The dramatic increase in intracranial pressure after subarachnoid hemorrhage leads to a decrease in cerebral perfusion pressure and a reduction in cerebral blood flow.Mitochondria are directly affected by direct facto...The dramatic increase in intracranial pressure after subarachnoid hemorrhage leads to a decrease in cerebral perfusion pressure and a reduction in cerebral blood flow.Mitochondria are directly affected by direct factors such as ischemia,hypoxia,excitotoxicity,and toxicity of free hemoglobin and its degradation products,which trigger mitochondrial dysfunction.Dysfunctional mitochondria release large amounts of reactive oxygen species,inflammatory mediators,and apoptotic proteins that activate apoptotic pathways,further damaging cells.In response to this array of damage,cells have adopted multiple mitochondrial quality control mechanisms through evolution,including mitochondrial protein quality control,mitochondrial dynamics,mitophagy,mitochondrial biogenesis,and intercellular mitochondrial transfer,to maintain mitochondrial homeostasis under pathological conditions.Specific interventions targeting mitochondrial quality control mechanisms have emerged as promising therapeutic strategies for subarachnoid hemorrhage.This review provides an overview of recent research advances in mitochondrial pathophysiological processes after subarachnoid hemorrhage,particularly mitochondrial quality control mechanisms.It also presents potential therapeutic strategies to target mitochondrial quality control in subarachnoid hemorrhage.展开更多
This work constructed a machine learning(ML)model to predict the atmospheric corrosion rate of low-alloy steels(LAS).The material properties of LAS,environmental factors,and exposure time were used as the input,while ...This work constructed a machine learning(ML)model to predict the atmospheric corrosion rate of low-alloy steels(LAS).The material properties of LAS,environmental factors,and exposure time were used as the input,while the corrosion rate as the output.6 dif-ferent ML algorithms were used to construct the proposed model.Through optimization and filtering,the eXtreme gradient boosting(XG-Boost)model exhibited good corrosion rate prediction accuracy.The features of material properties were then transformed into atomic and physical features using the proposed property transformation approach,and the dominant descriptors that affected the corrosion rate were filtered using the recursive feature elimination(RFE)as well as XGBoost methods.The established ML models exhibited better predic-tion performance and generalization ability via property transformation descriptors.In addition,the SHapley additive exPlanations(SHAP)method was applied to analyze the relationship between the descriptors and corrosion rate.The results showed that the property transformation model could effectively help with analyzing the corrosion behavior,thereby significantly improving the generalization ability of corrosion rate prediction models.展开更多
Laser powder bed fusion(L-PBF)of Mg alloys has provided tremendous opportunities for customized production of aeronautical and medical parts.Layer thickness(LT)is of great significance to the L-PBF process but has not...Laser powder bed fusion(L-PBF)of Mg alloys has provided tremendous opportunities for customized production of aeronautical and medical parts.Layer thickness(LT)is of great significance to the L-PBF process but has not been studied for Mg alloys.In this study,WE43 Mg alloy bulk cubes,porous scaffolds,and thin walls with layer thicknesses of 10,20,30,and 40μm were fabricated.The required laser energy input increased with increasing layer thickness and was different for the bulk cubes and porous scaffolds.Porosity tended to occur at the connection joints in porous scaffolds for LT40 and could be eliminated by reducing the laser energy input.For thin wall parts,a large overhang angle or a small wall thickness resulted in porosity when a large layer thicknesses was used,and the porosity disappeared by reducing the layer thickness or laser energy input.A deeper keyhole penetration was found in all occasions with porosity,explaining the influence of layer thickness,geometrical structure,and laser energy input on the porosity.All the samples achieved a high fusion quality with a relative density of over 99.5%using the optimized laser energy input.The increased layer thickness resulted to more precipitation phases,finer grain sizes and decreased grain texture.With the similar high fusion quality,the tensile strength and elongation of bulk samples were significantly improved from 257 MPa and 1.41%with the 10μm layer to 287 MPa and 15.12%with the 40μm layer,in accordance with the microstructural change.The effect of layer thickness on the compressive properties of porous scaffolds was limited.However,the corrosion rate of bulk samples accelerated with increasing the layer thickness,mainly attributed to the increased number of precipitation phases.展开更多
Nickel-based superalloys are extensively used in the crucial hot-section components of industrial gas turbines,aeronautics,and astronautics because of their excellent mechanical properties and corrosion resistance at ...Nickel-based superalloys are extensively used in the crucial hot-section components of industrial gas turbines,aeronautics,and astronautics because of their excellent mechanical properties and corrosion resistance at high temperatures.Fusion welding serves as an effective means for joining and repairing these alloys;however,fusion welding-induced liquation cracking has been a challenging issue.This paper comprehensively reviewed recent liquation cracking,discussing the formation mechanisms,cracking criteria,and remedies.In recent investigations,regulating material composition,changing the preweld heat treatment of the base metal,optimizing the welding process parameters,and applying auxiliary control methods are effective strategies for mitigating cracks.To promote the application of nickel-based superalloys,further research on the combination impact of multiple elements on cracking prevention and specific quantitative criteria for liquation cracking is necessary.展开更多
Multi-material laser-based powder bed fusion (PBF-LB) allows manufacturing of parts with 3-dimensional gradient and additional functionality in a single step. This research focuses on the combination of thermally-cond...Multi-material laser-based powder bed fusion (PBF-LB) allows manufacturing of parts with 3-dimensional gradient and additional functionality in a single step. This research focuses on the combination of thermally-conductive CuCr1Zr with hard M300 tool steel.Two interface configurations of M300 on CuCr1Zr and CuCr1Zr on M300 were investigated. Ultra-fine grains form at the interface due to the low mutual solubility of Cu and steel. The material mixing zone size is dependent on the configurations and tunable in the range of0.1–0.3 mm by introducing a separate set of parameters for the interface layers. Microcracks and pores mainly occur in the transition zone.Regardless of these defects, the thermal diffusivity of bimetallic parts with 50vol% of CuCr1Zr significantly increases by 70%–150%compared to pure M300. The thermal diffusivity of CuCr1Zr and the hardness of M300 steel can be enhanced simultaneously by applying the aging heat treatment.展开更多
The perception module of advanced driver assistance systems plays a vital role.Perception schemes often use a single sensor for data processing and environmental perception or adopt the information processing results ...The perception module of advanced driver assistance systems plays a vital role.Perception schemes often use a single sensor for data processing and environmental perception or adopt the information processing results of various sensors for the fusion of the detection layer.This paper proposes a multi-scale and multi-sensor data fusion strategy in the front end of perception and accomplishes a multi-sensor function disparity map generation scheme.A binocular stereo vision sensor composed of two cameras and a light deterction and ranging(LiDAR)sensor is used to jointly perceive the environment,and a multi-scale fusion scheme is employed to improve the accuracy of the disparity map.This solution not only has the advantages of dense perception of binocular stereo vision sensors but also considers the perception accuracy of LiDAR sensors.Experiments demonstrate that the multi-scale multi-sensor scheme proposed in this paper significantly improves disparity map estimation.展开更多
A liquid Li divertor is a promising alternative for future fusion devices.In this work a new divertor model is proposed,which is processed by 3D-printing technology to accurately control the size of the internal capil...A liquid Li divertor is a promising alternative for future fusion devices.In this work a new divertor model is proposed,which is processed by 3D-printing technology to accurately control the size of the internal capillary structure.At a steady-state heat load of 10 MW m^(-2),the thermal stress of the tungsten target is within the bearing range of tungsten by finite-element simulation.In order to evaluate the wicking ability of the capillary structure,the wicking process at 600℃ was simulated by FLUENT.The result was identical to that of the corresponding experiments.Within 1 s,liquid lithium was wicked to the target surface by the capillary structure of the target and quickly spread on the target surface.During the wicking process,the average wicking mass rate of lithium should reach 0.062 g s^(-1),which could even supplement the evaporation requirement of liquid lithium under an environment>950℃.Irradiation experiments under different plasma discharge currents were carried out in a linear plasma device(SCU-PSI),and the evolution of the vapor cloud during plasma irradiation was analyzed.It was found that the target temperature tends to plateau despite the gradually increased input current,indicating that the vapor shielding effect is gradually enhanced.The irradiation experiment also confirmed that the 3D-printed tungsten structure has better heat consumption performance than a tungsten mesh structure or multichannel structure.These results reveal the application potential and feasibility of a 3D-printed porous capillary structure in plasma-facing components and provide a reference for further liquid-solid combined target designs.展开更多
The dynamics of long-wavelength(kθ<1.4 cm^(-1)),broadband(20 kHz–200 kHz)electron temperature fluctuations(Te/Te)of plasmas in gas-puff experiments are observed for the first time in HL-2A tokamak.In a relatively...The dynamics of long-wavelength(kθ<1.4 cm^(-1)),broadband(20 kHz–200 kHz)electron temperature fluctuations(Te/Te)of plasmas in gas-puff experiments are observed for the first time in HL-2A tokamak.In a relatively low density(ne(0)■0.91×10^(19)m^(-3)–1.20×10^(19)m^(-3))scenario,after gas-puffing the core temperature increases and the edge temperature drops.On the contrary,temperature fluctuation drops at the core and increases at the edge.Analyses show the non-local emergence is accompanied with a long radial coherent length of turbulent fluctuations.While in a higher density(ne(0)?1.83×10^(19)m^(-3)–2.02×10^(19)m^(-3))scenario,the phenomena are not observed.Furthermore,compelling evidence indicates that E×B shear serves as a substantial contributor to this extensive radial interaction.This finding offers a direct explanatory link to the intriguing core-heating phenomenon witnessed within the realm of non-local transport.展开更多
Chinese Clinical Named Entity Recognition(CNER)is a crucial step in extracting medical information and is of great significance in promoting medical informatization.However,CNER poses challenges due to the specificity...Chinese Clinical Named Entity Recognition(CNER)is a crucial step in extracting medical information and is of great significance in promoting medical informatization.However,CNER poses challenges due to the specificity of clinical terminology,the complexity of Chinese text semantics,and the uncertainty of Chinese entity boundaries.To address these issues,we propose an improved CNER model,which is based on multi-feature fusion and multi-scale local context enhancement.The model simultaneously fuses multi-feature representations of pinyin,radical,Part of Speech(POS),word boundary with BERT deep contextual representations to enhance the semantic representation of text for more effective entity recognition.Furthermore,to address the model’s limitation of focusing just on global features,we incorporate Convolutional Neural Networks(CNNs)with various kernel sizes to capture multi-scale local features of the text and enhance the model’s comprehension of the text.Finally,we integrate the obtained global and local features,and employ multi-head attention mechanism(MHA)extraction to enhance the model’s focus on characters associated with medical entities,hence boosting the model’s performance.We obtained 92.74%,and 87.80%F1 scores on the two CNER benchmark datasets,CCKS2017 and CCKS2019,respectively.The results demonstrate that our model outperforms the latest models in CNER,showcasing its outstanding overall performance.It can be seen that the CNER model proposed in this study has an important application value in constructing clinical medical knowledge graph and intelligent Q&A system.展开更多
As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from bo...As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from both its environment and other agents,an agent can use various methods and sensor types to localize itself.With its high flexibility and robustness,collaborative positioning has become a widely used method in both military and civilian applications.This paper introduces the basic fundamental concepts and applications of collaborative positioning,and reviews recent progress in the field based on camera,LiDAR(Light Detection and Ranging),wireless sensor,and their integration.The paper compares the current methods with respect to their sensor type,summarizes their main paradigms,and analyzes their evaluation experiments.Finally,the paper discusses the main challenges and open issues that require further research.展开更多
Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities.Additionally,it leverages inter-modal correlation to enhance recognition performance.Concurrently,the robustness and ...Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities.Additionally,it leverages inter-modal correlation to enhance recognition performance.Concurrently,the robustness and recognition performance of the system can be enhanced through judiciously leveraging the correlation among multimodal features.Nevertheless,two issues persist in multi-modal feature fusion recognition:Firstly,the enhancement of recognition performance in fusion recognition has not comprehensively considered the inter-modality correlations among distinct modalities.Secondly,during modal fusion,improper weight selection diminishes the salience of crucial modal features,thereby diminishing the overall recognition performance.To address these two issues,we introduce an enhanced DenseNet multimodal recognition network founded on feature-level fusion.The information from the three modalities is fused akin to RGB,and the input network augments the correlation between modes through channel correlation.Within the enhanced DenseNet network,the Efficient Channel Attention Network(ECA-Net)dynamically adjusts the weight of each channel to amplify the salience of crucial information in each modal feature.Depthwise separable convolution markedly reduces the training parameters and further enhances the feature correlation.Experimental evaluations were conducted on four multimodal databases,comprising six unimodal databases,including multispectral palmprint and palm vein databases from the Chinese Academy of Sciences.The Equal Error Rates(EER)values were 0.0149%,0.0150%,0.0099%,and 0.0050%,correspondingly.In comparison to other network methods for palmprint,palm vein,and finger vein fusion recognition,this approach substantially enhances recognition performance,rendering it suitable for high-security environments with practical applicability.The experiments in this article utilized amodest sample database comprising 200 individuals.The subsequent phase involves preparing for the extension of the method to larger databases.展开更多
The early implementation of treatment therapies necessitates the swift and precise identification of COVID-19 pneumonia by the analysis of chest CT scans.This study aims to investigate the indispensable need for preci...The early implementation of treatment therapies necessitates the swift and precise identification of COVID-19 pneumonia by the analysis of chest CT scans.This study aims to investigate the indispensable need for precise and interpretable diagnostic tools for improving clinical decision-making for COVID-19 diagnosis.This paper proposes a novel deep learning approach,called Conformer Network,for explainable discrimination of viral pneumonia depending on the lung Region of Infections(ROI)within a single modality radiographic CT scan.Firstly,an efficient U-shaped transformer network is integrated for lung image segmentation.Then,a robust transfer learning technique is introduced to design a robust feature extractor based on pre-trained lightweight Big Transfer(BiT-L)and finetuned on medical data to effectively learn the patterns of infection in the input image.Secondly,this work presents a visual explanation method to guarantee clinical explainability for decisions made by Conformer Network.Experimental evaluation of real-world CT data demonstrated that the diagnostic accuracy of ourmodel outperforms cutting-edge studies with statistical significance.The Conformer Network achieves 97.40% of detection accuracy under cross-validation settings.Our model not only achieves high sensitivity and specificity but also affords visualizations of salient features contributing to each classification decision,enhancing the overall transparency and trustworthiness of our model.The findings provide obvious implications for the ability of our model to empower clinical staff by generating transparent intuitions about the features driving diagnostic decisions.展开更多
Brain homeostasis refe rs to the normal working state of the brain in a certain period,which is impo rtant for overall health and normal life activities.Currently,there is a lack of effective treatment methods for the...Brain homeostasis refe rs to the normal working state of the brain in a certain period,which is impo rtant for overall health and normal life activities.Currently,there is a lack of effective treatment methods for the adverse consequences caused by brain homeostasis imbalance.Snapin is a protein that assists in the formation of neuronal synapses and plays a crucial role in the normal growth and development of synapses.Recently,many researchers have reported the association between snapin and neurologic and psychiatric disorders,demonstrating that snapin can improve brain homeostasis.Clinical manifestations of brain disease often involve imbalances in brain homeostasis and may lead to neurological and behavioral sequelae.This article aims to explo re the role of snapin in restoring brain homeostasis after injury or diseases,highlighting its significance in maintaining brain homeostasis and treating brain diseases.Additionally,it comprehensively discusses the implications of snapin in other extracerebral diseases such as diabetes and viral infections,with the objective of determining the clinical potential of snapin in maintaining brain homeostasis.展开更多
In order to obtain more accurate precipitation data and better simulate the precipitation on the Tibetan Plateau,the simulation capability of 14 Coupled Model Intercomparison Project Phase 6(CMIP6)models of historical...In order to obtain more accurate precipitation data and better simulate the precipitation on the Tibetan Plateau,the simulation capability of 14 Coupled Model Intercomparison Project Phase 6(CMIP6)models of historical precipitation(1982-2014)on the Qinghai-Tibetan Plateau was evaluated in this study.Results indicate that all models exhibit an overestimation of precipitation through the analysis of the Taylor index,temporal and spatial statistical parameters.To correct the overestimation,a fusion correction method combining the Backpropagation Neural Network Correction(BP)and Quantum Mapping(QM)correction,named BQ method,was proposed.With this method,the historical precipitation of each model was corrected in space and time,respectively.The correction results were then analyzed in time,space,and analysis of variance(ANOVA)with those corrected by the BP and QM methods,respectively.Finally,the fusion correction method results for each model were compared with the Climatic Research Unit(CRU)data for significance analysis to obtain the trends of precipitation increase and decrease for each model.The results show that the IPSL-CM6A-LR model is relatively good in simulating historical precipitation on the Qinghai-Tibetan Plateau(R=0.7,RSME=0.15)among the uncorrected data.In terms of time,the total precipitation corrected by the fusion method has the same interannual trend and the closest precipitation values to the CRU data;In terms of space,the annual average precipitation corrected by the fusion method has the smallest difference with the CRU data,and the total historical annual average precipitation is not significantly different from the CRU data,which is better than BP and QM.Therefore,the correction effect of the fusion method on the historical precipitation of each model is better than that of the QM and BP methods.The precipitation in the central and northeastern parts of the plateau shows a significant increasing trend.The correlation coefficients between monthly precipitation and site-detected precipitation for all models after BQ correction exceed 0.8.展开更多
Improvement of fabrication efficiency and part performance was the main challenge for the large-scale powder bed fusion(PBF)process.In this study,a dynamic monitoring and feedback system of powder bed temperature fiel...Improvement of fabrication efficiency and part performance was the main challenge for the large-scale powder bed fusion(PBF)process.In this study,a dynamic monitoring and feedback system of powder bed temperature field using an infrared thermal imager has been established and integrated into a four-laser PBF equipment with a working area of 2000 mm×2000 mm.The heat-affected zone(HAZ)temperature field has been controlled by adjusting the scanning speed dynamically.Simultaneously,the relationship among spot size,HAZ temperature,and part performance has been established.The fluctuation of the HAZ temperature in four-laser scanning areas was decreased from 30.85℃to 17.41℃.Thus,the consistency of the sintering performance of the produced large component has been improved.Based on the controllable temperature field,a dynamically adjusting strategy for laser spot size was proposed,by which the fabrication efficiency was improved up to 65.38%.The current research results were of great significance to the further industrial applications of large-scale PBF equipment.展开更多
Evapotranspiration(ET)is a crucial variable in the terrestrial water,carbon,and energy cycles.At present,a large number of multi source ET products exist.Due to sparse observations,however,great challenges exist in th...Evapotranspiration(ET)is a crucial variable in the terrestrial water,carbon,and energy cycles.At present,a large number of multi source ET products exist.Due to sparse observations,however,great challenges exist in the evaluation and integration of ET products in remote and complex areas such as the Tibetan Plateau(TP).In this paper,the applicability of the multiple collocation(MC)method over the TP is evaluated for the first time,and the uncertainty of multisource ET products(based on reanalysis,remote sensing,and land surface models)is further analyzed,which provides a theoretical basis for ET data fusion.The results show that 1)ET uncertainties quantified via the MC method are lower in RS-based ET products(5.95 vs.7.06 mm month^(-1))than in LSM ET products(10.22 vs.17.97 mm month^(-1))and reanalysis ET estimates(7.27 vs.12.26 mm month-1).2)A multisource evapotranspiration(MET)dataset is generated at a monthly temporal scale with a spatial resolution of 0.25°across the TP during 2005-15.MET has better performance than any individual product.3)Based on the fusion product,the total ET amount over the TP and its patterns of spatiotemporal variability are clearly identified.The annual total ET over the entire TP is approximately 380.60 mm.Additionally,an increasing trend of 1.59±0.85 mm yr^(-1)over the TP is shown during 2005-15.This study provides a basis for future studies on water and energy cycles and water resource management over the TP and surrounding regions.展开更多
Because of their economy and applicability,high-power thyristor devices are widely used in the power supply systems for large fusion devices.When high-dose neutrons produced by deuterium–tritium(D–T)fusion reactions...Because of their economy and applicability,high-power thyristor devices are widely used in the power supply systems for large fusion devices.When high-dose neutrons produced by deuterium–tritium(D–T)fusion reactions are irradiated on a thyristor device for a long time,the electrical characteristics of the device change,which may eventually cause irreversible damage.In this study,with the thyristor switch of the commutation circuit in the quench protection system(QPS)of a fusion device as the study object,the relationship between the internal physical structure and external electrical parameters of the irradiated thyristor is established.Subsequently,a series of targeted thyristor physical simulations and neutron irradiation experiments are conducted to verify the accuracy of the theoretical analysis.In addition,the effect of irradiated thyristor electrical characteristic changes on the entire QPS is studied by accurate simulation,providing valuable guidelines for the maintenance and renovation of the QPS.展开更多
Rockbursts have become a significant hazard in underground mining,underscoring the need for a robust early warning model to ensure safety management.This study presents a novel approach for rockburst prediction,integr...Rockbursts have become a significant hazard in underground mining,underscoring the need for a robust early warning model to ensure safety management.This study presents a novel approach for rockburst prediction,integrating the Mann-Kendall trend test(MKT)and multi-indices fusion to enable real-time and quantitative assessment of rockburst hazards.The methodology employed in this study involves the development of a comprehensive precursory index library for rockbursts.The MKT is then applied to analyze the real-time trend of each index,with adherence to rockburst characterization laws serving as the warning criterion.By employing a confusion matrix,the warning effectiveness of each index is assessed,enabling index preference determination.Ultimately,the integrated rockburst hazard index Q is derived through data fusion.The results demonstrate that the proposed model achieves a warning effectiveness of 0.563 for Q,surpassing the performance of any individual index.Moreover,the model’s adaptability and scalability are enhanced through periodic updates driven by actual field monitoring data,making it suitable for complex underground working environments.By providing an efficient and accurate basis for decision-making,the proposed model holds great potential for the prevention and control of rockbursts.It offers a valuable tool for enhancing safety measures in underground mining operations.展开更多
Herein,we employ the threshold energy neutron analysis(TENA)technique to introduce the world's first active interrogation system to detect special nuclear materials(SNMs),including U-235 and Pu-239.The system util...Herein,we employ the threshold energy neutron analysis(TENA)technique to introduce the world's first active interrogation system to detect special nuclear materials(SNMs),including U-235 and Pu-239.The system utilizes a DD neutron generator based on inertial electrostatic confinement(IEC)to interrogate suspicious objects.To detect secondary neutrons produced during fission reactions induced in SNMs,a tensioned metastable fluid detector(TMFD)is employed.The current status of the system's development is reported in this paper,accompanied by the results from experiments conducted to detect 10 g of highly enriched uranium(HEU).Notably,the experimental findings demonstrate a distinct difference in the count rates of measurements with and without HEU.This difference in count rates surpasses two times the standard deviation,indicating a confidence level of more than 96% for identifying the presence of HEU.The paper presents and extensively discusses the proof-of-principle experimental results,along with the system's planned trajectory.展开更多
基金supported by the National Natural Science Foundation of China,Nos.82130037(to CH),81971122(to CH),82171323(to WL)the Natural Science Foundation of Jiangsu Province of China,No.BK20201113(to WL)。
文摘The dramatic increase in intracranial pressure after subarachnoid hemorrhage leads to a decrease in cerebral perfusion pressure and a reduction in cerebral blood flow.Mitochondria are directly affected by direct factors such as ischemia,hypoxia,excitotoxicity,and toxicity of free hemoglobin and its degradation products,which trigger mitochondrial dysfunction.Dysfunctional mitochondria release large amounts of reactive oxygen species,inflammatory mediators,and apoptotic proteins that activate apoptotic pathways,further damaging cells.In response to this array of damage,cells have adopted multiple mitochondrial quality control mechanisms through evolution,including mitochondrial protein quality control,mitochondrial dynamics,mitophagy,mitochondrial biogenesis,and intercellular mitochondrial transfer,to maintain mitochondrial homeostasis under pathological conditions.Specific interventions targeting mitochondrial quality control mechanisms have emerged as promising therapeutic strategies for subarachnoid hemorrhage.This review provides an overview of recent research advances in mitochondrial pathophysiological processes after subarachnoid hemorrhage,particularly mitochondrial quality control mechanisms.It also presents potential therapeutic strategies to target mitochondrial quality control in subarachnoid hemorrhage.
基金the National Key R&D Program of China(No.2021YFB3701705).
文摘This work constructed a machine learning(ML)model to predict the atmospheric corrosion rate of low-alloy steels(LAS).The material properties of LAS,environmental factors,and exposure time were used as the input,while the corrosion rate as the output.6 dif-ferent ML algorithms were used to construct the proposed model.Through optimization and filtering,the eXtreme gradient boosting(XG-Boost)model exhibited good corrosion rate prediction accuracy.The features of material properties were then transformed into atomic and physical features using the proposed property transformation approach,and the dominant descriptors that affected the corrosion rate were filtered using the recursive feature elimination(RFE)as well as XGBoost methods.The established ML models exhibited better predic-tion performance and generalization ability via property transformation descriptors.In addition,the SHapley additive exPlanations(SHAP)method was applied to analyze the relationship between the descriptors and corrosion rate.The results showed that the property transformation model could effectively help with analyzing the corrosion behavior,thereby significantly improving the generalization ability of corrosion rate prediction models.
基金funded by the National Key Research and Development Program of China(2018YFE0104200)National Natural Science Foundation of China(51875310,52175274,82172065)Tsinghua Precision Medicine Foundation.
文摘Laser powder bed fusion(L-PBF)of Mg alloys has provided tremendous opportunities for customized production of aeronautical and medical parts.Layer thickness(LT)is of great significance to the L-PBF process but has not been studied for Mg alloys.In this study,WE43 Mg alloy bulk cubes,porous scaffolds,and thin walls with layer thicknesses of 10,20,30,and 40μm were fabricated.The required laser energy input increased with increasing layer thickness and was different for the bulk cubes and porous scaffolds.Porosity tended to occur at the connection joints in porous scaffolds for LT40 and could be eliminated by reducing the laser energy input.For thin wall parts,a large overhang angle or a small wall thickness resulted in porosity when a large layer thicknesses was used,and the porosity disappeared by reducing the layer thickness or laser energy input.A deeper keyhole penetration was found in all occasions with porosity,explaining the influence of layer thickness,geometrical structure,and laser energy input on the porosity.All the samples achieved a high fusion quality with a relative density of over 99.5%using the optimized laser energy input.The increased layer thickness resulted to more precipitation phases,finer grain sizes and decreased grain texture.With the similar high fusion quality,the tensile strength and elongation of bulk samples were significantly improved from 257 MPa and 1.41%with the 10μm layer to 287 MPa and 15.12%with the 40μm layer,in accordance with the microstructural change.The effect of layer thickness on the compressive properties of porous scaffolds was limited.However,the corrosion rate of bulk samples accelerated with increasing the layer thickness,mainly attributed to the increased number of precipitation phases.
基金financially supported by the National Science and Technology Major Project of China(No.J2019-VI-0004-0117)。
文摘Nickel-based superalloys are extensively used in the crucial hot-section components of industrial gas turbines,aeronautics,and astronautics because of their excellent mechanical properties and corrosion resistance at high temperatures.Fusion welding serves as an effective means for joining and repairing these alloys;however,fusion welding-induced liquation cracking has been a challenging issue.This paper comprehensively reviewed recent liquation cracking,discussing the formation mechanisms,cracking criteria,and remedies.In recent investigations,regulating material composition,changing the preweld heat treatment of the base metal,optimizing the welding process parameters,and applying auxiliary control methods are effective strategies for mitigating cracks.To promote the application of nickel-based superalloys,further research on the combination impact of multiple elements on cracking prevention and specific quantitative criteria for liquation cracking is necessary.
基金supported by VTT Technical Research Centre of Finland,Aalto University,Aerosint SA,and partially from European Union Horizon 2020 (No.768775)。
文摘Multi-material laser-based powder bed fusion (PBF-LB) allows manufacturing of parts with 3-dimensional gradient and additional functionality in a single step. This research focuses on the combination of thermally-conductive CuCr1Zr with hard M300 tool steel.Two interface configurations of M300 on CuCr1Zr and CuCr1Zr on M300 were investigated. Ultra-fine grains form at the interface due to the low mutual solubility of Cu and steel. The material mixing zone size is dependent on the configurations and tunable in the range of0.1–0.3 mm by introducing a separate set of parameters for the interface layers. Microcracks and pores mainly occur in the transition zone.Regardless of these defects, the thermal diffusivity of bimetallic parts with 50vol% of CuCr1Zr significantly increases by 70%–150%compared to pure M300. The thermal diffusivity of CuCr1Zr and the hardness of M300 steel can be enhanced simultaneously by applying the aging heat treatment.
基金the National Key R&D Program of China(2018AAA0103103).
文摘The perception module of advanced driver assistance systems plays a vital role.Perception schemes often use a single sensor for data processing and environmental perception or adopt the information processing results of various sensors for the fusion of the detection layer.This paper proposes a multi-scale and multi-sensor data fusion strategy in the front end of perception and accomplishes a multi-sensor function disparity map generation scheme.A binocular stereo vision sensor composed of two cameras and a light deterction and ranging(LiDAR)sensor is used to jointly perceive the environment,and a multi-scale fusion scheme is employed to improve the accuracy of the disparity map.This solution not only has the advantages of dense perception of binocular stereo vision sensors but also considers the perception accuracy of LiDAR sensors.Experiments demonstrate that the multi-scale multi-sensor scheme proposed in this paper significantly improves disparity map estimation.
基金funded by the China Postdoctoral Science Foundation(No.2019M663487)the National Key Research and Development Program of China(No.2022YFE03130000)。
文摘A liquid Li divertor is a promising alternative for future fusion devices.In this work a new divertor model is proposed,which is processed by 3D-printing technology to accurately control the size of the internal capillary structure.At a steady-state heat load of 10 MW m^(-2),the thermal stress of the tungsten target is within the bearing range of tungsten by finite-element simulation.In order to evaluate the wicking ability of the capillary structure,the wicking process at 600℃ was simulated by FLUENT.The result was identical to that of the corresponding experiments.Within 1 s,liquid lithium was wicked to the target surface by the capillary structure of the target and quickly spread on the target surface.During the wicking process,the average wicking mass rate of lithium should reach 0.062 g s^(-1),which could even supplement the evaporation requirement of liquid lithium under an environment>950℃.Irradiation experiments under different plasma discharge currents were carried out in a linear plasma device(SCU-PSI),and the evolution of the vapor cloud during plasma irradiation was analyzed.It was found that the target temperature tends to plateau despite the gradually increased input current,indicating that the vapor shielding effect is gradually enhanced.The irradiation experiment also confirmed that the 3D-printed tungsten structure has better heat consumption performance than a tungsten mesh structure or multichannel structure.These results reveal the application potential and feasibility of a 3D-printed porous capillary structure in plasma-facing components and provide a reference for further liquid-solid combined target designs.
基金Project supported by the National Key Research and Development Program of China(Grant No.2017YFE0301203)the Innovation Program of Southwestern Institute of Physics(Grant No.202301XWCX001)+2 种基金the Sichuan Science and Technology Program(Grant Nos.2023ZYD0014 and 2021YFSY0044)the National Natural Science Foundation of China(Grant No.12175055)the Shenzhen Municipal Collaborative Innovation Technology Program-International Science and Technology Cooperation Project(Grant No.GJHZ20220913142609017)。
文摘The dynamics of long-wavelength(kθ<1.4 cm^(-1)),broadband(20 kHz–200 kHz)electron temperature fluctuations(Te/Te)of plasmas in gas-puff experiments are observed for the first time in HL-2A tokamak.In a relatively low density(ne(0)■0.91×10^(19)m^(-3)–1.20×10^(19)m^(-3))scenario,after gas-puffing the core temperature increases and the edge temperature drops.On the contrary,temperature fluctuation drops at the core and increases at the edge.Analyses show the non-local emergence is accompanied with a long radial coherent length of turbulent fluctuations.While in a higher density(ne(0)?1.83×10^(19)m^(-3)–2.02×10^(19)m^(-3))scenario,the phenomena are not observed.Furthermore,compelling evidence indicates that E×B shear serves as a substantial contributor to this extensive radial interaction.This finding offers a direct explanatory link to the intriguing core-heating phenomenon witnessed within the realm of non-local transport.
基金This study was supported by the National Natural Science Foundation of China(61911540482 and 61702324).
文摘Chinese Clinical Named Entity Recognition(CNER)is a crucial step in extracting medical information and is of great significance in promoting medical informatization.However,CNER poses challenges due to the specificity of clinical terminology,the complexity of Chinese text semantics,and the uncertainty of Chinese entity boundaries.To address these issues,we propose an improved CNER model,which is based on multi-feature fusion and multi-scale local context enhancement.The model simultaneously fuses multi-feature representations of pinyin,radical,Part of Speech(POS),word boundary with BERT deep contextual representations to enhance the semantic representation of text for more effective entity recognition.Furthermore,to address the model’s limitation of focusing just on global features,we incorporate Convolutional Neural Networks(CNNs)with various kernel sizes to capture multi-scale local features of the text and enhance the model’s comprehension of the text.Finally,we integrate the obtained global and local features,and employ multi-head attention mechanism(MHA)extraction to enhance the model’s focus on characters associated with medical entities,hence boosting the model’s performance.We obtained 92.74%,and 87.80%F1 scores on the two CNER benchmark datasets,CCKS2017 and CCKS2019,respectively.The results demonstrate that our model outperforms the latest models in CNER,showcasing its outstanding overall performance.It can be seen that the CNER model proposed in this study has an important application value in constructing clinical medical knowledge graph and intelligent Q&A system.
基金National Natural Science Foundation of China(Grant No.62101138)Shandong Natural Science Foundation(Grant No.ZR2021QD148)+1 种基金Guangdong Natural Science Foundation(Grant No.2022A1515012573)Guangzhou Basic and Applied Basic Research Project(Grant No.202102020701)for providing funds for publishing this paper。
文摘As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from both its environment and other agents,an agent can use various methods and sensor types to localize itself.With its high flexibility and robustness,collaborative positioning has become a widely used method in both military and civilian applications.This paper introduces the basic fundamental concepts and applications of collaborative positioning,and reviews recent progress in the field based on camera,LiDAR(Light Detection and Ranging),wireless sensor,and their integration.The paper compares the current methods with respect to their sensor type,summarizes their main paradigms,and analyzes their evaluation experiments.Finally,the paper discusses the main challenges and open issues that require further research.
基金funded by the National Natural Science Foundation of China(61991413)the China Postdoctoral Science Foundation(2019M651142)+1 种基金the Natural Science Foundation of Liaoning Province(2021-KF-12-07)the Natural Science Foundations of Liaoning Province(2023-MS-322).
文摘Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities.Additionally,it leverages inter-modal correlation to enhance recognition performance.Concurrently,the robustness and recognition performance of the system can be enhanced through judiciously leveraging the correlation among multimodal features.Nevertheless,two issues persist in multi-modal feature fusion recognition:Firstly,the enhancement of recognition performance in fusion recognition has not comprehensively considered the inter-modality correlations among distinct modalities.Secondly,during modal fusion,improper weight selection diminishes the salience of crucial modal features,thereby diminishing the overall recognition performance.To address these two issues,we introduce an enhanced DenseNet multimodal recognition network founded on feature-level fusion.The information from the three modalities is fused akin to RGB,and the input network augments the correlation between modes through channel correlation.Within the enhanced DenseNet network,the Efficient Channel Attention Network(ECA-Net)dynamically adjusts the weight of each channel to amplify the salience of crucial information in each modal feature.Depthwise separable convolution markedly reduces the training parameters and further enhances the feature correlation.Experimental evaluations were conducted on four multimodal databases,comprising six unimodal databases,including multispectral palmprint and palm vein databases from the Chinese Academy of Sciences.The Equal Error Rates(EER)values were 0.0149%,0.0150%,0.0099%,and 0.0050%,correspondingly.In comparison to other network methods for palmprint,palm vein,and finger vein fusion recognition,this approach substantially enhances recognition performance,rendering it suitable for high-security environments with practical applicability.The experiments in this article utilized amodest sample database comprising 200 individuals.The subsequent phase involves preparing for the extension of the method to larger databases.
基金funded by King Saud University,Riyadh,Saudi Arabia.Researchers Supporting Project Number(RSP2024R167),King Saud University,Riyadh,Saudi Arabia.
文摘The early implementation of treatment therapies necessitates the swift and precise identification of COVID-19 pneumonia by the analysis of chest CT scans.This study aims to investigate the indispensable need for precise and interpretable diagnostic tools for improving clinical decision-making for COVID-19 diagnosis.This paper proposes a novel deep learning approach,called Conformer Network,for explainable discrimination of viral pneumonia depending on the lung Region of Infections(ROI)within a single modality radiographic CT scan.Firstly,an efficient U-shaped transformer network is integrated for lung image segmentation.Then,a robust transfer learning technique is introduced to design a robust feature extractor based on pre-trained lightweight Big Transfer(BiT-L)and finetuned on medical data to effectively learn the patterns of infection in the input image.Secondly,this work presents a visual explanation method to guarantee clinical explainability for decisions made by Conformer Network.Experimental evaluation of real-world CT data demonstrated that the diagnostic accuracy of ourmodel outperforms cutting-edge studies with statistical significance.The Conformer Network achieves 97.40% of detection accuracy under cross-validation settings.Our model not only achieves high sensitivity and specificity but also affords visualizations of salient features contributing to each classification decision,enhancing the overall transparency and trustworthiness of our model.The findings provide obvious implications for the ability of our model to empower clinical staff by generating transparent intuitions about the features driving diagnostic decisions.
基金supported by the National Natural Science Foundation of China,Nos.82071382(to MZ),81601306(to HS)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)(to MZ)+5 种基金Jiangsu 333 High Level Talent Training Project(2022)(to HS)the Jiangsu Maternal and Child Health Research Key Project(F202013)(to HS)Jiangsu Talent Youth Medical Program,No.QNRC2016245(to HS)Shanghai Key Lab of Forensic Medicine,No.KF2102(to MZ)Suzhou Science and Technology Development Project,No.SYS2020089(to MZ)the Fifth Batch of Gusu District Health Talent Training Project,No.GSWS2019060(to HS)。
文摘Brain homeostasis refe rs to the normal working state of the brain in a certain period,which is impo rtant for overall health and normal life activities.Currently,there is a lack of effective treatment methods for the adverse consequences caused by brain homeostasis imbalance.Snapin is a protein that assists in the formation of neuronal synapses and plays a crucial role in the normal growth and development of synapses.Recently,many researchers have reported the association between snapin and neurologic and psychiatric disorders,demonstrating that snapin can improve brain homeostasis.Clinical manifestations of brain disease often involve imbalances in brain homeostasis and may lead to neurological and behavioral sequelae.This article aims to explo re the role of snapin in restoring brain homeostasis after injury or diseases,highlighting its significance in maintaining brain homeostasis and treating brain diseases.Additionally,it comprehensively discusses the implications of snapin in other extracerebral diseases such as diabetes and viral infections,with the objective of determining the clinical potential of snapin in maintaining brain homeostasis.
文摘In order to obtain more accurate precipitation data and better simulate the precipitation on the Tibetan Plateau,the simulation capability of 14 Coupled Model Intercomparison Project Phase 6(CMIP6)models of historical precipitation(1982-2014)on the Qinghai-Tibetan Plateau was evaluated in this study.Results indicate that all models exhibit an overestimation of precipitation through the analysis of the Taylor index,temporal and spatial statistical parameters.To correct the overestimation,a fusion correction method combining the Backpropagation Neural Network Correction(BP)and Quantum Mapping(QM)correction,named BQ method,was proposed.With this method,the historical precipitation of each model was corrected in space and time,respectively.The correction results were then analyzed in time,space,and analysis of variance(ANOVA)with those corrected by the BP and QM methods,respectively.Finally,the fusion correction method results for each model were compared with the Climatic Research Unit(CRU)data for significance analysis to obtain the trends of precipitation increase and decrease for each model.The results show that the IPSL-CM6A-LR model is relatively good in simulating historical precipitation on the Qinghai-Tibetan Plateau(R=0.7,RSME=0.15)among the uncorrected data.In terms of time,the total precipitation corrected by the fusion method has the same interannual trend and the closest precipitation values to the CRU data;In terms of space,the annual average precipitation corrected by the fusion method has the smallest difference with the CRU data,and the total historical annual average precipitation is not significantly different from the CRU data,which is better than BP and QM.Therefore,the correction effect of the fusion method on the historical precipitation of each model is better than that of the QM and BP methods.The precipitation in the central and northeastern parts of the plateau shows a significant increasing trend.The correlation coefficients between monthly precipitation and site-detected precipitation for all models after BQ correction exceed 0.8.
基金Supported by National High Technology Research and Development Program of China(863 Program,Grant No.2015AA042503)K.C.Wong Education Foundation.
文摘Improvement of fabrication efficiency and part performance was the main challenge for the large-scale powder bed fusion(PBF)process.In this study,a dynamic monitoring and feedback system of powder bed temperature field using an infrared thermal imager has been established and integrated into a four-laser PBF equipment with a working area of 2000 mm×2000 mm.The heat-affected zone(HAZ)temperature field has been controlled by adjusting the scanning speed dynamically.Simultaneously,the relationship among spot size,HAZ temperature,and part performance has been established.The fluctuation of the HAZ temperature in four-laser scanning areas was decreased from 30.85℃to 17.41℃.Thus,the consistency of the sintering performance of the produced large component has been improved.Based on the controllable temperature field,a dynamically adjusting strategy for laser spot size was proposed,by which the fabrication efficiency was improved up to 65.38%.The current research results were of great significance to the further industrial applications of large-scale PBF equipment.
基金funded by the Second Tibetan Plateau Scientific Expedition and Research(STEP)Program(Grant No.2019QZKK0103)National Natural Science Foundation of China(Grant Nos.41875031,42230610,41522501,41275028)CLIMATE-Pan-TPE in the framework of the ESA-MOST Dragon 5 Programme(Grant ID 58516)。
文摘Evapotranspiration(ET)is a crucial variable in the terrestrial water,carbon,and energy cycles.At present,a large number of multi source ET products exist.Due to sparse observations,however,great challenges exist in the evaluation and integration of ET products in remote and complex areas such as the Tibetan Plateau(TP).In this paper,the applicability of the multiple collocation(MC)method over the TP is evaluated for the first time,and the uncertainty of multisource ET products(based on reanalysis,remote sensing,and land surface models)is further analyzed,which provides a theoretical basis for ET data fusion.The results show that 1)ET uncertainties quantified via the MC method are lower in RS-based ET products(5.95 vs.7.06 mm month^(-1))than in LSM ET products(10.22 vs.17.97 mm month^(-1))and reanalysis ET estimates(7.27 vs.12.26 mm month-1).2)A multisource evapotranspiration(MET)dataset is generated at a monthly temporal scale with a spatial resolution of 0.25°across the TP during 2005-15.MET has better performance than any individual product.3)Based on the fusion product,the total ET amount over the TP and its patterns of spatiotemporal variability are clearly identified.The annual total ET over the entire TP is approximately 380.60 mm.Additionally,an increasing trend of 1.59±0.85 mm yr^(-1)over the TP is shown during 2005-15.This study provides a basis for future studies on water and energy cycles and water resource management over the TP and surrounding regions.
基金supported by the Fundamental Research Funds for the Central University(No.JZ2023HGTA0182)Comprehensive Research Facility for Fusion Technology Program of China(No.2018-000052-73-01-001228)。
文摘Because of their economy and applicability,high-power thyristor devices are widely used in the power supply systems for large fusion devices.When high-dose neutrons produced by deuterium–tritium(D–T)fusion reactions are irradiated on a thyristor device for a long time,the electrical characteristics of the device change,which may eventually cause irreversible damage.In this study,with the thyristor switch of the commutation circuit in the quench protection system(QPS)of a fusion device as the study object,the relationship between the internal physical structure and external electrical parameters of the irradiated thyristor is established.Subsequently,a series of targeted thyristor physical simulations and neutron irradiation experiments are conducted to verify the accuracy of the theoretical analysis.In addition,the effect of irradiated thyristor electrical characteristic changes on the entire QPS is studied by accurate simulation,providing valuable guidelines for the maintenance and renovation of the QPS.
基金The authors gratefully acknowledge the financial support from the National Natural Science Foundation of China(Grant Nos.52011530037 and 51904019)the Fundamental Research Funds for the Central Universities and the Youth Teacher International Exchange&Growth Program(Grant No.QNXM20210004).We also greatly appreciate the assistance provided by Kuangou coal mine,China Energy Group Xinjiang Energy Co.,Ltd.
文摘Rockbursts have become a significant hazard in underground mining,underscoring the need for a robust early warning model to ensure safety management.This study presents a novel approach for rockburst prediction,integrating the Mann-Kendall trend test(MKT)and multi-indices fusion to enable real-time and quantitative assessment of rockburst hazards.The methodology employed in this study involves the development of a comprehensive precursory index library for rockbursts.The MKT is then applied to analyze the real-time trend of each index,with adherence to rockburst characterization laws serving as the warning criterion.By employing a confusion matrix,the warning effectiveness of each index is assessed,enabling index preference determination.Ultimately,the integrated rockburst hazard index Q is derived through data fusion.The results demonstrate that the proposed model achieves a warning effectiveness of 0.563 for Q,surpassing the performance of any individual index.Moreover,the model’s adaptability and scalability are enhanced through periodic updates driven by actual field monitoring data,making it suitable for complex underground working environments.By providing an efficient and accurate basis for decision-making,the proposed model holds great potential for the prevention and control of rockbursts.It offers a valuable tool for enhancing safety measures in underground mining operations.
基金supported by Special Coordination Funds for Promoting Science and Technology,sponsored by Japan’s Ministry of Education,Culture,Sports,Science and Technology(MEXT).
文摘Herein,we employ the threshold energy neutron analysis(TENA)technique to introduce the world's first active interrogation system to detect special nuclear materials(SNMs),including U-235 and Pu-239.The system utilizes a DD neutron generator based on inertial electrostatic confinement(IEC)to interrogate suspicious objects.To detect secondary neutrons produced during fission reactions induced in SNMs,a tensioned metastable fluid detector(TMFD)is employed.The current status of the system's development is reported in this paper,accompanied by the results from experiments conducted to detect 10 g of highly enriched uranium(HEU).Notably,the experimental findings demonstrate a distinct difference in the count rates of measurements with and without HEU.This difference in count rates surpasses two times the standard deviation,indicating a confidence level of more than 96% for identifying the presence of HEU.The paper presents and extensively discusses the proof-of-principle experimental results,along with the system's planned trajectory.