Artificial Intelligence(AI)in healthcare enables predicting diabetes using data-driven methods instead of the traditional ways of screening the disease,which include hemoglobin A1c(HbA1c),oral glucose tolerance test(O...Artificial Intelligence(AI)in healthcare enables predicting diabetes using data-driven methods instead of the traditional ways of screening the disease,which include hemoglobin A1c(HbA1c),oral glucose tolerance test(OGTT),and fasting plasma glucose(FPG)screening techniques,which are invasive and limited in scale.Machine learning(ML)and deep neural network(DNN)models that use large datasets to learn the complex,nonlinear feature interactions,but the conventional ML algorithms are data sensitive and often show unstable predictive accuracy.Conversely,DNN models are more robust,though the ability to reach a high accuracy rate consistently on heterogeneous datasets is still an open challenge.For predicting diabetes,this work proposed a hybrid DNN approach by integrating a bidirectional long short-term memory(BiLSTM)network with a bidirectional gated recurrent unit(BiGRU).A robust DL model,developed by combining various datasets with weighted coefficients,dense operations in the connection of deep layers,and the output aggregation using batch normalization and dropout functions to avoid overfitting.The goal of this hybrid model is better generalization and consistency among various datasets,which facilitates the effective management and early intervention.The proposed DNN model exhibits an excellent predictive performance as compared to the state-of-the-art and baseline ML and DNN models for diabetes prediction tasks.The robust performance indicates the possible usefulness of DL-based models in the development of disease prediction in healthcare and other areas that demand high-quality analytics.展开更多
Portable ratiometric fluorescent platforms have emerged as promising tools for multifarious detection,yet remain unexplored for point-of-care monitoring doxorubicin(DOX),one of clinically antineoplastic drugs.To this ...Portable ratiometric fluorescent platforms have emerged as promising tools for multifarious detection,yet remain unexplored for point-of-care monitoring doxorubicin(DOX),one of clinically antineoplastic drugs.To this end,we herein develop a portable self-calibrating platform namely carbon dots(C-dots)-embedded hydrogel sensors with a smartphone-assisted high-throughput imaging device,for DOX sensing.The prepared green-emitting(λ_(em)=508 nm)and negatively-charged C-dots(−11.40±1.21 mV),which have sufficient spectral overlap with the absorption band of DOX(∼500 nm),can strongly bind with positively-charged DOX molecules by electrostatic attraction effects.As a result,DOX molecules are selectively and rapid(20 s)determined with a detection limit of 10.26 nmol/L via Förster resonance energy transfer processes,demonstrating a remarkably chromatic shift from green to red.Further integrated with a 3D-printed smartphone-assisted device,the platform enabled high-throughput quantification,achieving recoveries of 96.40%-101.85%in human urine/serum(RSDs<2.94%,n=3).Notably,the dual linear detection ranges of the platform align with the reported clinical DOX concentrations in urine and plasma(0-4 h post-administration),validating their capability for direct quantification of DOX in clinical samples without special pre-treatment processes.By virtue of attractive analytical performances and robust feasibility,this platform bridges laboratory precision and point-of-care testing needs,offering promising potential for personalized chemotherapy and multiplexed analyte screening.展开更多
As one of the major volatile components in extraterrestrial materials,nitrogen(N_(2))isotopes serve not only as tracers for the formation and evolution of the solar system,but also play a critical role in assessing pl...As one of the major volatile components in extraterrestrial materials,nitrogen(N_(2))isotopes serve not only as tracers for the formation and evolution of the solar system,but also play a critical role in assessing planetary habitability and the search for extraterrestrial life.The integrated measurement of N_(2)and argon(Ar)isotopes by using noble gas mass spectrometry represents a state-of-the-art technique for such investigations.To support the growing demands of planetary science research in China,we have developed a high-efficiency,high-precision method for the integrated analysis of N_(2)and Ar isotopes.This was achieved by enhancing gas extraction and purification systems and integrating them with a static noble gas mass spectrometer.This method enables integrated N_(2)-Ar isotope measurements on submilligram samples,significantly improving sample utilization and reducing the impact of sample heterogeneity on volatile analysis.The system integrates CO_(2)laser heating,a modular two-stage Zr-Al getter pump,and a CuO furnace-based purification process,effectively reducing background levels(N_(2)blank as low as 0.35×10^(−6)cubic centimeters at standard temperature and pressure[ccSTP]).Analytical precision is ensured through calibration with atmospheric air and CO corrections.To validate the reliability of the method,we performed N_(2)-Ar isotope analyses on the Allende carbonaceous chondrite,one of the most extensively studied meteorites internationally.The measured N_(2)concentrations range from 19.2 to 29.8 ppm,withδ15N values between−44.8‰and−33.0‰.Concentrations of 40Ar,36Ar,and 38Ar are(12.5-21.1)×10^(−6)ccSTP/g,(90.9-150.3)×10^(−9)ccSTP/g,and(19.2-30.7)×10^(−9)ccSTP/g,respectively.These values correspond to cosmic-ray exposure ages of 4.5-5.7 Ma,consistent with previous reports.Step-heating experiments further reveal distinct release patterns of N and Ar isotopes,as well as their associations with specific mineral phases in the meteorite.In summary,the combined N_(2)-Ar isotopic system offers significant advantages for tracing volatile sources in extraterrestrial materials and will provide essential analytical support for upcoming Chinese planetary missions,such as Tianwen-2.展开更多
Sampling-based path planning is a popular methodology for robot path planning.With a uniform sampling strategy to explore the state space,a feasible path can be found without the complex geometric modeling of the conf...Sampling-based path planning is a popular methodology for robot path planning.With a uniform sampling strategy to explore the state space,a feasible path can be found without the complex geometric modeling of the configuration space.However,the quality of the initial solution is not guaranteed,and the convergence speed to the optimal solution is slow.In this paper,we present a novel image-based path planning algorithm to overcome these limitations.Specifically,a generative adversarial network(GAN)is designed to take the environment map(denoted as RGB image)as the input without other preprocessing works.The output is also an RGB image where the promising region(where a feasible path probably exists)is segmented.This promising region is utilized as a heuristic to achieve non-uniform sampling for the path planner.We conduct a number of simulation experiments to validate the effectiveness of the proposed method,and the results demonstrate that our method performs much better in terms of the quality of the initial solution and the convergence speed to the optimal solution.Furthermore,apart from the environments similar to the training set,our method also works well on the environments which are very different from the training set.展开更多
Blade Tip-Timing(BTT)has been regarded as a promising way of on-line blade vibration monitoring.But blind multi-band BTT vibration reconstruction is a big challenge under variable speeds and under-sampling.In order to...Blade Tip-Timing(BTT)has been regarded as a promising way of on-line blade vibration monitoring.But blind multi-band BTT vibration reconstruction is a big challenge under variable speeds and under-sampling.In order to deal with it,a novel Compressed Sensing(CS)method is proposed based on Multi-Coset Angular Sampling(MCAS)in this paper.First,multi-coset sampling scheme of BTT vibration signals is presented.Then the CS model of BTT vibration signals is derived in order domain.A sufficient condition of the number of BTT sensors is derived for perfect reconstruction and optimal placement of BTT sensors is determined by minimizing the condition number.In the end,numerical simulations are done to validate the proposed method and the performances of four reconstruction algorithms are compared,i.e.,Orthogonal Matching Pursuit(OMP),Multiple Signal Classification(MUSIC),Basis Pursuit Denoising(BPDN)and Modified Focal Underdetermined System Solver(MFOCUSS).Influences of the sensor placement,the number of BTT sensors and measurement noises on the reconstruction performances are also testified.The results demonstrate that the proposed method is feasible and the overall performance of the BPDN algorithm is the best among the four algorithms.Also the reconstruction performance decreases with the accelerations of rotating speed.展开更多
Three-dimensional printing(3DP)offers valuable insight into the characterization of natural rocks and the verification of theoretical models due to its high reproducibility and accurate replication of complex defects ...Three-dimensional printing(3DP)offers valuable insight into the characterization of natural rocks and the verification of theoretical models due to its high reproducibility and accurate replication of complex defects such as cracks and pores.In this study,3DP gypsum samples with different printing directions were subjected to a series of uniaxial compression tests with in situ micro-computed tomography(micro-CT)scanning to quantitatively investigate their mechanical anisotropic properties and damage evolution characteristics.Based on the two-dimensional(2D)CT images obtained at different scanning steps,a novel void ratio variable was derived using the mean value and variance of CT intensity.Additionally,a constitutive model was formulated incorporating the proposed damage variable,utilizing the void ratio variable.The crack evolution and crack morphology of 3DP gypsum samples were obtained and analyzed using the 3D models reconstructed from the CT images.The results indicate that 3DP gypsum samples exhibit mechanical anisotropic characteristics similar to those found in naturally sedimentary rocks.The mechanical anisotropy is attributed to the bedding planes formed between adjacent layers and pillar-like structures along the printing direction formed by CaSO_(4)·2H_(2)O crystals of needle-like morphology.The mean gray intensity of the voids has a positive linear relationship with the threshold value,while the CT variance and void ratio have concave and convex relationships,respectively.The constitutive model can effectively match the stress–strain curves obtained from uniaxial compression experiments.This study provides comprehensive explanations of the failure modes and anisotropic mechanisms of 3DP gypsum samples,which is important for characterizing and understanding the failure mechanism and microstructural evolution of 3DP rocks when modeling natural rock behavior.展开更多
Industrial data mining usually deals with data from different sources.These heterogeneous datasets describe the same object in different views.However,samples from some of the datasets may be lost.Then the remaining s...Industrial data mining usually deals with data from different sources.These heterogeneous datasets describe the same object in different views.However,samples from some of the datasets may be lost.Then the remaining samples do not correspond one-to-one correctly.Mismatched datasets caused by missing samples make the industrial data unavailable for further machine learning.In order to align the mismatched samples,this article presents a cooperative iteration matching method(CIMM)based on the modified dynamic time warping(DTW).The proposed method regards the sequentially accumulated industrial data as the time series.Mismatched samples are aligned by the DTW.In addition,dynamic constraints are applied to the warping distance of the DTW process to make the alignment more efficient.Then a series of models are trained with the cumulated samples iteratively.Several groups of numerical experiments on different missing patterns and missing locations are designed and analyzed to prove the effectiveness and the applicability of the proposed method.展开更多
As an emerging microscopic detection tool,quantum microscopes based on the principle of quantum precision measurement have attracted widespread attention in recent years.Compared with the imaging of classical light,qu...As an emerging microscopic detection tool,quantum microscopes based on the principle of quantum precision measurement have attracted widespread attention in recent years.Compared with the imaging of classical light,quantum-enhanced imaging can achieve ultra-high resolution,ultra-sensitive detection,and anti-interference imaging.Here,we introduce a quantum-enhanced scanning microscope under illumination of an entangled NOON state in polarization.For the phase imager with NOON states,we propose a simple four-basis projection method to replace the four-step phase-shifting method.We have achieved the phase imaging of micrometer-sized birefringent samples and biological cell specimens,with sensitivity close to the Heisenberg limit.The visibility of transmittance-based imaging shows a great enhancement for NOON states.Besides,we also demonstrate that the scanning imaging with NOON states enables the spatial resolution enhancement of√N compared with classical measurement.Our imaging method may provide some reference for the practical application of quantum imaging and is expected to promote the development of microscopic detection.展开更多
In this paper,an image processing algorithm which is able to synthesize material textures of arbitrary shapes is proposed.The presented approach uses an arbitrary image to construct a structure layer of the material.T...In this paper,an image processing algorithm which is able to synthesize material textures of arbitrary shapes is proposed.The presented approach uses an arbitrary image to construct a structure layer of the material.The resulting structure layer is then used to constrain the material texture synthesis.The field of second-moment matrices is used to represent the structure layer.Many tests with various constraint images are conducted to ensure that the proposed approach accurately reproduces the visual aspects of the input material sample.The results demonstrate that the proposed algorithm is able to accurately synthesize arbitrary-shaped material textures while respecting the local characteristics of the exemplar.This paves the way toward the synthesis of 3D material textures of arbitrary shapes from 2D material samples,which has a wide application range in virtual material design and materials characterization.展开更多
Geological samples often contain significant amounts of iron,which,although not typically the target element,can substantially interfere with the analysis of other elements of interest.To mitigate these interferences,...Geological samples often contain significant amounts of iron,which,although not typically the target element,can substantially interfere with the analysis of other elements of interest.To mitigate these interferences,amidoximebased radiation grafted adsorbents have been identified as effective for iron removal.In this study,an amidoximefunctionalized,radiation-grafted adsorbent synthesized from polypropylene waste(PPw-g-AO-10)was employed to remove iron from leached geological samples.The adsorption process was systematically optimized by investigating the effects of pH,contact time,adsorbent dosage,and initial ferric ion concentration.Under optimal conditions-pH1.4,a contact time of 90 min,and an initial ferric ion concentration of 4500 mg/L-the adsorbent exhibited a maximum iron adsorption capacity of 269.02 mg/g.After optimizing the critical adsorption parameters,the adsorbent was applied to the leached geological samples,achieving a 91%removal of the iron content.The adsorbent was regenerated through two consecutive cycles using 0.2 N HNO_(3),achieving a regeneration efficiency of 65%.These findings confirm the efficacy of the synthesized PPw-g-AO-10 as a cost-effective and eco-friendly adsorbent for successfully removing iron from leached geological matrices while maintaining a reasonable degree of reusability.展开更多
A lifespan prediction model was developed based on a few samples to provide decision-making information for operation and maintenance,as well as improve the economy and safety of nuclear power plant(NPP)operations.Thi...A lifespan prediction model was developed based on a few samples to provide decision-making information for operation and maintenance,as well as improve the economy and safety of nuclear power plant(NPP)operations.This paper applies a Weibull model to forecast the lifespan of electronic cards with a few samples in NPPs.Relationship between the lifespan prediction of electronic cards and the ambient temperature is revealed using the Arrhenius equation.Censored samples are used to compensate for the lack of fault electronic card data.Scale parameter and shape parameter of the Weibull model are optimized by adjusting the weight ratio between the censored data and the fault data.Characteristic life is then obtained using the rank regression fitting equation.Parameters of the Arrhenius equation can be calculated by dividing the samples into groups according to the ambient temperature.A case study of the intermediate range high-voltage electric card of ex-core neutron detectors demonstrates that the lifespan prediction of electronic cards in NPPs can be successfully predicted with a few samples by combining the Weibull model and the Arrhenius model.This can help provide preventive maintenance recommendations for electronic cards.Finally,operation suggestions for the electronic card’s ambient temperature can be made by utilizing the temperature-life model.展开更多
When the 2025 Intertextile Apparel Fabrics Exhibition(Autumn/Winter)was held in Shanghai,more than 3,700 top exhibitors from 26 countries and regions around the world participated.From September 2nd to 4th,the 2025&qu...When the 2025 Intertextile Apparel Fabrics Exhibition(Autumn/Winter)was held in Shanghai,more than 3,700 top exhibitors from 26 countries and regions around the world participated.From September 2nd to 4th,the 2025"Keqiao Selected"exhibition shone brightly at the event,showcasing the high-end quality of its products and the innovative strength of its regional brands.展开更多
The investigation of whether sediment samples contain representative grain size distribution information is important for the accurate extraction of sediment characteristics and conduct of related sedimentary record s...The investigation of whether sediment samples contain representative grain size distribution information is important for the accurate extraction of sediment characteristics and conduct of related sedimentary record studies.This study comparatively analyzed the numerical and qualitative differences and the degree of correlation of 36 sets of the characteristic parameters of surface sediment parallel sample grain size distribution from three sampling profiles at Jinsha Bay Beach in Zhanjiang,western Guangdong.At each sampling point,five parallel subsamples were established at intervals of 0,10,20,50,and 100 cm along the coastline.The research findings indicate the following:1)relatively large differences in the mean values of the different parallel samples(0.19–0.34Φ),with smaller differences observed in other characteristic grain sizes(D_(10),D_(50),and D_(90));2)small differences in characteristic values among various parallel sample grain size parameters,with at least 33%of the combinations of qualitative results showing inconsistency;3)50%of the regression equations between the skewness of different parallel samples displaying no significant correlation;4)relative deviations of−47.91%to 27.63%and−49.20%to 2.08%existing between the particle size parameters of a single sample and parallel samples(with the average obtained)at intervals of 10 and 50 cm,respectively.As such,small spatial differences,even within 100 cm,can considerably affect grain size parameters.Given the uncertain reasons underlying the representativeness of the samples,which may only cover the area immediately surrounding the sampling station,researchers are advised to design parallel sample collection strategies based on the spatiotemporal distribution characteristics of the parameters of interest during sediment sample collection.This study provides a typical case of the comparative analysis of parallel sample grain size parameters,with a focus on small spatial beach sediment,which contributes to the enhanced understanding of the accuracy and reliability of sediment sample collection strategies and extraction of grain size information.展开更多
Traditional sampling-based path planning algorithms,such as the rapidly-exploring random tree star(RRT^(*)),encounter critical limitations in unstructured orchard environments,including low sampling efficiency in narr...Traditional sampling-based path planning algorithms,such as the rapidly-exploring random tree star(RRT^(*)),encounter critical limitations in unstructured orchard environments,including low sampling efficiency in narrow passages,slow convergence,and high computational costs.To address these challenges,this paper proposes a novel hybrid global path planning algorithm integrating Gaussian sampling and quadtree optimization(RRT^(*)-GSQ).This methodology aims to enhance path planning by synergistically combining a Gaussian mixture sampling strategy to improve node generation in critical regions,an adaptive step-size and direction optimization mechanism for enhanced obstacle avoidance,a Quadtree-AABB collision detection framework to lower computational complexity,and a dynamic iteration control strategy for more efficient convergence.In obstacle-free and obstructed scenarios,compared with the conventional RRT^(*),the proposed algorithm reduced the number of node evaluations by 67.57%and 62.72%,and decreased the search time by 79.72%and 78.52%,respectively.In path tracking tests,the proposed algorithm achieved substantial reductions in RMSE of the final path compared to the conventional RRT^(*).Specifically,the lateral RMSE was reduced by 41.5%in obstacle-free environments and 59.3%in obstructed environments,while the longitudinal RMSE was reduced by 57.2%and 58.5%,respectively.Furthermore,the maximum absolute errors in both lateral and longitudinal directions were constrained within 0.75 m.Field validation experiments in an operational orchard confirmed the algorithm's practical effectiveness,showing reductions in the mean tracking error of 47.6%(obstacle-free)and 58.3%(with obstructed),alongside a 5.1%and 7.2%shortening of the path length compared to the baseline method.The proposed algorithm effectively enhances path planning efficiency and navigation accuracy for robots,presenting a superior solution for high-precision autonomous navigation of agricultural robots in orchard environments and holding significant value for engineering applications.展开更多
Large in-stream wood (LW) is a critical component of riparian systems that increases heterogeneity of flow regimes and provides high quality habitat for salmonids and other fishes. We present four sampling-based ...Large in-stream wood (LW) is a critical component of riparian systems that increases heterogeneity of flow regimes and provides high quality habitat for salmonids and other fishes. We present four sampling-based methods to estimate two-dimensional LW for a 61-hectare river restoration project on the South Fork McKenzie River near Rainbow, OR (USA). We manually delineated LW area, from unoccupied aircraft systems (UAS) multispectral imagery for 40 randomly selected 51.46 m<sup>2</sup> hexagonal plots. Seven auxiliary variables were extracted from the imagery and imagery derivatives to be incorporated in four estimators by summarizing spectral statistics for each plot including Random forest (RF) classification of segmented imagery (Cohen’s kappa = 0.75, balanced accuracy = 0.86). The four estimators were: difference estimator, simple linear regression estimator with one auxiliary variable, general regression estimator with seven auxiliary variables, and simple random sample without replacement. We assessed variance of the estimators and found that the simple random sample without replacement produced the largest estimate for LW area and widest confidence interval (17,283 m<sup>2</sup>, 95% CI 10,613 - 23,952 m<sup>2</sup>) while the generalized regression approach resulted in the smallest estimate and narrowest confidence interval (16,593 m<sup>2</sup>, 95% CI 13,054 - 20,133 m<sup>2</sup>). These methods facilitate efficient estimates of critical habitat components, that are especially suited to efforts that seek to quantify large amounts of these components through time. When combined with traditional sampling methods, classified imagery acquired via UAS promises to enhance the temporal resolution of the data products associated with restoration efforts while minimizing the necessity for potentially hazardous field work.展开更多
The exploration of asteroids has received increasing attention since the 1990s because of the unique information these objects contain about the history of the early solar system.Quasi-satellites are a population of a...The exploration of asteroids has received increasing attention since the 1990s because of the unique information these objects contain about the history of the early solar system.Quasi-satellites are a population of asteroids that co-orbit closely with,but are outside the gravitational control of,the planet.So far,only five Earth quasi-satellites have been recognized,among which(469219)Kamo’oalewa(provisionally designated as 2016 HO3)is currently considered the most stable and the closest of these.However,little is known about this particular asteroid or this class of near-Earth asteroids because of the difficulties of observing them.China has announced that Tianwen-2,the asteroid sample-return mission to Kamo’oalewa,will be launched in 2025.Here,we review the current knowledge of Kamo’oalewa in terms of its physical characteristics,dynamic evolution,surface environment,and origin,and we propose possible breakthroughs that the samples could bring concerning the asteroid Kamo’oalewa as an Earth quasi-satellite.Confirming the origin of Kamo’oalewa,from its prevailing provenance as debris of the Moon,could be a promising start to inferring the evolutionary history of the Moon.This history would probably include a more comprehensive view of the lunar farside and the origin of the asymmetry between the two sides of the Moon.Comparing the samples from the Moon and Kamo’oalewa would also provide new insights into the Earth wind.展开更多
Lightweight nodes are crucial for blockchain scalability,but verifying the availability of complete block data puts significant strain on bandwidth and latency.Existing data availability sampling(DAS)schemes either re...Lightweight nodes are crucial for blockchain scalability,but verifying the availability of complete block data puts significant strain on bandwidth and latency.Existing data availability sampling(DAS)schemes either require trusted setups or suffer from high communication overhead and low verification efficiency.This paper presents ISTIRDA,a DAS scheme that lets light clients certify availability by sampling small random codeword symbols.Built on ISTIR,an improved Reed–Solomon interactive oracle proof of proximity,ISTIRDA combines adaptive folding with dynamic code rate adjustment to preserve soundness while lowering communication.This paper formalizes opening consistency and prove security with bounded error in the random oracle model,giving polylogarithmic verifier queries and no trusted setup.In a prototype compared with FRIDA under equal soundness,ISTIRDA reduces communication by 40.65%to 80%.For data larger than 16 MB,ISTIRDA verifies faster and the advantage widens;at 128 MB,proofs are about 60%smaller and verification time is roughly 25%shorter,while prover overhead remains modest.In peer-to-peer emulation under injected latency and loss,ISTIRDA reaches confidence more quickly and is less sensitive to packet loss and load.These results indicate that ISTIRDA is a scalable and provably secure DAS scheme suitable for high-throughput,large-block public blockchains,substantially easing bandwidth and latency pressure on lightweight nodes.展开更多
Video emotion recognition is widely used due to its alignment with the temporal characteristics of human emotional expression,but existingmodels have significant shortcomings.On the one hand,Transformermultihead self-...Video emotion recognition is widely used due to its alignment with the temporal characteristics of human emotional expression,but existingmodels have significant shortcomings.On the one hand,Transformermultihead self-attention modeling of global temporal dependency has problems of high computational overhead and feature similarity.On the other hand,fixed-size convolution kernels are often used,which have weak perception ability for emotional regions of different scales.Therefore,this paper proposes a video emotion recognition model that combines multi-scale region-aware convolution with temporal interactive sampling.In terms of space,multi-branch large-kernel stripe convolution is used to perceive emotional region features at different scales,and attention weights are generated for each scale feature.In terms of time,multi-layer odd-even down-sampling is performed on the time series,and oddeven sub-sequence interaction is performed to solve the problem of feature similarity,while reducing computational costs due to the linear relationship between sampling and convolution overhead.This paper was tested on CMU-MOSI,CMU-MOSEI,and Hume Reaction.The Acc-2 reached 83.4%,85.2%,and 81.2%,respectively.The experimental results show that the model can significantly improve the accuracy of emotion recognition.展开更多
Distribution transformers play a vital role in power distribution systems,and their reliable operation is crucial for grid stability.This study presents a simulation-based framework for active fault diagnosis and earl...Distribution transformers play a vital role in power distribution systems,and their reliable operation is crucial for grid stability.This study presents a simulation-based framework for active fault diagnosis and early warning of distribution transformers,integrating Sample Ensemble Learning(SEL)with a Self-Optimizing Support Vector Machine(SO-SVM).The SEL technique enhances data diversity and mitigates class imbalance,while SO-SVM adaptively tunes its hyperparameters to improve classification accuracy.A comprehensive transformer model was developed in MATLAB/Simulink to simulate diverse fault scenarios,including inter-turn winding faults,core saturation,and thermal aging.Feature vectors were extracted from voltage,current,and temperature measurements to train and validate the proposed hybrid model.Quantitative analysis shows that the SEL–SO-SVM framework achieves a classification accuracy of 97.8%,a precision of 96.5%,and an F1-score of 97.2%.Beyond classification,the model effectively identified incipient faults,providing an early warning lead time of up to 2.5 s before significant deviations in operational parameters.This predictive capability underscores its potential for preventing catastrophic transformer failures and enabling timely maintenance actions.The proposed approach demonstrates strong applicability for enhancing the reliability and operational safety of distribution transformers in simulated environments,offering a promising foundation for future real-time and field-level implementations.展开更多
[Objective] This study aimed to compare the residue situation of cimaterol,a kind of forbidden veterinary drug in hair, urine and flesh of pig, so as to provide theoretical basis for monitoring veterinary drug residue...[Objective] This study aimed to compare the residue situation of cimaterol,a kind of forbidden veterinary drug in hair, urine and flesh of pig, so as to provide theoretical basis for monitoring veterinary drug residue in bred animals. [Method]Total three different concentrations of cimaterol were administered to pigs, and the residue amounts of cimaterol in pig hair, urine and flesh were monitored at different raising stage. [Result] During the administration period, the residue amount of cimaterol was highest in urine, so urine is the suitable sample for rapid detection of cimaterol in manufacturing enterprises. Cimaterol could be accumulated in pig hair,where cimaterol was metabolized slowly. Thus, pig hair can be used as the test sample for tracing illegal use of veterinary drugs and for vivo detection. Flesh can be used as test sample for direct judgment whether cimaterol residue exceeds the relevant standard. [Conclusion] This study will provide certain theoretical basis for drug monitor in animal husbandry.展开更多
基金supported by the School of Digital Science,Universiti Brunei Darussalam,Brunei.
文摘Artificial Intelligence(AI)in healthcare enables predicting diabetes using data-driven methods instead of the traditional ways of screening the disease,which include hemoglobin A1c(HbA1c),oral glucose tolerance test(OGTT),and fasting plasma glucose(FPG)screening techniques,which are invasive and limited in scale.Machine learning(ML)and deep neural network(DNN)models that use large datasets to learn the complex,nonlinear feature interactions,but the conventional ML algorithms are data sensitive and often show unstable predictive accuracy.Conversely,DNN models are more robust,though the ability to reach a high accuracy rate consistently on heterogeneous datasets is still an open challenge.For predicting diabetes,this work proposed a hybrid DNN approach by integrating a bidirectional long short-term memory(BiLSTM)network with a bidirectional gated recurrent unit(BiGRU).A robust DL model,developed by combining various datasets with weighted coefficients,dense operations in the connection of deep layers,and the output aggregation using batch normalization and dropout functions to avoid overfitting.The goal of this hybrid model is better generalization and consistency among various datasets,which facilitates the effective management and early intervention.The proposed DNN model exhibits an excellent predictive performance as compared to the state-of-the-art and baseline ML and DNN models for diabetes prediction tasks.The robust performance indicates the possible usefulness of DL-based models in the development of disease prediction in healthcare and other areas that demand high-quality analytics.
基金supported by the National NaturalScience Foundation of China(No.22274001)the Key Project of Natural Science Research of the Education Department of Anhui Province(No.2022AH051032)the Excellent Research and Innovation Team of Universities in Anhui Province(No.2024AH010016).
文摘Portable ratiometric fluorescent platforms have emerged as promising tools for multifarious detection,yet remain unexplored for point-of-care monitoring doxorubicin(DOX),one of clinically antineoplastic drugs.To this end,we herein develop a portable self-calibrating platform namely carbon dots(C-dots)-embedded hydrogel sensors with a smartphone-assisted high-throughput imaging device,for DOX sensing.The prepared green-emitting(λ_(em)=508 nm)and negatively-charged C-dots(−11.40±1.21 mV),which have sufficient spectral overlap with the absorption band of DOX(∼500 nm),can strongly bind with positively-charged DOX molecules by electrostatic attraction effects.As a result,DOX molecules are selectively and rapid(20 s)determined with a detection limit of 10.26 nmol/L via Förster resonance energy transfer processes,demonstrating a remarkably chromatic shift from green to red.Further integrated with a 3D-printed smartphone-assisted device,the platform enabled high-throughput quantification,achieving recoveries of 96.40%-101.85%in human urine/serum(RSDs<2.94%,n=3).Notably,the dual linear detection ranges of the platform align with the reported clinical DOX concentrations in urine and plasma(0-4 h post-administration),validating their capability for direct quantification of DOX in clinical samples without special pre-treatment processes.By virtue of attractive analytical performances and robust feasibility,this platform bridges laboratory precision and point-of-care testing needs,offering promising potential for personalized chemotherapy and multiplexed analyte screening.
基金supported by the Bureau of Frontier Sciences and Basic Research,Chinese Academy of Sciences(Grant No.QYJ-2025-0103)the National Natural Science Foundation of China(Grant Nos.42441834,42241105,42441825,and 42203048)the Key Research Program of the Institute of Geology and Geophysics,Chinese Academy of Sciences(Grant No.IGGCAS-202401).
文摘As one of the major volatile components in extraterrestrial materials,nitrogen(N_(2))isotopes serve not only as tracers for the formation and evolution of the solar system,but also play a critical role in assessing planetary habitability and the search for extraterrestrial life.The integrated measurement of N_(2)and argon(Ar)isotopes by using noble gas mass spectrometry represents a state-of-the-art technique for such investigations.To support the growing demands of planetary science research in China,we have developed a high-efficiency,high-precision method for the integrated analysis of N_(2)and Ar isotopes.This was achieved by enhancing gas extraction and purification systems and integrating them with a static noble gas mass spectrometer.This method enables integrated N_(2)-Ar isotope measurements on submilligram samples,significantly improving sample utilization and reducing the impact of sample heterogeneity on volatile analysis.The system integrates CO_(2)laser heating,a modular two-stage Zr-Al getter pump,and a CuO furnace-based purification process,effectively reducing background levels(N_(2)blank as low as 0.35×10^(−6)cubic centimeters at standard temperature and pressure[ccSTP]).Analytical precision is ensured through calibration with atmospheric air and CO corrections.To validate the reliability of the method,we performed N_(2)-Ar isotope analyses on the Allende carbonaceous chondrite,one of the most extensively studied meteorites internationally.The measured N_(2)concentrations range from 19.2 to 29.8 ppm,withδ15N values between−44.8‰and−33.0‰.Concentrations of 40Ar,36Ar,and 38Ar are(12.5-21.1)×10^(−6)ccSTP/g,(90.9-150.3)×10^(−9)ccSTP/g,and(19.2-30.7)×10^(−9)ccSTP/g,respectively.These values correspond to cosmic-ray exposure ages of 4.5-5.7 Ma,consistent with previous reports.Step-heating experiments further reveal distinct release patterns of N and Ar isotopes,as well as their associations with specific mineral phases in the meteorite.In summary,the combined N_(2)-Ar isotopic system offers significant advantages for tracing volatile sources in extraterrestrial materials and will provide essential analytical support for upcoming Chinese planetary missions,such as Tianwen-2.
基金This work was partially supported by National Key R&D Program of China(2019YFB1312400)Shenzhen Key Laboratory of Robotics Perception and Intelligence(ZDSYS20200810171800001)+1 种基金Hong Kong RGC GRF(14200618)Hong Kong RGC CRF(C4063-18G).
文摘Sampling-based path planning is a popular methodology for robot path planning.With a uniform sampling strategy to explore the state space,a feasible path can be found without the complex geometric modeling of the configuration space.However,the quality of the initial solution is not guaranteed,and the convergence speed to the optimal solution is slow.In this paper,we present a novel image-based path planning algorithm to overcome these limitations.Specifically,a generative adversarial network(GAN)is designed to take the environment map(denoted as RGB image)as the input without other preprocessing works.The output is also an RGB image where the promising region(where a feasible path probably exists)is segmented.This promising region is utilized as a heuristic to achieve non-uniform sampling for the path planner.We conduct a number of simulation experiments to validate the effectiveness of the proposed method,and the results demonstrate that our method performs much better in terms of the quality of the initial solution and the convergence speed to the optimal solution.Furthermore,apart from the environments similar to the training set,our method also works well on the environments which are very different from the training set.
基金supported by the National Natural Science Foundation of China(No.51975206)。
文摘Blade Tip-Timing(BTT)has been regarded as a promising way of on-line blade vibration monitoring.But blind multi-band BTT vibration reconstruction is a big challenge under variable speeds and under-sampling.In order to deal with it,a novel Compressed Sensing(CS)method is proposed based on Multi-Coset Angular Sampling(MCAS)in this paper.First,multi-coset sampling scheme of BTT vibration signals is presented.Then the CS model of BTT vibration signals is derived in order domain.A sufficient condition of the number of BTT sensors is derived for perfect reconstruction and optimal placement of BTT sensors is determined by minimizing the condition number.In the end,numerical simulations are done to validate the proposed method and the performances of four reconstruction algorithms are compared,i.e.,Orthogonal Matching Pursuit(OMP),Multiple Signal Classification(MUSIC),Basis Pursuit Denoising(BPDN)and Modified Focal Underdetermined System Solver(MFOCUSS).Influences of the sensor placement,the number of BTT sensors and measurement noises on the reconstruction performances are also testified.The results demonstrate that the proposed method is feasible and the overall performance of the BPDN algorithm is the best among the four algorithms.Also the reconstruction performance decreases with the accelerations of rotating speed.
基金supported by grants from the Human Resources Development program(Grant No.20204010600250)the Training Program of CCUS for the Green Growth(Grant No.20214000000500)by the Korea Institute of Energy Technology Evaluation and Planning(KETEP)funded by the Ministry of Trade,Industry,and Energy of the Korean Government(MOTIE).
文摘Three-dimensional printing(3DP)offers valuable insight into the characterization of natural rocks and the verification of theoretical models due to its high reproducibility and accurate replication of complex defects such as cracks and pores.In this study,3DP gypsum samples with different printing directions were subjected to a series of uniaxial compression tests with in situ micro-computed tomography(micro-CT)scanning to quantitatively investigate their mechanical anisotropic properties and damage evolution characteristics.Based on the two-dimensional(2D)CT images obtained at different scanning steps,a novel void ratio variable was derived using the mean value and variance of CT intensity.Additionally,a constitutive model was formulated incorporating the proposed damage variable,utilizing the void ratio variable.The crack evolution and crack morphology of 3DP gypsum samples were obtained and analyzed using the 3D models reconstructed from the CT images.The results indicate that 3DP gypsum samples exhibit mechanical anisotropic characteristics similar to those found in naturally sedimentary rocks.The mechanical anisotropy is attributed to the bedding planes formed between adjacent layers and pillar-like structures along the printing direction formed by CaSO_(4)·2H_(2)O crystals of needle-like morphology.The mean gray intensity of the voids has a positive linear relationship with the threshold value,while the CT variance and void ratio have concave and convex relationships,respectively.The constitutive model can effectively match the stress–strain curves obtained from uniaxial compression experiments.This study provides comprehensive explanations of the failure modes and anisotropic mechanisms of 3DP gypsum samples,which is important for characterizing and understanding the failure mechanism and microstructural evolution of 3DP rocks when modeling natural rock behavior.
基金the Key National Natural Science Foundation of China(No.U1864211)the National Natural Science Foundation of China(No.11772191)the Natural Science Foundation of Shanghai(No.21ZR1431500)。
文摘Industrial data mining usually deals with data from different sources.These heterogeneous datasets describe the same object in different views.However,samples from some of the datasets may be lost.Then the remaining samples do not correspond one-to-one correctly.Mismatched datasets caused by missing samples make the industrial data unavailable for further machine learning.In order to align the mismatched samples,this article presents a cooperative iteration matching method(CIMM)based on the modified dynamic time warping(DTW).The proposed method regards the sequentially accumulated industrial data as the time series.Mismatched samples are aligned by the DTW.In addition,dynamic constraints are applied to the warping distance of the DTW process to make the alignment more efficient.Then a series of models are trained with the cumulated samples iteratively.Several groups of numerical experiments on different missing patterns and missing locations are designed and analyzed to prove the effectiveness and the applicability of the proposed method.
基金supported by he National Natural Science Foundation of China(Grant Nos.12304359,12304398,12404382,12234009,12274215,and 12427808)the China Postdoctoral Science Foundation(Grant No.2023M731611)+4 种基金the Jiangsu Funding Program for Excellent Postdoctoral Talent(Grant No.2023ZB717)Innovation Program for Quantum Science and Technology(Grant No.2021ZD0301400)Key R&D Program of Jiangsu Province(Grant No.BE2023002)Natural Science Foundation of Jiangsu Province(Grant Nos.BK20220759 and BK20233001)Program for Innovative Talents and Entrepreneurs in Jiangsu,and Key R&D Program of Guangdong Province(Grant No.2020B0303010001).
文摘As an emerging microscopic detection tool,quantum microscopes based on the principle of quantum precision measurement have attracted widespread attention in recent years.Compared with the imaging of classical light,quantum-enhanced imaging can achieve ultra-high resolution,ultra-sensitive detection,and anti-interference imaging.Here,we introduce a quantum-enhanced scanning microscope under illumination of an entangled NOON state in polarization.For the phase imager with NOON states,we propose a simple four-basis projection method to replace the four-step phase-shifting method.We have achieved the phase imaging of micrometer-sized birefringent samples and biological cell specimens,with sensitivity close to the Heisenberg limit.The visibility of transmittance-based imaging shows a great enhancement for NOON states.Besides,we also demonstrate that the scanning imaging with NOON states enables the spatial resolution enhancement of√N compared with classical measurement.Our imaging method may provide some reference for the practical application of quantum imaging and is expected to promote the development of microscopic detection.
文摘In this paper,an image processing algorithm which is able to synthesize material textures of arbitrary shapes is proposed.The presented approach uses an arbitrary image to construct a structure layer of the material.The resulting structure layer is then used to constrain the material texture synthesis.The field of second-moment matrices is used to represent the structure layer.Many tests with various constraint images are conducted to ensure that the proposed approach accurately reproduces the visual aspects of the input material sample.The results demonstrate that the proposed algorithm is able to accurately synthesize arbitrary-shaped material textures while respecting the local characteristics of the exemplar.This paves the way toward the synthesis of 3D material textures of arbitrary shapes from 2D material samples,which has a wide application range in virtual material design and materials characterization.
文摘Geological samples often contain significant amounts of iron,which,although not typically the target element,can substantially interfere with the analysis of other elements of interest.To mitigate these interferences,amidoximebased radiation grafted adsorbents have been identified as effective for iron removal.In this study,an amidoximefunctionalized,radiation-grafted adsorbent synthesized from polypropylene waste(PPw-g-AO-10)was employed to remove iron from leached geological samples.The adsorption process was systematically optimized by investigating the effects of pH,contact time,adsorbent dosage,and initial ferric ion concentration.Under optimal conditions-pH1.4,a contact time of 90 min,and an initial ferric ion concentration of 4500 mg/L-the adsorbent exhibited a maximum iron adsorption capacity of 269.02 mg/g.After optimizing the critical adsorption parameters,the adsorbent was applied to the leached geological samples,achieving a 91%removal of the iron content.The adsorbent was regenerated through two consecutive cycles using 0.2 N HNO_(3),achieving a regeneration efficiency of 65%.These findings confirm the efficacy of the synthesized PPw-g-AO-10 as a cost-effective and eco-friendly adsorbent for successfully removing iron from leached geological matrices while maintaining a reasonable degree of reusability.
基金the Major Scientific Instrument Research of National Natural Science Foundation of China(No.61627810)the National Science and Technology Major Program of China(No.2018YFB1305003)。
文摘A lifespan prediction model was developed based on a few samples to provide decision-making information for operation and maintenance,as well as improve the economy and safety of nuclear power plant(NPP)operations.This paper applies a Weibull model to forecast the lifespan of electronic cards with a few samples in NPPs.Relationship between the lifespan prediction of electronic cards and the ambient temperature is revealed using the Arrhenius equation.Censored samples are used to compensate for the lack of fault electronic card data.Scale parameter and shape parameter of the Weibull model are optimized by adjusting the weight ratio between the censored data and the fault data.Characteristic life is then obtained using the rank regression fitting equation.Parameters of the Arrhenius equation can be calculated by dividing the samples into groups according to the ambient temperature.A case study of the intermediate range high-voltage electric card of ex-core neutron detectors demonstrates that the lifespan prediction of electronic cards in NPPs can be successfully predicted with a few samples by combining the Weibull model and the Arrhenius model.This can help provide preventive maintenance recommendations for electronic cards.Finally,operation suggestions for the electronic card’s ambient temperature can be made by utilizing the temperature-life model.
文摘When the 2025 Intertextile Apparel Fabrics Exhibition(Autumn/Winter)was held in Shanghai,more than 3,700 top exhibitors from 26 countries and regions around the world participated.From September 2nd to 4th,the 2025"Keqiao Selected"exhibition shone brightly at the event,showcasing the high-end quality of its products and the innovative strength of its regional brands.
基金supported by the Innovation Driven Development Foundation of Guangxi(No.AD22080035)the Open Project Funding of the Key Laboratory of Tropical Marine Ecosystem and Bioresource,Ministry of Natural Resources(No.2023-QN04)+1 种基金the Guangdong Provincial Ordinary University Youth Innovative Talent Project in 2024(No.2024KQNCX134)the Guangdong Provincial Special Fund Project for Talent Development Strategy in 2024(No.2024R3005).
文摘The investigation of whether sediment samples contain representative grain size distribution information is important for the accurate extraction of sediment characteristics and conduct of related sedimentary record studies.This study comparatively analyzed the numerical and qualitative differences and the degree of correlation of 36 sets of the characteristic parameters of surface sediment parallel sample grain size distribution from three sampling profiles at Jinsha Bay Beach in Zhanjiang,western Guangdong.At each sampling point,five parallel subsamples were established at intervals of 0,10,20,50,and 100 cm along the coastline.The research findings indicate the following:1)relatively large differences in the mean values of the different parallel samples(0.19–0.34Φ),with smaller differences observed in other characteristic grain sizes(D_(10),D_(50),and D_(90));2)small differences in characteristic values among various parallel sample grain size parameters,with at least 33%of the combinations of qualitative results showing inconsistency;3)50%of the regression equations between the skewness of different parallel samples displaying no significant correlation;4)relative deviations of−47.91%to 27.63%and−49.20%to 2.08%existing between the particle size parameters of a single sample and parallel samples(with the average obtained)at intervals of 10 and 50 cm,respectively.As such,small spatial differences,even within 100 cm,can considerably affect grain size parameters.Given the uncertain reasons underlying the representativeness of the samples,which may only cover the area immediately surrounding the sampling station,researchers are advised to design parallel sample collection strategies based on the spatiotemporal distribution characteristics of the parameters of interest during sediment sample collection.This study provides a typical case of the comparative analysis of parallel sample grain size parameters,with a focus on small spatial beach sediment,which contributes to the enhanced understanding of the accuracy and reliability of sediment sample collection strategies and extraction of grain size information.
基金National Natural Science Foundation of China(32301712)Natural Science Foundation of Jiangsu Province(BK20230548,BK20250876)+2 种基金Project of Faculty of Agricultural Equipment of Jiangsu University(NGXB20240203)A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD-2023-87)Open Funding Project of the Key Laboratory of Modern Agricultural Equipment and Technology(Jiangsu University),Ministry of Education(MAET202101)。
文摘Traditional sampling-based path planning algorithms,such as the rapidly-exploring random tree star(RRT^(*)),encounter critical limitations in unstructured orchard environments,including low sampling efficiency in narrow passages,slow convergence,and high computational costs.To address these challenges,this paper proposes a novel hybrid global path planning algorithm integrating Gaussian sampling and quadtree optimization(RRT^(*)-GSQ).This methodology aims to enhance path planning by synergistically combining a Gaussian mixture sampling strategy to improve node generation in critical regions,an adaptive step-size and direction optimization mechanism for enhanced obstacle avoidance,a Quadtree-AABB collision detection framework to lower computational complexity,and a dynamic iteration control strategy for more efficient convergence.In obstacle-free and obstructed scenarios,compared with the conventional RRT^(*),the proposed algorithm reduced the number of node evaluations by 67.57%and 62.72%,and decreased the search time by 79.72%and 78.52%,respectively.In path tracking tests,the proposed algorithm achieved substantial reductions in RMSE of the final path compared to the conventional RRT^(*).Specifically,the lateral RMSE was reduced by 41.5%in obstacle-free environments and 59.3%in obstructed environments,while the longitudinal RMSE was reduced by 57.2%and 58.5%,respectively.Furthermore,the maximum absolute errors in both lateral and longitudinal directions were constrained within 0.75 m.Field validation experiments in an operational orchard confirmed the algorithm's practical effectiveness,showing reductions in the mean tracking error of 47.6%(obstacle-free)and 58.3%(with obstructed),alongside a 5.1%and 7.2%shortening of the path length compared to the baseline method.The proposed algorithm effectively enhances path planning efficiency and navigation accuracy for robots,presenting a superior solution for high-precision autonomous navigation of agricultural robots in orchard environments and holding significant value for engineering applications.
文摘Large in-stream wood (LW) is a critical component of riparian systems that increases heterogeneity of flow regimes and provides high quality habitat for salmonids and other fishes. We present four sampling-based methods to estimate two-dimensional LW for a 61-hectare river restoration project on the South Fork McKenzie River near Rainbow, OR (USA). We manually delineated LW area, from unoccupied aircraft systems (UAS) multispectral imagery for 40 randomly selected 51.46 m<sup>2</sup> hexagonal plots. Seven auxiliary variables were extracted from the imagery and imagery derivatives to be incorporated in four estimators by summarizing spectral statistics for each plot including Random forest (RF) classification of segmented imagery (Cohen’s kappa = 0.75, balanced accuracy = 0.86). The four estimators were: difference estimator, simple linear regression estimator with one auxiliary variable, general regression estimator with seven auxiliary variables, and simple random sample without replacement. We assessed variance of the estimators and found that the simple random sample without replacement produced the largest estimate for LW area and widest confidence interval (17,283 m<sup>2</sup>, 95% CI 10,613 - 23,952 m<sup>2</sup>) while the generalized regression approach resulted in the smallest estimate and narrowest confidence interval (16,593 m<sup>2</sup>, 95% CI 13,054 - 20,133 m<sup>2</sup>). These methods facilitate efficient estimates of critical habitat components, that are especially suited to efforts that seek to quantify large amounts of these components through time. When combined with traditional sampling methods, classified imagery acquired via UAS promises to enhance the temporal resolution of the data products associated with restoration efforts while minimizing the necessity for potentially hazardous field work.
基金supported by the National Natural Science Foundation of China(Grant Nos.42241106 and 42388101).
文摘The exploration of asteroids has received increasing attention since the 1990s because of the unique information these objects contain about the history of the early solar system.Quasi-satellites are a population of asteroids that co-orbit closely with,but are outside the gravitational control of,the planet.So far,only five Earth quasi-satellites have been recognized,among which(469219)Kamo’oalewa(provisionally designated as 2016 HO3)is currently considered the most stable and the closest of these.However,little is known about this particular asteroid or this class of near-Earth asteroids because of the difficulties of observing them.China has announced that Tianwen-2,the asteroid sample-return mission to Kamo’oalewa,will be launched in 2025.Here,we review the current knowledge of Kamo’oalewa in terms of its physical characteristics,dynamic evolution,surface environment,and origin,and we propose possible breakthroughs that the samples could bring concerning the asteroid Kamo’oalewa as an Earth quasi-satellite.Confirming the origin of Kamo’oalewa,from its prevailing provenance as debris of the Moon,could be a promising start to inferring the evolutionary history of the Moon.This history would probably include a more comprehensive view of the lunar farside and the origin of the asymmetry between the two sides of the Moon.Comparing the samples from the Moon and Kamo’oalewa would also provide new insights into the Earth wind.
基金supported in part by the Research Fund of Key Lab of Education Blockchain and Intelligent Technology,Ministry of Education(EBME25-F-08).
文摘Lightweight nodes are crucial for blockchain scalability,but verifying the availability of complete block data puts significant strain on bandwidth and latency.Existing data availability sampling(DAS)schemes either require trusted setups or suffer from high communication overhead and low verification efficiency.This paper presents ISTIRDA,a DAS scheme that lets light clients certify availability by sampling small random codeword symbols.Built on ISTIR,an improved Reed–Solomon interactive oracle proof of proximity,ISTIRDA combines adaptive folding with dynamic code rate adjustment to preserve soundness while lowering communication.This paper formalizes opening consistency and prove security with bounded error in the random oracle model,giving polylogarithmic verifier queries and no trusted setup.In a prototype compared with FRIDA under equal soundness,ISTIRDA reduces communication by 40.65%to 80%.For data larger than 16 MB,ISTIRDA verifies faster and the advantage widens;at 128 MB,proofs are about 60%smaller and verification time is roughly 25%shorter,while prover overhead remains modest.In peer-to-peer emulation under injected latency and loss,ISTIRDA reaches confidence more quickly and is less sensitive to packet loss and load.These results indicate that ISTIRDA is a scalable and provably secure DAS scheme suitable for high-throughput,large-block public blockchains,substantially easing bandwidth and latency pressure on lightweight nodes.
基金supported,in part,by the National Nature Science Foundation of China under Grant 62272236,62376128in part,by the Natural Science Foundation of Jiangsu Province under Grant BK20201136,BK20191401.
文摘Video emotion recognition is widely used due to its alignment with the temporal characteristics of human emotional expression,but existingmodels have significant shortcomings.On the one hand,Transformermultihead self-attention modeling of global temporal dependency has problems of high computational overhead and feature similarity.On the other hand,fixed-size convolution kernels are often used,which have weak perception ability for emotional regions of different scales.Therefore,this paper proposes a video emotion recognition model that combines multi-scale region-aware convolution with temporal interactive sampling.In terms of space,multi-branch large-kernel stripe convolution is used to perceive emotional region features at different scales,and attention weights are generated for each scale feature.In terms of time,multi-layer odd-even down-sampling is performed on the time series,and oddeven sub-sequence interaction is performed to solve the problem of feature similarity,while reducing computational costs due to the linear relationship between sampling and convolution overhead.This paper was tested on CMU-MOSI,CMU-MOSEI,and Hume Reaction.The Acc-2 reached 83.4%,85.2%,and 81.2%,respectively.The experimental results show that the model can significantly improve the accuracy of emotion recognition.
文摘Distribution transformers play a vital role in power distribution systems,and their reliable operation is crucial for grid stability.This study presents a simulation-based framework for active fault diagnosis and early warning of distribution transformers,integrating Sample Ensemble Learning(SEL)with a Self-Optimizing Support Vector Machine(SO-SVM).The SEL technique enhances data diversity and mitigates class imbalance,while SO-SVM adaptively tunes its hyperparameters to improve classification accuracy.A comprehensive transformer model was developed in MATLAB/Simulink to simulate diverse fault scenarios,including inter-turn winding faults,core saturation,and thermal aging.Feature vectors were extracted from voltage,current,and temperature measurements to train and validate the proposed hybrid model.Quantitative analysis shows that the SEL–SO-SVM framework achieves a classification accuracy of 97.8%,a precision of 96.5%,and an F1-score of 97.2%.Beyond classification,the model effectively identified incipient faults,providing an early warning lead time of up to 2.5 s before significant deviations in operational parameters.This predictive capability underscores its potential for preventing catastrophic transformer failures and enabling timely maintenance actions.The proposed approach demonstrates strong applicability for enhancing the reliability and operational safety of distribution transformers in simulated environments,offering a promising foundation for future real-time and field-level implementations.
基金Supported by Key Science and Technology Program(GKZ1222003-2-2)~~
文摘[Objective] This study aimed to compare the residue situation of cimaterol,a kind of forbidden veterinary drug in hair, urine and flesh of pig, so as to provide theoretical basis for monitoring veterinary drug residue in bred animals. [Method]Total three different concentrations of cimaterol were administered to pigs, and the residue amounts of cimaterol in pig hair, urine and flesh were monitored at different raising stage. [Result] During the administration period, the residue amount of cimaterol was highest in urine, so urine is the suitable sample for rapid detection of cimaterol in manufacturing enterprises. Cimaterol could be accumulated in pig hair,where cimaterol was metabolized slowly. Thus, pig hair can be used as the test sample for tracing illegal use of veterinary drugs and for vivo detection. Flesh can be used as test sample for direct judgment whether cimaterol residue exceeds the relevant standard. [Conclusion] This study will provide certain theoretical basis for drug monitor in animal husbandry.
