses the precision of AlphaFold2 and molecular dynamics simulations in determining the three-dimensional structures of these enzymes,utilizing protein conformation rationality assessment,residue correlation matrix,and other techniques.This provides robust models for subsequent polyamine catabolic metabolism calculations and offers valuable insights for modeling proteins that have yet to acquire crystal structures.展开更多
BACKGROUND Colorectal cancer(CRC)remains a major global health burden due to its high incidence and mortality,with treatment efficacy often hindered by tumor hetero-geneity,drug resistance,and a complex tumor microenv...BACKGROUND Colorectal cancer(CRC)remains a major global health burden due to its high incidence and mortality,with treatment efficacy often hindered by tumor hetero-geneity,drug resistance,and a complex tumor microenvironment(TME).Lactate metabolism plays a pivotal role in reshaping the TME,promoting immune eva-sion and epithelial-mesenchymal transition,making it a promising target for novel therapeutic strategies and prognostic modeling in CRC.AIM To offer an in-depth analysis of the role of lactate metabolism in CRC,high-lighting its significance in the TME and therapeutic response.METHODS Utilizing single-cell and transcriptomic data from the Gene Expression Omnibus and The Cancer Genome Atlas,we identified key lactate metabolic activities,particularly in the monocyte/macrophage subpopulation.RESULTS Seven lactate metabolism-associated genes were significantly linked to CRC prognosis and used to construct a predictive model.This model accurately forecasts patient outcomes and reveals notable distinct patterns of immune infiltration and transcriptomic profiles mutation profiles between high-and low-risk groups.High-risk patients demonstrated elevated immune cell infiltration,increased mutation frequencies,and heightened sensitivity to specific drugs(AZD6482,tozasertib,and SB216763),providing a foundation for personalized treatment approaches.Additionally,a nomogram integrating clinical and metabolic data effectively predicted 1-,3-,and 5-year survival rates.CONCLUSION This report underscored the pivotal mechanism of lactate metabolism in CRC prognosis and suggest novel avenues for therapeutic intervention.展开更多
Thermal Protection System(TPS)with thick tiles,low thermal conductivity,and a short re-entry stage stands as a critical element within reusable aircraft,whose reliability is related to the function and changes with th...Thermal Protection System(TPS)with thick tiles,low thermal conductivity,and a short re-entry stage stands as a critical element within reusable aircraft,whose reliability is related to the function and changes with their physical properties,external conditions,and degradation.Meanwhile,due to the limitation of testing resources,epistemic uncertainties stemming from the small samples are present in TPS reliability modeling.However,current TPS reliability modeling methods face challenges in characterizing the relationships among reliability and physical properties,external conditions,degradation,and epistemic uncertainties.Therefore,under the framework of belief reliability theory,a TPS reliability model is constructed,which takes into account the physical principle,external conditions,performance degradation,and epistemic uncertainties.A reliability simulation algorithm is proposed to calculate TPS reliability.Through a case study and comparison analysis,the proposed method is validated as more effective than the existing method.Additionally,reliability sensitivity analysis is conducted to identify the sensitive factors of reliability under the condition of small samples,through which suggestions are provided for TPS functional design and improvement.展开更多
As the complexity of scientific satellite missions increases,the requirements for their magnetic fields,magnetic field fluctuations,and even magnetic field gradients and variations become increasingly stringent.Additi...As the complexity of scientific satellite missions increases,the requirements for their magnetic fields,magnetic field fluctuations,and even magnetic field gradients and variations become increasingly stringent.Additionally,there is a growing need to address the alternating magnetic fields produced by the spacecraft itself.This paper introduces a novel modeling method for spacecraft magnetic dipoles using an integrated self-attention mechanism and a transformer combined with Kolmogorov-Arnold Networks.The self-attention mechanism captures correlations among globally sparse data,establishing dependencies b.etween sparse magnetometer readings.Concurrently,the Kolmogorov-Arnold Network,proficient in modeling implicit numerical relationships between data features,enhances the ability to learn subtle patterns.Comparative experiments validate the capability of the proposed method to precisely model magnetic dipoles,achieving maximum Root Mean Square Errors of 24.06 mA·m^(2)and 0.32 cm for size and location modeling,respectively.The spacecraft magnetic model established using this method accurately computes magnetic fields and alternating magnetic fields at designated surfaces or points.This approach facilitates the rapid and precise construction of individual and complete spacecraft magnetic models,enabling the verification of magnetic specifications from the spacecraft design phase.展开更多
This study integrates seismic and petrophysical data to evaluate the subsurface geology of the Keva Field,located onshore in the Niger Delta,with the objective of constructing a 3D geological model and estimating the ...This study integrates seismic and petrophysical data to evaluate the subsurface geology of the Keva Field,located onshore in the Niger Delta,with the objective of constructing a 3D geological model and estimating the recoverable hydrocarbon volumes.Seismic lines and well log data from six wells—KV-2,KV-3,KV-4,KV-5,KV-6,and KV-7—were utilized for the interpretation.The seismic profiles revealed that the KV-4 well is the only well drilled on the up-thrown side of a significant horst fault block,bounded by four major normal faults,while all the other wells penetrated the downthrown side.Petrophysical analysis identified three key reservoirs,C500,D200,and E900,which exhibit excellent reservoir quality with high net-to-gross ratios,good porosity,and high hydrocarbon saturation.The identified depositional environments are tidal-and fluvial-dominated shoreface settings,with sheet sands deposited in distributary splay systems.The C500,D200,and E900 reservoirs have Gas Initially in Place(GIIP)values of 156.37,28.44,and 27.89 BSCF,respectively,with corresponding Estimated Ultimate Recovery(EUR)values of 104.77,19.06,and 18.69 BSCF,respectively.The Stock Tank Original Oil in Place(STOOIP)values are 24.43,91.29,and 86.41 MMSTB,with EURs of 7.32,27.4,and 25.92 MMSTB,respectively.The combined GIIP is 212.72 BSCF with EUR of 142.52 BSCF,while the total STOOIP is 202.13 MMSTB with a recoverable volume of 60.64 MMSTB.The reservoirs present an average porosity of 22.62%,with gas saturation of 84.66%and oil saturation of 73%.The evaluated reservoir qualities suggest high potential for optimized hydrocarbon production.展开更多
Ferroptosis,an iron-dependent form of programmed cell death,has garnered significant attention in tumor research in recent years.Its core characteristics include aberrant accumulation of lipid peroxides and impairment...Ferroptosis,an iron-dependent form of programmed cell death,has garnered significant attention in tumor research in recent years.Its core characteristics include aberrant accumulation of lipid peroxides and impairment of antioxidant defense mechanisms,such as dysfunction of glutathione peroxidase 4.These fea-tures are closely intertwined with the initiation,progression,and therapeutic resistance of hepatocellular carcinoma(HCC).This review presents a systematic overview of the fundamental molecular mechanisms underlying ferroptosis,en-compassing iron metabolism,lipid metabolism,and the antioxidant system.Fur-thermore,it summarizes the potential applications of targeting ferroptosis in liver cancer treatment,including the mechanisms of action of anticancer agents(e.g.,sorafenib)and relevant ferroptosis-related enzymes.Against the backdrop of the growing potential of artificial intelligence(AI)in liver cancer research,various AI-based predictive models for liver cancer are being increasingly developed.On the one hand,this review examines the mechanisms of ferroptosis in HCC to explore novel early detection markers for liver cancer,to provide new insights for the development of AI-based early diagnostic models.On the other hand,it syn-thesizes the current research progress of existing liver cancer predictive models while summarizing key challenges that AI predictive models may encounter in the diagnosis and treatment of HCC.展开更多
High-volume fraction silicon particle-reinforced aluminium matrix composites(Si/Al)are increasingly applied in aerospace,radar communications,and large-scale integrated circuits because of their superior thermal condu...High-volume fraction silicon particle-reinforced aluminium matrix composites(Si/Al)are increasingly applied in aerospace,radar communications,and large-scale integrated circuits because of their superior thermal conductivity,wear resistance,and low thermal expansion coefficient.However,the abrasive and adhesive wear caused by the hard silicon reinforcement and the ductile aluminium matrix leads to significant tool wear,decreased machining efficiency,and compromised surface quality.This study combines theoretical analysis and cutting experiments to investigate polycrystalline diamond(PCD)tool wear during milling of 70 vol%Si/Al composite.A key contribution of this work is the development of a tool wear model that incorporates reinforcement particle characteristics,treating them as ellipsoidal structures,which enhances the accuracy of predicting abrasive and adhesive wear mechanisms.The model is based on abrasive and adhesive wear mechanisms,and can analyze the interaction between silicon particles,aluminium matrix,and tool components,thus providing deeper insights into PCD tool wear processes.Experimental validation of the model shows a good agreement with the results,with a mean deviation of approximately 10%.The findings on the tool wear mechanism reveal that,as tool wear progresses,the proportion of abrasive wear increases from 40%in the running-in stage to 75%in the rapid wear stage,while adhesive wear decreases.The optimal machining parameters of 120 m·min^(–1) cutting speed(v_(c))and 0.04 mm·z^(–1) feed rate(f_(z)),result in tool life of 33 min and surface roughness(S_(a))of 2.2μm.The study uncovers the variation patterns of abrasive and adhesive wear during the tool wear process,and the proposed model offers a robust framework for predicting tool wear during the machining of high-volume fraction Si/Al composites.The research findings also offer key insights for optimizing tool selection and machining parameters,advancing both the theoretical understanding and practical application of PCD tool wear.展开更多
In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and cha...In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.展开更多
The complex behaviors of expansive soils,particularly their volumetric changes driven by moisture variations,pose significant challenges in urban geotechnical engineering.Although vegetation-induced moisture changes a...The complex behaviors of expansive soils,particularly their volumetric changes driven by moisture variations,pose significant challenges in urban geotechnical engineering.Although vegetation-induced moisture changes are known to affect ground movement,quantitative characterization of tree–soil interactions remains limited due to insufficient field data and unclear relationships between tree water uptake and soil response.This study investigates the mechanical behavior of expansive clay soils influenced by two Lophostemon confertus samples during a 14-month field monitoring program in Melbourne,Australia.The research methodology integrates measurements of soil displacement,total soil suction,moisture content,and tree water consumption through instrumentation and monitoring systems.Field measurements suggest that tree roots reached the limits of their water extraction capacity when total soil suction exceeded 2880 kPa within the active root zone.The spatial extent of tree-induced soil desiccation reached 0.6–0.7 times the tree height laterally and penetrated to depths of 2.5–3.3 m vertically.The mature sample,with an 86%greater crown area and a threefold larger sapwood area,exhibited 142%higher water consumption(35 kL),demonstrating the scalability of tree–soil interaction mechanisms.A multiple linear regression model was developed to quantify the coupled relationships between soil movement and key variables,achieving a high adjusted R2 value of 0.97,which provides engineers and practitioners with a practical tool for estimating ground movement near trees.These findings offer valuable insights for infrastructure design in tree-adjacent environments and can inform computational models and design codes to enable more accurate site assessments and sustainable urban development.展开更多
Data-driven techniques are reshaping blast furnace iron-making process(BFIP)modeling,but their“black-box”nature often obscures interpretability and accuracy.To overcome these limitations,our mechanism and data co-dr...Data-driven techniques are reshaping blast furnace iron-making process(BFIP)modeling,but their“black-box”nature often obscures interpretability and accuracy.To overcome these limitations,our mechanism and data co-driven strategy(MDCDS)enhances model transparency and molten iron quality(MIQ)prediction.By zoning the furnace and applying mechanism-based features for material and thermal trends,coupled with a novel stationary broad feature learning system(StaBFLS),interference caused by nonstationary process characteristics are mitigated and the intrinsic information embedded in BFIP is mined.Subsequently,by integrating stationary feature representation with mechanism features,our temporal matching broad learning system(TMBLS)aligns process and quality variables using MIQ as the target.This integration allows us to establish process monitoring statistics using both mechanism and data-driven features,as well as detect modeling deviations.Validated against real-world BFIP data,our MDCDS model demonstrates consistent process alignment,robust feature extraction,and improved MIQ modeling—Yielding better fault detection.Additionally,we offer detailed insights into the validation process,including parameter baselining and optimization.展开更多
Kinetic impact is the most practical planetary-defense technique,with momentum-transfer efficiency central to deflection design.We present a Monte Carlo photometric framework that couples ejecta sampling,dynamical evo...Kinetic impact is the most practical planetary-defense technique,with momentum-transfer efficiency central to deflection design.We present a Monte Carlo photometric framework that couples ejecta sampling,dynamical evolution,and image synthesis to compare directly with HST,LICIACube,ground-based and Lucy observations of the DART impact.Decomposing ejecta into(1)a highvelocity(~1600 m/s)plume exhibiting Na/K resonance,(2)a low-velocity(~1 m/s)conical component shaped by binary gravity and solar radiation pressure,and(3)meter-scale boulders,we quantify each component’s mass and momentum.Fitting photometric decay curves and morphological evolution yields size-velocity distributions and,via scaling laws,estimates of Dimorphos’bulk density,cratering parameters,and cohesive strength that agree with dynamical constraints.Photometric ejecta modeling therefore provides a robust route to constrain momentum enhancement and target properties,improving predictive capability for kinetic-deflection missions.展开更多
Background:Wenqing Yin(WQY)is a classic prescription used to treat skin diseases like atopic dermatitis(AD)in China,and the aim of this study is to investigate the therapeutic effects and molecular mechanisms of WQY o...Background:Wenqing Yin(WQY)is a classic prescription used to treat skin diseases like atopic dermatitis(AD)in China,and the aim of this study is to investigate the therapeutic effects and molecular mechanisms of WQY on AD.Methods:The DNFB-induced mouse models of AD were established to investigate the therapeutic effects of WQY on AD.The symptoms of AD in the ears and backs of the mice were assessed,while inflammatory factors in the ear were quantified using quantitative real-time-polymerase chain reaction(qRT-PCR),and the percentages of CD4^(+)and CD8^(+)cells in the spleen were analyzed through flow cytometry.The compounds in WQY were identified using ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)analysis and the key targets and pathways of WQY to treat AD were predicted by network pharmacology.Subsequently,the key genes were tested and verified by qRT-PCR,and the potential active components and target proteins were verified by molecular docking.Results:WQY relieved the AD symptoms and histopathological injuries in the ear and back skin of mice with AD.Meanwhile,WQY significantly reduced the levels of inflammatory factors IL-6 and IL-1βin ear tissue,as well as the ratio of CD4^(+)/CD8^(+)cells in spleen.Additionally,a total of 142 compounds were identified from the water extract of WQY by UPLC-Orbitrap-MS/MS.39 key targets related to AD were screened out by network pharmacology methods.The KEGG analysis indicated that the effects of WQY were primarily mediated through pathways associated with Toll-like receptor signaling and T cell receptor signaling.Moreover,the results of qRT-PCR demonstrated that WQY significantly reduced the mRNA expressions of IL-4,IL-10,GATA3 and FOXP3,and molecular docking simulation verified that the active components of WQY had excellent binding abilities with IL-4,IL-10,GATA3 and FOXP3 proteins.Conclusion:The present study demonstrated that WQY effectively relieved AD symptoms in mice,decreased the inflammatory factors levels,regulated the balance of CD4^(+)and CD8^(+)cells,and the mechanism may be associated with the suppression of Th2 and Treg cell immune responses.展开更多
文摘A 3D crustal model was constructed using a combination of cutting-edge techniques,which were integrated to provide a density model for Egypt and address the sporadic distribution of seismic data.These techniques include obtaining gravity data from the Gravity Field and Steady-State Ocean Circulation Explorer(GOCE),creating seismic profiles,analyzing the receiver functions of seismic data,obtaining information from boreholes,and providing geological interpretations.GOCE satellite gravity data were processed to construct a preliminary model based on nonlinear inversions of the data.A regional crustal thickness model was developed using receiver functions,seismic refraction profiles,and geological insights.The inverted model was validated using borehole data and compared with seismic estimates.The model exhibited strong consistency and revealed a correlation between crustal thickness,geology,and tectonics of Egypt.It showed that the shallowest depths of the Moho are located in the north along the Mediterranean Sea and in the eastern part along the Red Sea,reflecting an oceanic plate with a thin,high-density crust.The deepest Moho depths are located in the southwestern part of Egypt,Red Sea coastal mountains,and Sinai Peninsula.The obtained 3D model of crustal thickness provided finely detailed Moho depth estimates that aligned closely with geology and tectonic characteristics of Egypt,contributing valuable insights into the subsurface structure and tectonic processes of region.
基金supported by the National Natural Science Foundation of China(Nos.12172315,12072304,11702232)the Fujian Provincial Natural Science Foundation,China(No.2021J01050)the Aeronautical Science Foundation of China(No.20220013068002).
文摘Unsteady aerodynamic characteristics at high angles of attack are of great importance to the design and development of advanced fighter aircraft, which are characterized by post-stall maneuverability with multiple Degrees-of-Freedom(multi-DOF) and complex flow field structure.In this paper, a special kind of cable-driven parallel mechanism is firstly utilized as a new suspension method to conduct unsteady dynamic wind tunnel tests at high angles of attack, thereby providing experimental aerodynamic data. These tests include a wide range of multi-DOF coupled oscillatory motions with various amplitudes and frequencies. Then, for aerodynamic modeling and analysis, a novel data-driven Feature-Level Attention Recurrent neural network(FLAR) is proposed. This model incorporates a specially designed feature-level attention module that focuses on the state variables affecting the aerodynamic coefficients, thereby enhancing the physical interpretability of the aerodynamic model. Subsequently, spin maneuver simulations, using a mathematical model as the baseline, are conducted to validate the effectiveness of the FLAR. Finally, the results on wind tunnel data reveal that the FLAR accurately predicts aerodynamic coefficients, and observations through the visualization of attention scores identify the key state variables that affect the aerodynamic coefficients. It is concluded that the proposed FLAR enhances the interpretability of the aerodynamic model while achieving good prediction accuracy and generalization capability for multi-DOF coupling motion at high angles of attack.
基金Supported by National High-quality Development Project of China(Grant No.2340STCZB193).
文摘The average stiffness performance indices throughout the workspace are commonly used as global stiffness performance indices to evaluate the overall stiffness performance of parallel mechanisms,which involves an analysis of the stiffness performance of numerous discrete points in the workspace.This necessitates time-consuming and inefficient calculation,which is particularly pronounced in the optimization design stage of the mechanism,where the variations in the global stiffness performance indices versus various dimensional and structural parameters need to be analyzed.This paper presents a semi-analytical approach for stiffness modeling of the novel(R(RPS&RP))&2-UPS parallel mechanism(referred to as the Trifree mechanism)and proposes“local”stiffness performance indices as alternatives to global indices.Drawing on the screw theory,the Cartesian stiffness matrix of the Trifree mechanism is formulated explicitly by considering the compliances of all elastic elements and the over-constraint characteristics inherent in the mechanism.Based on the spherical motion pattern of the Trifree mechanism,four special reference configurations are extracted within the workspace.This yields“local”stiffness performance indices capable of accurately evaluating the overall stiffness performance of the mechanism and effectively improving the computational efficiency.The variations in global and“local”stiffness performance indices versus key design parameters are investigated.Furthermore,the proposed indices are applied to the Tricept and Trimule mechanisms.The results demonstrate that the proposed indices exhibit excellent computational accuracy and efficiency in evaluating the overall stiffness performance of these spherical parallel mechanisms.Moreover,the stiffness performance of the novel parallel mechanism investigated in this study closely resembles that of the well-known Tricept and Trimule mechanisms.This research proposes a semi-analytic stiffness model of the Trifree mechanism and“local”stiffness performance indices to evaluate the overall stiffness performance,thereby substantially improving the computational efficiency without sacrificing accuracy.
基金funded by the National Key Research and Development Program of China(Grant No.2022YFB3402500)the National Natural Science Foundation of China(Grant No.12372129).
文摘Embedding optical fiber sensors into composite materials offers the advantage of real-time structural monitoring.However,there is an order-of-magnitude difference in diameter between optical fibers and reinforcing fibers,and the detailed mechanism of how embedded optical fibers affect the micromechanical behavior and damage failure processes within composite materials remains unclear.This paper presents a micromechanical simulation analysis of composite materials embedded with optical fibers.By constructing representative volume elements(RVEs)with randomly distributed reinforcing fibers,the optical fiber,the matrix,and the interface phase,the micromechanical behavior and damage evolution under transverse tensile and compressive loads are explored.The study finds that the presence of embedded optical fibers significantly influences the initiation and propagation of microscopic damage within the composites.Under transverse tension,the fiber-matrix interface cracks first,followed by plastic cracking in the matrix surrounding the fibers,forming micro-cracks.Eventually,these cracks connect with the debonded areas at the fiber-matrix interface to form a dominant crack that spans the entire model.Under transverse compression,plastic cracking first occurs in the resin surrounding the optical fibers,connecting with the interface debonding areas between the optical fibers and the matrix to form two parallel shear bands.Additionally,it is observed that the strength of the interface between the optical fiber and the matrix critically affects the simulation results.The simulated damage morphologies align closely with those observed using scanning electron microscopy(SEM).These findings offer theoretical insights that can inform the design and fabrication of smart composite materials with embedded optical fiber sensors for advanced structural health monitoring.
基金National Natural Science Foundation of China(22073023)Natural Science Foundation of Henan Province(242300421134)+1 种基金the Young Backbone Teacher in Colleges and Universities of Henan Province(2021GGJS020)Foundation of State Key Laboratory of Antiviral Drugs。
文摘The acetylpolyamine oxidase(APAO),spermine oxidase(SMO),and spermidine/spermine N1-acetyltransferase(SSAT)are pivotal enzymes in polyamine metabolism,exerting direct influence on polyamine homeostasis regulation.Dysfunctions in these enzymes are intricately linked to inflammatory diseases and cancers.Establishing their three-dimensional structures is essential for exploring enzymatic catalytic mechanisms and designing inhibitors at the atomic level.This article primarily assesses the precision of AlphaFold2 and molecular dynamics simulations in determining the three-dimensional structures of these enzymes,utilizing protein conformation rationality assessment,residue correlation matrix,and other techniques.This provides robust models for subsequent polyamine catabolic metabolism calculations and offers valuable insights for modeling proteins that have yet to acquire crystal structures.
基金Supported by Henan Province Science and Technology Research Project,No.232102310043Henan Provincial Science and Technology Research and Development Plan Joint Fund,No.222103810047Key Scientific Research Project Plan of Colleges and Universities in Henan Province,No.22A320033.
文摘BACKGROUND Colorectal cancer(CRC)remains a major global health burden due to its high incidence and mortality,with treatment efficacy often hindered by tumor hetero-geneity,drug resistance,and a complex tumor microenvironment(TME).Lactate metabolism plays a pivotal role in reshaping the TME,promoting immune eva-sion and epithelial-mesenchymal transition,making it a promising target for novel therapeutic strategies and prognostic modeling in CRC.AIM To offer an in-depth analysis of the role of lactate metabolism in CRC,high-lighting its significance in the TME and therapeutic response.METHODS Utilizing single-cell and transcriptomic data from the Gene Expression Omnibus and The Cancer Genome Atlas,we identified key lactate metabolic activities,particularly in the monocyte/macrophage subpopulation.RESULTS Seven lactate metabolism-associated genes were significantly linked to CRC prognosis and used to construct a predictive model.This model accurately forecasts patient outcomes and reveals notable distinct patterns of immune infiltration and transcriptomic profiles mutation profiles between high-and low-risk groups.High-risk patients demonstrated elevated immune cell infiltration,increased mutation frequencies,and heightened sensitivity to specific drugs(AZD6482,tozasertib,and SB216763),providing a foundation for personalized treatment approaches.Additionally,a nomogram integrating clinical and metabolic data effectively predicted 1-,3-,and 5-year survival rates.CONCLUSION This report underscored the pivotal mechanism of lactate metabolism in CRC prognosis and suggest novel avenues for therapeutic intervention.
基金supported by the steady supports scientific research of Key Laboratory of Defense Science and Technology,China(No.WDZC20220105)the National Natural Science Foundation of China(Nos.51775020,62073009,U20B2002)the Science Challenge Project,China(No.TZ2018007)。
文摘Thermal Protection System(TPS)with thick tiles,low thermal conductivity,and a short re-entry stage stands as a critical element within reusable aircraft,whose reliability is related to the function and changes with their physical properties,external conditions,and degradation.Meanwhile,due to the limitation of testing resources,epistemic uncertainties stemming from the small samples are present in TPS reliability modeling.However,current TPS reliability modeling methods face challenges in characterizing the relationships among reliability and physical properties,external conditions,degradation,and epistemic uncertainties.Therefore,under the framework of belief reliability theory,a TPS reliability model is constructed,which takes into account the physical principle,external conditions,performance degradation,and epistemic uncertainties.A reliability simulation algorithm is proposed to calculate TPS reliability.Through a case study and comparison analysis,the proposed method is validated as more effective than the existing method.Additionally,reliability sensitivity analysis is conducted to identify the sensitive factors of reliability under the condition of small samples,through which suggestions are provided for TPS functional design and improvement.
基金supported by the National Key Research and Development Program of China(2020YFC2200901)。
文摘As the complexity of scientific satellite missions increases,the requirements for their magnetic fields,magnetic field fluctuations,and even magnetic field gradients and variations become increasingly stringent.Additionally,there is a growing need to address the alternating magnetic fields produced by the spacecraft itself.This paper introduces a novel modeling method for spacecraft magnetic dipoles using an integrated self-attention mechanism and a transformer combined with Kolmogorov-Arnold Networks.The self-attention mechanism captures correlations among globally sparse data,establishing dependencies b.etween sparse magnetometer readings.Concurrently,the Kolmogorov-Arnold Network,proficient in modeling implicit numerical relationships between data features,enhances the ability to learn subtle patterns.Comparative experiments validate the capability of the proposed method to precisely model magnetic dipoles,achieving maximum Root Mean Square Errors of 24.06 mA·m^(2)and 0.32 cm for size and location modeling,respectively.The spacecraft magnetic model established using this method accurately computes magnetic fields and alternating magnetic fields at designated surfaces or points.This approach facilitates the rapid and precise construction of individual and complete spacecraft magnetic models,enabling the verification of magnetic specifications from the spacecraft design phase.
基金the support of African Union Commission through the Pan African University Life and Earth Sciences Institute(including Health and Agriculture),Ibadan,Nigeria,for funding this study。
文摘This study integrates seismic and petrophysical data to evaluate the subsurface geology of the Keva Field,located onshore in the Niger Delta,with the objective of constructing a 3D geological model and estimating the recoverable hydrocarbon volumes.Seismic lines and well log data from six wells—KV-2,KV-3,KV-4,KV-5,KV-6,and KV-7—were utilized for the interpretation.The seismic profiles revealed that the KV-4 well is the only well drilled on the up-thrown side of a significant horst fault block,bounded by four major normal faults,while all the other wells penetrated the downthrown side.Petrophysical analysis identified three key reservoirs,C500,D200,and E900,which exhibit excellent reservoir quality with high net-to-gross ratios,good porosity,and high hydrocarbon saturation.The identified depositional environments are tidal-and fluvial-dominated shoreface settings,with sheet sands deposited in distributary splay systems.The C500,D200,and E900 reservoirs have Gas Initially in Place(GIIP)values of 156.37,28.44,and 27.89 BSCF,respectively,with corresponding Estimated Ultimate Recovery(EUR)values of 104.77,19.06,and 18.69 BSCF,respectively.The Stock Tank Original Oil in Place(STOOIP)values are 24.43,91.29,and 86.41 MMSTB,with EURs of 7.32,27.4,and 25.92 MMSTB,respectively.The combined GIIP is 212.72 BSCF with EUR of 142.52 BSCF,while the total STOOIP is 202.13 MMSTB with a recoverable volume of 60.64 MMSTB.The reservoirs present an average porosity of 22.62%,with gas saturation of 84.66%and oil saturation of 73%.The evaluated reservoir qualities suggest high potential for optimized hydrocarbon production.
基金Supported by Henan Provincial Science and Technology Research Project,No.252102311168 and No.242102310066the Medical Education Research Project in Henan Province,No.WJLX2024153.
文摘Ferroptosis,an iron-dependent form of programmed cell death,has garnered significant attention in tumor research in recent years.Its core characteristics include aberrant accumulation of lipid peroxides and impairment of antioxidant defense mechanisms,such as dysfunction of glutathione peroxidase 4.These fea-tures are closely intertwined with the initiation,progression,and therapeutic resistance of hepatocellular carcinoma(HCC).This review presents a systematic overview of the fundamental molecular mechanisms underlying ferroptosis,en-compassing iron metabolism,lipid metabolism,and the antioxidant system.Fur-thermore,it summarizes the potential applications of targeting ferroptosis in liver cancer treatment,including the mechanisms of action of anticancer agents(e.g.,sorafenib)and relevant ferroptosis-related enzymes.Against the backdrop of the growing potential of artificial intelligence(AI)in liver cancer research,various AI-based predictive models for liver cancer are being increasingly developed.On the one hand,this review examines the mechanisms of ferroptosis in HCC to explore novel early detection markers for liver cancer,to provide new insights for the development of AI-based early diagnostic models.On the other hand,it syn-thesizes the current research progress of existing liver cancer predictive models while summarizing key challenges that AI predictive models may encounter in the diagnosis and treatment of HCC.
基金supported by the National Natural Science Foundation of China(Grant No.52075255)the Jiangsu Provincial Science and Technology Plan(Grant No.BZ2023005).
文摘High-volume fraction silicon particle-reinforced aluminium matrix composites(Si/Al)are increasingly applied in aerospace,radar communications,and large-scale integrated circuits because of their superior thermal conductivity,wear resistance,and low thermal expansion coefficient.However,the abrasive and adhesive wear caused by the hard silicon reinforcement and the ductile aluminium matrix leads to significant tool wear,decreased machining efficiency,and compromised surface quality.This study combines theoretical analysis and cutting experiments to investigate polycrystalline diamond(PCD)tool wear during milling of 70 vol%Si/Al composite.A key contribution of this work is the development of a tool wear model that incorporates reinforcement particle characteristics,treating them as ellipsoidal structures,which enhances the accuracy of predicting abrasive and adhesive wear mechanisms.The model is based on abrasive and adhesive wear mechanisms,and can analyze the interaction between silicon particles,aluminium matrix,and tool components,thus providing deeper insights into PCD tool wear processes.Experimental validation of the model shows a good agreement with the results,with a mean deviation of approximately 10%.The findings on the tool wear mechanism reveal that,as tool wear progresses,the proportion of abrasive wear increases from 40%in the running-in stage to 75%in the rapid wear stage,while adhesive wear decreases.The optimal machining parameters of 120 m·min^(–1) cutting speed(v_(c))and 0.04 mm·z^(–1) feed rate(f_(z)),result in tool life of 33 min and surface roughness(S_(a))of 2.2μm.The study uncovers the variation patterns of abrasive and adhesive wear during the tool wear process,and the proposed model offers a robust framework for predicting tool wear during the machining of high-volume fraction Si/Al composites.The research findings also offer key insights for optimizing tool selection and machining parameters,advancing both the theoretical understanding and practical application of PCD tool wear.
基金the World Climate Research Programme(WCRP),Climate Variability and Predictability(CLIVAR),and Global Energy and Water Exchanges(GEWEX)for facilitating the coordination of African monsoon researchsupport from the Center for Earth System Modeling,Analysis,and Data at the Pennsylvania State Universitythe support of the Office of Science of the U.S.Department of Energy Biological and Environmental Research as part of the Regional&Global Model Analysis(RGMA)program area。
文摘In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.
基金funded by the Australian Research Council via the ARC Linkage(Grant No.LP16160100649).
文摘The complex behaviors of expansive soils,particularly their volumetric changes driven by moisture variations,pose significant challenges in urban geotechnical engineering.Although vegetation-induced moisture changes are known to affect ground movement,quantitative characterization of tree–soil interactions remains limited due to insufficient field data and unclear relationships between tree water uptake and soil response.This study investigates the mechanical behavior of expansive clay soils influenced by two Lophostemon confertus samples during a 14-month field monitoring program in Melbourne,Australia.The research methodology integrates measurements of soil displacement,total soil suction,moisture content,and tree water consumption through instrumentation and monitoring systems.Field measurements suggest that tree roots reached the limits of their water extraction capacity when total soil suction exceeded 2880 kPa within the active root zone.The spatial extent of tree-induced soil desiccation reached 0.6–0.7 times the tree height laterally and penetrated to depths of 2.5–3.3 m vertically.The mature sample,with an 86%greater crown area and a threefold larger sapwood area,exhibited 142%higher water consumption(35 kL),demonstrating the scalability of tree–soil interaction mechanisms.A multiple linear regression model was developed to quantify the coupled relationships between soil movement and key variables,achieving a high adjusted R2 value of 0.97,which provides engineers and practitioners with a practical tool for estimating ground movement near trees.These findings offer valuable insights for infrastructure design in tree-adjacent environments and can inform computational models and design codes to enable more accurate site assessments and sustainable urban development.
基金supported in part by the National Natural Science Foundation of China(61933015,61703371,62273030)the Central University Basic Research Fund of China(K20200002)(for NGICS Platform,Zhejiang University)the Social Development Project of Zhejiang Provincial Public Technology Research(LGF19F030004,LGG21F030015).
文摘Data-driven techniques are reshaping blast furnace iron-making process(BFIP)modeling,but their“black-box”nature often obscures interpretability and accuracy.To overcome these limitations,our mechanism and data co-driven strategy(MDCDS)enhances model transparency and molten iron quality(MIQ)prediction.By zoning the furnace and applying mechanism-based features for material and thermal trends,coupled with a novel stationary broad feature learning system(StaBFLS),interference caused by nonstationary process characteristics are mitigated and the intrinsic information embedded in BFIP is mined.Subsequently,by integrating stationary feature representation with mechanism features,our temporal matching broad learning system(TMBLS)aligns process and quality variables using MIQ as the target.This integration allows us to establish process monitoring statistics using both mechanism and data-driven features,as well as detect modeling deviations.Validated against real-world BFIP data,our MDCDS model demonstrates consistent process alignment,robust feature extraction,and improved MIQ modeling—Yielding better fault detection.Additionally,we offer detailed insights into the validation process,including parameter baselining and optimization.
基金supported by the National Natural Science Foundation of China(Grant No.12272018)the National Key Basic Research Project(2022JCJQZD20600).
文摘Kinetic impact is the most practical planetary-defense technique,with momentum-transfer efficiency central to deflection design.We present a Monte Carlo photometric framework that couples ejecta sampling,dynamical evolution,and image synthesis to compare directly with HST,LICIACube,ground-based and Lucy observations of the DART impact.Decomposing ejecta into(1)a highvelocity(~1600 m/s)plume exhibiting Na/K resonance,(2)a low-velocity(~1 m/s)conical component shaped by binary gravity and solar radiation pressure,and(3)meter-scale boulders,we quantify each component’s mass and momentum.Fitting photometric decay curves and morphological evolution yields size-velocity distributions and,via scaling laws,estimates of Dimorphos’bulk density,cratering parameters,and cohesive strength that agree with dynamical constraints.Photometric ejecta modeling therefore provides a robust route to constrain momentum enhancement and target properties,improving predictive capability for kinetic-deflection missions.
基金supported by grants from the National Natural Science Foundation of China(82004252)the Project of Administration of Traditional Chinese Medicine of Guangdong Province(202405112017596500)the Basic and Applied Basic Research Foundation of Guangzhou Municipal Science and Technology Bureau(202102020533).
文摘Background:Wenqing Yin(WQY)is a classic prescription used to treat skin diseases like atopic dermatitis(AD)in China,and the aim of this study is to investigate the therapeutic effects and molecular mechanisms of WQY on AD.Methods:The DNFB-induced mouse models of AD were established to investigate the therapeutic effects of WQY on AD.The symptoms of AD in the ears and backs of the mice were assessed,while inflammatory factors in the ear were quantified using quantitative real-time-polymerase chain reaction(qRT-PCR),and the percentages of CD4^(+)and CD8^(+)cells in the spleen were analyzed through flow cytometry.The compounds in WQY were identified using ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)analysis and the key targets and pathways of WQY to treat AD were predicted by network pharmacology.Subsequently,the key genes were tested and verified by qRT-PCR,and the potential active components and target proteins were verified by molecular docking.Results:WQY relieved the AD symptoms and histopathological injuries in the ear and back skin of mice with AD.Meanwhile,WQY significantly reduced the levels of inflammatory factors IL-6 and IL-1βin ear tissue,as well as the ratio of CD4^(+)/CD8^(+)cells in spleen.Additionally,a total of 142 compounds were identified from the water extract of WQY by UPLC-Orbitrap-MS/MS.39 key targets related to AD were screened out by network pharmacology methods.The KEGG analysis indicated that the effects of WQY were primarily mediated through pathways associated with Toll-like receptor signaling and T cell receptor signaling.Moreover,the results of qRT-PCR demonstrated that WQY significantly reduced the mRNA expressions of IL-4,IL-10,GATA3 and FOXP3,and molecular docking simulation verified that the active components of WQY had excellent binding abilities with IL-4,IL-10,GATA3 and FOXP3 proteins.Conclusion:The present study demonstrated that WQY effectively relieved AD symptoms in mice,decreased the inflammatory factors levels,regulated the balance of CD4^(+)and CD8^(+)cells,and the mechanism may be associated with the suppression of Th2 and Treg cell immune responses.
