The quantificational and normative design is the precondition of improving the design of copper staves for blast furnaces. Based on a 3-dimensional temperature field calculation model, from the view point of heat tran...The quantificational and normative design is the precondition of improving the design of copper staves for blast furnaces. Based on a 3-dimensional temperature field calculation model, from the view point of heat transfer and long campaigns note with the core of forming accretion, the forming-accretion-ability （FAA） and the rib hot surface maximum temperature difference （ATmax） as quantificational indexes to direct and evaluate the design of copper staves for blast furnaces were presented. The application of the two indexes in design essentially embodies the new long campaigns in the stage of design. With the application of the two indexes, good results can be obtained. Firstly, it was suggested that the rib height of a copper stave can be reduced to 15 mm, which is a new method and theory for the reduction of copper staves. Secondly, the influence of insert on FAA and ATmax, is decided by the volume of insert. According to this, the principle of design for the hot surface geometry of copper staves was put forward that the ratio of the rib hot surface to the copper stave hot surface （abbreviated as the ratio of rib to stave） must be maintained in the range of 45% to 55%; for the present copper stave with a 35-40 mm thick rib, the ratio of rib to stave in the range of 50% to 55% can optimize the design of copper staves; for the copper stave with a smaller rib thickness, for example 15 ram, the ratio of rib to stave in the range of 45% to 50% can optimize the design of copper staves. It can be summarized that the thicker the rib thickness, the larger is the ratio of rib to stave. 2008 University of Science and Technology Beijing. All rights reserved.展开更多
OBJECTIVE:To propose an automatic acupuncture robot system for performing acupuncture operations.METHODS:The acupuncture robot system consists of three components:automatic acupoint localization,acupuncture manipulati...OBJECTIVE:To propose an automatic acupuncture robot system for performing acupuncture operations.METHODS:The acupuncture robot system consists of three components:automatic acupoint localization,acupuncture manipulations,and De Qi sensation detection.The OptiTrack motion capture system is used to locate acupoints,which are then translated into coordinates in the robot control system.A flexible collaborative robot with an intelligent gripper is then used to perform acupuncture manipulations with high precision.In addition,a De Qi sensation detection system is proposed to evaluate the effect of acupuncture.To verify the stability of the designed acupuncture robot,acupoints'coordinates localized by the acupuncture robot are compared with the Gold Standard labeled by a professional acupuncturist using significant level tests.RESULTS:Through repeated experiments for eight acupoints,the acupuncture robot achieved a positioning error within 3.3 mm,which is within the allowable range of needle extraction and acupoint insertion.During needle insertion,the robot arm followed the prescribed trajectory with a mean deviation distance of 0.02 mm and a deviation angle of less than 0.15°.The results of the lifting thrusting operation in the Xingzhen process show that the mean acupuncture depth error of the designed acupuncture robot is approximately 2 mm,which is within the recommended depth range for the Xingzhen operation.In addition,the average detection accuracy of the De Qi keywords is 94.52%,which meets the requirements of acupuncture effect testing for different dialects.CONCLUSION:The proposed acupuncture robot system streamlines the acupuncture process,increases efficiency,and reduces practitioner fatigue,while also allowing for the quantification of acupuncture manipulations and evaluation of therapeutic effects.The development of an acupuncture robot system has the potential to revolutionize low back pain treatment and improve patient outcomes.展开更多
A two-stage algorithm based on deep learning for the detection and recognition of can bottom spray codes and numbers is proposed to address the problems of small character areas and fast production line speeds in can ...A two-stage algorithm based on deep learning for the detection and recognition of can bottom spray codes and numbers is proposed to address the problems of small character areas and fast production line speeds in can bottom spray code number recognition.In the coding number detection stage,Differentiable Binarization Network is used as the backbone network,combined with the Attention and Dilation Convolutions Path Aggregation Network feature fusion structure to enhance the model detection effect.In terms of text recognition,using the Scene Visual Text Recognition coding number recognition network for end-to-end training can alleviate the problem of coding recognition errors caused by image color distortion due to variations in lighting and background noise.In addition,model pruning and quantization are used to reduce the number ofmodel parameters to meet deployment requirements in resource-constrained environments.A comparative experiment was conducted using the dataset of tank bottom spray code numbers collected on-site,and a transfer experiment was conducted using the dataset of packaging box production date.The experimental results show that the algorithm proposed in this study can effectively locate the coding of cans at different positions on the roller conveyor,and can accurately identify the coding numbers at high production line speeds.The Hmean value of the coding number detection is 97.32%,and the accuracy of the coding number recognition is 98.21%.This verifies that the algorithm proposed in this paper has high accuracy in coding number detection and recognition.展开更多
Background:Rosa chinensis Jacq.and Rosa rugosa Thunb.are not only of ornamental value,but also edible flowers and the flower buds have been listed in the Chinese Pharmacopoeia as traditional medicines.The two plants h...Background:Rosa chinensis Jacq.and Rosa rugosa Thunb.are not only of ornamental value,but also edible flowers and the flower buds have been listed in the Chinese Pharmacopoeia as traditional medicines.The two plants have some differences in efficacy,but the flower buds are easily confused for similar traits.In addition,large-scale cultivation of ornamental rose flowers may lead to a decrease in the effective components of medicinal roses.Therefore,it is necessary to study the chemical composition and make quality evaluation of Rosae Chinensis Flos(Yueji)and Rosae Rugosae Flos(Meigui).Methods:In this study,40 batches of samples including Meigui and Yueji from different regions in China were collected to establish high-performance liquid chromatography fingerprints.Then,the fingerprints data was analyzed using principal component analysis,hierarchical cluster analysis,and partial least squares discriminant analysis analysis chemometrics to obtain information on intergroup differences,and non-targeted metabolomic techniques were applied to identify and compare chemical compositions of samples which were chosen from groups with large differences.Differential compounds were screened by orthogonal partial least-squares discriminant analysis and S-plot,and finally multi-component quantification was performed to comprehensively evaluate the quality of Yueji and Meigui.Results:The similarity between the fingerprints of 40 batches roses and the reference print R was 0.73 to 0.93,indicating that there were similarities and differences between the samples.Through principal component analysis and hierarchical cluster analysis of fingerprints data,the samples from different origins and varieties were intuitively divided into four groups.Partial least-squares discriminant analysis analysis showed that Meigui and Yueji cluster into two categories and the model was reliable.A total of 89 compounds were identified by high resolution mass spectrometry,mainly were flavonoids and flavonoid glycosides,as well as phenolic acids.Eight differential components were screened out by orthogonal partial least-squares discriminant analysis and S-plot analysis.Quantitative analyses of the eight compounds,including gallic acid,ellagic acid,hyperoside,isoquercitrin,etc.,showed that Yueji was generally richer in phenolic acids and flavonoids than Meigui,and the quality of Yueji from Shandong and Hebei was better.It is worth noting that Xinjiang rose is rich in various components,which is worth focusing on more in-depth research.Conclusion:In this study,the fingerprints of Meigui and Yueji were established.The chemical components information of roses was further improved based on non-targeted metabolomics and mass spectrometry technology.At the same time,eight differential components of Meigui and Yueji were screened out and quantitatively analyzed.The research results provided a scientific basis for the quality control and rational development and utilization of Rosae Chinensis Flos and Rosae Rugosae Flos,and also laid a foundation for the study of their pharmacodynamic material basis.展开更多
Viral diseases are an important threat to crop yield,as they are responsible for losses greater than US$30 billion annually.Thus,understanding the dynamics of virus propagation within plant cells is essential for devi...Viral diseases are an important threat to crop yield,as they are responsible for losses greater than US$30 billion annually.Thus,understanding the dynamics of virus propagation within plant cells is essential for devising effective control strategies.However,viruses are complex to propagate and quantify.Existing methodologies for viral quantification tend to be expensive and time-consuming.Here,we present a rapid cost-effective approach to quantify viral propagation using an engineered virus expressing a fluorescent reporter.Using a microplate reader,we measured viral protein levels and we validated our findings through comparison by western blot analysis of viral coat protein,the most common approach to quantify viral titer.Our proposed methodology provides a practical and accessible approach to studying virus-host interactions and could contribute to enhancing our understanding of plant virology.展开更多
Background:Changes in lower limb joint coordination have been shown to increase localized stress on knee joint soft tissue—a known precursor of osteoarthritis.While 50%of individuals who undergo anterior cruciate lig...Background:Changes in lower limb joint coordination have been shown to increase localized stress on knee joint soft tissue—a known precursor of osteoarthritis.While 50%of individuals who undergo anterior cruciate ligament reconstruction(ACLR)develop radiographic osteoarthritis,it is unclear how underlying joint coordination during gait changes post-ACLR.The purpose of this study was twofold:to determine differences in lower limb coordination patterns during gait in ACLR individuals 2,4,and 6 months post-ACLR and to compare the coordination profiles of the ACLR participants at each timepoint post-ACLR to uninjured matched controls.Methods:We conducted a longitudinal assessment to quantify lower limb coordination at 3 timepoints post-ACLR and compared the ACLR coordination profiles to uninjured controls.Thirty-four ACLR(age=21.43±4.24 years,mean±SD;70.59%female)and 34 controls(age=21.42±3.43 years;70.59%female)participated.The ACLR group completed 3 overground gait assessments(2,4,and 6 months post-ACLR),and the controls completed one assessment,at which lower limb kinematics were collected.Cross-recurrence quantification analysis was used to characterize sagittal and frontal plane ankle-knee,ankle-hip,and knee-hip coordination dynamics.Comprehensive general linear mixed models were constructed to compare between-limb and within-limb coordination outcomes over time post-ACLR and a between-group comparison across timepoints.Results:The ACLR limb demonstrated a more"stuck"sagittal plane knee-hip coordination profile(greater trapping time(TT);p=0.004)compared bilaterally.Between groups,the ACLR participants exhibited a more predictable ankle-knee coordination pattern(percent determinism(%DET);p<0.05),stronger coupling between joints(meanline(MNLine))across all segments(p<0.05),and greater knee-hip TT(more"stuck";p<0.05)compared to the controls at each timepoint in the sagittal plane.Stronger frontal plane knee-hip joint coupling(MNLine)persisted across timepoints within the ACLR group compared to the controls(p<0.05).Conclusion:The results indicate ACLR individuals exhibit a distinct and rigid coordination pattern during gait compared to controls within6-month post-ACLR,which may have long-term implications for knee-joint health.展开更多
BACKGROUND The Streptococcus salivarius(S.salivarius)group,which produces the enzyme urease has been identified as a potential contributor to ammonia production in the gut.Researchers have reported that patients with ...BACKGROUND The Streptococcus salivarius(S.salivarius)group,which produces the enzyme urease has been identified as a potential contributor to ammonia production in the gut.Researchers have reported that patients with minimal HE had an increased abundance of the S.salivarius group,which is a specific change in the gut microbiota that distinguishes them from healthy individuals.The correlation between the aggregation of specific bacterial species and fibrosis progression in chronic liver disease(CLD)is yet to be fully elucidated.AIM To quantify S.salivarius using digital PCR(dPCR)as a liver fibrosis marker of CLD.METHODS This study retrospectively analysed 52 patients with CLD.To quantify S.salivarius in patients with CLD using dPCR,we evaluated the specificity and sensitivity of S.salivarius bacterial load using dPCR for a type strain.Next,we evaluated the clinical usefulness of dPCR for S.salivarius load quantification for detecting liver fibrosis in patients with CLD.The liver fibrosis stage was categorized into mild and advanced fibrosis based on pathological findings.RESULTS The dPCR assay revealed that S.salivarius was highly positive for the tnpA gene.The lower limit of quantification for dPCR using the tnpA gene with a 1μL template comprising 1.28×102 CFU/mL was 4.3 copies.After considering the detection range in dPCR,we adjusted the extracted DNA concentration to 5.0×10-4 ng/μL from 200 mg stool samples.The median bacterial loads of S.salivarius in stool sample from patients with mild and advanced fibrosis were 1.9 and 7.4 copies/μL,respectively.The quantification of S.salivarius load was observed more frequently in patients with advanced fibrosis than in those with mild fibrosis(P=0.032).CONCLUSION Quantifying of S.salivarius load using digital PCR is a useful biomarker for liver fibrosis in patients with CLD.展开更多
Avian wings are central to their remarkable flight ability and diverse life history strategies,including behaviors such as fighting and mating.These multifaceted functions are intricately tied to wing shape,which vari...Avian wings are central to their remarkable flight ability and diverse life history strategies,including behaviors such as fighting and mating.These multifaceted functions are intricately tied to wing shape,which varies significantly across species because of the complex interplay of evolutionary and ecological pressures.Many indices have been developed to quantify wing characteristics to facilitate the study and comparison of avian wing morphology across species.This study provides a comprehensive overview of existing quantitative methods for analyzing avian wing shapes.We then constructed a new quantification framework through the beta distribution,which can generate indices reflecting the shape of avian wings(center,dispersion,skewness,and kurtosis).Next,we used the flight feathers of 613 bird species to perform different quantitative analyses and explore the relationships between various wing shape quantification methods and life history traits,which serve as proxies for the selective forces shaping wing morphology.We find that the wing shape indices are more strongly associated with ecological variables than with morphological variables,especially for migration,habitat and territoriality.This research guides the selection of appropriate methods for wing shape analysis,contributing to a deeper understanding of avian morphology and its evolutionary drivers.展开更多
Ultrasensitive detection of nucleic acids is of great significance for precision medicine.Digital polymerase chain reaction(dPCR)is the most sensitive method but requires sophisticated and expensive instruments and a ...Ultrasensitive detection of nucleic acids is of great significance for precision medicine.Digital polymerase chain reaction(dPCR)is the most sensitive method but requires sophisticated and expensive instruments and a long reaction time.Digital PCR-free technologies,which mean the digital assay not relying on thermal cycling to amplify the signal for quantitative detection of nucleic acids at the singlemolecule level,include the digital isothermal amplification techniques(d IATs)and the digital clustered regularly interspaced short palindromic repeats(CRISPR)technologies.They combine the advantages of d PCR and IATs,which could be fast and simple,enabling absolute quantification of nucleic acids at a single-molecule level with minimum instrument,representing the next-generation molecular diagnostic technology.Herein,we systematically summarized the strategies and applications of various dIATs,including the digital loop-mediated isothermal amplification(dLAMP),the digital recombinase polymerase amplification(dRPA),the digital rolling circle amplification(dRCA),the digital nucleic acid sequencebased amplification(d NASBA)and the digital multiple displacement amplification(d MDA),and evaluated the pros and cons of each method.The emerging digital CRISPR technologies,including the detection mechanism of CRISPR and the various strategies for signal amplification,are also introduced comprehensively in this review.The current challenges as well as the future perspectives of the digital PCR-free technology were discussed.展开更多
Geomechanical properties of rocks vary across different measurement scales,primarily due to heterogeneity.Micro-scale geomechanical tests,including micro-scale“scratch tests”and nano-scale nanoindentation tests,are ...Geomechanical properties of rocks vary across different measurement scales,primarily due to heterogeneity.Micro-scale geomechanical tests,including micro-scale“scratch tests”and nano-scale nanoindentation tests,are attractive at different scales.Each method requires minimal sample volume,is low cost,and includes a relatively rapid measurement turnaround time.However,recent micro-scale test results–including scratch test results and nanoindentation results–exhibit tangible variance and uncertainty,suggesting a need to correlate mineral composition mapping to elastic modulus mapping to isolate the relative impact of specific minerals.Different research labs often utilize different interpretation methods,and it is clear that future micro-mechanical tests may benefit from standardized testing and interpretation procedures.The objectives of this study are to seek options for standardized testing and interpretation procedures,through two specific objectives:(1)Quantify chemical and physical controls on micro-mechanical properties and(2)Quantify the source of uncertainties associated with nanoindentation measurements.To reach these goals,we conducted mechanical tests on three different scales:triaxial compression tests,scratch tests,and nanoindentation tests.We found that mineral phase weight percentage is highly correlated with nanoindentation elastic modulus distribution.Finally,we conclude that nanoindentation testing is a mineralogy and microstructure-based method and generally yields significant uncertainty and overestimation.The uncertainty of the testing method is largely associated with not mapping pore space a priori.Lastly,the uncertainty can be reduced by combining phase mapping and modulus mapping with substantial and random data sampling.展开更多
During high-speed forward flight,helicopter rotor blades operate across a wide range of Reynolds and Mach numbers.Under such conditions,their aerodynamic performance is significantly influenced by dynamic stall—a com...During high-speed forward flight,helicopter rotor blades operate across a wide range of Reynolds and Mach numbers.Under such conditions,their aerodynamic performance is significantly influenced by dynamic stall—a complex,unsteady flow phenomenon highly sensitive to inlet conditions such asMach and Reynolds numbers.The key features of three-dimensional blade stall can be effectively represented by the dynamic stall behavior of a pitching airfoil.In this study,we conduct an uncertainty quantification analysis of dynamic stall aerodynamics in high-Mach-number flows over pitching airfoils,accounting for uncertainties in inlet parameters.A computational fluid dynamics(CFD)model based on the compressible unsteady Reynolds-averagedNavier–Stokes(URANS)equations,coupledwith sliding mesh techniques,is developed to simulate the unsteady aerodynamic behavior and associated flow fields.To efficiently capture the aerodynamic responses while maintaining high accuracy,a multi-fidelity Co-Kriging surrogate model is constructed.This model integrates the precision of high-fidelity wind tunnel experiments with the computational efficiency of lower-fidelity URANS simulations.Its accuracy is validated through direct comparison with experimental data.Building upon this surrogate model,we employ interval analysis and the Sobol sensitivity method to quantify the uncertainty and parameter sensitivity of the unsteady aerodynamic forces resulting frominlet condition variability.Both the inlet Mach number and Reynolds number are treated as uncertain inputs,modeled using interval representations.Our results demonstrate that variations inMach number contribute far more significantly to aerodynamic uncertainty than those in Reynolds number.Moreover,the presence of dynamic stall vortices markedly amplifies the aerodynamic sensitivity to Mach number fluctuations.展开更多
Background Physical activity can regulate and affect gene expression in multiple tissues and cells.Recently,with the development of next-generation sequencing,a large number of RNA-sequencing(RNA-seq)-based gene expre...Background Physical activity can regulate and affect gene expression in multiple tissues and cells.Recently,with the development of next-generation sequencing,a large number of RNA-sequencing(RNA-seq)-based gene expression profiles about physical activity have been shared in public resources;however,they are poorly curated and underutilized.To tackle this problem,we developed a data atlas of such data through comprehensive data collection,curation,and organization.Methods The data atlas,termed gene expression profiles of RNA-seq-based exercise responses(GEPREP),was built on a comprehensive collection of high-quality RNA-seq data on exercise responses.The metadata of each sample were manually curated.Data were uniformly processed and batch effects corrected.All the information was well organized in an easy-to-use website for free search,visualization,and download.Results GEPREP now includes 69 RNA-seq datasets of pre-and post-exercise,comprising 26 human datasets(1120 samples)and 43 mouse datasets(1006 samples).Specifically,there were 977(87.2%)human samples of skeletal muscle and 143(12.8%)human samples of blood.There were also samples across 9 mice tissues with skeletal muscle(359,35.7%)and brain(280,27.8%)accounting for the main fractions.Metadata—including subject,exercise interventions,sampling sites,and post-processing methods—are also included.The metadata and gene expression profiles are freely accessible at http://www.geprep.org.cn/.Conclusion GEPREP is a comprehensive data atlas of RNA-seq-based gene expression profiles responding to exercise.With its reliable annotations and user-friendly interfaces,it has the potential to deepen our understanding of exercise physiology.展开更多
In the data transaction process within a data asset trading platform,quantifying the trustworthiness of data source nodes is challenging due to their numerous attributes and complex structures.To address this issue,a ...In the data transaction process within a data asset trading platform,quantifying the trustworthiness of data source nodes is challenging due to their numerous attributes and complex structures.To address this issue,a distributed data source trust assessment management framework,a trust quantification model,and a dynamic adjustment mechanism are proposed.Themodel integrates the Analytic Hierarchy Process(AHP)and Dempster-Shafer(D-S)evidence theory to determine attribute weights and calculate direct trust values,while the PageRank algorithm is employed to derive indirect trust values.Thedirect and indirect trust values are then combined to compute the comprehensive trust value of the data source.Furthermore,a dynamic adjustment mechanism is introduced to continuously update the comprehensive trust value based on historical assessment data.By leveraging the collaborative efforts of multiple nodes in the distributed network,the proposed framework enables a comprehensive,dynamic,and objective evaluation of data source trustworthiness.Extensive experimental analyses demonstrate that the trust quantification model effectively handles large-scale data source trust assessments,exhibiting both strong trust differentiation capability and high robustness.展开更多
Accelerating urbanization is driving an upgrade in the demand for real estate fine finishing,with multi-sector differentiated management and technical risks urgently requiring systematic solutions.Based on the“Guangz...Accelerating urbanization is driving an upgrade in the demand for real estate fine finishing,with multi-sector differentiated management and technical risks urgently requiring systematic solutions.Based on the“Guangzhou City Building and Municipal Infrastructure Engineering Quality Management Measures”(2024),this study constructs a“technical standards-process control-risk hedging”three-dimensional system,integrating BIM collaborative design,prefabricated construction,and big data risk assessment.Empirical evidence shows that the application of this system has shortened the construction period of super high-rise complexes by 12%and kept the cost deviation rate within 1.5%.Differentiated management balances functional complexity with dynamic commercial demands,the fuzzy analytic hierarchy process quantifies risk paths,and penetration testing interrupts chains of quality defects.The outcomes provide support for engineering standardization and intelligent transformation.展开更多
Excessive Fe^(3+) ion concentrations in wastewater pose a long-standing threat to human health.Achieving low-cost,high-efficiency quantification of Fe^(3+) ion concentration in unknown solutions can guide environmenta...Excessive Fe^(3+) ion concentrations in wastewater pose a long-standing threat to human health.Achieving low-cost,high-efficiency quantification of Fe^(3+) ion concentration in unknown solutions can guide environmental management decisions and optimize water treatment processes.In this study,by leveraging the rapid,real-time detection capabilities of nanopores and the specific chemical binding affinity of tannic acid to Fe^(3+),a linear relationship between the ion current and Fe^(3+) ion concentration was established.Utilizing this linear relationship,quantification of Fe^(3+) ion concentration in unknown solutions was achieved.Furthermore,ethylenediaminetetraacetic acid disodium salt was employed to displace Fe^(3+) from the nanopores,allowing them to be restored to their initial conditions and reused for Fe^(3+) ion quantification.The reusable bioinspired nanopores remain functional over 330 days of storage.This recycling capability and the long-term stability of the nanopores contribute to a significant reduction in costs.This study provides a strategy for the quantification of unknown Fe^(3+) concentration using nanopores,with potential applications in environmental assessment,health monitoring,and so forth.展开更多
Infrared unmanned aerial vehicle(UAV)target detection presents significant challenges due to the inter-play between small targets and complex backgrounds.Traditional methods,while effective in controlled environments,...Infrared unmanned aerial vehicle(UAV)target detection presents significant challenges due to the inter-play between small targets and complex backgrounds.Traditional methods,while effective in controlled environments,often fail in scenarios involving long-range targets,high noise levels,or intricate backgrounds,highlighting the need for more robust approaches.To address these challenges,we propose a novel three-stage UAV segmentation framework that leverages uncertainty quantification to enhance target saliency.This framework incorporates a Bayesian convolutional neural network capable of generating both segmentation maps and probabilistic uncertainty maps.By utilizing uncer-tainty predictions,our method refines segmentation outcomes,achieving superior detection accuracy.Notably,this marks the first application of uncertainty modeling within the context of infrared UAV target detection.Experimental evaluations on three publicly available infrared UAV datasets demonstrate the effectiveness of the proposed framework.The results reveal significant improvements in both detection precision and robustness when compared to state-of-the-art deep learning models.Our approach also extends the capabilities of encoder-decoder convolutional neural networks by introducing uncertainty modeling,enabling the network to better handle the challenges posed by small targets and complex environmental conditions.By bridging the gap between theoretical uncertainty modeling and practical detection tasks,our work offers a new perspective on enhancing model interpretability and performance.The codes of this work are available openly at https://github.com/general-learner/UQ_Anti_UAV(acceessed on 11 November 2024).展开更多
Floor heave is a common defect in mountainous tunnels.It is critical but challenging to predict the risk of floor heave,as traditional methods often fail to characterize this phenomenon effectively.This study proposes...Floor heave is a common defect in mountainous tunnels.It is critical but challenging to predict the risk of floor heave,as traditional methods often fail to characterize this phenomenon effectively.This study proposes a data-driven approach utilizing a support vector machine(SVM)optimized by the sparrow search algorithm(SSA)to address the issue.The model was developed and validated using a dataset collected from 100 tunnels.Shapley value analysis was conducted to identify the key features influencing floor heave defects.Moreover,a committee-based uncertainty quantification method is presented to evaluate the reliability of each prediction.The results show that:(1)Data feature engineering and SSA play pivotal roles in expediting the convergence of the SVM model.(2)Groundwater and high in situ stress are key factors contributing to tunnel floor heave.(3)In comparison to backpropagation(BP)neural networks,the SSA-SVM demonstrates superior robustness in handling imperfect and limited data.(4)The committee-based uncertainty quantification method is proven effective to evaluate the trustworthiness of each prediction.This data-driven surrogate model offers an effective strategy for understanding the factors that impact tunnel floor defects and accurately predicting tunnel floor heave deformation.展开更多
Quantitative analysis of clinical function parameters from MRI images is crucial for diagnosing and assessing cardiovascular disease.However,the manual calculation of these parameters is challenging due to the high va...Quantitative analysis of clinical function parameters from MRI images is crucial for diagnosing and assessing cardiovascular disease.However,the manual calculation of these parameters is challenging due to the high variability among patients and the time-consuming nature of the process.In this study,the authors introduce a framework named MultiJSQ,comprising the feature presentation network(FRN)and the indicator prediction network(IEN),which is designed for simultaneous joint segmentation and quantification.The FRN is tailored for representing global image features,facilitating the direct acquisition of left ventricle(LV)contour images through pixel classification.Additionally,the IEN incorporates specifically designed modules to extract relevant clinical indices.The authors’method considers the interdependence of different tasks,demonstrating the validity of these relationships and yielding favourable results.Through extensive experiments on cardiac MR images from 145 patients,MultiJSQ achieves impressive outcomes,with low mean absolute errors of 124 mm^(2),1.72 mm,and 1.21 mm for areas,dimensions,and regional wall thicknesses,respectively,along with a Dice metric score of 0.908.The experimental findings underscore the excellent performance of our framework in LV segmentation and quantification,highlighting its promising clinical application prospects.展开更多
The effect from the interaction of the alternating current(AC)magnetic field with kilogram-level test mass(TM)limits the detectivity of the TianQin space-based gravitational wave detection.The quantifed effect require...The effect from the interaction of the alternating current(AC)magnetic field with kilogram-level test mass(TM)limits the detectivity of the TianQin space-based gravitational wave detection.The quantifed effect requires the determination of the AC magnetic susceptibilityχ(f)of the TM.A torque method is proposed to measure theχ(f)of kg-level samples at the mHz band with a precision of 1×10^(-7).Combined with our previous work[Phys.Rev.Appl.18044010(2022)],the general frequency-dependent susceptibility of the alloy cube with side length L and electrical conductivityσis determined asχ(f)=χ0+(0.24±0.01)σμ0L^(2)f from 0.1 mHz to 1 Hz.The determination is helpful for the preliminary estimation of the in-band eddy current efect in the TianQin noise budget.The technique can be adopted to accurately measureχ(f)of the actual TM in other precision experiments,where the magnetic noise is a signifcant detection limit.展开更多
As an essential tool for quantitative analysis of lower limb coordination,optical motion capture systems with marker-based encoding still suffer from inefficiency,high costs,spatial constraints,and the requirement for...As an essential tool for quantitative analysis of lower limb coordination,optical motion capture systems with marker-based encoding still suffer from inefficiency,high costs,spatial constraints,and the requirement for multiple markers.While 3D pose estimation algorithms combined with ordinary cameras offer an alternative,their accuracy often deteriorates under significant body occlusion.To address the challenge of insufficient 3D pose estimation precision in occluded scenarios—which hinders the quantitative analysis of athletes’lower-limb coordination—this paper proposes a multimodal training framework integrating spatiotemporal dependency networks with text-semantic guidance.Compared to traditional optical motion capture systems,this work achieves low-cost,high-precision motion parameter acquisition through the following innovations:(1)spatiotemporal dependency attention module is designed to establish dynamic spatiotemporal correlation graphs via cross-frame joint semantic matching,effectively resolving the feature fragmentation issue in existing methods.(2)noise-suppressed multi-scale temporal module is proposed,leveraging KL divergence-based information gain analysis for progressive feature filtering in long-range dependencies,reducing errors by 1.91 mm compared to conventional temporal convolutions.(3)text-pose contrastive learning paradigm is introduced for the first time,where BERT-generated action descriptions align semantic-geometric features via the BERT encoder,significantly enhancing robustness under severe occlusion(50%joint invisibility).On the Human3.6M dataset,the proposed method achieves an MPJPE of 56.21 mm under Protocol 1,outperforming the state-of-the-art baseline MHFormer by 3.3%.Extensive ablation studies on Human3.6M demonstrate the individual contributions of the core modules:the spatiotemporal dependency module and noise-suppressed multi-scale temporal module reduce MPJPE by 0.30 and 0.34 mm,respectively,while the multimodal training strategy further decreases MPJPE by 0.6 mm through text-skeleton contrastive learning.Comparative experiments involving 16 athletes show that the sagittal plane coupling angle measurements of hip-ankle joints differ by less than 1.2°from those obtained via traditional optical systems(two one-sided t-tests,p<0.05),validating real-world reliability.This study provides an AI-powered analytical solution for competitive sports training,serving as a viable alternative to specialized equipment.展开更多
基金the National Natural Science Foundation of China(No.60672145).
文摘The quantificational and normative design is the precondition of improving the design of copper staves for blast furnaces. Based on a 3-dimensional temperature field calculation model, from the view point of heat transfer and long campaigns note with the core of forming accretion, the forming-accretion-ability （FAA） and the rib hot surface maximum temperature difference （ATmax） as quantificational indexes to direct and evaluate the design of copper staves for blast furnaces were presented. The application of the two indexes in design essentially embodies the new long campaigns in the stage of design. With the application of the two indexes, good results can be obtained. Firstly, it was suggested that the rib height of a copper stave can be reduced to 15 mm, which is a new method and theory for the reduction of copper staves. Secondly, the influence of insert on FAA and ATmax, is decided by the volume of insert. According to this, the principle of design for the hot surface geometry of copper staves was put forward that the ratio of the rib hot surface to the copper stave hot surface （abbreviated as the ratio of rib to stave） must be maintained in the range of 45% to 55%; for the present copper stave with a 35-40 mm thick rib, the ratio of rib to stave in the range of 50% to 55% can optimize the design of copper staves; for the copper stave with a smaller rib thickness, for example 15 ram, the ratio of rib to stave in the range of 45% to 50% can optimize the design of copper staves. It can be summarized that the thicker the rib thickness, the larger is the ratio of rib to stave. 2008 University of Science and Technology Beijing. All rights reserved.
基金Modernization of Traditional Chinese Medicine Project of National Key R&D Program of China:The construction of the theoretical system of Traditional Chinese Medicine nonpharmacological therapy based on body surface stimulation(2023YFC3502704)Sichuan Provincial Science and Technology Program Project:Research and Development of Chinese Medicine Intelligent Tongue Diagnosis Equipment for Digestive System Chinese Medicine Advantageous Diseases(2023YFS0327)+2 种基金Research and Development of Chinese Medicine Intelligent Detection System for Intestinal Functions(2024YFFK0044)Research and Application of Chinese Medicine Diagnosis and Treatment Program for Herpes Zoster Treated by Shu Pai Fire Acupuncture(2024YFFK0089)Major Research and Development Project of The China Academy of Chinese Medical Sciences Innovation:Construction and application of the theoretical research mode of Traditional Chinese Medicine diagnosis and treatment of modern diseases(CI2021A00104)。
文摘OBJECTIVE:To propose an automatic acupuncture robot system for performing acupuncture operations.METHODS:The acupuncture robot system consists of three components:automatic acupoint localization,acupuncture manipulations,and De Qi sensation detection.The OptiTrack motion capture system is used to locate acupoints,which are then translated into coordinates in the robot control system.A flexible collaborative robot with an intelligent gripper is then used to perform acupuncture manipulations with high precision.In addition,a De Qi sensation detection system is proposed to evaluate the effect of acupuncture.To verify the stability of the designed acupuncture robot,acupoints'coordinates localized by the acupuncture robot are compared with the Gold Standard labeled by a professional acupuncturist using significant level tests.RESULTS:Through repeated experiments for eight acupoints,the acupuncture robot achieved a positioning error within 3.3 mm,which is within the allowable range of needle extraction and acupoint insertion.During needle insertion,the robot arm followed the prescribed trajectory with a mean deviation distance of 0.02 mm and a deviation angle of less than 0.15°.The results of the lifting thrusting operation in the Xingzhen process show that the mean acupuncture depth error of the designed acupuncture robot is approximately 2 mm,which is within the recommended depth range for the Xingzhen operation.In addition,the average detection accuracy of the De Qi keywords is 94.52%,which meets the requirements of acupuncture effect testing for different dialects.CONCLUSION:The proposed acupuncture robot system streamlines the acupuncture process,increases efficiency,and reduces practitioner fatigue,while also allowing for the quantification of acupuncture manipulations and evaluation of therapeutic effects.The development of an acupuncture robot system has the potential to revolutionize low back pain treatment and improve patient outcomes.
文摘A two-stage algorithm based on deep learning for the detection and recognition of can bottom spray codes and numbers is proposed to address the problems of small character areas and fast production line speeds in can bottom spray code number recognition.In the coding number detection stage,Differentiable Binarization Network is used as the backbone network,combined with the Attention and Dilation Convolutions Path Aggregation Network feature fusion structure to enhance the model detection effect.In terms of text recognition,using the Scene Visual Text Recognition coding number recognition network for end-to-end training can alleviate the problem of coding recognition errors caused by image color distortion due to variations in lighting and background noise.In addition,model pruning and quantization are used to reduce the number ofmodel parameters to meet deployment requirements in resource-constrained environments.A comparative experiment was conducted using the dataset of tank bottom spray code numbers collected on-site,and a transfer experiment was conducted using the dataset of packaging box production date.The experimental results show that the algorithm proposed in this study can effectively locate the coding of cans at different positions on the roller conveyor,and can accurately identify the coding numbers at high production line speeds.The Hmean value of the coding number detection is 97.32%,and the accuracy of the coding number recognition is 98.21%.This verifies that the algorithm proposed in this paper has high accuracy in coding number detection and recognition.
基金supported by the key project at the central government level:The ability establishment of sustainable use for valuable Chinese medicine resources(Grant number 2060302)the National Natural Science Foundation of China(Grant number 82373982,82173929).
文摘Background:Rosa chinensis Jacq.and Rosa rugosa Thunb.are not only of ornamental value,but also edible flowers and the flower buds have been listed in the Chinese Pharmacopoeia as traditional medicines.The two plants have some differences in efficacy,but the flower buds are easily confused for similar traits.In addition,large-scale cultivation of ornamental rose flowers may lead to a decrease in the effective components of medicinal roses.Therefore,it is necessary to study the chemical composition and make quality evaluation of Rosae Chinensis Flos(Yueji)and Rosae Rugosae Flos(Meigui).Methods:In this study,40 batches of samples including Meigui and Yueji from different regions in China were collected to establish high-performance liquid chromatography fingerprints.Then,the fingerprints data was analyzed using principal component analysis,hierarchical cluster analysis,and partial least squares discriminant analysis analysis chemometrics to obtain information on intergroup differences,and non-targeted metabolomic techniques were applied to identify and compare chemical compositions of samples which were chosen from groups with large differences.Differential compounds were screened by orthogonal partial least-squares discriminant analysis and S-plot,and finally multi-component quantification was performed to comprehensively evaluate the quality of Yueji and Meigui.Results:The similarity between the fingerprints of 40 batches roses and the reference print R was 0.73 to 0.93,indicating that there were similarities and differences between the samples.Through principal component analysis and hierarchical cluster analysis of fingerprints data,the samples from different origins and varieties were intuitively divided into four groups.Partial least-squares discriminant analysis analysis showed that Meigui and Yueji cluster into two categories and the model was reliable.A total of 89 compounds were identified by high resolution mass spectrometry,mainly were flavonoids and flavonoid glycosides,as well as phenolic acids.Eight differential components were screened out by orthogonal partial least-squares discriminant analysis and S-plot analysis.Quantitative analyses of the eight compounds,including gallic acid,ellagic acid,hyperoside,isoquercitrin,etc.,showed that Yueji was generally richer in phenolic acids and flavonoids than Meigui,and the quality of Yueji from Shandong and Hebei was better.It is worth noting that Xinjiang rose is rich in various components,which is worth focusing on more in-depth research.Conclusion:In this study,the fingerprints of Meigui and Yueji were established.The chemical components information of roses was further improved based on non-targeted metabolomics and mass spectrometry technology.At the same time,eight differential components of Meigui and Yueji were screened out and quantitatively analyzed.The research results provided a scientific basis for the quality control and rational development and utilization of Rosae Chinensis Flos and Rosae Rugosae Flos,and also laid a foundation for the study of their pharmacodynamic material basis.
基金Funding from Natural Sciences and Engineering Research Council of Canada award number RGPIN/4002-2020.
文摘Viral diseases are an important threat to crop yield,as they are responsible for losses greater than US$30 billion annually.Thus,understanding the dynamics of virus propagation within plant cells is essential for devising effective control strategies.However,viruses are complex to propagate and quantify.Existing methodologies for viral quantification tend to be expensive and time-consuming.Here,we present a rapid cost-effective approach to quantify viral propagation using an engineered virus expressing a fluorescent reporter.Using a microplate reader,we measured viral protein levels and we validated our findings through comparison by western blot analysis of viral coat protein,the most common approach to quantify viral titer.Our proposed methodology provides a practical and accessible approach to studying virus-host interactions and could contribute to enhancing our understanding of plant virology.
基金supported by the Arthritis Foundation(principal investigator:BP)the National Institute of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health(P30-AR072580)。
文摘Background:Changes in lower limb joint coordination have been shown to increase localized stress on knee joint soft tissue—a known precursor of osteoarthritis.While 50%of individuals who undergo anterior cruciate ligament reconstruction(ACLR)develop radiographic osteoarthritis,it is unclear how underlying joint coordination during gait changes post-ACLR.The purpose of this study was twofold:to determine differences in lower limb coordination patterns during gait in ACLR individuals 2,4,and 6 months post-ACLR and to compare the coordination profiles of the ACLR participants at each timepoint post-ACLR to uninjured matched controls.Methods:We conducted a longitudinal assessment to quantify lower limb coordination at 3 timepoints post-ACLR and compared the ACLR coordination profiles to uninjured controls.Thirty-four ACLR(age=21.43±4.24 years,mean±SD;70.59%female)and 34 controls(age=21.42±3.43 years;70.59%female)participated.The ACLR group completed 3 overground gait assessments(2,4,and 6 months post-ACLR),and the controls completed one assessment,at which lower limb kinematics were collected.Cross-recurrence quantification analysis was used to characterize sagittal and frontal plane ankle-knee,ankle-hip,and knee-hip coordination dynamics.Comprehensive general linear mixed models were constructed to compare between-limb and within-limb coordination outcomes over time post-ACLR and a between-group comparison across timepoints.Results:The ACLR limb demonstrated a more"stuck"sagittal plane knee-hip coordination profile(greater trapping time(TT);p=0.004)compared bilaterally.Between groups,the ACLR participants exhibited a more predictable ankle-knee coordination pattern(percent determinism(%DET);p<0.05),stronger coupling between joints(meanline(MNLine))across all segments(p<0.05),and greater knee-hip TT(more"stuck";p<0.05)compared to the controls at each timepoint in the sagittal plane.Stronger frontal plane knee-hip joint coupling(MNLine)persisted across timepoints within the ACLR group compared to the controls(p<0.05).Conclusion:The results indicate ACLR individuals exhibit a distinct and rigid coordination pattern during gait compared to controls within6-month post-ACLR,which may have long-term implications for knee-joint health.
文摘BACKGROUND The Streptococcus salivarius(S.salivarius)group,which produces the enzyme urease has been identified as a potential contributor to ammonia production in the gut.Researchers have reported that patients with minimal HE had an increased abundance of the S.salivarius group,which is a specific change in the gut microbiota that distinguishes them from healthy individuals.The correlation between the aggregation of specific bacterial species and fibrosis progression in chronic liver disease(CLD)is yet to be fully elucidated.AIM To quantify S.salivarius using digital PCR(dPCR)as a liver fibrosis marker of CLD.METHODS This study retrospectively analysed 52 patients with CLD.To quantify S.salivarius in patients with CLD using dPCR,we evaluated the specificity and sensitivity of S.salivarius bacterial load using dPCR for a type strain.Next,we evaluated the clinical usefulness of dPCR for S.salivarius load quantification for detecting liver fibrosis in patients with CLD.The liver fibrosis stage was categorized into mild and advanced fibrosis based on pathological findings.RESULTS The dPCR assay revealed that S.salivarius was highly positive for the tnpA gene.The lower limit of quantification for dPCR using the tnpA gene with a 1μL template comprising 1.28×102 CFU/mL was 4.3 copies.After considering the detection range in dPCR,we adjusted the extracted DNA concentration to 5.0×10-4 ng/μL from 200 mg stool samples.The median bacterial loads of S.salivarius in stool sample from patients with mild and advanced fibrosis were 1.9 and 7.4 copies/μL,respectively.The quantification of S.salivarius load was observed more frequently in patients with advanced fibrosis than in those with mild fibrosis(P=0.032).CONCLUSION Quantifying of S.salivarius load using digital PCR is a useful biomarker for liver fibrosis in patients with CLD.
基金supported by the National Natural Science Foundation of China(No.32170491)the Scientific Research Team Project of the College of Life Sciences,Beijing Normal University in 2024。
文摘Avian wings are central to their remarkable flight ability and diverse life history strategies,including behaviors such as fighting and mating.These multifaceted functions are intricately tied to wing shape,which varies significantly across species because of the complex interplay of evolutionary and ecological pressures.Many indices have been developed to quantify wing characteristics to facilitate the study and comparison of avian wing morphology across species.This study provides a comprehensive overview of existing quantitative methods for analyzing avian wing shapes.We then constructed a new quantification framework through the beta distribution,which can generate indices reflecting the shape of avian wings(center,dispersion,skewness,and kurtosis).Next,we used the flight feathers of 613 bird species to perform different quantitative analyses and explore the relationships between various wing shape quantification methods and life history traits,which serve as proxies for the selective forces shaping wing morphology.We find that the wing shape indices are more strongly associated with ecological variables than with morphological variables,especially for migration,habitat and territoriality.This research guides the selection of appropriate methods for wing shape analysis,contributing to a deeper understanding of avian morphology and its evolutionary drivers.
基金supported by the National Key Research and Development Program of China(Nos.2023YFC2307305,2021YFF0703300)the Shenzhen Medical Research Fund(No.B2303003)+3 种基金Shenzhen Research Funding Program(Nos.JCYJ20220818102014028,RCBS20210609104339043)National Natural Science Foundation of China(No.22174167)Guangdong Basic and Applied Basic Research(No.2024A1515011281)Fundamental Research Funds for the Central Universities(No.24qnpy087)from Sun Yat-sen University。
文摘Ultrasensitive detection of nucleic acids is of great significance for precision medicine.Digital polymerase chain reaction(dPCR)is the most sensitive method but requires sophisticated and expensive instruments and a long reaction time.Digital PCR-free technologies,which mean the digital assay not relying on thermal cycling to amplify the signal for quantitative detection of nucleic acids at the singlemolecule level,include the digital isothermal amplification techniques(d IATs)and the digital clustered regularly interspaced short palindromic repeats(CRISPR)technologies.They combine the advantages of d PCR and IATs,which could be fast and simple,enabling absolute quantification of nucleic acids at a single-molecule level with minimum instrument,representing the next-generation molecular diagnostic technology.Herein,we systematically summarized the strategies and applications of various dIATs,including the digital loop-mediated isothermal amplification(dLAMP),the digital recombinase polymerase amplification(dRPA),the digital rolling circle amplification(dRCA),the digital nucleic acid sequencebased amplification(d NASBA)and the digital multiple displacement amplification(d MDA),and evaluated the pros and cons of each method.The emerging digital CRISPR technologies,including the detection mechanism of CRISPR and the various strategies for signal amplification,are also introduced comprehensively in this review.The current challenges as well as the future perspectives of the digital PCR-free technology were discussed.
基金support of this project through the Southwest Regional Partnership on Carbon Sequestration(Grant No.DE-FC26-05NT42591)Improving Production in the Emerging Paradox Oil Play(Grant No.DE-FE0031775).
文摘Geomechanical properties of rocks vary across different measurement scales,primarily due to heterogeneity.Micro-scale geomechanical tests,including micro-scale“scratch tests”and nano-scale nanoindentation tests,are attractive at different scales.Each method requires minimal sample volume,is low cost,and includes a relatively rapid measurement turnaround time.However,recent micro-scale test results–including scratch test results and nanoindentation results–exhibit tangible variance and uncertainty,suggesting a need to correlate mineral composition mapping to elastic modulus mapping to isolate the relative impact of specific minerals.Different research labs often utilize different interpretation methods,and it is clear that future micro-mechanical tests may benefit from standardized testing and interpretation procedures.The objectives of this study are to seek options for standardized testing and interpretation procedures,through two specific objectives:(1)Quantify chemical and physical controls on micro-mechanical properties and(2)Quantify the source of uncertainties associated with nanoindentation measurements.To reach these goals,we conducted mechanical tests on three different scales:triaxial compression tests,scratch tests,and nanoindentation tests.We found that mineral phase weight percentage is highly correlated with nanoindentation elastic modulus distribution.Finally,we conclude that nanoindentation testing is a mineralogy and microstructure-based method and generally yields significant uncertainty and overestimation.The uncertainty of the testing method is largely associated with not mapping pore space a priori.Lastly,the uncertainty can be reduced by combining phase mapping and modulus mapping with substantial and random data sampling.
文摘During high-speed forward flight,helicopter rotor blades operate across a wide range of Reynolds and Mach numbers.Under such conditions,their aerodynamic performance is significantly influenced by dynamic stall—a complex,unsteady flow phenomenon highly sensitive to inlet conditions such asMach and Reynolds numbers.The key features of three-dimensional blade stall can be effectively represented by the dynamic stall behavior of a pitching airfoil.In this study,we conduct an uncertainty quantification analysis of dynamic stall aerodynamics in high-Mach-number flows over pitching airfoils,accounting for uncertainties in inlet parameters.A computational fluid dynamics(CFD)model based on the compressible unsteady Reynolds-averagedNavier–Stokes(URANS)equations,coupledwith sliding mesh techniques,is developed to simulate the unsteady aerodynamic behavior and associated flow fields.To efficiently capture the aerodynamic responses while maintaining high accuracy,a multi-fidelity Co-Kriging surrogate model is constructed.This model integrates the precision of high-fidelity wind tunnel experiments with the computational efficiency of lower-fidelity URANS simulations.Its accuracy is validated through direct comparison with experimental data.Building upon this surrogate model,we employ interval analysis and the Sobol sensitivity method to quantify the uncertainty and parameter sensitivity of the unsteady aerodynamic forces resulting frominlet condition variability.Both the inlet Mach number and Reynolds number are treated as uncertain inputs,modeled using interval representations.Our results demonstrate that variations inMach number contribute far more significantly to aerodynamic uncertainty than those in Reynolds number.Moreover,the presence of dynamic stall vortices markedly amplifies the aerodynamic sensitivity to Mach number fluctuations.
基金supported by grants from the Shanghai“Science and Technology Innovation Action Plan”Social Development Science and Technology Reach Project(22dz1204600)Shanghai Sports Science and Technology Program(24C002)+2 种基金the National Key R&D Program of China(2020YFA0803800)the National Natural Science Foundation of China(32200515,32271226)Shanghai Municipal Science and Technology Committee of Shanghai outstanding academic leaders plan(21XD1403200).
文摘Background Physical activity can regulate and affect gene expression in multiple tissues and cells.Recently,with the development of next-generation sequencing,a large number of RNA-sequencing(RNA-seq)-based gene expression profiles about physical activity have been shared in public resources;however,they are poorly curated and underutilized.To tackle this problem,we developed a data atlas of such data through comprehensive data collection,curation,and organization.Methods The data atlas,termed gene expression profiles of RNA-seq-based exercise responses(GEPREP),was built on a comprehensive collection of high-quality RNA-seq data on exercise responses.The metadata of each sample were manually curated.Data were uniformly processed and batch effects corrected.All the information was well organized in an easy-to-use website for free search,visualization,and download.Results GEPREP now includes 69 RNA-seq datasets of pre-and post-exercise,comprising 26 human datasets(1120 samples)and 43 mouse datasets(1006 samples).Specifically,there were 977(87.2%)human samples of skeletal muscle and 143(12.8%)human samples of blood.There were also samples across 9 mice tissues with skeletal muscle(359,35.7%)and brain(280,27.8%)accounting for the main fractions.Metadata—including subject,exercise interventions,sampling sites,and post-processing methods—are also included.The metadata and gene expression profiles are freely accessible at http://www.geprep.org.cn/.Conclusion GEPREP is a comprehensive data atlas of RNA-seq-based gene expression profiles responding to exercise.With its reliable annotations and user-friendly interfaces,it has the potential to deepen our understanding of exercise physiology.
基金funded by Haikou Science and Technology Plan Project(2022-007),in part by key Laboratory of PK System Technologies Research of Hainan,China.
文摘In the data transaction process within a data asset trading platform,quantifying the trustworthiness of data source nodes is challenging due to their numerous attributes and complex structures.To address this issue,a distributed data source trust assessment management framework,a trust quantification model,and a dynamic adjustment mechanism are proposed.Themodel integrates the Analytic Hierarchy Process(AHP)and Dempster-Shafer(D-S)evidence theory to determine attribute weights and calculate direct trust values,while the PageRank algorithm is employed to derive indirect trust values.Thedirect and indirect trust values are then combined to compute the comprehensive trust value of the data source.Furthermore,a dynamic adjustment mechanism is introduced to continuously update the comprehensive trust value based on historical assessment data.By leveraging the collaborative efforts of multiple nodes in the distributed network,the proposed framework enables a comprehensive,dynamic,and objective evaluation of data source trustworthiness.Extensive experimental analyses demonstrate that the trust quantification model effectively handles large-scale data source trust assessments,exhibiting both strong trust differentiation capability and high robustness.
文摘Accelerating urbanization is driving an upgrade in the demand for real estate fine finishing,with multi-sector differentiated management and technical risks urgently requiring systematic solutions.Based on the“Guangzhou City Building and Municipal Infrastructure Engineering Quality Management Measures”(2024),this study constructs a“technical standards-process control-risk hedging”three-dimensional system,integrating BIM collaborative design,prefabricated construction,and big data risk assessment.Empirical evidence shows that the application of this system has shortened the construction period of super high-rise complexes by 12%and kept the cost deviation rate within 1.5%.Differentiated management balances functional complexity with dynamic commercial demands,the fuzzy analytic hierarchy process quantifies risk paths,and penetration testing interrupts chains of quality defects.The outcomes provide support for engineering standardization and intelligent transformation.
基金supported by the National Natural Science Foundation of China(Nos.52303380,52025132,52273305,22205185,21621091,22021001,and 22121001)Fundamental Research Funds for the Central Universities(No.20720240041)+3 种基金the 111 Project(Nos.B17027 and B16029)the National Science Foundation of Fujian Province of China(No.2022J02059)the Science and Technology Projects of Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province(No.RD2022070601)the New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘Excessive Fe^(3+) ion concentrations in wastewater pose a long-standing threat to human health.Achieving low-cost,high-efficiency quantification of Fe^(3+) ion concentration in unknown solutions can guide environmental management decisions and optimize water treatment processes.In this study,by leveraging the rapid,real-time detection capabilities of nanopores and the specific chemical binding affinity of tannic acid to Fe^(3+),a linear relationship between the ion current and Fe^(3+) ion concentration was established.Utilizing this linear relationship,quantification of Fe^(3+) ion concentration in unknown solutions was achieved.Furthermore,ethylenediaminetetraacetic acid disodium salt was employed to displace Fe^(3+) from the nanopores,allowing them to be restored to their initial conditions and reused for Fe^(3+) ion quantification.The reusable bioinspired nanopores remain functional over 330 days of storage.This recycling capability and the long-term stability of the nanopores contribute to a significant reduction in costs.This study provides a strategy for the quantification of unknown Fe^(3+) concentration using nanopores,with potential applications in environmental assessment,health monitoring,and so forth.
基金supported by the Science and Technology Project of Sichuan(Grant No.2024ZHCG0170)the National Key Research and Development Program of China,“Key Technologies for Instrumentation and Control System Program Security Based on Blockchain”(Project No.2024YFB3311000)+1 种基金States Key Laboratory of Air Traffic Management System(Grant No.SKLATM202202)the Chengdu Science and Technology Project(Grant No.2022-YF05-00068-SN).
文摘Infrared unmanned aerial vehicle(UAV)target detection presents significant challenges due to the inter-play between small targets and complex backgrounds.Traditional methods,while effective in controlled environments,often fail in scenarios involving long-range targets,high noise levels,or intricate backgrounds,highlighting the need for more robust approaches.To address these challenges,we propose a novel three-stage UAV segmentation framework that leverages uncertainty quantification to enhance target saliency.This framework incorporates a Bayesian convolutional neural network capable of generating both segmentation maps and probabilistic uncertainty maps.By utilizing uncer-tainty predictions,our method refines segmentation outcomes,achieving superior detection accuracy.Notably,this marks the first application of uncertainty modeling within the context of infrared UAV target detection.Experimental evaluations on three publicly available infrared UAV datasets demonstrate the effectiveness of the proposed framework.The results reveal significant improvements in both detection precision and robustness when compared to state-of-the-art deep learning models.Our approach also extends the capabilities of encoder-decoder convolutional neural networks by introducing uncertainty modeling,enabling the network to better handle the challenges posed by small targets and complex environmental conditions.By bridging the gap between theoretical uncertainty modeling and practical detection tasks,our work offers a new perspective on enhancing model interpretability and performance.The codes of this work are available openly at https://github.com/general-learner/UQ_Anti_UAV(acceessed on 11 November 2024).
基金financially supported by the National Natural Science Foundation of China(Grant No.52008039)the Guizhou Provincial Department of Transportation Science and Technology Project(Project No.2024-121-043)the Changsha University of Science and Technology Graduate Research Innovation Project(Grant No.CLSJCX23036).
文摘Floor heave is a common defect in mountainous tunnels.It is critical but challenging to predict the risk of floor heave,as traditional methods often fail to characterize this phenomenon effectively.This study proposes a data-driven approach utilizing a support vector machine(SVM)optimized by the sparrow search algorithm(SSA)to address the issue.The model was developed and validated using a dataset collected from 100 tunnels.Shapley value analysis was conducted to identify the key features influencing floor heave defects.Moreover,a committee-based uncertainty quantification method is presented to evaluate the reliability of each prediction.The results show that:(1)Data feature engineering and SSA play pivotal roles in expediting the convergence of the SVM model.(2)Groundwater and high in situ stress are key factors contributing to tunnel floor heave.(3)In comparison to backpropagation(BP)neural networks,the SSA-SVM demonstrates superior robustness in handling imperfect and limited data.(4)The committee-based uncertainty quantification method is proven effective to evaluate the trustworthiness of each prediction.This data-driven surrogate model offers an effective strategy for understanding the factors that impact tunnel floor defects and accurately predicting tunnel floor heave deformation.
基金Hefei Municipal Natural Science Foundation,Grant/Award Number:2022009Suqian Guiding Program Project,Grant/Award Number:Z202309Suqian Traditional Chinese Medicine Science and Technology Plan,Grant/Award Number:MS202301。
文摘Quantitative analysis of clinical function parameters from MRI images is crucial for diagnosing and assessing cardiovascular disease.However,the manual calculation of these parameters is challenging due to the high variability among patients and the time-consuming nature of the process.In this study,the authors introduce a framework named MultiJSQ,comprising the feature presentation network(FRN)and the indicator prediction network(IEN),which is designed for simultaneous joint segmentation and quantification.The FRN is tailored for representing global image features,facilitating the direct acquisition of left ventricle(LV)contour images through pixel classification.Additionally,the IEN incorporates specifically designed modules to extract relevant clinical indices.The authors’method considers the interdependence of different tasks,demonstrating the validity of these relationships and yielding favourable results.Through extensive experiments on cardiac MR images from 145 patients,MultiJSQ achieves impressive outcomes,with low mean absolute errors of 124 mm^(2),1.72 mm,and 1.21 mm for areas,dimensions,and regional wall thicknesses,respectively,along with a Dice metric score of 0.908.The experimental findings underscore the excellent performance of our framework in LV segmentation and quantification,highlighting its promising clinical application prospects.
基金supported by the National Key R&D Program of China(Grant No.2020YFC2200500)the Key Laboratory of Tian Qin Project(Sun Yat-sen University),Ministry of Education+1 种基金the National Natural Science Foundation of China(Grant Nos.12075325,12005308,and 11605065)the Doctoral Research Foundation Project of Hubei University of Arts and Science(Grant No.kyqdf2059017)。
文摘The effect from the interaction of the alternating current(AC)magnetic field with kilogram-level test mass(TM)limits the detectivity of the TianQin space-based gravitational wave detection.The quantifed effect requires the determination of the AC magnetic susceptibilityχ(f)of the TM.A torque method is proposed to measure theχ(f)of kg-level samples at the mHz band with a precision of 1×10^(-7).Combined with our previous work[Phys.Rev.Appl.18044010(2022)],the general frequency-dependent susceptibility of the alloy cube with side length L and electrical conductivityσis determined asχ(f)=χ0+(0.24±0.01)σμ0L^(2)f from 0.1 mHz to 1 Hz.The determination is helpful for the preliminary estimation of the in-band eddy current efect in the TianQin noise budget.The technique can be adopted to accurately measureχ(f)of the actual TM in other precision experiments,where the magnetic noise is a signifcant detection limit.
基金supported by the Major Sports Research Projects of Jiangsu Provincial Sports Bureau in 2022(No.ST221101).
文摘As an essential tool for quantitative analysis of lower limb coordination,optical motion capture systems with marker-based encoding still suffer from inefficiency,high costs,spatial constraints,and the requirement for multiple markers.While 3D pose estimation algorithms combined with ordinary cameras offer an alternative,their accuracy often deteriorates under significant body occlusion.To address the challenge of insufficient 3D pose estimation precision in occluded scenarios—which hinders the quantitative analysis of athletes’lower-limb coordination—this paper proposes a multimodal training framework integrating spatiotemporal dependency networks with text-semantic guidance.Compared to traditional optical motion capture systems,this work achieves low-cost,high-precision motion parameter acquisition through the following innovations:(1)spatiotemporal dependency attention module is designed to establish dynamic spatiotemporal correlation graphs via cross-frame joint semantic matching,effectively resolving the feature fragmentation issue in existing methods.(2)noise-suppressed multi-scale temporal module is proposed,leveraging KL divergence-based information gain analysis for progressive feature filtering in long-range dependencies,reducing errors by 1.91 mm compared to conventional temporal convolutions.(3)text-pose contrastive learning paradigm is introduced for the first time,where BERT-generated action descriptions align semantic-geometric features via the BERT encoder,significantly enhancing robustness under severe occlusion(50%joint invisibility).On the Human3.6M dataset,the proposed method achieves an MPJPE of 56.21 mm under Protocol 1,outperforming the state-of-the-art baseline MHFormer by 3.3%.Extensive ablation studies on Human3.6M demonstrate the individual contributions of the core modules:the spatiotemporal dependency module and noise-suppressed multi-scale temporal module reduce MPJPE by 0.30 and 0.34 mm,respectively,while the multimodal training strategy further decreases MPJPE by 0.6 mm through text-skeleton contrastive learning.Comparative experiments involving 16 athletes show that the sagittal plane coupling angle measurements of hip-ankle joints differ by less than 1.2°from those obtained via traditional optical systems(two one-sided t-tests,p<0.05),validating real-world reliability.This study provides an AI-powered analytical solution for competitive sports training,serving as a viable alternative to specialized equipment.
