This paper presents a unified Unmanned Aerial Vehicle-based(UAV-based)traffic monitoring framework that integrates vehicle detection,tracking,counting,motion prediction,and classification in a modular and co-optimized...This paper presents a unified Unmanned Aerial Vehicle-based(UAV-based)traffic monitoring framework that integrates vehicle detection,tracking,counting,motion prediction,and classification in a modular and co-optimized pipeline.Unlike prior works that address these tasks in isolation,our approach combines You Only Look Once(YOLO)v10 detection,ByteTrack tracking,optical-flow density estimation,Long Short-Term Memory-based(LSTM-based)trajectory forecasting,and hybrid Speeded-Up Robust Feature(SURF)+Gray-Level Co-occurrence Matrix(GLCM)feature engineering with VGG16 classification.Upon the validation across datasets(UAVDT and UAVID)our framework achieved a detection accuracy of 94.2%,and 92.3%detection accuracy when conducting a real-time UAV field validation.Our comprehensive evaluations,including multi-metric analyses,ablation studies,and cross-dataset validations,confirm the framework’s accuracy,efficiency,and generalizability.These results highlight the novelty of integrating complementary methods into a single framework,offering a practical solution for accurate and efficient UAV-based traffic monitoring.展开更多
Underwater gas-liquid two-phase propulsion technology is an emerging propulsion method that offers high efficiency and unrestricted navigation speed.The integration of this technology into water ramjet engines can sig...Underwater gas-liquid two-phase propulsion technology is an emerging propulsion method that offers high efficiency and unrestricted navigation speed.The integration of this technology into water ramjet engines can significantly enhance propulsion efficiency and holds substantial potential for broad applications.However,forming a gas-liquid two-phase flow within the nozzle requires introducing a large amount of rammed seawater.At this time,there is a complex phase transition problem of combustion products in the combustion chamber,which makes the thermodynamic calculation for gas-liquid two-phase water ramjet engines particularly challenging.This paper proposes a thermodynamic calculation method for gas-liquid two-phase water ramjet engines,based on the energy equation for gas-liquid two-phase flow and traditional thermodynamic principles,enabling thermodynamic calculations under conditions of ultra-high water-fuel ratios.Additionally,ground ignition tests of the gas-liquid two-phase engine were conducted,yielding critical engine test parameters.The results demonstrate that the gas-liquid two-phase water ramjet engine achieves a high specific impulse,with a theoretical maximum specific impulse of up to 7000(N s)/kg.The multiphase flow effects significantly impact engine performance,with specific impulse losses reaching up to 25.86%.The error between the thrust and specific impulse in the ground test and the theoretical values is within 10%,validating the proposed thermodynamic calculation method as a reliable reference for further research on gas-liquid two-phase water ramjet engines.展开更多
In permafrost regions of the QinghaiXizang Plateau,embankments of the Qinghai-Xizang Highway and Qinghai-Xizang Railway experiencing roadside water accumulation exhibit more pronounced engineering deteriorations.A wid...In permafrost regions of the QinghaiXizang Plateau,embankments of the Qinghai-Xizang Highway and Qinghai-Xizang Railway experiencing roadside water accumulation exhibit more pronounced engineering deteriorations.A widely accepted view is that the accumulated water adjacent to the embankment possesses substantial thermal energy,which accelerates the degradation-even disappearance-of the underlying permafrost.Moreover,the presence of roadside water keeps the embankment soil in a persistently high-moisture state,thereby making the frozen-soil embankment more susceptible to deformation under traffic loading.However,in the permafrost regions of the QinghaiXizang Plateau,deteriorations of embankments affected by roadside water are more commonly manifested as undulating pavement surfaces,and extensive crack networks appear on the embankment crest even where thermosyphons are installed.These manifestations are not fully consistent with the deterioration mechanisms proposed by existing viewpoints.We propose the hypothesis that temperature gradients,formed due to the freezing and thawing processes between the roadside wateraffected soil and the roadbed soil,lead to moisture migration under the influence of temperature gradients,resulting in frost heave and thaw settlement in the roadbed soil.To validate this hypothesis,we conducted the following investigations sequentially.Initially,we selected a roadbed with a thermosyphon(TPCT)system,which has a significant cooling effect,as the study object.By analyzing the temperature monitoring data of the roadbed section,the temperature variance was calculated to identify the time nodes where the temperature gradient of the roadbed soil was maximum and minimum.Subsequently,corresponding roadbed temperature distribution maps were drawn,illustrating the changes in the temperature and position of the lowtemperature core near the TPCT over time.Furthermore,using small-scale indoor model experiments,we qualitatively concluded that moisture in the soil migrates toward the TPCT due to the temperature gradient.Thereafter,combining borehole water content data and precipitation data from the sloped terrain construction site,the formation mechanisms and timing characteristics of roadside water accumulation were analyzed.Ultimately,by integrating the ground temperature data,air temperature data,roadside water formation mechanisms,and the operating characteristics of the TPCT,it was concluded that roadside water,while in a thawed state during TPCT operation,acts as a supplementary source for moisture migration in the roadbed soil.This migration leads to cracking in the TPCT roadbed.Therefore,this study reveals a novel damage mechanism:asynchronous freeze-thaw processes induce temperature gradients,which drive the migration of roadside water into the roadbed and are responsible for the cracking damage.展开更多
This study investigates the droplet formation for the liquid–liquid two-phase flow within a square T-junction microchannel through numerical simulation using volume of fluid method and experimental visualization usin...This study investigates the droplet formation for the liquid–liquid two-phase flow within a square T-junction microchannel through numerical simulation using volume of fluid method and experimental visualization using high-speed camera imaging.The T-junction microchannel has a cross-sectional width of 0.6 mm and a total length of 27.3 mm.The solution of cyclohexane with 2%and 3%mass concentrations of sorbitan trioleate surfactant were used as the continuous phase,and water was used as the dispersed phase.Slug flow,characteristic of squeezing regime,were predominantly observed.The effects of liquid–liquid two-phase flow rate ratio,and dimensionless number on droplet size,and pressure drop were investigated.The squeezing regime was mapped for 0.0005≤Ca_(c)≤0.0052(capillary number)and 0.1≤q≤10(flow rate ratio).The pressure drops of slugs were in the range from 40 Pa to 200 Pa.The slug lengths were measured between 1 mm and 9 mm.A universal flow map dependent on Ca_(c)Re_(d)^(0.5) are projected to investigate the droplet formation behavior in T-junction microchannel.Correlation expressions are proposed to predict pressure drops and the slug lengths for liquid–liquid two-phase flow in a square T-junction microchannel,using dimensionless numbers such as flow rate ratio and capillary number.The result shows that large continuous phase flow rates facilitate smaller slugs,whereas higher dispersed phase flow rates result in longer shorts.展开更多
Deep-sea mineral resource transportation predominantly utilizes hydraulic pipeline methodology.Environmental factors induce vibrations in flexible pipelines,thereby affecting the internal flow characteristics.Therefor...Deep-sea mineral resource transportation predominantly utilizes hydraulic pipeline methodology.Environmental factors induce vibrations in flexible pipelines,thereby affecting the internal flow characteristics.Therefore,real-time monitoring of solid–liquid two-phase flow in pipelines is crucial for system maintenance.This study develops an autoencoder-based deep learning framework to reconstruct three-dimensional solid–liquid two-phase flow within flexible vibrating pipelines utilizing sparse wall information from sensors.Within this framework,separate X-model and F-model with distinct hidden-layer structures are established to reconstruct the coordinates and flow field information on the computational domain grid of the pipeline under traveling wave vibration.Following hyperparameter optimization,the models achieved high reconstruction accuracy,demonstrating R^(2)values of 0.990 and 0.945,respectively.The models’robustness is evaluated across three aspects:vibration parameters,physical fields,and vibration modes,demonstrating good reconstruction performance.Results concerning sensors show that 20 sensors(0.06%of total grids)achieve a balance between accuracy and cost,with superior accuracy obtained when arranged along the full length of the pipe compared to a dense arrangement at the front end.The models exhibited a signal-to-noise ratio tolerance of approximately 27 dB,with reconstruction accuracy being more affected by sensor failures at both ends of the pipeline.展开更多
The influence of the squeeze film between the tube and the support structure on flow-induced vibrations is a critical factor in tube bundles subjected to two-phase cross-flow.This aspect can significantly alter the th...The influence of the squeeze film between the tube and the support structure on flow-induced vibrations is a critical factor in tube bundles subjected to two-phase cross-flow.This aspect can significantly alter the threshold for fluidelastic instability and affect heat transfer efficiency.This paper presents a mathematical model incorporating the squeeze film force between the tube and the support structure.We aim to clarify the mechanisms underlying fluidelastic instability in tube bundle systems exposed to two-phase flow.Using a self-developed computer program,we performed numerical calculations to examine the influence of the squeeze film on the threshold of fluidelastic instability in the tube bundle system.Furthermore,we analyzed how the thickness and length of the squeeze film affect both the underlying mechanisms and the critical velocity of fluidelastic instability.展开更多
Clayey-silt natural gas hydrate reservoirs in the South China Sea exhibit loose and unconsolidated structures, heterogeneous pore structures, high clay mineral contents, and strong hydrophilicity. These characteristic...Clayey-silt natural gas hydrate reservoirs in the South China Sea exhibit loose and unconsolidated structures, heterogeneous pore structures, high clay mineral contents, and strong hydrophilicity. These characteristics complicate the gas-water two-phase flow process in porous media following hydrate decomposition, posing challenges for efficient development. This study examines the transport response of clayey-silt reservoir samples from the Shenhu area using gas-water two-phase flow experiments and CT scanning to explore changes in pore structure, gas-water distribution, and relative permeability under varying flow conditions. The results indicate that pore heterogeneity significantly influences flow characteristics. Gas preferentially displaces water in larger pores, forming fracture-like pores, which serve as preferential flow channels for gas migration. The preferential flow channels enhance gas-phase permeability up to 19 times that of the water phase when fluid pressures exceed total stresses. However,small pores retain liquid, leading to a high residual water saturation of 0.561. CT imaging reveals that these hydro-fractures improve gas permeability but also confine gas flow to specific channels. Pore network analysis shows that gas injection expands the pore-throat network, enhancing connectivity and forming fracture-like pores. Residual water remains trapped in smaller pores and throats, while structural changes, including new fractures, improve gas flow pathways and overall connectivity. Relative permeability curves demonstrate a narrow gas-water cocurrent-flow zone, a right-shifted iso-permeability point and high reservoir capillary pressure, indicating a strong "water-blocking" effect. The findings suggest that optimizing reservoir stimulation techniques to enhance fracture formation, reduce residual water saturation, and improve gas flow capacity is critical for efficient hydrate reservoir development.展开更多
This work investigated the dynamic behavior of vertical pipes conveying gas-liquid two-phase flow when subjected to external excitations at both ends.Even with minimal excitation amplitude,resonance can occur when the...This work investigated the dynamic behavior of vertical pipes conveying gas-liquid two-phase flow when subjected to external excitations at both ends.Even with minimal excitation amplitude,resonance can occur when the excitation frequency aligns with the natural frequency of the pipe,significantly increasing the degree of operational risk.The governing equation of motion based on the Euler-Bernoulli beam is derived for the relative deflection with stationary simply supported ends,with the effects of the external excitations represented by source terms distributed along the pipe length.The fourth-order partial differential equation is solved via the generalized integral transform technique(GITT),with the solution successfully verified via comparison with results in the literature.A comprehensive analysis of the vibration phenomena and changes in the motion state of the pipe is conducted for three classes of external excitation conditions:same frequency and amplitude(SFSA),same frequency but different amplitudes(SFDA),and different frequencies and amplitudes(DFDA).The numerical results show that with increasing gas volume fraction,the position corresponding to the maximum vibration displacement shifts upward.Compared with conditions without external excitation,the vibration displacement of the pipe conveying two-phase flow under external excitation increases significantly.The frequency of external excitation has a significant effect on the dynamic behavior of a pipe conveying two-phase flow.展开更多
Polymer flooding is an important means of improving oil recovery and is widely used in Daqing,Xinjiang,and Shengli oilfields,China.Different from conventional injection media such as water and gas,viscoelastic polymer...Polymer flooding is an important means of improving oil recovery and is widely used in Daqing,Xinjiang,and Shengli oilfields,China.Different from conventional injection media such as water and gas,viscoelastic polymer solutions exhibit non-Newtonian and nonlinear flow behavior including shear thinning and shear thickening,polymer convection,diffusion,adsorption,retention,inaccessible pore volume,and reduced effective permeability.However,available well test model of polymer flooding wells generally simplifies these characteristics on pressure transient response,which may lead to inaccurate results.This work proposes a novel two-phase numerical well test model to better describe the polymer viscoelasticity and nonlinear flow behavior.Different influence factors that related to near-well blockage during polymer flooding process,including the degree of blockage(inner zone permeability),the extent of blockage(composite radius),and polymer flooding front radius are explored to investigate these impacts on bottom hole pressure responses.Results show that polymer viscoelasticity has a significant impact on the transitional flow segment of type curves,and the effects of near-well formation blockage and polymer concentration distribution on well test curves are very similar.Thus,to accurately interpret the degree of near-well blockage in injection wells,it is essential to first eliminate the influence of polymer viscoelasticity.Finally,a field case is comprehensively analyzed and discussed to illustrate the applicability of the proposed model.展开更多
Cleat serves as the primary flow pathway for coalbed methane(CBM)and water.However,few studies consider the impact of local contact on two-phase flow within cleats.A visual generalized model of endogenous cleats was c...Cleat serves as the primary flow pathway for coalbed methane(CBM)and water.However,few studies consider the impact of local contact on two-phase flow within cleats.A visual generalized model of endogenous cleats was constructed based on microfluidics.A microscopic and mesoscopic observation technique was proposed to simultaneously capture gas-liquid interface morphology of pores and throat and the two-phase flow characteristics in entire cleat system.The local contact characteristics of cleats reduced absolute permeability,which resulted in a sharp increase in the starting pressure.The reduced gas flow capacity narrowed the co-infiltration area and decreased water saturation at the isotonic point in a hydrophilic environment.The increased local contact area of cleats weakened gas phase flow capacity and narrowed the co-infiltration area.Jumping events occurred in methane-water flow due to altered porosity caused by local contact in cleats.The distribution of residual phases changed the jumping direction on the micro-scale as well as the dominant channel on the mesoscale.Besides,jumping events caused additional energy dissipation,which was ignored in traditional two-phase flow models.This might contribute to the overestimation of relative permeability.The work provides new methods and insights for investigating unsaturated flow in complex porous media.展开更多
In this study, the three-dimensional non-premixed two-phase kerosene/air rotating detonation engines with different isolator configurations and throat area ratios are simulated by the Eulerian-Lagrangian method. The e...In this study, the three-dimensional non-premixed two-phase kerosene/air rotating detonation engines with different isolator configurations and throat area ratios are simulated by the Eulerian-Lagrangian method. The effects of the divergence, straight, and convergence isolators on the rotating detonation wave dynamics and the upstream oblique shock wave propagation mechanism are analyzed. The differences in the rotating detonation wave behaviors between ground and flight operations are clarified.The results indicate that the propagation regimes of the upstream oblique shock wave depend on the isolator configurations and operation conditions. With a divergence isolator, the airflow is accelerated throughout the isolator and divergence section, leading to a maximum Mach number(~1.8) before the normal shock. The total pressure loss reaches the largest, and the detonation pressure drops. The upstream oblique shock wave can be suppressed within the divergence section with the divergence isolator.However, for the straight and convergence isolators, the airflow in the isolator with a larger ψ_(1)(0.3 and0.4) can suffer from the disturbance of the upstream oblique shock wave. The critical incident angle is around 39° at ground operation conditions. The upstream oblique shock wave tends to be suppressed when the engine operates under flight operation conditions. The critical pressure ratio β_(cr0) is found to be able to help in distinguishing the propagation regimes of the upstream oblique shock wave. Slightly below or above the β_(cr0) can obtain different marginal propagation results. The high-speed airflow in the divergence section affects the fuel droplet penetration distance, which deteriorates the reactant mixing and the detonation area. Significant detonation velocity deficits are observed and the maximum velocity deficit reaches 26%. The results indicate the engine channel design should adopt different isolator configurations based on the purpose of total pressure loss or disturbance suppression. This study can provide useful guidance for the channel design of a more complete two-phase rotating detonation engine.展开更多
Two-phase partitioning bioreactors(TPPBs)have been widely used because they overcome the mass-transfer limitation of hydrophobic volatile organic compounds(VOCs)in waste gas biological treatments.Understanding the mec...Two-phase partitioning bioreactors(TPPBs)have been widely used because they overcome the mass-transfer limitation of hydrophobic volatile organic compounds(VOCs)in waste gas biological treatments.Understanding the mechanisms of mass-transfer enhancement in TPPBs would enable efficient predictions for further industrial applications.In this study,influences of gradually increasing silicone oil ratio on the TPPB was explored,and a 94.35%reduction of the n-hexane partition coefficient was observed with 0.1 vol.%silicone,which increased to 80.7%along with a 40-fold removal efficiency enhancement in the stabilised removal period.The elimination capacity increased from 1.47 to 148.35 g/(m^(3)·h),i.e.a 101-fold increase compared with that of the single-phase reactors,when 10 vol.%(3 Critical Micelle Concentration)silicone oil was added.The significantly promoted partition coefficient was the main reason for the mass transfer enhancement,which covered the negative influences of the decreased total mass-transfer coefficient with increasing silicone oil volume ratio.The gradually rising stirring rate was benefit to the n-hexane removal,which became negative when the dominant resistance shifted from mass transfer to biodegradation.Moreover,a mass-transfer-reaction kinetic model of the TPPB was constructed based on the balance of n-hexane concentration,dissolved oxygen and biomass.Similar to the mechanism,the partition factor was predicted sensitive to the removal performance,and another five sensitive parameters were found simultaneously.This forecasting method enables the optimisation of TPPB performance and provides theoretical support for hydrophobic VOCs degradation.展开更多
Existing weakly supervised semantic segmentation(WSSS)methods based on image-level labels always rely on class activation maps(CAMs),which measure the relationships between features and classifiers.However,CAMs only f...Existing weakly supervised semantic segmentation(WSSS)methods based on image-level labels always rely on class activation maps(CAMs),which measure the relationships between features and classifiers.However,CAMs only focus on the most discriminative regions of images,resulting in their poor coverage performance.We attribute this to the deficiency in the recognition ability of a single classifier and the negative impacts caused by magnitudes during the CAMs normalisation process.To address the aforementioned issues,we propose to construct selective multiple classifiers(SMC).During the training process,we extract multiple prototypes for each class and store them in the corresponding memory bank.These prototypes are divided into foreground and background prototypes,with the former used to identify foreground objects and the latter aimed at preventing the false activation of background pixels.As for the inference stage,multiple prototypes are adaptively selected from the memory bank for each image as SMC.Subsequently,CAMs are generated by measuring the angle between SMC and features.We enhance the recognition ability of classifiers by adaptively constructing multiple classifiers for each image,while only relying on angle measurement to generate CAMs can alleviate the suppression phenomenon caused by magnitudes.Furthermore,SMC can be integrated into other WSSS approaches to help generate better CAMs.Extensive experiments conducted on standard WSSS benchmarks such as PASCAL VOC 2012 and MS COCO 2014 demonstrate the superiority of our proposed method.展开更多
With the increasing miniaturization of systems and surging demand for power density,accurate prediction and control of two-phase flow pressure drop have become a core challenge restricting the performance of microchan...With the increasing miniaturization of systems and surging demand for power density,accurate prediction and control of two-phase flow pressure drop have become a core challenge restricting the performance of microchannel heat exchangers.Pressure drop,a critical hydraulic characteristic,serves as both a natural constraint for cooling systems and determines the power required to pump the working fluid through microchannels.This paper reviews the characteristics,prediction models,and optimization measures of two-phase flow pressure drop for low-boiling-point working fluids in microchannels.It systematically analyzes key influencing factors such as fluid physical properties,operating conditions,channel geometry,and flow patterns,and discusses the complex mechanisms of pressure drop under the coupling effect of multi-physical fields.Mainstream prediction models are reviewed:the homogeneous flow model simplifies calculations but shows large deviations at low quality;the separated flow model considers interphase interactions and can be applied to micro-scales after modification;the flow-pattern-based model performs zoned modeling but relies on subjective classification;machine learning improves prediction accuracy but faces the“black-box”problem.In terms of optimization,channel designs are improved through porous structures and micro-rib arrays,and flow rate distribution is optimized using splitters to balance pressure drop and heat transfer performance.This study provides theoretical support for microchannel thermal management in high-power-density devices.展开更多
Human Activity Recognition(HAR)in drone-captured videos has become popular because of the interest in various fields such as video surveillance,sports analysis,and human-robot interaction.However,recognizing actions f...Human Activity Recognition(HAR)in drone-captured videos has become popular because of the interest in various fields such as video surveillance,sports analysis,and human-robot interaction.However,recognizing actions from such videos poses the following challenges:variations of human motion,the complexity of backdrops,motion blurs,occlusions,and restricted camera angles.This research presents a human activity recognition system to address these challenges by working with drones’red-green-blue(RGB)videos.The first step in the proposed system involves partitioning videos into frames and then using bilateral filtering to improve the quality of object foregrounds while reducing background interference before converting from RGB to grayscale images.The YOLO(You Only Look Once)algorithm detects and extracts humans from each frame,obtaining their skeletons for further processing.The joint angles,displacement and velocity,histogram of oriented gradients(HOG),3D points,and geodesic Distance are included.These features are optimized using Quadratic Discriminant Analysis(QDA)and utilized in a Neuro-Fuzzy Classifier(NFC)for activity classification.Real-world evaluations on the Drone-Action,Unmanned Aerial Vehicle(UAV)-Gesture,and Okutama-Action datasets substantiate the proposed system’s superiority in accuracy rates over existing methods.In particular,the system obtains recognition rates of 93%for drone action,97%for UAV gestures,and 81%for Okutama-action,demonstrating the system’s reliability and ability to learn human activity from drone videos.展开更多
By combining with an improved model on engraving process,a two-phase flow interior ballistic model has been proposed to accurately predict the flow and energy conversion behaviors of pyrotechnic actuators.Using comput...By combining with an improved model on engraving process,a two-phase flow interior ballistic model has been proposed to accurately predict the flow and energy conversion behaviors of pyrotechnic actuators.Using computational fluid dynamics(CFD),the two-phase flow and piston engraving characteristics of a pyrotechnic actuator are investigated.Initially,the current model was utilized to examine the intricate,multi-dimensional flow,and energy conversion characteristics of the propellant grains and combustion gas within the pyrotechnic actuator chamber.It was discovered that the combustion gas on the wall's constant transition from potential to kinetic energy,along with the combined effect of the propellant motion,are what create the pressure oscillation within the chamber.Additionally,a numerical analysis was conducted to determine the impact of various parameters on the pressure oscillation and piston motion,including pyrotechnic charge,pyrotechnic particle size,and chamber structural dimension.The findings show that decreasing the pyrotechnic charge will lower the terminal velocity,while increasing and decreasing the pyrotechnic particle size will reduce the pressure oscillation in the chamber.The pyrotechnic particle size has minimal bearing on the terminal velocity.The results of this investigation offer a trustworthy forecasting instrument for comprehending and creating pyrotechnic actuator designs.展开更多
The exosomes hold significant potential in disease diagnosis and therapeutic interventions.The objective of this study was to investigate the potential of aqueous two-phase systems(ATPSs)for the separation of bovine m...The exosomes hold significant potential in disease diagnosis and therapeutic interventions.The objective of this study was to investigate the potential of aqueous two-phase systems(ATPSs)for the separation of bovine milk exosomes.The milk exosome partition behaviors and bovine milk separation were investigated,and the ATPSs and bovine milk whey addition was optimized.The optimal separation conditions were identified as 16%(mass)polyethylene glycol 4000,10%(mass)dipotassium phosphate,and 1%(mass)enzymatic hydrolysis bovine milk whey.During the separation process,bovine milk exosomes were predominantly enriched in the interphase,while protein impurities were primarily found in the bottom phase.The process yielded bovine milk exosomes of 2.0×10^(11)particles per ml whey with high purity(staining rate>90%,7.01×10^(10)particles per mg protein)and high uniformity(polydispersity index<0.03).The isolated exosomes were characterized and identified by transmission electron microscopy,zeta potential and size distribution.The results demonstrated aqueous two-phase extraction possesses a robust capability for the enrichment and separation of exosomes directly from bovine milk whey,presenting a novel approach for the large-scale isolation of exosomes.展开更多
Background:In the field of genetic diagnostics,DNA sequencing is an important tool because the depth and complexity of this field have major implications in light of the genetic architectures of diseases and the ident...Background:In the field of genetic diagnostics,DNA sequencing is an important tool because the depth and complexity of this field have major implications in light of the genetic architectures of diseases and the identification of risk factors associated with genetic disorders.Methods:Our study introduces a novel two-tiered analytical framework to raise the precision and reliability of genetic data interpretation.It is initiated by extracting and analyzing salient features from DNA sequences through a CNN-based feature analysis,taking advantage of the power inherent in Convolutional neural networks(CNNs)to attain complex patterns and minute mutations in genetic data.This study embraces an elite collection of machine learning classifiers interweaved through a stern voting mechanism,which synergistically joins the predictions made from multiple classifiers to generate comprehensive and well-balanced interpretations of the genetic data.Results:This state-of-the-art method was further tested by carrying out an empirical analysis on a variants'dataset of DNA sequences taken from patients affected by breast cancer,juxtaposed with a control group composed of healthy people.Thus,the integration of CNNs with a voting-based ensemble of classifiers returned outstanding outcomes,with performance metrics accuracy,precision,recall,and F1-scorereaching the outstanding rate of 0.88,outperforming previous models.Conclusions:This dual accomplishment underlines the transformative potential that integrating deep learning techniques with ensemble machine learning might provide in real added value for further genetic diagnostics and prognostics.These results from this study set a new benchmark in the accuracy of disease diagnosis through DNA sequencing and promise future studies on improved personalized medicine and healthcare approaches with precise genetic information.展开更多
As space technology advances,thermal control systems must effectively collect and dissipate heat from distributed,multi-source environments.Loop heat pipe is a highly reliable two-phase heat transfer component,but it ...As space technology advances,thermal control systems must effectively collect and dissipate heat from distributed,multi-source environments.Loop heat pipe is a highly reliable two-phase heat transfer component,but it has several limitations when addressing multi-source heat dissipation.Inspired by the transport and heat dissipation system of plants,large trees achieve stable and efficient liquid supply under the influence of two driving forces:capillary force during transpiration in the leaves(pull)and root pressure generated by osmotic pressure in the roots(push).The root pressure provides an effective liquid supply with a driving force exceeding 2 MPa,far greater than the driving force in conventional capillary-pumped two-phase loops.Research has shown that osmotic heat pipes offer a powerful driving force,and combining osmotic pressure with capillary force has significant advantages.Therefore,this paper designs a multi-evaporator,dual-drive two-phase loop,using both osmotic pressure and capillary force to solve the multi-source heat dissipation challenge.First,a transmembrane water flux model for the osmotic pressure-driven device was established to predict the maximum heat transfer capacity of the dual-drive two-phase loop.Then,an experimental setup for a multi-evaporator“osmotic pressure+capillary force”dual-drive two-phase loop was constructed,capable of transferring at least 235 W of power under a reverse gravity condition of 20 m.The study also analyzed the effects of reverse gravity height,heat load distribution among the three evaporators,startup sequence,and varying branch resistances on the performance of the dual-drive two-phase loop.展开更多
基金supported by the IITP(Institute of Information&Communications Technology Planning&Evaluation)-ICAN(ICT Challenge and Advanced Network of HRD)(IITP-2025-RS-2022-00156326,50)grant funded by theKorea government(Ministry of Science and ICT)supported and funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R410)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia。
文摘This paper presents a unified Unmanned Aerial Vehicle-based(UAV-based)traffic monitoring framework that integrates vehicle detection,tracking,counting,motion prediction,and classification in a modular and co-optimized pipeline.Unlike prior works that address these tasks in isolation,our approach combines You Only Look Once(YOLO)v10 detection,ByteTrack tracking,optical-flow density estimation,Long Short-Term Memory-based(LSTM-based)trajectory forecasting,and hybrid Speeded-Up Robust Feature(SURF)+Gray-Level Co-occurrence Matrix(GLCM)feature engineering with VGG16 classification.Upon the validation across datasets(UAVDT and UAVID)our framework achieved a detection accuracy of 94.2%,and 92.3%detection accuracy when conducting a real-time UAV field validation.Our comprehensive evaluations,including multi-metric analyses,ablation studies,and cross-dataset validations,confirm the framework’s accuracy,efficiency,and generalizability.These results highlight the novelty of integrating complementary methods into a single framework,offering a practical solution for accurate and efficient UAV-based traffic monitoring.
基金supported by the Stable Support Fund forBasic Disciplines,China(No.3072024WD0201)。
文摘Underwater gas-liquid two-phase propulsion technology is an emerging propulsion method that offers high efficiency and unrestricted navigation speed.The integration of this technology into water ramjet engines can significantly enhance propulsion efficiency and holds substantial potential for broad applications.However,forming a gas-liquid two-phase flow within the nozzle requires introducing a large amount of rammed seawater.At this time,there is a complex phase transition problem of combustion products in the combustion chamber,which makes the thermodynamic calculation for gas-liquid two-phase water ramjet engines particularly challenging.This paper proposes a thermodynamic calculation method for gas-liquid two-phase water ramjet engines,based on the energy equation for gas-liquid two-phase flow and traditional thermodynamic principles,enabling thermodynamic calculations under conditions of ultra-high water-fuel ratios.Additionally,ground ignition tests of the gas-liquid two-phase engine were conducted,yielding critical engine test parameters.The results demonstrate that the gas-liquid two-phase water ramjet engine achieves a high specific impulse,with a theoretical maximum specific impulse of up to 7000(N s)/kg.The multiphase flow effects significantly impact engine performance,with specific impulse losses reaching up to 25.86%.The error between the thrust and specific impulse in the ground test and the theoretical values is within 10%,validating the proposed thermodynamic calculation method as a reliable reference for further research on gas-liquid two-phase water ramjet engines.
基金supported by the Major Science and Technology Project of Gansu Province(Grant No.24ZD13FA003 and 23ZDWA005)National Natural Science Foundation of China(Grant No.42371140,42301163,41971087 and 42272332)the program of the State Key Laboratory of Cryospheric Science and Frozen Soil Engineering,CAS(No.CSFSEZZ-2411)。
文摘In permafrost regions of the QinghaiXizang Plateau,embankments of the Qinghai-Xizang Highway and Qinghai-Xizang Railway experiencing roadside water accumulation exhibit more pronounced engineering deteriorations.A widely accepted view is that the accumulated water adjacent to the embankment possesses substantial thermal energy,which accelerates the degradation-even disappearance-of the underlying permafrost.Moreover,the presence of roadside water keeps the embankment soil in a persistently high-moisture state,thereby making the frozen-soil embankment more susceptible to deformation under traffic loading.However,in the permafrost regions of the QinghaiXizang Plateau,deteriorations of embankments affected by roadside water are more commonly manifested as undulating pavement surfaces,and extensive crack networks appear on the embankment crest even where thermosyphons are installed.These manifestations are not fully consistent with the deterioration mechanisms proposed by existing viewpoints.We propose the hypothesis that temperature gradients,formed due to the freezing and thawing processes between the roadside wateraffected soil and the roadbed soil,lead to moisture migration under the influence of temperature gradients,resulting in frost heave and thaw settlement in the roadbed soil.To validate this hypothesis,we conducted the following investigations sequentially.Initially,we selected a roadbed with a thermosyphon(TPCT)system,which has a significant cooling effect,as the study object.By analyzing the temperature monitoring data of the roadbed section,the temperature variance was calculated to identify the time nodes where the temperature gradient of the roadbed soil was maximum and minimum.Subsequently,corresponding roadbed temperature distribution maps were drawn,illustrating the changes in the temperature and position of the lowtemperature core near the TPCT over time.Furthermore,using small-scale indoor model experiments,we qualitatively concluded that moisture in the soil migrates toward the TPCT due to the temperature gradient.Thereafter,combining borehole water content data and precipitation data from the sloped terrain construction site,the formation mechanisms and timing characteristics of roadside water accumulation were analyzed.Ultimately,by integrating the ground temperature data,air temperature data,roadside water formation mechanisms,and the operating characteristics of the TPCT,it was concluded that roadside water,while in a thawed state during TPCT operation,acts as a supplementary source for moisture migration in the roadbed soil.This migration leads to cracking in the TPCT roadbed.Therefore,this study reveals a novel damage mechanism:asynchronous freeze-thaw processes induce temperature gradients,which drive the migration of roadside water into the roadbed and are responsible for the cracking damage.
基金supports for this project from the National Natural Science Foundation of China(22378295).
文摘This study investigates the droplet formation for the liquid–liquid two-phase flow within a square T-junction microchannel through numerical simulation using volume of fluid method and experimental visualization using high-speed camera imaging.The T-junction microchannel has a cross-sectional width of 0.6 mm and a total length of 27.3 mm.The solution of cyclohexane with 2%and 3%mass concentrations of sorbitan trioleate surfactant were used as the continuous phase,and water was used as the dispersed phase.Slug flow,characteristic of squeezing regime,were predominantly observed.The effects of liquid–liquid two-phase flow rate ratio,and dimensionless number on droplet size,and pressure drop were investigated.The squeezing regime was mapped for 0.0005≤Ca_(c)≤0.0052(capillary number)and 0.1≤q≤10(flow rate ratio).The pressure drops of slugs were in the range from 40 Pa to 200 Pa.The slug lengths were measured between 1 mm and 9 mm.A universal flow map dependent on Ca_(c)Re_(d)^(0.5) are projected to investigate the droplet formation behavior in T-junction microchannel.Correlation expressions are proposed to predict pressure drops and the slug lengths for liquid–liquid two-phase flow in a square T-junction microchannel,using dimensionless numbers such as flow rate ratio and capillary number.The result shows that large continuous phase flow rates facilitate smaller slugs,whereas higher dispersed phase flow rates result in longer shorts.
基金financial support by the National Natural Science Foundation of China (Nos.52471293 and 12372270)the National Youth Science Foundation of China (Nos.52101322 and 52108375)+3 种基金the Program for Intergovernmental International S&T Cooperation Projects of Shanghai Municipality, China (Nos.24510711100 and 22160710200)The Oceanic Interdisciplinary Program of Shanghai Jiao Tong University (No.SL2022PT101)funded by the Open Fund of the State Key Laboratory of Coastal and Offshore Engineering of Dalian University of Technology (No.LP2415)National Key R&D Program of China (No.2023YFC2811600)
文摘Deep-sea mineral resource transportation predominantly utilizes hydraulic pipeline methodology.Environmental factors induce vibrations in flexible pipelines,thereby affecting the internal flow characteristics.Therefore,real-time monitoring of solid–liquid two-phase flow in pipelines is crucial for system maintenance.This study develops an autoencoder-based deep learning framework to reconstruct three-dimensional solid–liquid two-phase flow within flexible vibrating pipelines utilizing sparse wall information from sensors.Within this framework,separate X-model and F-model with distinct hidden-layer structures are established to reconstruct the coordinates and flow field information on the computational domain grid of the pipeline under traveling wave vibration.Following hyperparameter optimization,the models achieved high reconstruction accuracy,demonstrating R^(2)values of 0.990 and 0.945,respectively.The models’robustness is evaluated across three aspects:vibration parameters,physical fields,and vibration modes,demonstrating good reconstruction performance.Results concerning sensors show that 20 sensors(0.06%of total grids)achieve a balance between accuracy and cost,with superior accuracy obtained when arranged along the full length of the pipe compared to a dense arrangement at the front end.The models exhibited a signal-to-noise ratio tolerance of approximately 27 dB,with reconstruction accuracy being more affected by sensor failures at both ends of the pipeline.
基金financially supported by the National Natural Science Foundation of China(Grant No.12072336).
文摘The influence of the squeeze film between the tube and the support structure on flow-induced vibrations is a critical factor in tube bundles subjected to two-phase cross-flow.This aspect can significantly alter the threshold for fluidelastic instability and affect heat transfer efficiency.This paper presents a mathematical model incorporating the squeeze film force between the tube and the support structure.We aim to clarify the mechanisms underlying fluidelastic instability in tube bundle systems exposed to two-phase flow.Using a self-developed computer program,we performed numerical calculations to examine the influence of the squeeze film on the threshold of fluidelastic instability in the tube bundle system.Furthermore,we analyzed how the thickness and length of the squeeze film affect both the underlying mechanisms and the critical velocity of fluidelastic instability.
基金the National Natural Science Foundation of China (Nos. 42302143, 42172159)China Geological Survey Project (No. DD20211350)support from the G. Albert Shoemaker endowment
文摘Clayey-silt natural gas hydrate reservoirs in the South China Sea exhibit loose and unconsolidated structures, heterogeneous pore structures, high clay mineral contents, and strong hydrophilicity. These characteristics complicate the gas-water two-phase flow process in porous media following hydrate decomposition, posing challenges for efficient development. This study examines the transport response of clayey-silt reservoir samples from the Shenhu area using gas-water two-phase flow experiments and CT scanning to explore changes in pore structure, gas-water distribution, and relative permeability under varying flow conditions. The results indicate that pore heterogeneity significantly influences flow characteristics. Gas preferentially displaces water in larger pores, forming fracture-like pores, which serve as preferential flow channels for gas migration. The preferential flow channels enhance gas-phase permeability up to 19 times that of the water phase when fluid pressures exceed total stresses. However,small pores retain liquid, leading to a high residual water saturation of 0.561. CT imaging reveals that these hydro-fractures improve gas permeability but also confine gas flow to specific channels. Pore network analysis shows that gas injection expands the pore-throat network, enhancing connectivity and forming fracture-like pores. Residual water remains trapped in smaller pores and throats, while structural changes, including new fractures, improve gas flow pathways and overall connectivity. Relative permeability curves demonstrate a narrow gas-water cocurrent-flow zone, a right-shifted iso-permeability point and high reservoir capillary pressure, indicating a strong "water-blocking" effect. The findings suggest that optimizing reservoir stimulation techniques to enhance fracture formation, reduce residual water saturation, and improve gas flow capacity is critical for efficient hydrate reservoir development.
基金financially supported by the Key Research and Development Program of Shandong Province(Grant Nos.2022CXGC020405,2023CXGC010415 and 2025TSGCCZZB0238)the National Natural Science Foundation of China(Grant No.52171288)the financial support from CNPq,FAPERJ,ANP,Embrapii,and China National Petroleum Corporation(CNPC).
文摘This work investigated the dynamic behavior of vertical pipes conveying gas-liquid two-phase flow when subjected to external excitations at both ends.Even with minimal excitation amplitude,resonance can occur when the excitation frequency aligns with the natural frequency of the pipe,significantly increasing the degree of operational risk.The governing equation of motion based on the Euler-Bernoulli beam is derived for the relative deflection with stationary simply supported ends,with the effects of the external excitations represented by source terms distributed along the pipe length.The fourth-order partial differential equation is solved via the generalized integral transform technique(GITT),with the solution successfully verified via comparison with results in the literature.A comprehensive analysis of the vibration phenomena and changes in the motion state of the pipe is conducted for three classes of external excitation conditions:same frequency and amplitude(SFSA),same frequency but different amplitudes(SFDA),and different frequencies and amplitudes(DFDA).The numerical results show that with increasing gas volume fraction,the position corresponding to the maximum vibration displacement shifts upward.Compared with conditions without external excitation,the vibration displacement of the pipe conveying two-phase flow under external excitation increases significantly.The frequency of external excitation has a significant effect on the dynamic behavior of a pipe conveying two-phase flow.
基金supported by the National Natural Science Foundation of China(52104049)the Young Elite Scientist Sponsorship Program by Beijing Association for Science and Technology(BYESS2023262)。
文摘Polymer flooding is an important means of improving oil recovery and is widely used in Daqing,Xinjiang,and Shengli oilfields,China.Different from conventional injection media such as water and gas,viscoelastic polymer solutions exhibit non-Newtonian and nonlinear flow behavior including shear thinning and shear thickening,polymer convection,diffusion,adsorption,retention,inaccessible pore volume,and reduced effective permeability.However,available well test model of polymer flooding wells generally simplifies these characteristics on pressure transient response,which may lead to inaccurate results.This work proposes a novel two-phase numerical well test model to better describe the polymer viscoelasticity and nonlinear flow behavior.Different influence factors that related to near-well blockage during polymer flooding process,including the degree of blockage(inner zone permeability),the extent of blockage(composite radius),and polymer flooding front radius are explored to investigate these impacts on bottom hole pressure responses.Results show that polymer viscoelasticity has a significant impact on the transitional flow segment of type curves,and the effects of near-well formation blockage and polymer concentration distribution on well test curves are very similar.Thus,to accurately interpret the degree of near-well blockage in injection wells,it is essential to first eliminate the influence of polymer viscoelasticity.Finally,a field case is comprehensively analyzed and discussed to illustrate the applicability of the proposed model.
基金the financial support from the National Natural Science Foundation of China (No.42102127)the Postdoctoral Research Foundation of China (No.2024 M751860)。
文摘Cleat serves as the primary flow pathway for coalbed methane(CBM)and water.However,few studies consider the impact of local contact on two-phase flow within cleats.A visual generalized model of endogenous cleats was constructed based on microfluidics.A microscopic and mesoscopic observation technique was proposed to simultaneously capture gas-liquid interface morphology of pores and throat and the two-phase flow characteristics in entire cleat system.The local contact characteristics of cleats reduced absolute permeability,which resulted in a sharp increase in the starting pressure.The reduced gas flow capacity narrowed the co-infiltration area and decreased water saturation at the isotonic point in a hydrophilic environment.The increased local contact area of cleats weakened gas phase flow capacity and narrowed the co-infiltration area.Jumping events occurred in methane-water flow due to altered porosity caused by local contact in cleats.The distribution of residual phases changed the jumping direction on the micro-scale as well as the dominant channel on the mesoscale.Besides,jumping events caused additional energy dissipation,which was ignored in traditional two-phase flow models.This might contribute to the overestimation of relative permeability.The work provides new methods and insights for investigating unsaturated flow in complex porous media.
基金supported by the National Natural Science Foundation of China (Grant No. 12202204)the Natural Science Foundation of Jiangsu Province (Grant No. BK20220953)+1 种基金the Fundamental Research Funds for the Central Universitiesthe Science and Technology Association's Young Talent Nurturing Program of Jiangsu Province (Grant No. JSTJ-2024-004)
文摘In this study, the three-dimensional non-premixed two-phase kerosene/air rotating detonation engines with different isolator configurations and throat area ratios are simulated by the Eulerian-Lagrangian method. The effects of the divergence, straight, and convergence isolators on the rotating detonation wave dynamics and the upstream oblique shock wave propagation mechanism are analyzed. The differences in the rotating detonation wave behaviors between ground and flight operations are clarified.The results indicate that the propagation regimes of the upstream oblique shock wave depend on the isolator configurations and operation conditions. With a divergence isolator, the airflow is accelerated throughout the isolator and divergence section, leading to a maximum Mach number(~1.8) before the normal shock. The total pressure loss reaches the largest, and the detonation pressure drops. The upstream oblique shock wave can be suppressed within the divergence section with the divergence isolator.However, for the straight and convergence isolators, the airflow in the isolator with a larger ψ_(1)(0.3 and0.4) can suffer from the disturbance of the upstream oblique shock wave. The critical incident angle is around 39° at ground operation conditions. The upstream oblique shock wave tends to be suppressed when the engine operates under flight operation conditions. The critical pressure ratio β_(cr0) is found to be able to help in distinguishing the propagation regimes of the upstream oblique shock wave. Slightly below or above the β_(cr0) can obtain different marginal propagation results. The high-speed airflow in the divergence section affects the fuel droplet penetration distance, which deteriorates the reactant mixing and the detonation area. Significant detonation velocity deficits are observed and the maximum velocity deficit reaches 26%. The results indicate the engine channel design should adopt different isolator configurations based on the purpose of total pressure loss or disturbance suppression. This study can provide useful guidance for the channel design of a more complete two-phase rotating detonation engine.
基金supported by the National Key Research and Development Program of China(No.2022YFC3702000)the National Natural Science Foundation of China(No.52070169)the Project of Bureau of Science and Technology of Zhoushan,China(No.2022C41013).
文摘Two-phase partitioning bioreactors(TPPBs)have been widely used because they overcome the mass-transfer limitation of hydrophobic volatile organic compounds(VOCs)in waste gas biological treatments.Understanding the mechanisms of mass-transfer enhancement in TPPBs would enable efficient predictions for further industrial applications.In this study,influences of gradually increasing silicone oil ratio on the TPPB was explored,and a 94.35%reduction of the n-hexane partition coefficient was observed with 0.1 vol.%silicone,which increased to 80.7%along with a 40-fold removal efficiency enhancement in the stabilised removal period.The elimination capacity increased from 1.47 to 148.35 g/(m^(3)·h),i.e.a 101-fold increase compared with that of the single-phase reactors,when 10 vol.%(3 Critical Micelle Concentration)silicone oil was added.The significantly promoted partition coefficient was the main reason for the mass transfer enhancement,which covered the negative influences of the decreased total mass-transfer coefficient with increasing silicone oil volume ratio.The gradually rising stirring rate was benefit to the n-hexane removal,which became negative when the dominant resistance shifted from mass transfer to biodegradation.Moreover,a mass-transfer-reaction kinetic model of the TPPB was constructed based on the balance of n-hexane concentration,dissolved oxygen and biomass.Similar to the mechanism,the partition factor was predicted sensitive to the removal performance,and another five sensitive parameters were found simultaneously.This forecasting method enables the optimisation of TPPB performance and provides theoretical support for hydrophobic VOCs degradation.
基金supported by the National Natural Science Foundation of China(Grants 62176097,61433007)Fundamental Research Funds for the Central Universities(Grant 2019kfyXKJC024)the 111 Project on Computational Intelligence and Intelligent Control(Grant B18024).
文摘Existing weakly supervised semantic segmentation(WSSS)methods based on image-level labels always rely on class activation maps(CAMs),which measure the relationships between features and classifiers.However,CAMs only focus on the most discriminative regions of images,resulting in their poor coverage performance.We attribute this to the deficiency in the recognition ability of a single classifier and the negative impacts caused by magnitudes during the CAMs normalisation process.To address the aforementioned issues,we propose to construct selective multiple classifiers(SMC).During the training process,we extract multiple prototypes for each class and store them in the corresponding memory bank.These prototypes are divided into foreground and background prototypes,with the former used to identify foreground objects and the latter aimed at preventing the false activation of background pixels.As for the inference stage,multiple prototypes are adaptively selected from the memory bank for each image as SMC.Subsequently,CAMs are generated by measuring the angle between SMC and features.We enhance the recognition ability of classifiers by adaptively constructing multiple classifiers for each image,while only relying on angle measurement to generate CAMs can alleviate the suppression phenomenon caused by magnitudes.Furthermore,SMC can be integrated into other WSSS approaches to help generate better CAMs.Extensive experiments conducted on standard WSSS benchmarks such as PASCAL VOC 2012 and MS COCO 2014 demonstrate the superiority of our proposed method.
基金supported by the Beijing Municipal Science&Technology Commission(Z231100006123010).
文摘With the increasing miniaturization of systems and surging demand for power density,accurate prediction and control of two-phase flow pressure drop have become a core challenge restricting the performance of microchannel heat exchangers.Pressure drop,a critical hydraulic characteristic,serves as both a natural constraint for cooling systems and determines the power required to pump the working fluid through microchannels.This paper reviews the characteristics,prediction models,and optimization measures of two-phase flow pressure drop for low-boiling-point working fluids in microchannels.It systematically analyzes key influencing factors such as fluid physical properties,operating conditions,channel geometry,and flow patterns,and discusses the complex mechanisms of pressure drop under the coupling effect of multi-physical fields.Mainstream prediction models are reviewed:the homogeneous flow model simplifies calculations but shows large deviations at low quality;the separated flow model considers interphase interactions and can be applied to micro-scales after modification;the flow-pattern-based model performs zoned modeling but relies on subjective classification;machine learning improves prediction accuracy but faces the“black-box”problem.In terms of optimization,channel designs are improved through porous structures and micro-rib arrays,and flow rate distribution is optimized using splitters to balance pressure drop and heat transfer performance.This study provides theoretical support for microchannel thermal management in high-power-density devices.
基金funded by the Open Access Initiative of the University of Bremen and the DFG via SuUB Bremen.Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2024R348),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Human Activity Recognition(HAR)in drone-captured videos has become popular because of the interest in various fields such as video surveillance,sports analysis,and human-robot interaction.However,recognizing actions from such videos poses the following challenges:variations of human motion,the complexity of backdrops,motion blurs,occlusions,and restricted camera angles.This research presents a human activity recognition system to address these challenges by working with drones’red-green-blue(RGB)videos.The first step in the proposed system involves partitioning videos into frames and then using bilateral filtering to improve the quality of object foregrounds while reducing background interference before converting from RGB to grayscale images.The YOLO(You Only Look Once)algorithm detects and extracts humans from each frame,obtaining their skeletons for further processing.The joint angles,displacement and velocity,histogram of oriented gradients(HOG),3D points,and geodesic Distance are included.These features are optimized using Quadratic Discriminant Analysis(QDA)and utilized in a Neuro-Fuzzy Classifier(NFC)for activity classification.Real-world evaluations on the Drone-Action,Unmanned Aerial Vehicle(UAV)-Gesture,and Okutama-Action datasets substantiate the proposed system’s superiority in accuracy rates over existing methods.In particular,the system obtains recognition rates of 93%for drone action,97%for UAV gestures,and 81%for Okutama-action,demonstrating the system’s reliability and ability to learn human activity from drone videos.
基金supported by the National Natural Science Foundation of China(Grant No.11972194).
文摘By combining with an improved model on engraving process,a two-phase flow interior ballistic model has been proposed to accurately predict the flow and energy conversion behaviors of pyrotechnic actuators.Using computational fluid dynamics(CFD),the two-phase flow and piston engraving characteristics of a pyrotechnic actuator are investigated.Initially,the current model was utilized to examine the intricate,multi-dimensional flow,and energy conversion characteristics of the propellant grains and combustion gas within the pyrotechnic actuator chamber.It was discovered that the combustion gas on the wall's constant transition from potential to kinetic energy,along with the combined effect of the propellant motion,are what create the pressure oscillation within the chamber.Additionally,a numerical analysis was conducted to determine the impact of various parameters on the pressure oscillation and piston motion,including pyrotechnic charge,pyrotechnic particle size,and chamber structural dimension.The findings show that decreasing the pyrotechnic charge will lower the terminal velocity,while increasing and decreasing the pyrotechnic particle size will reduce the pressure oscillation in the chamber.The pyrotechnic particle size has minimal bearing on the terminal velocity.The results of this investigation offer a trustworthy forecasting instrument for comprehending and creating pyrotechnic actuator designs.
基金supported by the National Natural Science Foundation of China(22378350).
文摘The exosomes hold significant potential in disease diagnosis and therapeutic interventions.The objective of this study was to investigate the potential of aqueous two-phase systems(ATPSs)for the separation of bovine milk exosomes.The milk exosome partition behaviors and bovine milk separation were investigated,and the ATPSs and bovine milk whey addition was optimized.The optimal separation conditions were identified as 16%(mass)polyethylene glycol 4000,10%(mass)dipotassium phosphate,and 1%(mass)enzymatic hydrolysis bovine milk whey.During the separation process,bovine milk exosomes were predominantly enriched in the interphase,while protein impurities were primarily found in the bottom phase.The process yielded bovine milk exosomes of 2.0×10^(11)particles per ml whey with high purity(staining rate>90%,7.01×10^(10)particles per mg protein)and high uniformity(polydispersity index<0.03).The isolated exosomes were characterized and identified by transmission electron microscopy,zeta potential and size distribution.The results demonstrated aqueous two-phase extraction possesses a robust capability for the enrichment and separation of exosomes directly from bovine milk whey,presenting a novel approach for the large-scale isolation of exosomes.
文摘Background:In the field of genetic diagnostics,DNA sequencing is an important tool because the depth and complexity of this field have major implications in light of the genetic architectures of diseases and the identification of risk factors associated with genetic disorders.Methods:Our study introduces a novel two-tiered analytical framework to raise the precision and reliability of genetic data interpretation.It is initiated by extracting and analyzing salient features from DNA sequences through a CNN-based feature analysis,taking advantage of the power inherent in Convolutional neural networks(CNNs)to attain complex patterns and minute mutations in genetic data.This study embraces an elite collection of machine learning classifiers interweaved through a stern voting mechanism,which synergistically joins the predictions made from multiple classifiers to generate comprehensive and well-balanced interpretations of the genetic data.Results:This state-of-the-art method was further tested by carrying out an empirical analysis on a variants'dataset of DNA sequences taken from patients affected by breast cancer,juxtaposed with a control group composed of healthy people.Thus,the integration of CNNs with a voting-based ensemble of classifiers returned outstanding outcomes,with performance metrics accuracy,precision,recall,and F1-scorereaching the outstanding rate of 0.88,outperforming previous models.Conclusions:This dual accomplishment underlines the transformative potential that integrating deep learning techniques with ensemble machine learning might provide in real added value for further genetic diagnostics and prognostics.These results from this study set a new benchmark in the accuracy of disease diagnosis through DNA sequencing and promise future studies on improved personalized medicine and healthcare approaches with precise genetic information.
基金Science Foundation for Distinguished Young Scholars 2020-JCJQ-ZQ-042 Intelligent and Bionic Spacecraft Thermal Control Technology Inspired by Tree Sap Transport Principle.
文摘As space technology advances,thermal control systems must effectively collect and dissipate heat from distributed,multi-source environments.Loop heat pipe is a highly reliable two-phase heat transfer component,but it has several limitations when addressing multi-source heat dissipation.Inspired by the transport and heat dissipation system of plants,large trees achieve stable and efficient liquid supply under the influence of two driving forces:capillary force during transpiration in the leaves(pull)and root pressure generated by osmotic pressure in the roots(push).The root pressure provides an effective liquid supply with a driving force exceeding 2 MPa,far greater than the driving force in conventional capillary-pumped two-phase loops.Research has shown that osmotic heat pipes offer a powerful driving force,and combining osmotic pressure with capillary force has significant advantages.Therefore,this paper designs a multi-evaporator,dual-drive two-phase loop,using both osmotic pressure and capillary force to solve the multi-source heat dissipation challenge.First,a transmembrane water flux model for the osmotic pressure-driven device was established to predict the maximum heat transfer capacity of the dual-drive two-phase loop.Then,an experimental setup for a multi-evaporator“osmotic pressure+capillary force”dual-drive two-phase loop was constructed,capable of transferring at least 235 W of power under a reverse gravity condition of 20 m.The study also analyzed the effects of reverse gravity height,heat load distribution among the three evaporators,startup sequence,and varying branch resistances on the performance of the dual-drive two-phase loop.
