The aggregation/dispersion of ultrafine particles is of interest for both fundamental and practical perspective. These behaviors of ultrafine silica in flotagent solution and the heter coagulation of silica and alumin...The aggregation/dispersion of ultrafine particles is of interest for both fundamental and practical perspective. These behaviors of ultrafine silica in flotagent solution and the heter coagulation of silica and alumina were examined using particle size analyzer, electrokinetic potential, contact angle measurements. The flotation reagents have a pronounced effect on the aggregation or dispersion behaviors of ultrafine silica suspensions. Collector dodecylamine chloride renders silica surfaces hydrophobic and the aggregation between silica particles takes place. Modifier tripolyphosphate makes the silica surface completely hydrophilic and enhances the stability of silica suspension. These experimental results can be explained based on the extended DLVO theory by considering polar interfacial interaction between particle surfaces.展开更多
One-dimensional ensemble dispersion entropy(EDE1D)is an effective nonlinear dynamic analysis method for complexity measurement of time series.However,it is only restricted to assessing the complexity of one-di-mension...One-dimensional ensemble dispersion entropy(EDE1D)is an effective nonlinear dynamic analysis method for complexity measurement of time series.However,it is only restricted to assessing the complexity of one-di-mensional time series(TS1d)with the extracted complexity features only at a single scale.Aiming at these problems,a new nonlinear dynamic analysis method termed two-dimensional composite multi-scale ensemble Gramian dispersion entropy(CMEGDE_(2D))is proposed in this paper.First,the TS_(1D) is transformed into a two-dimensional image(I_(2D))by using Gramian angular fields(GAF)with more internal data structures and geometri features,which preserve the global characteristics and time dependence of vibration signals.Second,the I2D is analyzed at multiple scales through the composite coarse-graining method,which overcomes the limitation of a single scale and provides greater stability compared to traditional coarse-graining methods.Subsequently,a new fault diagnosis method of rolling bearing is proposed based on the proposed CMEGDE_(2D) for fault feature ex-traction and the chicken swarm algorithm optimized support vector machine(CsO-SvM)for fault pattern identification.The simulation signals and two data sets of rolling bearings are utilized to verify the effectiveness of the proposed fault diagnosis method.The results demonstrate that the proposed method has stronger dis-crimination ability,higher fault diagnosis accuracy and better stability than the other compared methods.展开更多
The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects,radiative transfer,and microphysical processes.However,previous studies have been mostly concerned with clouds,with...The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects,radiative transfer,and microphysical processes.However,previous studies have been mostly concerned with clouds,with limited studies on fog,particularly those that examine the combined influences of all key physical processes and their roles during fog evolution.As such,this study aims to conduct a comprehensive investigation by examining the relationships between relative dispersion and other microphysical variables,as well as the underlying microphysical and dynamic processes,based on field fog campaigns in polluted and clean conditions.In polluted fog,droplet concentrations are higher,leading to smaller droplets and increased dispersion.The correlation between dispersion and droplet volume-mean radius is positive in the polluted fog,but shifts to negative in clean fog.We attribute the difference to various microphysical processes like aerosol activation,condensation,collision-coalescence,and entrainment-mixing.In polluted fog,high aerosol concentrations,low supersaturations,and strong turbulence(entrainment-mixing)provide suitable conditions for the simultaneous occurrence of droplet condensation and aerosol activation,resulting in a positive correlation between dispersion and volume-mean radius,especially during the fog formation stage.In contrast,during the mature stage in clean fog,condensation is dominant with weak aerosol activation leading to a negative correlation between relative dispersion and volume-mean radius.The collision-coalescence process is more active in the mature stage,increasing radii and leading to the negative correlation between dispersion and volume-mean radius.This result sheds new light on understanding the relative dispersion and mechanisms in fog under different aerosol backgrounds.展开更多
Nanoparticle-reinforced Mg matrix composites(NPMMCs)capitalize on the synergistic properties of nanoparticles and Mg matrix,resulting in enhanced mechanical attributes compared to matrix.Nonetheless,effective high-tem...Nanoparticle-reinforced Mg matrix composites(NPMMCs)capitalize on the synergistic properties of nanoparticles and Mg matrix,resulting in enhanced mechanical attributes compared to matrix.Nonetheless,effective high-temperature dispersion of nanoparticles remains challenging.This study employs a molten salt dispersant(NaCl-KCl-MgCl_(2))effectively mitigating the oxidation and combustion of TiC nanoparticles(TiC_(np)).Compared with the atmosphere,the molten salt facilitates the pre-dispersion of TiC_(np)through thermal motion at elevated temperatures,thereby reducing agglomeration between the TiC_(np).Simultaneously,the molten salt effectively wets and disrupts the oxide layer on the surface of Mg melt,facilitating the wetting of TiC_(np)by the Mg melt.The successful incorporation of 3 vol.%TiC_(np)into the Mg matrix is achieved by utilizing molten salt,and the addition of TiC_(np)increases the viscosity of mg melt.Further dispersed by ultrasonic dispersion,the unique distribution of TiC_(np)within ring-like structures was obtained which was attributed to the increase of viscosity.As a configurational distribution,the ring-like TiC_(np)distribution morphology significantly enhances the mechanical properties of composites,as evidenced by an approximate 50%increase in compressive strength(UCS).展开更多
Recently,large-scale deep learning models have been increasingly adopted for point cloud classification.However,thesemethods typically require collecting extensive datasets frommultiple clients,which may lead to priva...Recently,large-scale deep learning models have been increasingly adopted for point cloud classification.However,thesemethods typically require collecting extensive datasets frommultiple clients,which may lead to privacy leaks.Federated learning provides an effective solution to data leakage by eliminating the need for data transmission,relying instead on the exchange of model parameters.However,the uneven distribution of client data can still affect the model’s ability to generalize effectively.To address these challenges,we propose a new framework for point cloud classification called Federated Dynamic Aggregation Selection Strategy-based Multi-Receptive Field Fusion Classification Framework(FDASS-MRFCF).Specifically,we tackle these challenges with two key innovations:(1)During the client local training phase,we propose a Multi-Receptive Field Fusion Classification Model(MRFCM),which captures local and global structures in point cloud data through dynamic convolution and multi-scale feature fusion,enhancing the robustness of point cloud classification.(2)In the server aggregation phase,we introduce a Federated Dynamic Aggregation Selection Strategy(FDASS),which employs a hybrid strategy to average client model parameters,skip aggregation,or reallocate local models to different clients,thereby balancing global consistency and local diversity.We evaluate our framework using the ModelNet40 and ShapeNetPart benchmarks,demonstrating its effectiveness.The proposed method is expected to significantly advance the field of point cloud classification in a secure environment.展开更多
This letter addresses challenges in the clinical translation of BIBR1532,a promising telomerase inhibitor,for the treatment of esophageal squamous cell carcinoma(ESCC).BIBR1532 exerts its anti-cancer effect by activat...This letter addresses challenges in the clinical translation of BIBR1532,a promising telomerase inhibitor,for the treatment of esophageal squamous cell carcinoma(ESCC).BIBR1532 exerts its anti-cancer effect by activating DNA damage response(ATR/CHK1 and ATM/CHK2)pathways and downregulating telomere-binding proteins.Although its therapeutic potential is limited by poor aqueous solubility,solid dispersion(SD)technology may overcome this obstacle.Systematic analysis using PubChem-derived simplified molecular input line entry system identifiers and artificial intelligence-driven FormulationDT platform evaluation(oral formulation feasibility index:0.38)revealed that the SD technology,with superior scalability(32 approved products by 2021)and lower production risks,outperforms lipid-based formulations as an optimal dissolution strategy.Material analysis revealed hydroxypropyl methylcellulose(HPMC)as the optimal carrier with lower hygroscopicity,higher temperature and no intestinal targeting,thus enabling ESCC therapy.HPMC-based SD enhances BIBR1532 solubility and bioavailability for effective ESCC treatment.Future studies should focus on pilot tests for SD fabrication.展开更多
Accurate estimation of photovoltaic(PV)parameters is essential for optimizing solar module perfor-mance and enhancing resource efficiency in renewable energy systems.This study presents a process innovation by introdu...Accurate estimation of photovoltaic(PV)parameters is essential for optimizing solar module perfor-mance and enhancing resource efficiency in renewable energy systems.This study presents a process innovation by introducing,for the first time,the Triangulation Topology Aggregation Optimizer(TTAO)integrated with parallel computing to address PV parameter estimation challenges.The effectiveness and robustness of TTAO are rigorously evaluated using two standard benchmark datasets(KC200GT and R.T.C.France solar cells)and a real-world dataset(Poly70W solar module)under single-,double-,and triple-diode configurations.Results show that TTAO consistently achieves superior accuracy by producing the lowest RMSE values and faster convergence compared to state-of-the-art metaheuristic algorithms.In addition,the integration of parallel computing significantly enhances computational efficiency,reducing execution time by up to 85%without compromising accuracy.Validation using real-world data further demonstrates TTAO’s adaptability and practical relevance in renewable energy systems,effectively bridging the gap between theoretical modeling and real-world implementation for PV system monitoring and optimization,contributing to climate mitigation through improved solar energy performance.展开更多
Oxide dispersion strengthened(ODS)alloys are extensively used owing to high thermostability and creep strength contributed from uniformly dispersed fine oxides particles.However,the existence of these strengthening pa...Oxide dispersion strengthened(ODS)alloys are extensively used owing to high thermostability and creep strength contributed from uniformly dispersed fine oxides particles.However,the existence of these strengthening particles also deteriorates the processability and it is of great importance to establish accurate processing maps to guide the thermomechanical processes to enhance the formability.In this study,we performed particle swarm optimization-based back propagation artificial neural network model to predict the high temperature flow behavior of 0.25wt%Al2O3 particle-reinforced Cu alloys,and compared the accuracy with that of derived by Arrhenius-type constitutive model and back propagation artificial neural network model.To train these models,we obtained the raw data by fabricating ODS Cu alloys using the internal oxidation and reduction method,and conducting systematic hot compression tests between 400 and800℃with strain rates of 10^(-2)-10 S^(-1).At last,processing maps for ODS Cu alloys were proposed by combining processing parameters,mechanical behavior,microstructure characterization,and the modeling results achieved a coefficient of determination higher than>99%.展开更多
Dispersion and aggregation of nanoparticles in aqueous solutions are important factors for safe application of nanoparticles. In this study, dispersion and aggregation of nano-TiO2 in aqueous solutions containing vari...Dispersion and aggregation of nanoparticles in aqueous solutions are important factors for safe application of nanoparticles. In this study, dispersion and aggregation of nano-TiO2 in aqueous solutions containing various anions were investigated. The influences of anion concentration and valence on the aggregation size, zeta potential and aggregation kinetics were individually investigated. Results showed that the zeta potential decreased from 19.8 to-41.4 mV when PO4^（3-） concentration was increased from 0 to 50 mg/L, while the corresponding average size of nano-TiO2 particles decreased from 613.2 to 540.3 nm. Both SO4^（2-） and NO3^-enhanced aggregation of nano-TiO2in solution. As SO4^（2-） concentration was increased from 0 to 500 mg/L, the zeta potential decreased from 19.8 to 1.4 mV, and aggregate sizes increased from 613.2 to 961.3 nm.The trend for NO3^- fluctuation was similar to that for SO4^（2-） although the range of variation for NO3^- was relatively narrow. SO4^（2-） and NO3^-accelerated the aggregation rapidly, while PO4^（3-） did so slowly. These findings facilitate the understanding of aggregation and dispersion mechanisms of nano-TiO2 in aqueous solutions in the presence of anions of interest.展开更多
Quantum chemical simulation calculation shows that kaolinite is cleaved to produce （001） and （001） basal planes. （001） plane is dominant by （[SiO4]） tetrahedral, which interacted easily with hydrogen ion or ot...Quantum chemical simulation calculation shows that kaolinite is cleaved to produce （001） and （001） basal planes. （001） plane is dominant by （[SiO4]） tetrahedral, which interacted easily with hydrogen ion or other positive ions by electrostatic forces or hydrogen bonding. （001） plane is dominant by （[AlO2（OH）4]）, which interacted easily with high negativity group such as -O-, -N-, F- etc. The apparent zeta potential and surface points of zero charge（PZC） are different for hard and soft kaolinites depending on their crystallinity index （HI）. The self-aggregation between edge and basal plane due to the electrostatic interactions may occur at acidic media. The dispersion of kaolinite particles at alkaline media may be attributed to the electrostatic repulsion between basal planes and/or edges. The aggregation or dispersion behavior is revealed by scan electron microscope and the transmittance measurements for the suspension of kaolinite particles.展开更多
A fascinating colloid phenomenon was observed in a specially designed template-assisted cell under an alternating electrical field. Most colloidal particles experienced the processes of aggregation, dispersion and cli...A fascinating colloid phenomenon was observed in a specially designed template-assisted cell under an alternating electrical field. Most colloidal particles experienced the processes of aggregation, dispersion and climbing up to the plateaus of the patterns pre-lithographed on the indium tin oxide glass as the frequency of the alternating electrical field increased. Two critical frequencies fcritl ≈ 15 kHz and fcrit2 ≈ 40 kHz, corresponding to the transitions of the colloid behaviour were observed. When f 〈 15 kHz, the particles were forced to aggregate along the grooves of the negative photoresist patterned template. When 15 kHz 〈 f 〈 40 kHz, the particle clusters became unstable and most particles started to disperse and were blocked by the fringes of the negative photoresist patterns. As the frequency increased to above 40 kHz, the majority of particles started to climb up to the plateaus of the patterns. Furthermore, the dynamics analysis for the behaviour of the colloids was given and we found out that positive or negative dielectrophoresis force, electrohydrodynamic force, particle-particle interactions and Brownian motion change with the frequency of the alternating electric field. Thus, changes of the related forces affect or control the behaviour of the colloids.展开更多
By using molecular dynamics simulations based on the classical mechanic method,the dispersion behavior of gasoline detergent in deposit aggregation system was investigated.The representative simulation relating to the...By using molecular dynamics simulations based on the classical mechanic method,the dispersion behavior of gasoline detergent in deposit aggregation system was investigated.The representative simulation relating to the deposit molecules and the gasoline detergent molecules with high market share were selected as the model compounds.The microscopic mechanism of dispersing function of gasoline detergent was revealed in detail.It was found that due to Einterac(depo-depo)>Einteraction(gaso-gaso)>Einteraction(gaso-depo),the deposits were driven to gradually aggregate themselves in the gasoline medium.The relative strong interaction between characteristic groups in detergent molecules and deposits could weaken the interaction between deposit aggregates,which mainly comes from the Van der Waals force,the electrostatic interaction,and the orbital interaction.In order to play the dispersing role of detergent,the main factor is to enhance the interaction between the gasoline detergent and the deposit appropriately from the viewpoint of molecular structure design.展开更多
We report dispersion property for femtosecond optical Kerr effect in the solutions of no-aggregation 16(trifluoro ethoxy1)vanadyl phthalocyanine in the wavelength range of 850-770 nm.The optical Kerr effect spectrum s...We report dispersion property for femtosecond optical Kerr effect in the solutions of no-aggregation 16(trifluoro ethoxy1)vanadyl phthalocyanine in the wavelength range of 850-770 nm.The optical Kerr effect spectrum shows a broad near-resonant enhancement on the third-order nonlinear optical response of the molecule.展开更多
A technology of mechanochemical treatment (MCT) is introduced to modify nanodiamond (ND) surface aiming to obtaining a stable suspension with well-dispersed ND particles in aqueous medium. ND investigated in this pape...A technology of mechanochemical treatment (MCT) is introduced to modify nanodiamond (ND) surface aiming to obtaining a stable suspension with well-dispersed ND particles in aqueous medium. ND investigated in this paper is a purified product of nanometer-sized diamond synthesized by explosive detonation. As obvious aggregation and sediment were observed when the sample was added into deionized water, it is crucial to conduct deaggregation and dispersion investigations. Amid a series of mechanical treatments, i.e. grinding, stirring, ultrasonic and classification, some reagents are introduced to modify the newly created surface during aggregates comminution. For the co-effects of mechanical forces and surfactants, the mean size of particles was reduced and a stable system containing ND with narrow size distribution was prepared. Mechanism of surface reaction and modification are discussed, while AFM, Zetasizer3000HS, XRD, XPS and FTIR are utilized for the analysis. The functional chemical structure of ND particle surface and surface electrical property changed during the modification processes, and the dispersion character and stability of suspension can consequently be improved.展开更多
Diesel engine technology innovation causes excessive soot accumulated in engine oil.Due to its detrimental effect on lubricant and diesel engine,improving the dispersibility of engine oil to restrain soot aggregation ...Diesel engine technology innovation causes excessive soot accumulated in engine oil.Due to its detrimental effect on lubricant and diesel engine,improving the dispersibility of engine oil to restrain soot aggregation efficiently is the key technique for formulations.In this study,the aggregation of soot and interaction between dispersant and soot were investigated by molecular dynamic simulation.It was found that the molecular interaction between the dispersant and the soot aggregation system had a significant influence on disrupting the soot aggregation.Bis-PIBSI was more beneficial to having more interaction sites with soot molecules,while the mono-PIBSI with a high proportion of polar groups had stronger interaction with soot molecules.According to the simulation result,suggestions for use of additives were proposed.Carbon black dispersancy test was exploited to verify the dispersion effect of different dispersants on carbon black.The results indicate that mono-PIBSI and bis-PIBSI added at suitable mixture ratio to lubricant could perform good dispersion ability.展开更多
In global navigation satellite system denial environment,cross-view geo-localization based on image retrieval presents an exceedingly critical visual localization solution for Unmanned Aerial Vehicle(UAV)systems.The e...In global navigation satellite system denial environment,cross-view geo-localization based on image retrieval presents an exceedingly critical visual localization solution for Unmanned Aerial Vehicle(UAV)systems.The essence of cross-view geo-localization resides in matching images containing the same geographical targets from disparate platforms,such as UAV-view and satellite-view images.However,images of the same geographical targets may suffer from occlusions and geometric distortions due to variations in the capturing platform,view,and timing.The existing methods predominantly extract features by segmenting feature maps,which overlook the holistic semantic distribution and structural information of objects,resulting in loss of image information.To address these challenges,dilated neighborhood attention Transformer is employed as the feature extraction backbone,and Multi-feature representations based on Multi-scale Hierarchical Contextual Aggregation(MMHCA)is proposed.In the proposed MMHCA method,the multiscale hierarchical contextual aggregation method is utilized to extract contextual information from local to global across various granularity levels,establishing feature associations of contextual information with global and local information in the image.Subsequently,the multi-feature representations method is utilized to obtain rich discriminative feature information,bolstering the robustness of model in scenarios characterized by positional shifts,varying distances,and scale ambiguities.Comprehensive experiments conducted on the extensively utilized University-1652 and SUES-200 benchmarks indicate that the MMHCA method surpasses the existing techniques.showing outstanding results in UAV localization and navigation.展开更多
Neurons are highly polarized cells with axons reaching over a meter long in adult humans.To survive and maintain their proper function,neurons depend on specific mechanisms that regulate spatiotemporal signaling and m...Neurons are highly polarized cells with axons reaching over a meter long in adult humans.To survive and maintain their proper function,neurons depend on specific mechanisms that regulate spatiotemporal signaling and metabolic events,which need to be carried out at the right place,time,and intensity.Such mechanisms include axonal transport,local synthesis,and liquid-liquid phase separations.Alterations and malfunctions in these processes are correlated to neurodegenerative diseases such as amyotrophic lateral sclerosis(ALS).展开更多
The rapid proliferation of electric vehicle(EV)charging infrastructure introduces critical cybersecurity vulnerabilities to power grids system.This study presents an innovative anomaly detection framework for EV charg...The rapid proliferation of electric vehicle(EV)charging infrastructure introduces critical cybersecurity vulnerabilities to power grids system.This study presents an innovative anomaly detection framework for EV charging stations,addressing the unique challenges posed by third-party aggregation platforms.Our approach integrates node equations-based on the parameter identification with a novel deep learning model,xDeepCIN,to detect abnormal data reporting indicative of aggregation attacks.We employ a graph-theoretic approach to model EV charging networks and utilize Markov Chain Monte Carlo techniques for accurate parameter estimation.The xDeepCIN model,incorporating a Compressed Interaction Network,has the ability to capture complex feature interactions in sparse,high-dimensional charging data.Experimental results on both proprietary and public datasets demonstrate significant improvements in anomaly detection performance,with F1-scores increasing by up to 32.3%for specific anomaly types compared to traditional methods,such as wide&deep and DeepFM(Factorization-Machine).Our framework exhibits robust scalability,effectively handling networks ranging from 8 to 85 charging points.Furthermore,we achieve real-time monitoring capabilities,with parameter identification completing within seconds for networks up to 1000 nodes.This research contributes to enhancing the security and reliability of renewable energy systems against evolving cyber threats,offering a comprehensive solution for safeguarding the rapidly expanding EV charging infrastructure.展开更多
As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy protection.Current research emphasizes data security and use...As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy protection.Current research emphasizes data security and user privacy concerns within smart grids.However,existing methods struggle with efficiency and security when processing large-scale data.Balancing efficient data processing with stringent privacy protection during data aggregation in smart grids remains an urgent challenge.This paper proposes an AI-based multi-type data aggregation method designed to enhance aggregation efficiency and security by standardizing and normalizing various data modalities.The approach optimizes data preprocessing,integrates Long Short-Term Memory(LSTM)networks for handling time-series data,and employs homomorphic encryption to safeguard user privacy.It also explores the application of Boneh Lynn Shacham(BLS)signatures for user authentication.The proposed scheme’s efficiency,security,and privacy protection capabilities are validated through rigorous security proofs and experimental analysis.展开更多
Fine particulatematter(PM_(2.5))samples were collected in two neighboring cities,Beijing and Baoding,China.High-concentration events of PM_(2.5) in which the average mass concentration exceeded 75μg/m^(3) were freque...Fine particulatematter(PM_(2.5))samples were collected in two neighboring cities,Beijing and Baoding,China.High-concentration events of PM_(2.5) in which the average mass concentration exceeded 75μg/m^(3) were frequently observed during the heating season.Dispersion Normalized Positive Matrix Factorization was applied for the source apportionment of PM_(2.5) as minimize the dilution effects of meteorology and better reflect the source strengths in these two cities.Secondary nitrate had the highest contribution for Beijing(37.3%),and residential heating/biomass burning was the largest for Baoding(27.1%).Secondary nitrate,mobile,biomass burning,district heating,oil combustion,aged sea salt sources showed significant differences between the heating and non-heating seasons in Beijing for same period(2019.01.10–2019.08.22)(Mann-Whitney Rank Sum Test P<0.05).In case of Baoding,soil,residential heating/biomass burning,incinerator,coal combustion,oil combustion sources showed significant differences.The results of Pearson correlation analysis for the common sources between the two cities showed that long-range transported sources and some sources with seasonal patterns such as oil combustion and soil had high correlation coefficients.Conditional Bivariate Probability Function(CBPF)was used to identify the inflow directions for the sources,and joint-PSCF(Potential Source Contribution Function)was performed to determine the common potential source areas for sources affecting both cities.These models facilitated a more precise verification of city-specific influences on PM_(2.5) sources.The results of this study will aid in prioritizing air pollution mitigation strategies during the heating season and strengthening air quality management to reduce the impact of downwind neighboring cities.展开更多
文摘The aggregation/dispersion of ultrafine particles is of interest for both fundamental and practical perspective. These behaviors of ultrafine silica in flotagent solution and the heter coagulation of silica and alumina were examined using particle size analyzer, electrokinetic potential, contact angle measurements. The flotation reagents have a pronounced effect on the aggregation or dispersion behaviors of ultrafine silica suspensions. Collector dodecylamine chloride renders silica surfaces hydrophobic and the aggregation between silica particles takes place. Modifier tripolyphosphate makes the silica surface completely hydrophilic and enhances the stability of silica suspension. These experimental results can be explained based on the extended DLVO theory by considering polar interfacial interaction between particle surfaces.
基金Supported by the National Natural Science Foundation of China(Grant No.51975004)the Outstanding Youth Fund of Universities in Anhui Province of China(Grant No.2022AH020032).
文摘One-dimensional ensemble dispersion entropy(EDE1D)is an effective nonlinear dynamic analysis method for complexity measurement of time series.However,it is only restricted to assessing the complexity of one-di-mensional time series(TS1d)with the extracted complexity features only at a single scale.Aiming at these problems,a new nonlinear dynamic analysis method termed two-dimensional composite multi-scale ensemble Gramian dispersion entropy(CMEGDE_(2D))is proposed in this paper.First,the TS_(1D) is transformed into a two-dimensional image(I_(2D))by using Gramian angular fields(GAF)with more internal data structures and geometri features,which preserve the global characteristics and time dependence of vibration signals.Second,the I2D is analyzed at multiple scales through the composite coarse-graining method,which overcomes the limitation of a single scale and provides greater stability compared to traditional coarse-graining methods.Subsequently,a new fault diagnosis method of rolling bearing is proposed based on the proposed CMEGDE_(2D) for fault feature ex-traction and the chicken swarm algorithm optimized support vector machine(CsO-SvM)for fault pattern identification.The simulation signals and two data sets of rolling bearings are utilized to verify the effectiveness of the proposed fault diagnosis method.The results demonstrate that the proposed method has stronger dis-crimination ability,higher fault diagnosis accuracy and better stability than the other compared methods.
基金supported by the Chinese National Natural Science Foundation under Grant Nos.(41975181,42325503,42375197,42575207,42205090)Y.LIU is supported by the U.S.Department of Energy’s Atmospheric System Research(ASR)program.
文摘The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects,radiative transfer,and microphysical processes.However,previous studies have been mostly concerned with clouds,with limited studies on fog,particularly those that examine the combined influences of all key physical processes and their roles during fog evolution.As such,this study aims to conduct a comprehensive investigation by examining the relationships between relative dispersion and other microphysical variables,as well as the underlying microphysical and dynamic processes,based on field fog campaigns in polluted and clean conditions.In polluted fog,droplet concentrations are higher,leading to smaller droplets and increased dispersion.The correlation between dispersion and droplet volume-mean radius is positive in the polluted fog,but shifts to negative in clean fog.We attribute the difference to various microphysical processes like aerosol activation,condensation,collision-coalescence,and entrainment-mixing.In polluted fog,high aerosol concentrations,low supersaturations,and strong turbulence(entrainment-mixing)provide suitable conditions for the simultaneous occurrence of droplet condensation and aerosol activation,resulting in a positive correlation between dispersion and volume-mean radius,especially during the fog formation stage.In contrast,during the mature stage in clean fog,condensation is dominant with weak aerosol activation leading to a negative correlation between relative dispersion and volume-mean radius.The collision-coalescence process is more active in the mature stage,increasing radii and leading to the negative correlation between dispersion and volume-mean radius.This result sheds new light on understanding the relative dispersion and mechanisms in fog under different aerosol backgrounds.
基金funded by the National Key Research&Development Program of China(grant no 2022YFB3705705)the National Natural Science Foundation of China(grant nos.52301142,52371107,52201115)+3 种基金the Heilongjiang Provincial Postdoctoral Science Foundation(grant no LBH-11Z22167)The Fundamental Research Funds for the Central Universities(grant no HIT.OCEF.2024035)The Science and Technology Innovation Program of Hunan Province(grant no 2022RC4012)The Shanxi Provincial Science and Technology Major Special Project plan of“Taking the lead in unveiling the list”[grant nos.202201050201012].
文摘Nanoparticle-reinforced Mg matrix composites(NPMMCs)capitalize on the synergistic properties of nanoparticles and Mg matrix,resulting in enhanced mechanical attributes compared to matrix.Nonetheless,effective high-temperature dispersion of nanoparticles remains challenging.This study employs a molten salt dispersant(NaCl-KCl-MgCl_(2))effectively mitigating the oxidation and combustion of TiC nanoparticles(TiC_(np)).Compared with the atmosphere,the molten salt facilitates the pre-dispersion of TiC_(np)through thermal motion at elevated temperatures,thereby reducing agglomeration between the TiC_(np).Simultaneously,the molten salt effectively wets and disrupts the oxide layer on the surface of Mg melt,facilitating the wetting of TiC_(np)by the Mg melt.The successful incorporation of 3 vol.%TiC_(np)into the Mg matrix is achieved by utilizing molten salt,and the addition of TiC_(np)increases the viscosity of mg melt.Further dispersed by ultrasonic dispersion,the unique distribution of TiC_(np)within ring-like structures was obtained which was attributed to the increase of viscosity.As a configurational distribution,the ring-like TiC_(np)distribution morphology significantly enhances the mechanical properties of composites,as evidenced by an approximate 50%increase in compressive strength(UCS).
基金supported in part by the National Key Research and Development Program of Chinaunder(Grant 2021YFB3101100)in part by the National Natural Science Foundation of Chinaunder(Grant 42461057),(Grant 62272123),and(Grant 42371470)+1 种基金in part by the Fundamental Research Program of Shanxi Province under(Grant 202303021212164)in part by the Postgraduate Education Innovation Program of Shanxi Province under(Grant 2024KY474).
文摘Recently,large-scale deep learning models have been increasingly adopted for point cloud classification.However,thesemethods typically require collecting extensive datasets frommultiple clients,which may lead to privacy leaks.Federated learning provides an effective solution to data leakage by eliminating the need for data transmission,relying instead on the exchange of model parameters.However,the uneven distribution of client data can still affect the model’s ability to generalize effectively.To address these challenges,we propose a new framework for point cloud classification called Federated Dynamic Aggregation Selection Strategy-based Multi-Receptive Field Fusion Classification Framework(FDASS-MRFCF).Specifically,we tackle these challenges with two key innovations:(1)During the client local training phase,we propose a Multi-Receptive Field Fusion Classification Model(MRFCM),which captures local and global structures in point cloud data through dynamic convolution and multi-scale feature fusion,enhancing the robustness of point cloud classification.(2)In the server aggregation phase,we introduce a Federated Dynamic Aggregation Selection Strategy(FDASS),which employs a hybrid strategy to average client model parameters,skip aggregation,or reallocate local models to different clients,thereby balancing global consistency and local diversity.We evaluate our framework using the ModelNet40 and ShapeNetPart benchmarks,demonstrating its effectiveness.The proposed method is expected to significantly advance the field of point cloud classification in a secure environment.
基金Supported by“Continuation”Project of Excellent Doctors,Guangdong Basic and Applied Basic Research Foundation,No.2025A04J5082Guangdong Basic and Applied Basic Research Foundation,No.2024A1515011236.
文摘This letter addresses challenges in the clinical translation of BIBR1532,a promising telomerase inhibitor,for the treatment of esophageal squamous cell carcinoma(ESCC).BIBR1532 exerts its anti-cancer effect by activating DNA damage response(ATR/CHK1 and ATM/CHK2)pathways and downregulating telomere-binding proteins.Although its therapeutic potential is limited by poor aqueous solubility,solid dispersion(SD)technology may overcome this obstacle.Systematic analysis using PubChem-derived simplified molecular input line entry system identifiers and artificial intelligence-driven FormulationDT platform evaluation(oral formulation feasibility index:0.38)revealed that the SD technology,with superior scalability(32 approved products by 2021)and lower production risks,outperforms lipid-based formulations as an optimal dissolution strategy.Material analysis revealed hydroxypropyl methylcellulose(HPMC)as the optimal carrier with lower hygroscopicity,higher temperature and no intestinal targeting,thus enabling ESCC therapy.HPMC-based SD enhances BIBR1532 solubility and bioavailability for effective ESCC treatment.Future studies should focus on pilot tests for SD fabrication.
基金funded by the Malaysian Ministry of Higher Education through the Fundamental Research Grant Scheme(FRGS/1/2024/ICT02/UCSI/02/1).
文摘Accurate estimation of photovoltaic(PV)parameters is essential for optimizing solar module perfor-mance and enhancing resource efficiency in renewable energy systems.This study presents a process innovation by introducing,for the first time,the Triangulation Topology Aggregation Optimizer(TTAO)integrated with parallel computing to address PV parameter estimation challenges.The effectiveness and robustness of TTAO are rigorously evaluated using two standard benchmark datasets(KC200GT and R.T.C.France solar cells)and a real-world dataset(Poly70W solar module)under single-,double-,and triple-diode configurations.Results show that TTAO consistently achieves superior accuracy by producing the lowest RMSE values and faster convergence compared to state-of-the-art metaheuristic algorithms.In addition,the integration of parallel computing significantly enhances computational efficiency,reducing execution time by up to 85%without compromising accuracy.Validation using real-world data further demonstrates TTAO’s adaptability and practical relevance in renewable energy systems,effectively bridging the gap between theoretical modeling and real-world implementation for PV system monitoring and optimization,contributing to climate mitigation through improved solar energy performance.
基金financial support of the National Natural Science Foundation of China(No.52371103)the Fundamental Research Funds for the Central Universities,China(No.2242023K40028)+1 种基金the Open Research Fund of Jiangsu Key Laboratory for Advanced Metallic Materials,China(No.AMM2023B01).financial support of the Research Fund of Shihezi Key Laboratory of AluminumBased Advanced Materials,China(No.2023PT02)financial support of Guangdong Province Science and Technology Major Project,China(No.2021B0301030005)。
文摘Oxide dispersion strengthened(ODS)alloys are extensively used owing to high thermostability and creep strength contributed from uniformly dispersed fine oxides particles.However,the existence of these strengthening particles also deteriorates the processability and it is of great importance to establish accurate processing maps to guide the thermomechanical processes to enhance the formability.In this study,we performed particle swarm optimization-based back propagation artificial neural network model to predict the high temperature flow behavior of 0.25wt%Al2O3 particle-reinforced Cu alloys,and compared the accuracy with that of derived by Arrhenius-type constitutive model and back propagation artificial neural network model.To train these models,we obtained the raw data by fabricating ODS Cu alloys using the internal oxidation and reduction method,and conducting systematic hot compression tests between 400 and800℃with strain rates of 10^(-2)-10 S^(-1).At last,processing maps for ODS Cu alloys were proposed by combining processing parameters,mechanical behavior,microstructure characterization,and the modeling results achieved a coefficient of determination higher than>99%.
基金supported by the International S&T Cooperation Program of China(No.2015DFG92750)the National Natural Science Foundation of China(No.51478172)the Department of Science and Technology of Hunan Province(No.2014GK1012)
文摘Dispersion and aggregation of nanoparticles in aqueous solutions are important factors for safe application of nanoparticles. In this study, dispersion and aggregation of nano-TiO2 in aqueous solutions containing various anions were investigated. The influences of anion concentration and valence on the aggregation size, zeta potential and aggregation kinetics were individually investigated. Results showed that the zeta potential decreased from 19.8 to-41.4 mV when PO4^（3-） concentration was increased from 0 to 50 mg/L, while the corresponding average size of nano-TiO2 particles decreased from 613.2 to 540.3 nm. Both SO4^（2-） and NO3^-enhanced aggregation of nano-TiO2in solution. As SO4^（2-） concentration was increased from 0 to 500 mg/L, the zeta potential decreased from 19.8 to 1.4 mV, and aggregate sizes increased from 613.2 to 961.3 nm.The trend for NO3^- fluctuation was similar to that for SO4^（2-） although the range of variation for NO3^- was relatively narrow. SO4^（2-） and NO3^-accelerated the aggregation rapidly, while PO4^（3-） did so slowly. These findings facilitate the understanding of aggregation and dispersion mechanisms of nano-TiO2 in aqueous solutions in the presence of anions of interest.
文摘Quantum chemical simulation calculation shows that kaolinite is cleaved to produce （001） and （001） basal planes. （001） plane is dominant by （[SiO4]） tetrahedral, which interacted easily with hydrogen ion or other positive ions by electrostatic forces or hydrogen bonding. （001） plane is dominant by （[AlO2（OH）4]）, which interacted easily with high negativity group such as -O-, -N-, F- etc. The apparent zeta potential and surface points of zero charge（PZC） are different for hard and soft kaolinites depending on their crystallinity index （HI）. The self-aggregation between edge and basal plane due to the electrostatic interactions may occur at acidic media. The dispersion of kaolinite particles at alkaline media may be attributed to the electrostatic repulsion between basal planes and/or edges. The aggregation or dispersion behavior is revealed by scan electron microscope and the transmittance measurements for the suspension of kaolinite particles.
基金Project supported by the National Natural Science Foundation of China (Grant Nos.10874153 and 50773003)the Science Foundation of Zhejiang Sci-Tech University of China,and the Innovation Research Project for Graduate Student of Zhejiang Province of China (Grant No.YK 2009051)
文摘A fascinating colloid phenomenon was observed in a specially designed template-assisted cell under an alternating electrical field. Most colloidal particles experienced the processes of aggregation, dispersion and climbing up to the plateaus of the patterns pre-lithographed on the indium tin oxide glass as the frequency of the alternating electrical field increased. Two critical frequencies fcritl ≈ 15 kHz and fcrit2 ≈ 40 kHz, corresponding to the transitions of the colloid behaviour were observed. When f 〈 15 kHz, the particles were forced to aggregate along the grooves of the negative photoresist patterned template. When 15 kHz 〈 f 〈 40 kHz, the particle clusters became unstable and most particles started to disperse and were blocked by the fringes of the negative photoresist patterns. As the frequency increased to above 40 kHz, the majority of particles started to climb up to the plateaus of the patterns. Furthermore, the dynamics analysis for the behaviour of the colloids was given and we found out that positive or negative dielectrophoresis force, electrohydrodynamic force, particle-particle interactions and Brownian motion change with the frequency of the alternating electric field. Thus, changes of the related forces affect or control the behaviour of the colloids.
基金This work was supported financially by the National Key Research and Development Program of China(No.2017YFB0306505)the SINOPEC research project(No.118023-1 and No.119026-2).
文摘By using molecular dynamics simulations based on the classical mechanic method,the dispersion behavior of gasoline detergent in deposit aggregation system was investigated.The representative simulation relating to the deposit molecules and the gasoline detergent molecules with high market share were selected as the model compounds.The microscopic mechanism of dispersing function of gasoline detergent was revealed in detail.It was found that due to Einterac(depo-depo)>Einteraction(gaso-gaso)>Einteraction(gaso-depo),the deposits were driven to gradually aggregate themselves in the gasoline medium.The relative strong interaction between characteristic groups in detergent molecules and deposits could weaken the interaction between deposit aggregates,which mainly comes from the Van der Waals force,the electrostatic interaction,and the orbital interaction.In order to play the dispersing role of detergent,the main factor is to enhance the interaction between the gasoline detergent and the deposit appropriately from the viewpoint of molecular structure design.
基金Supported in part by the National Natural Science Foundation of China.
文摘We report dispersion property for femtosecond optical Kerr effect in the solutions of no-aggregation 16(trifluoro ethoxy1)vanadyl phthalocyanine in the wavelength range of 850-770 nm.The optical Kerr effect spectrum shows a broad near-resonant enhancement on the third-order nonlinear optical response of the molecule.
文摘A technology of mechanochemical treatment (MCT) is introduced to modify nanodiamond (ND) surface aiming to obtaining a stable suspension with well-dispersed ND particles in aqueous medium. ND investigated in this paper is a purified product of nanometer-sized diamond synthesized by explosive detonation. As obvious aggregation and sediment were observed when the sample was added into deionized water, it is crucial to conduct deaggregation and dispersion investigations. Amid a series of mechanical treatments, i.e. grinding, stirring, ultrasonic and classification, some reagents are introduced to modify the newly created surface during aggregates comminution. For the co-effects of mechanical forces and surfactants, the mean size of particles was reduced and a stable system containing ND with narrow size distribution was prepared. Mechanism of surface reaction and modification are discussed, while AFM, Zetasizer3000HS, XRD, XPS and FTIR are utilized for the analysis. The functional chemical structure of ND particle surface and surface electrical property changed during the modification processes, and the dispersion character and stability of suspension can consequently be improved.
基金We gratefully acknowledge the support from the China Petrochemical Corporation funding(Sinopec Group,No.117022)on this work.
文摘Diesel engine technology innovation causes excessive soot accumulated in engine oil.Due to its detrimental effect on lubricant and diesel engine,improving the dispersibility of engine oil to restrain soot aggregation efficiently is the key technique for formulations.In this study,the aggregation of soot and interaction between dispersant and soot were investigated by molecular dynamic simulation.It was found that the molecular interaction between the dispersant and the soot aggregation system had a significant influence on disrupting the soot aggregation.Bis-PIBSI was more beneficial to having more interaction sites with soot molecules,while the mono-PIBSI with a high proportion of polar groups had stronger interaction with soot molecules.According to the simulation result,suggestions for use of additives were proposed.Carbon black dispersancy test was exploited to verify the dispersion effect of different dispersants on carbon black.The results indicate that mono-PIBSI and bis-PIBSI added at suitable mixture ratio to lubricant could perform good dispersion ability.
基金supported by the National Natural Science Foundation of China(Nos.12072027,62103052,61603346 and 62103379)the Henan Key Laboratory of General Aviation Technology,China(No.ZHKF-230201)+3 种基金the Funding for the Open Research Project of the Rotor Aerodynamics Key Laboratory,China(No.RAL20200101)the Key Research and Development Program of Henan Province,China(Nos.241111222000 and 241111222900)the Key Science and Technology Program of Henan Province,China(No.232102220067)the Scholarship Funding from the China Scholarship Council(No.202206030079).
文摘In global navigation satellite system denial environment,cross-view geo-localization based on image retrieval presents an exceedingly critical visual localization solution for Unmanned Aerial Vehicle(UAV)systems.The essence of cross-view geo-localization resides in matching images containing the same geographical targets from disparate platforms,such as UAV-view and satellite-view images.However,images of the same geographical targets may suffer from occlusions and geometric distortions due to variations in the capturing platform,view,and timing.The existing methods predominantly extract features by segmenting feature maps,which overlook the holistic semantic distribution and structural information of objects,resulting in loss of image information.To address these challenges,dilated neighborhood attention Transformer is employed as the feature extraction backbone,and Multi-feature representations based on Multi-scale Hierarchical Contextual Aggregation(MMHCA)is proposed.In the proposed MMHCA method,the multiscale hierarchical contextual aggregation method is utilized to extract contextual information from local to global across various granularity levels,establishing feature associations of contextual information with global and local information in the image.Subsequently,the multi-feature representations method is utilized to obtain rich discriminative feature information,bolstering the robustness of model in scenarios characterized by positional shifts,varying distances,and scale ambiguities.Comprehensive experiments conducted on the extensively utilized University-1652 and SUES-200 benchmarks indicate that the MMHCA method surpasses the existing techniques.showing outstanding results in UAV localization and navigation.
文摘Neurons are highly polarized cells with axons reaching over a meter long in adult humans.To survive and maintain their proper function,neurons depend on specific mechanisms that regulate spatiotemporal signaling and metabolic events,which need to be carried out at the right place,time,and intensity.Such mechanisms include axonal transport,local synthesis,and liquid-liquid phase separations.Alterations and malfunctions in these processes are correlated to neurodegenerative diseases such as amyotrophic lateral sclerosis(ALS).
基金supported by Jiangsu Provincial Science and Technology Project,grant number J2023124.Jing Guo received this grant,the URLs of sponsors’website is https://kxjst.jiangsu.gov.cn/(accessed on 06 June 2024).
文摘The rapid proliferation of electric vehicle(EV)charging infrastructure introduces critical cybersecurity vulnerabilities to power grids system.This study presents an innovative anomaly detection framework for EV charging stations,addressing the unique challenges posed by third-party aggregation platforms.Our approach integrates node equations-based on the parameter identification with a novel deep learning model,xDeepCIN,to detect abnormal data reporting indicative of aggregation attacks.We employ a graph-theoretic approach to model EV charging networks and utilize Markov Chain Monte Carlo techniques for accurate parameter estimation.The xDeepCIN model,incorporating a Compressed Interaction Network,has the ability to capture complex feature interactions in sparse,high-dimensional charging data.Experimental results on both proprietary and public datasets demonstrate significant improvements in anomaly detection performance,with F1-scores increasing by up to 32.3%for specific anomaly types compared to traditional methods,such as wide&deep and DeepFM(Factorization-Machine).Our framework exhibits robust scalability,effectively handling networks ranging from 8 to 85 charging points.Furthermore,we achieve real-time monitoring capabilities,with parameter identification completing within seconds for networks up to 1000 nodes.This research contributes to enhancing the security and reliability of renewable energy systems against evolving cyber threats,offering a comprehensive solution for safeguarding the rapidly expanding EV charging infrastructure.
基金supported by the National Key R&D Program of China(No.2023YFB2703700)the National Natural Science Foundation of China(Nos.U21A20465,62302457,62402444,62172292)+4 种基金the Fundamental Research Funds of Zhejiang Sci-Tech University(Nos.23222092-Y,22222266-Y)the Program for Leading Innovative Research Team of Zhejiang Province(No.2023R01001)the Zhejiang Provincial Natural Science Foundation of China(Nos.LQ24F020008,LQ24F020012)the Foundation of State Key Laboratory of Public Big Data(No.[2022]417)the“Pioneer”and“Leading Goose”R&D Program of Zhejiang(No.2023C01119).
文摘As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy protection.Current research emphasizes data security and user privacy concerns within smart grids.However,existing methods struggle with efficiency and security when processing large-scale data.Balancing efficient data processing with stringent privacy protection during data aggregation in smart grids remains an urgent challenge.This paper proposes an AI-based multi-type data aggregation method designed to enhance aggregation efficiency and security by standardizing and normalizing various data modalities.The approach optimizes data preprocessing,integrates Long Short-Term Memory(LSTM)networks for handling time-series data,and employs homomorphic encryption to safeguard user privacy.It also explores the application of Boneh Lynn Shacham(BLS)signatures for user authentication.The proposed scheme’s efficiency,security,and privacy protection capabilities are validated through rigorous security proofs and experimental analysis.
基金supported by the National Institute of Environmental Research(NIER)funded by the Ministry of Environment(No.NIER-2019-04-02-039)supported by Particulate Matter Management Specialized Graduate Program through the Korea Environmental Industry&Technology Institute(KEITI)funded by the Ministry of Environment(MOE).
文摘Fine particulatematter(PM_(2.5))samples were collected in two neighboring cities,Beijing and Baoding,China.High-concentration events of PM_(2.5) in which the average mass concentration exceeded 75μg/m^(3) were frequently observed during the heating season.Dispersion Normalized Positive Matrix Factorization was applied for the source apportionment of PM_(2.5) as minimize the dilution effects of meteorology and better reflect the source strengths in these two cities.Secondary nitrate had the highest contribution for Beijing(37.3%),and residential heating/biomass burning was the largest for Baoding(27.1%).Secondary nitrate,mobile,biomass burning,district heating,oil combustion,aged sea salt sources showed significant differences between the heating and non-heating seasons in Beijing for same period(2019.01.10–2019.08.22)(Mann-Whitney Rank Sum Test P<0.05).In case of Baoding,soil,residential heating/biomass burning,incinerator,coal combustion,oil combustion sources showed significant differences.The results of Pearson correlation analysis for the common sources between the two cities showed that long-range transported sources and some sources with seasonal patterns such as oil combustion and soil had high correlation coefficients.Conditional Bivariate Probability Function(CBPF)was used to identify the inflow directions for the sources,and joint-PSCF(Potential Source Contribution Function)was performed to determine the common potential source areas for sources affecting both cities.These models facilitated a more precise verification of city-specific influences on PM_(2.5) sources.The results of this study will aid in prioritizing air pollution mitigation strategies during the heating season and strengthening air quality management to reduce the impact of downwind neighboring cities.
